"""Generated message classes for aiplatform version v1beta1. Train high-quality custom machine learning models with minimal machine learning expertise and effort. """ # NOTE: This file is autogenerated and should not be edited by hand. from __future__ import absolute_import from apitools.base.protorpclite import messages as _messages from apitools.base.py import encoding from apitools.base.py import extra_types package = 'aiplatform' class AiplatformAgentsOperationsCancelRequest(_messages.Message): r"""A AiplatformAgentsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformAgentsOperationsDeleteRequest(_messages.Message): r"""A AiplatformAgentsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformAgentsOperationsGetRequest(_messages.Message): r"""A AiplatformAgentsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformAgentsOperationsListRequest(_messages.Message): r"""A AiplatformAgentsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformAgentsOperationsWaitRequest(_messages.Message): r"""A AiplatformAgentsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformAppsOperationsCancelRequest(_messages.Message): r"""A AiplatformAppsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformAppsOperationsDeleteRequest(_messages.Message): r"""A AiplatformAppsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformAppsOperationsGetRequest(_messages.Message): r"""A AiplatformAppsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformAppsOperationsListRequest(_messages.Message): r"""A AiplatformAppsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformAppsOperationsWaitRequest(_messages.Message): r"""A AiplatformAppsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformBatchPredictionJobsCreateRequest(_messages.Message): r"""A AiplatformBatchPredictionJobsCreateRequest object. Fields: googleCloudAiplatformV1beta1BatchPredictionJob: A GoogleCloudAiplatformV1beta1BatchPredictionJob resource to be passed as the request body. parent: Required. The resource name of the Location to create the BatchPredictionJob in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1BatchPredictionJob = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchPredictionJob', 1) parent = _messages.StringField(2) class AiplatformBatchPredictionJobsGetRequest(_messages.Message): r"""A AiplatformBatchPredictionJobsGetRequest object. Fields: name: Required. The name of the BatchPredictionJob resource. Format: `proj ects/{project}/locations/{location}/batchPredictionJobs/{batch_predictio n_job}` """ name = _messages.StringField(1, required=True) class AiplatformBatchPredictionJobsListRequest(_messages.Message): r"""A AiplatformBatchPredictionJobsListRequest object. Fields: filter: The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `model_display_name` supports `=`, `!=` comparisons. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`<`, `<=`,`>`, `>=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state="JOB_STATE_SUCCEEDED" AND display_name:"my_job_*"` * `state!="JOB_STATE_FAILED" OR display_name="my_job"` * `NOT display_name="my_job"` * `create_time>"2021-05-18T00:00:00Z"` * `labels.keyA=valueA` * `labels.keyB:*` pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via ListBatchPredictionJobsResponse.next_page_token of the previous JobService.ListBatchPredictionJobs call. parent: Required. The resource name of the Location to list the BatchPredictionJobs from. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4) readMask = _messages.StringField(5) class AiplatformCustomJobsOperationsCancelRequest(_messages.Message): r"""A AiplatformCustomJobsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformCustomJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformCustomJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformCustomJobsOperationsGetRequest(_messages.Message): r"""A AiplatformCustomJobsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformCustomJobsOperationsListRequest(_messages.Message): r"""A AiplatformCustomJobsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformCustomJobsOperationsWaitRequest(_messages.Message): r"""A AiplatformCustomJobsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformDataLabelingJobsOperationsCancelRequest(_messages.Message): r"""A AiplatformDataLabelingJobsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformDataLabelingJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformDataLabelingJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformDataLabelingJobsOperationsGetRequest(_messages.Message): r"""A AiplatformDataLabelingJobsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformDataLabelingJobsOperationsListRequest(_messages.Message): r"""A AiplatformDataLabelingJobsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformDataLabelingJobsOperationsWaitRequest(_messages.Message): r"""A AiplatformDataLabelingJobsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformDatasetsAnnotationSpecsOperationsCancelRequest(_messages.Message): r"""A AiplatformDatasetsAnnotationSpecsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsAnnotationSpecsOperationsDeleteRequest(_messages.Message): r"""A AiplatformDatasetsAnnotationSpecsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsAnnotationSpecsOperationsGetRequest(_messages.Message): r"""A AiplatformDatasetsAnnotationSpecsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsAnnotationSpecsOperationsListRequest(_messages.Message): r"""A AiplatformDatasetsAnnotationSpecsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformDatasetsAnnotationSpecsOperationsWaitRequest(_messages.Message): r"""A AiplatformDatasetsAnnotationSpecsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformDatasetsCreateRequest(_messages.Message): r"""A AiplatformDatasetsCreateRequest object. Fields: googleCloudAiplatformV1beta1Dataset: A GoogleCloudAiplatformV1beta1Dataset resource to be passed as the request body. parent: Required. The resource name of the Location to create the Dataset in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1Dataset = _messages.MessageField('GoogleCloudAiplatformV1beta1Dataset', 1) parent = _messages.StringField(2) class AiplatformDatasetsDataItemsAnnotationsOperationsCancelRequest(_messages.Message): r"""A AiplatformDatasetsDataItemsAnnotationsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsDataItemsAnnotationsOperationsDeleteRequest(_messages.Message): r"""A AiplatformDatasetsDataItemsAnnotationsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsDataItemsAnnotationsOperationsGetRequest(_messages.Message): r"""A AiplatformDatasetsDataItemsAnnotationsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsDataItemsAnnotationsOperationsListRequest(_messages.Message): r"""A AiplatformDatasetsDataItemsAnnotationsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformDatasetsDataItemsAnnotationsOperationsWaitRequest(_messages.Message): r"""A AiplatformDatasetsDataItemsAnnotationsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformDatasetsDataItemsOperationsCancelRequest(_messages.Message): r"""A AiplatformDatasetsDataItemsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsDataItemsOperationsDeleteRequest(_messages.Message): r"""A AiplatformDatasetsDataItemsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsDataItemsOperationsGetRequest(_messages.Message): r"""A AiplatformDatasetsDataItemsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsDataItemsOperationsListRequest(_messages.Message): r"""A AiplatformDatasetsDataItemsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformDatasetsDataItemsOperationsWaitRequest(_messages.Message): r"""A AiplatformDatasetsDataItemsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformDatasetsDatasetVersionsCreateRequest(_messages.Message): r"""A AiplatformDatasetsDatasetVersionsCreateRequest object. Fields: googleCloudAiplatformV1beta1DatasetVersion: A GoogleCloudAiplatformV1beta1DatasetVersion resource to be passed as the request body. parent: Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}` """ googleCloudAiplatformV1beta1DatasetVersion = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetVersion', 1) parent = _messages.StringField(2, required=True) class AiplatformDatasetsDatasetVersionsDeleteRequest(_messages.Message): r"""A AiplatformDatasetsDatasetVersionsDeleteRequest object. Fields: name: Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/data setVersions/{dataset_version}` """ name = _messages.StringField(1, required=True) class AiplatformDatasetsDatasetVersionsGetRequest(_messages.Message): r"""A AiplatformDatasetsDatasetVersionsGetRequest object. Fields: name: Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/data setVersions/{dataset_version}` readMask: Mask specifying which fields to read. """ name = _messages.StringField(1, required=True) readMask = _messages.StringField(2) class AiplatformDatasetsDatasetVersionsListRequest(_messages.Message): r"""A AiplatformDatasetsDatasetVersionsListRequest object. Fields: filter: Optional. The standard list filter. orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. parent: Required. The resource name of the Dataset to list DatasetVersions from. Format: `projects/{project}/locations/{location}/datasets/{dataset}` readMask: Optional. Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformDatasetsDatasetVersionsPatchRequest(_messages.Message): r"""A AiplatformDatasetsDatasetVersionsPatchRequest object. Fields: googleCloudAiplatformV1beta1DatasetVersion: A GoogleCloudAiplatformV1beta1DatasetVersion resource to be passed as the request body. name: Output only. Identifier. The resource name of the DatasetVersion. Format: `projects/{project}/locations/{location}/datasets/{dataset}/data setVersions/{dataset_version}` updateMask: Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name` """ googleCloudAiplatformV1beta1DatasetVersion = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetVersion', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformDatasetsDatasetVersionsRestoreRequest(_messages.Message): r"""A AiplatformDatasetsDatasetVersionsRestoreRequest object. Fields: name: Required. The name of the DatasetVersion resource. Format: `projects /{project}/locations/{location}/datasets/{dataset}/datasetVersions/{data set_version}` """ name = _messages.StringField(1, required=True) class AiplatformDatasetsDeleteRequest(_messages.Message): r"""A AiplatformDatasetsDeleteRequest object. Fields: name: Required. The resource name of the Dataset to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}` """ name = _messages.StringField(1, required=True) class AiplatformDatasetsGetRequest(_messages.Message): r"""A AiplatformDatasetsGetRequest object. Fields: name: Required. The name of the Dataset resource. readMask: Mask specifying which fields to read. """ name = _messages.StringField(1, required=True) readMask = _messages.StringField(2) class AiplatformDatasetsListRequest(_messages.Message): r"""A AiplatformDatasetsListRequest object. Fields: filter: An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `display_name`: supports = and != * `metadata_schema_uri`: supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels."a key"`. Some examples: * `displayName="myDisplayName"` * `labels.myKey="myValue"` orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` pageSize: The standard list page size. pageToken: The standard list page token. parent: Required. The name of the Dataset's parent resource. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5) readMask = _messages.StringField(6) class AiplatformDatasetsOperationsCancelRequest(_messages.Message): r"""A AiplatformDatasetsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsOperationsDeleteRequest(_messages.Message): r"""A AiplatformDatasetsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsOperationsGetRequest(_messages.Message): r"""A AiplatformDatasetsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsOperationsListRequest(_messages.Message): r"""A AiplatformDatasetsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformDatasetsOperationsWaitRequest(_messages.Message): r"""A AiplatformDatasetsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformDatasetsPatchRequest(_messages.Message): r"""A AiplatformDatasetsPatchRequest object. Fields: googleCloudAiplatformV1beta1Dataset: A GoogleCloudAiplatformV1beta1Dataset resource to be passed as the request body. name: Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}` updateMask: Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name` * `description` * `labels` """ googleCloudAiplatformV1beta1Dataset = _messages.MessageField('GoogleCloudAiplatformV1beta1Dataset', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformDatasetsSavedQueriesOperationsCancelRequest(_messages.Message): r"""A AiplatformDatasetsSavedQueriesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsSavedQueriesOperationsDeleteRequest(_messages.Message): r"""A AiplatformDatasetsSavedQueriesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsSavedQueriesOperationsGetRequest(_messages.Message): r"""A AiplatformDatasetsSavedQueriesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformDatasetsSavedQueriesOperationsListRequest(_messages.Message): r"""A AiplatformDatasetsSavedQueriesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformDatasetsSavedQueriesOperationsWaitRequest(_messages.Message): r"""A AiplatformDatasetsSavedQueriesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformDeploymentResourcePoolsOperationsCancelRequest(_messages.Message): r"""A AiplatformDeploymentResourcePoolsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformDeploymentResourcePoolsOperationsDeleteRequest(_messages.Message): r"""A AiplatformDeploymentResourcePoolsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformDeploymentResourcePoolsOperationsGetRequest(_messages.Message): r"""A AiplatformDeploymentResourcePoolsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformDeploymentResourcePoolsOperationsListRequest(_messages.Message): r"""A AiplatformDeploymentResourcePoolsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformDeploymentResourcePoolsOperationsWaitRequest(_messages.Message): r"""A AiplatformDeploymentResourcePoolsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformEdgeDevicesOperationsCancelRequest(_messages.Message): r"""A AiplatformEdgeDevicesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformEdgeDevicesOperationsDeleteRequest(_messages.Message): r"""A AiplatformEdgeDevicesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformEdgeDevicesOperationsGetRequest(_messages.Message): r"""A AiplatformEdgeDevicesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformEdgeDevicesOperationsListRequest(_messages.Message): r"""A AiplatformEdgeDevicesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformEdgeDevicesOperationsWaitRequest(_messages.Message): r"""A AiplatformEdgeDevicesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformEndpointsChatCompletionsRequest(_messages.Message): r"""A AiplatformEndpointsChatCompletionsRequest object. Fields: endpoint: Required. The name of the endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleApiHttpBody: A GoogleApiHttpBody resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleApiHttpBody = _messages.MessageField('GoogleApiHttpBody', 2) class AiplatformEndpointsComputeTokensRequest(_messages.Message): r"""A AiplatformEndpointsComputeTokensRequest object. Fields: endpoint: Required. The name of the Endpoint requested to get lists of tokens and token ids. googleCloudAiplatformV1beta1ComputeTokensRequest: A GoogleCloudAiplatformV1beta1ComputeTokensRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1ComputeTokensRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ComputeTokensRequest', 2) class AiplatformEndpointsCountTokensRequest(_messages.Message): r"""A AiplatformEndpointsCountTokensRequest object. Fields: endpoint: Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1CountTokensRequest: A GoogleCloudAiplatformV1beta1CountTokensRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1CountTokensRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CountTokensRequest', 2) class AiplatformEndpointsFetchPredictOperationRequest(_messages.Message): r"""A AiplatformEndpointsFetchPredictOperationRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `proje cts/{project}/locations/{location}/publishers/{publisher}/models/{model} ` googleCloudAiplatformV1beta1FetchPredictOperationRequest: A GoogleCloudAiplatformV1beta1FetchPredictOperationRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1FetchPredictOperationRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1FetchPredictOperationRequest', 2) class AiplatformEndpointsGenerateContentRequest(_messages.Message): r"""A AiplatformEndpointsGenerateContentRequest object. Fields: googleCloudAiplatformV1beta1GenerateContentRequest: A GoogleCloudAiplatformV1beta1GenerateContentRequest resource to be passed as the request body. model: Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` """ googleCloudAiplatformV1beta1GenerateContentRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateContentRequest', 1) model = _messages.StringField(2, required=True) class AiplatformEndpointsOperationsCancelRequest(_messages.Message): r"""A AiplatformEndpointsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformEndpointsOperationsDeleteRequest(_messages.Message): r"""A AiplatformEndpointsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformEndpointsOperationsGetRequest(_messages.Message): r"""A AiplatformEndpointsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformEndpointsOperationsListRequest(_messages.Message): r"""A AiplatformEndpointsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformEndpointsOperationsWaitRequest(_messages.Message): r"""A AiplatformEndpointsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformEndpointsPredictLongRunningRequest(_messages.Message): r"""A AiplatformEndpointsPredictLongRunningRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `proje cts/{project}/locations/{location}/publishers/{publisher}/models/{model} ` googleCloudAiplatformV1beta1PredictLongRunningRequest: A GoogleCloudAiplatformV1beta1PredictLongRunningRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1PredictLongRunningRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictLongRunningRequest', 2) class AiplatformEndpointsPredictRequest(_messages.Message): r"""A AiplatformEndpointsPredictRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1PredictRequest: A GoogleCloudAiplatformV1beta1PredictRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1PredictRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictRequest', 2) class AiplatformEndpointsStreamGenerateContentRequest(_messages.Message): r"""A AiplatformEndpointsStreamGenerateContentRequest object. Fields: googleCloudAiplatformV1beta1GenerateContentRequest: A GoogleCloudAiplatformV1beta1GenerateContentRequest resource to be passed as the request body. model: Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` """ googleCloudAiplatformV1beta1GenerateContentRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateContentRequest', 1) model = _messages.StringField(2, required=True) class AiplatformEvaluationItemsOperationsDeleteRequest(_messages.Message): r"""A AiplatformEvaluationItemsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformEvaluationItemsOperationsGetRequest(_messages.Message): r"""A AiplatformEvaluationItemsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformEvaluationItemsOperationsListRequest(_messages.Message): r"""A AiplatformEvaluationItemsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformEvaluationItemsOperationsWaitRequest(_messages.Message): r"""A AiplatformEvaluationItemsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformEvaluationRunsOperationsDeleteRequest(_messages.Message): r"""A AiplatformEvaluationRunsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformEvaluationRunsOperationsGetRequest(_messages.Message): r"""A AiplatformEvaluationRunsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformEvaluationRunsOperationsListRequest(_messages.Message): r"""A AiplatformEvaluationRunsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformEvaluationRunsOperationsWaitRequest(_messages.Message): r"""A AiplatformEvaluationRunsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformEvaluationSetsOperationsDeleteRequest(_messages.Message): r"""A AiplatformEvaluationSetsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformEvaluationSetsOperationsGetRequest(_messages.Message): r"""A AiplatformEvaluationSetsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformEvaluationSetsOperationsListRequest(_messages.Message): r"""A AiplatformEvaluationSetsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformEvaluationSetsOperationsWaitRequest(_messages.Message): r"""A AiplatformEvaluationSetsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformEvaluationTasksOperationsDeleteRequest(_messages.Message): r"""A AiplatformEvaluationTasksOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformEvaluationTasksOperationsGetRequest(_messages.Message): r"""A AiplatformEvaluationTasksOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformEvaluationTasksOperationsListRequest(_messages.Message): r"""A AiplatformEvaluationTasksOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformEvaluationTasksOperationsWaitRequest(_messages.Message): r"""A AiplatformEvaluationTasksOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformExampleStoresOperationsCancelRequest(_messages.Message): r"""A AiplatformExampleStoresOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformExampleStoresOperationsDeleteRequest(_messages.Message): r"""A AiplatformExampleStoresOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformExampleStoresOperationsGetRequest(_messages.Message): r"""A AiplatformExampleStoresOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformExampleStoresOperationsListRequest(_messages.Message): r"""A AiplatformExampleStoresOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformExampleStoresOperationsWaitRequest(_messages.Message): r"""A AiplatformExampleStoresOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformExtensionControllersOperationsCancelRequest(_messages.Message): r"""A AiplatformExtensionControllersOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformExtensionControllersOperationsDeleteRequest(_messages.Message): r"""A AiplatformExtensionControllersOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformExtensionControllersOperationsGetRequest(_messages.Message): r"""A AiplatformExtensionControllersOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformExtensionControllersOperationsListRequest(_messages.Message): r"""A AiplatformExtensionControllersOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformExtensionControllersOperationsWaitRequest(_messages.Message): r"""A AiplatformExtensionControllersOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformExtensionsOperationsCancelRequest(_messages.Message): r"""A AiplatformExtensionsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformExtensionsOperationsDeleteRequest(_messages.Message): r"""A AiplatformExtensionsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformExtensionsOperationsGetRequest(_messages.Message): r"""A AiplatformExtensionsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformExtensionsOperationsListRequest(_messages.Message): r"""A AiplatformExtensionsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformExtensionsOperationsWaitRequest(_messages.Message): r"""A AiplatformExtensionsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformFeatureGroupsFeatureMonitorsOperationsDeleteRequest(_messages.Message): r"""A AiplatformFeatureGroupsFeatureMonitorsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformFeatureGroupsFeatureMonitorsOperationsGetRequest(_messages.Message): r"""A AiplatformFeatureGroupsFeatureMonitorsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformFeatureGroupsFeatureMonitorsOperationsListRequest(_messages.Message): r"""A AiplatformFeatureGroupsFeatureMonitorsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformFeatureGroupsFeatureMonitorsOperationsWaitRequest(_messages.Message): r"""A AiplatformFeatureGroupsFeatureMonitorsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformFeatureGroupsFeaturesOperationsDeleteRequest(_messages.Message): r"""A AiplatformFeatureGroupsFeaturesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformFeatureGroupsFeaturesOperationsGetRequest(_messages.Message): r"""A AiplatformFeatureGroupsFeaturesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformFeatureGroupsFeaturesOperationsListRequest(_messages.Message): r"""A AiplatformFeatureGroupsFeaturesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformFeatureGroupsFeaturesOperationsWaitRequest(_messages.Message): r"""A AiplatformFeatureGroupsFeaturesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformFeatureGroupsOperationsDeleteRequest(_messages.Message): r"""A AiplatformFeatureGroupsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformFeatureGroupsOperationsGetRequest(_messages.Message): r"""A AiplatformFeatureGroupsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformFeatureGroupsOperationsListRequest(_messages.Message): r"""A AiplatformFeatureGroupsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformFeatureGroupsOperationsWaitRequest(_messages.Message): r"""A AiplatformFeatureGroupsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformFeatureOnlineStoresFeatureViewsOperationsDeleteRequest(_messages.Message): r"""A AiplatformFeatureOnlineStoresFeatureViewsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformFeatureOnlineStoresFeatureViewsOperationsGetRequest(_messages.Message): r"""A AiplatformFeatureOnlineStoresFeatureViewsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformFeatureOnlineStoresFeatureViewsOperationsListRequest(_messages.Message): r"""A AiplatformFeatureOnlineStoresFeatureViewsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformFeatureOnlineStoresFeatureViewsOperationsWaitRequest(_messages.Message): r"""A AiplatformFeatureOnlineStoresFeatureViewsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformFeatureOnlineStoresOperationsDeleteRequest(_messages.Message): r"""A AiplatformFeatureOnlineStoresOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformFeatureOnlineStoresOperationsGetRequest(_messages.Message): r"""A AiplatformFeatureOnlineStoresOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformFeatureOnlineStoresOperationsListRequest(_messages.Message): r"""A AiplatformFeatureOnlineStoresOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformFeatureOnlineStoresOperationsWaitRequest(_messages.Message): r"""A AiplatformFeatureOnlineStoresOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformFeaturestoresEntityTypesFeaturesOperationsCancelRequest(_messages.Message): r"""A AiplatformFeaturestoresEntityTypesFeaturesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformFeaturestoresEntityTypesFeaturesOperationsDeleteRequest(_messages.Message): r"""A AiplatformFeaturestoresEntityTypesFeaturesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformFeaturestoresEntityTypesFeaturesOperationsGetRequest(_messages.Message): r"""A AiplatformFeaturestoresEntityTypesFeaturesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformFeaturestoresEntityTypesFeaturesOperationsListRequest(_messages.Message): r"""A AiplatformFeaturestoresEntityTypesFeaturesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformFeaturestoresEntityTypesFeaturesOperationsWaitRequest(_messages.Message): r"""A AiplatformFeaturestoresEntityTypesFeaturesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformFeaturestoresEntityTypesOperationsCancelRequest(_messages.Message): r"""A AiplatformFeaturestoresEntityTypesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformFeaturestoresEntityTypesOperationsDeleteRequest(_messages.Message): r"""A AiplatformFeaturestoresEntityTypesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformFeaturestoresEntityTypesOperationsGetRequest(_messages.Message): r"""A AiplatformFeaturestoresEntityTypesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformFeaturestoresEntityTypesOperationsListRequest(_messages.Message): r"""A AiplatformFeaturestoresEntityTypesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformFeaturestoresEntityTypesOperationsWaitRequest(_messages.Message): r"""A AiplatformFeaturestoresEntityTypesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformFeaturestoresOperationsCancelRequest(_messages.Message): r"""A AiplatformFeaturestoresOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformFeaturestoresOperationsDeleteRequest(_messages.Message): r"""A AiplatformFeaturestoresOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformFeaturestoresOperationsGetRequest(_messages.Message): r"""A AiplatformFeaturestoresOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformFeaturestoresOperationsListRequest(_messages.Message): r"""A AiplatformFeaturestoresOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformFeaturestoresOperationsWaitRequest(_messages.Message): r"""A AiplatformFeaturestoresOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformHyperparameterTuningJobsOperationsCancelRequest(_messages.Message): r"""A AiplatformHyperparameterTuningJobsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformHyperparameterTuningJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformHyperparameterTuningJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformHyperparameterTuningJobsOperationsGetRequest(_messages.Message): r"""A AiplatformHyperparameterTuningJobsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformHyperparameterTuningJobsOperationsListRequest(_messages.Message): r"""A AiplatformHyperparameterTuningJobsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformHyperparameterTuningJobsOperationsWaitRequest(_messages.Message): r"""A AiplatformHyperparameterTuningJobsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformIndexEndpointsOperationsCancelRequest(_messages.Message): r"""A AiplatformIndexEndpointsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformIndexEndpointsOperationsDeleteRequest(_messages.Message): r"""A AiplatformIndexEndpointsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformIndexEndpointsOperationsGetRequest(_messages.Message): r"""A AiplatformIndexEndpointsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformIndexEndpointsOperationsListRequest(_messages.Message): r"""A AiplatformIndexEndpointsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformIndexEndpointsOperationsWaitRequest(_messages.Message): r"""A AiplatformIndexEndpointsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformIndexesOperationsCancelRequest(_messages.Message): r"""A AiplatformIndexesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformIndexesOperationsDeleteRequest(_messages.Message): r"""A AiplatformIndexesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformIndexesOperationsGetRequest(_messages.Message): r"""A AiplatformIndexesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformIndexesOperationsListRequest(_messages.Message): r"""A AiplatformIndexesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformIndexesOperationsWaitRequest(_messages.Message): r"""A AiplatformIndexesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformMediaUploadRequest(_messages.Message): r"""A AiplatformMediaUploadRequest object. Fields: googleCloudAiplatformV1beta1UploadRagFileRequest: A GoogleCloudAiplatformV1beta1UploadRagFileRequest resource to be passed as the request body. parent: Required. The name of the RagCorpus resource into which to upload the file. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}` """ googleCloudAiplatformV1beta1UploadRagFileRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1UploadRagFileRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformMetadataStoresArtifactsOperationsCancelRequest(_messages.Message): r"""A AiplatformMetadataStoresArtifactsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformMetadataStoresArtifactsOperationsDeleteRequest(_messages.Message): r"""A AiplatformMetadataStoresArtifactsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformMetadataStoresArtifactsOperationsGetRequest(_messages.Message): r"""A AiplatformMetadataStoresArtifactsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformMetadataStoresArtifactsOperationsListRequest(_messages.Message): r"""A AiplatformMetadataStoresArtifactsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformMetadataStoresArtifactsOperationsWaitRequest(_messages.Message): r"""A AiplatformMetadataStoresArtifactsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformMetadataStoresContextsOperationsCancelRequest(_messages.Message): r"""A AiplatformMetadataStoresContextsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformMetadataStoresContextsOperationsDeleteRequest(_messages.Message): r"""A AiplatformMetadataStoresContextsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformMetadataStoresContextsOperationsGetRequest(_messages.Message): r"""A AiplatformMetadataStoresContextsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformMetadataStoresContextsOperationsListRequest(_messages.Message): r"""A AiplatformMetadataStoresContextsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformMetadataStoresContextsOperationsWaitRequest(_messages.Message): r"""A AiplatformMetadataStoresContextsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformMetadataStoresExecutionsOperationsCancelRequest(_messages.Message): r"""A AiplatformMetadataStoresExecutionsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformMetadataStoresExecutionsOperationsDeleteRequest(_messages.Message): r"""A AiplatformMetadataStoresExecutionsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformMetadataStoresExecutionsOperationsGetRequest(_messages.Message): r"""A AiplatformMetadataStoresExecutionsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformMetadataStoresExecutionsOperationsListRequest(_messages.Message): r"""A AiplatformMetadataStoresExecutionsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformMetadataStoresExecutionsOperationsWaitRequest(_messages.Message): r"""A AiplatformMetadataStoresExecutionsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformMetadataStoresOperationsCancelRequest(_messages.Message): r"""A AiplatformMetadataStoresOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformMetadataStoresOperationsDeleteRequest(_messages.Message): r"""A AiplatformMetadataStoresOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformMetadataStoresOperationsGetRequest(_messages.Message): r"""A AiplatformMetadataStoresOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformMetadataStoresOperationsListRequest(_messages.Message): r"""A AiplatformMetadataStoresOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformMetadataStoresOperationsWaitRequest(_messages.Message): r"""A AiplatformMetadataStoresOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformMigratableResourcesOperationsCancelRequest(_messages.Message): r"""A AiplatformMigratableResourcesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformMigratableResourcesOperationsDeleteRequest(_messages.Message): r"""A AiplatformMigratableResourcesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformMigratableResourcesOperationsGetRequest(_messages.Message): r"""A AiplatformMigratableResourcesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformMigratableResourcesOperationsListRequest(_messages.Message): r"""A AiplatformMigratableResourcesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformMigratableResourcesOperationsWaitRequest(_messages.Message): r"""A AiplatformMigratableResourcesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformModelDeploymentMonitoringJobsOperationsCancelRequest(_messages.Message): r"""A AiplatformModelDeploymentMonitoringJobsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformModelDeploymentMonitoringJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformModelDeploymentMonitoringJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformModelDeploymentMonitoringJobsOperationsGetRequest(_messages.Message): r"""A AiplatformModelDeploymentMonitoringJobsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformModelDeploymentMonitoringJobsOperationsListRequest(_messages.Message): r"""A AiplatformModelDeploymentMonitoringJobsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformModelDeploymentMonitoringJobsOperationsWaitRequest(_messages.Message): r"""A AiplatformModelDeploymentMonitoringJobsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformModelMonitorsOperationsCancelRequest(_messages.Message): r"""A AiplatformModelMonitorsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformModelMonitorsOperationsDeleteRequest(_messages.Message): r"""A AiplatformModelMonitorsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformModelMonitorsOperationsGetRequest(_messages.Message): r"""A AiplatformModelMonitorsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformModelMonitorsOperationsListRequest(_messages.Message): r"""A AiplatformModelMonitorsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformModelMonitorsOperationsWaitRequest(_messages.Message): r"""A AiplatformModelMonitorsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformModelsEvaluationsOperationsCancelRequest(_messages.Message): r"""A AiplatformModelsEvaluationsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformModelsEvaluationsOperationsDeleteRequest(_messages.Message): r"""A AiplatformModelsEvaluationsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformModelsEvaluationsOperationsGetRequest(_messages.Message): r"""A AiplatformModelsEvaluationsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformModelsEvaluationsOperationsListRequest(_messages.Message): r"""A AiplatformModelsEvaluationsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformModelsEvaluationsOperationsWaitRequest(_messages.Message): r"""A AiplatformModelsEvaluationsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformModelsOperationsCancelRequest(_messages.Message): r"""A AiplatformModelsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformModelsOperationsDeleteRequest(_messages.Message): r"""A AiplatformModelsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformModelsOperationsGetRequest(_messages.Message): r"""A AiplatformModelsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformModelsOperationsListRequest(_messages.Message): r"""A AiplatformModelsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformModelsOperationsWaitRequest(_messages.Message): r"""A AiplatformModelsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformNotebookExecutionJobsOperationsCancelRequest(_messages.Message): r"""A AiplatformNotebookExecutionJobsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformNotebookExecutionJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformNotebookExecutionJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformNotebookExecutionJobsOperationsGetRequest(_messages.Message): r"""A AiplatformNotebookExecutionJobsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformNotebookExecutionJobsOperationsListRequest(_messages.Message): r"""A AiplatformNotebookExecutionJobsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformNotebookExecutionJobsOperationsWaitRequest(_messages.Message): r"""A AiplatformNotebookExecutionJobsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformNotebookRuntimeTemplatesOperationsCancelRequest(_messages.Message): r"""A AiplatformNotebookRuntimeTemplatesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformNotebookRuntimeTemplatesOperationsDeleteRequest(_messages.Message): r"""A AiplatformNotebookRuntimeTemplatesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformNotebookRuntimeTemplatesOperationsGetRequest(_messages.Message): r"""A AiplatformNotebookRuntimeTemplatesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformNotebookRuntimeTemplatesOperationsListRequest(_messages.Message): r"""A AiplatformNotebookRuntimeTemplatesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformNotebookRuntimeTemplatesOperationsWaitRequest(_messages.Message): r"""A AiplatformNotebookRuntimeTemplatesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformNotebookRuntimesOperationsCancelRequest(_messages.Message): r"""A AiplatformNotebookRuntimesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformNotebookRuntimesOperationsDeleteRequest(_messages.Message): r"""A AiplatformNotebookRuntimesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformNotebookRuntimesOperationsGetRequest(_messages.Message): r"""A AiplatformNotebookRuntimesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformNotebookRuntimesOperationsListRequest(_messages.Message): r"""A AiplatformNotebookRuntimesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformNotebookRuntimesOperationsWaitRequest(_messages.Message): r"""A AiplatformNotebookRuntimesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformOperationsCancelRequest(_messages.Message): r"""A AiplatformOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformOperationsDeleteRequest(_messages.Message): r"""A AiplatformOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformOperationsGetRequest(_messages.Message): r"""A AiplatformOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformOperationsListRequest(_messages.Message): r"""A AiplatformOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformOperationsWaitRequest(_messages.Message): r"""A AiplatformOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformPersistentResourcesOperationsCancelRequest(_messages.Message): r"""A AiplatformPersistentResourcesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformPersistentResourcesOperationsDeleteRequest(_messages.Message): r"""A AiplatformPersistentResourcesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformPersistentResourcesOperationsGetRequest(_messages.Message): r"""A AiplatformPersistentResourcesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformPersistentResourcesOperationsListRequest(_messages.Message): r"""A AiplatformPersistentResourcesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformPersistentResourcesOperationsWaitRequest(_messages.Message): r"""A AiplatformPersistentResourcesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformPipelineJobsOperationsCancelRequest(_messages.Message): r"""A AiplatformPipelineJobsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformPipelineJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformPipelineJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformPipelineJobsOperationsGetRequest(_messages.Message): r"""A AiplatformPipelineJobsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformPipelineJobsOperationsListRequest(_messages.Message): r"""A AiplatformPipelineJobsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformPipelineJobsOperationsWaitRequest(_messages.Message): r"""A AiplatformPipelineJobsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectLocationsDatasetsGetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectLocationsDatasetsGetIamPolicyRequest object. Fields: options_requestedPolicyVersion: Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). resource: REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ options_requestedPolicyVersion = _messages.IntegerField(1, variant=_messages.Variant.INT32) resource = _messages.StringField(2, required=True) class AiplatformProjectsFetchPublisherModelConfigRequest(_messages.Message): r"""A AiplatformProjectsFetchPublisherModelConfigRequest object. Fields: name: Required. The name of the publisher model, in the format of `project s/{project}/locations/{location}/publishers/{publisher}/models/{model}`. """ name = _messages.StringField(1, required=True) class AiplatformProjectsGetCacheConfigRequest(_messages.Message): r"""A AiplatformProjectsGetCacheConfigRequest object. Fields: name: Required. Name of the cache config. Format: - `projects/{project}/cacheConfig`. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsAgentsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsAgentsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsAgentsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsAgentsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsAgentsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsAgentsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsAgentsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsAgentsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsAgentsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsAgentsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsAppsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsAppsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsAppsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsAppsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsAppsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsAppsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsAppsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsAppsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsAppsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsAppsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsAugmentPromptRequest(_messages.Message): r"""A AiplatformProjectsLocationsAugmentPromptRequest object. Fields: googleCloudAiplatformV1beta1AugmentPromptRequest: A GoogleCloudAiplatformV1beta1AugmentPromptRequest resource to be passed as the request body. parent: Required. The resource name of the Location from which to augment prompt. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`. """ googleCloudAiplatformV1beta1AugmentPromptRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1AugmentPromptRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsBatchPredictionJobsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsBatchPredictionJobsCancelRequest object. Fields: googleCloudAiplatformV1beta1CancelBatchPredictionJobRequest: A GoogleCloudAiplatformV1beta1CancelBatchPredictionJobRequest resource to be passed as the request body. name: Required. The name of the BatchPredictionJob to cancel. Format: `pro jects/{project}/locations/{location}/batchPredictionJobs/{batch_predicti on_job}` """ googleCloudAiplatformV1beta1CancelBatchPredictionJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CancelBatchPredictionJobRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsBatchPredictionJobsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsBatchPredictionJobsCreateRequest object. Fields: googleCloudAiplatformV1beta1BatchPredictionJob: A GoogleCloudAiplatformV1beta1BatchPredictionJob resource to be passed as the request body. parent: Required. The resource name of the Location to create the BatchPredictionJob in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1BatchPredictionJob = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchPredictionJob', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsBatchPredictionJobsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsBatchPredictionJobsDeleteRequest object. Fields: name: Required. The name of the BatchPredictionJob resource to be deleted. Format: `projects/{project}/locations/{location}/batchPredictionJobs/{ba tch_prediction_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsBatchPredictionJobsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsBatchPredictionJobsGetRequest object. Fields: name: Required. The name of the BatchPredictionJob resource. Format: `proj ects/{project}/locations/{location}/batchPredictionJobs/{batch_predictio n_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsBatchPredictionJobsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsBatchPredictionJobsListRequest object. Fields: filter: The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `model_display_name` supports `=`, `!=` comparisons. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`<`, `<=`,`>`, `>=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state="JOB_STATE_SUCCEEDED" AND display_name:"my_job_*"` * `state!="JOB_STATE_FAILED" OR display_name="my_job"` * `NOT display_name="my_job"` * `create_time>"2021-05-18T00:00:00Z"` * `labels.keyA=valueA` * `labels.keyB:*` pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via ListBatchPredictionJobsResponse.next_page_token of the previous JobService.ListBatchPredictionJobs call. parent: Required. The resource name of the Location to list the BatchPredictionJobs from. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsCachedContentsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsCachedContentsCreateRequest object. Fields: googleCloudAiplatformV1beta1CachedContent: A GoogleCloudAiplatformV1beta1CachedContent resource to be passed as the request body. parent: Required. The parent resource where the cached content will be created """ googleCloudAiplatformV1beta1CachedContent = _messages.MessageField('GoogleCloudAiplatformV1beta1CachedContent', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsCachedContentsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsCachedContentsDeleteRequest object. Fields: name: Required. The resource name referring to the cached content """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsCachedContentsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsCachedContentsGetRequest object. Fields: name: Required. The resource name referring to the cached content """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsCachedContentsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsCachedContentsListRequest object. Fields: pageSize: Optional. The maximum number of cached contents to return. The service may return fewer than this value. If unspecified, some default (under maximum) number of items will be returned. The maximum value is 1000; values above 1000 will be coerced to 1000. pageToken: Optional. A page token, received from a previous `ListCachedContents` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `ListCachedContents` must match the call that provided the page token. parent: Required. The parent, which owns this collection of cached contents. """ pageSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) pageToken = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsCachedContentsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsCachedContentsPatchRequest object. Fields: googleCloudAiplatformV1beta1CachedContent: A GoogleCloudAiplatformV1beta1CachedContent resource to be passed as the request body. name: Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content} updateMask: Required. The list of fields to update. """ googleCloudAiplatformV1beta1CachedContent = _messages.MessageField('GoogleCloudAiplatformV1beta1CachedContent', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsCorroborateContentRequest(_messages.Message): r"""A AiplatformProjectsLocationsCorroborateContentRequest object. Fields: googleCloudAiplatformV1beta1CorroborateContentRequest: A GoogleCloudAiplatformV1beta1CorroborateContentRequest resource to be passed as the request body. parent: Required. The resource name of the Location from which to corroborate text. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`. """ googleCloudAiplatformV1beta1CorroborateContentRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CorroborateContentRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsCustomJobsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsCustomJobsCancelRequest object. Fields: googleCloudAiplatformV1beta1CancelCustomJobRequest: A GoogleCloudAiplatformV1beta1CancelCustomJobRequest resource to be passed as the request body. name: Required. The name of the CustomJob to cancel. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}` """ googleCloudAiplatformV1beta1CancelCustomJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CancelCustomJobRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsCustomJobsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsCustomJobsCreateRequest object. Fields: googleCloudAiplatformV1beta1CustomJob: A GoogleCloudAiplatformV1beta1CustomJob resource to be passed as the request body. parent: Required. The resource name of the Location to create the CustomJob in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1CustomJob = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomJob', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsCustomJobsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsCustomJobsDeleteRequest object. Fields: name: Required. The name of the CustomJob resource to be deleted. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsCustomJobsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsCustomJobsGetRequest object. Fields: name: Required. The name of the CustomJob resource. Format: `projects/{project}/locations/{location}/customJobs/{custom_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsCustomJobsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsCustomJobsListRequest object. Fields: filter: The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`<`, `<=`,`>`, `>=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state="JOB_STATE_SUCCEEDED" AND display_name:"my_job_*"` * `state!="JOB_STATE_FAILED" OR display_name="my_job"` * `NOT display_name="my_job"` * `create_time>"2021-05-18T00:00:00Z"` * `labels.keyA=valueA` * `labels.keyB:*` pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via ListCustomJobsResponse.next_page_token of the previous JobService.ListCustomJobs call. parent: Required. The resource name of the Location to list the CustomJobs from. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsCustomJobsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsCustomJobsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsCustomJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsCustomJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsCustomJobsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsCustomJobsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsCustomJobsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsCustomJobsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsCustomJobsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsCustomJobsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsDataLabelingJobsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsDataLabelingJobsCancelRequest object. Fields: googleCloudAiplatformV1beta1CancelDataLabelingJobRequest: A GoogleCloudAiplatformV1beta1CancelDataLabelingJobRequest resource to be passed as the request body. name: Required. The name of the DataLabelingJob. Format: `projects/{projec t}/locations/{location}/dataLabelingJobs/{data_labeling_job}` """ googleCloudAiplatformV1beta1CancelDataLabelingJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CancelDataLabelingJobRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsDataLabelingJobsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsDataLabelingJobsCreateRequest object. Fields: googleCloudAiplatformV1beta1DataLabelingJob: A GoogleCloudAiplatformV1beta1DataLabelingJob resource to be passed as the request body. parent: Required. The parent of the DataLabelingJob. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1DataLabelingJob = _messages.MessageField('GoogleCloudAiplatformV1beta1DataLabelingJob', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsDataLabelingJobsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsDataLabelingJobsDeleteRequest object. Fields: name: Required. The name of the DataLabelingJob to be deleted. Format: `pr ojects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_jo b}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDataLabelingJobsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsDataLabelingJobsGetRequest object. Fields: name: Required. The name of the DataLabelingJob. Format: `projects/{projec t}/locations/{location}/dataLabelingJobs/{data_labeling_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDataLabelingJobsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDataLabelingJobsListRequest object. Fields: filter: The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`<`, `<=`,`>`, `>=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state="JOB_STATE_SUCCEEDED" AND display_name:"my_job_*"` * `state!="JOB_STATE_FAILED" OR display_name="my_job"` * `NOT display_name="my_job"` * `create_time>"2021-05-18T00:00:00Z"` * `labels.keyA=valueA` * `labels.keyB:*` orderBy: A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending. pageSize: The standard list page size. pageToken: The standard list page token. parent: Required. The parent of the DataLabelingJob. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. FieldMask represents a set of symbolic field paths. For example, the mask can be `paths: "name"`. The "name" here is a field in DataLabelingJob. If this field is not set, all fields of the DataLabelingJob are returned. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsDataLabelingJobsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsDataLabelingJobsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDataLabelingJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsDataLabelingJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDataLabelingJobsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsDataLabelingJobsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDataLabelingJobsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDataLabelingJobsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsDataLabelingJobsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsDataLabelingJobsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsDatasetsAnnotationSpecsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsAnnotationSpecsGetRequest object. Fields: name: Required. The name of the AnnotationSpec resource. Format: `projects /{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{anno tation_spec}` readMask: Mask specifying which fields to read. """ name = _messages.StringField(1, required=True) readMask = _messages.StringField(2) class AiplatformProjectsLocationsDatasetsAnnotationSpecsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsAnnotationSpecsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsAnnotationSpecsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsAnnotationSpecsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsAnnotationSpecsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsAnnotationSpecsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsAnnotationSpecsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsAnnotationSpecsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsDatasetsAnnotationSpecsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsAnnotationSpecsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsDatasetsAssembleRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsAssembleRequest object. Fields: googleCloudAiplatformV1beta1AssembleDataRequest: A GoogleCloudAiplatformV1beta1AssembleDataRequest resource to be passed as the request body. name: Required. The name of the Dataset resource (used only for MULTIMODAL datasets). Format: `projects/{project}/locations/{location}/datasets/{dataset}` """ googleCloudAiplatformV1beta1AssembleDataRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1AssembleDataRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsDatasetsAssessRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsAssessRequest object. Fields: googleCloudAiplatformV1beta1AssessDataRequest: A GoogleCloudAiplatformV1beta1AssessDataRequest resource to be passed as the request body. name: Required. The name of the Dataset resource. Used only for MULTIMODAL datasets. Format: `projects/{project}/locations/{location}/datasets/{dataset}` """ googleCloudAiplatformV1beta1AssessDataRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1AssessDataRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsDatasetsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsCreateRequest object. Fields: googleCloudAiplatformV1beta1Dataset: A GoogleCloudAiplatformV1beta1Dataset resource to be passed as the request body. parent: Required. The resource name of the Location to create the Dataset in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1Dataset = _messages.MessageField('GoogleCloudAiplatformV1beta1Dataset', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsDatasetsDataItemsAnnotationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDataItemsAnnotationsListRequest object. Fields: filter: The standard list filter. orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. pageSize: The standard list page size. pageToken: The standard list page token. parent: Required. The resource name of the DataItem to list Annotations from. Format: `projects/{project}/locations/{location}/datasets/{dataset }/dataItems/{data_item}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsDatasetsDataItemsAnnotationsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDataItemsAnnotationsOperationsCance lRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsDataItemsAnnotationsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDataItemsAnnotationsOperationsDelet eRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsDataItemsAnnotationsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDataItemsAnnotationsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsDataItemsAnnotationsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDataItemsAnnotationsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsDatasetsDataItemsAnnotationsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDataItemsAnnotationsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsDatasetsDataItemsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDataItemsListRequest object. Fields: filter: The standard list filter. orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. pageSize: The standard list page size. pageToken: The standard list page token. parent: Required. The resource name of the Dataset to list DataItems from. Format: `projects/{project}/locations/{location}/datasets/{dataset}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsDatasetsDataItemsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDataItemsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsDataItemsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDataItemsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsDataItemsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDataItemsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsDataItemsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDataItemsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsDatasetsDataItemsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDataItemsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsDatasetsDatasetVersionsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDatasetVersionsCreateRequest object. Fields: googleCloudAiplatformV1beta1DatasetVersion: A GoogleCloudAiplatformV1beta1DatasetVersion resource to be passed as the request body. parent: Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}` """ googleCloudAiplatformV1beta1DatasetVersion = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetVersion', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsDatasetsDatasetVersionsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDatasetVersionsDeleteRequest object. Fields: name: Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/data setVersions/{dataset_version}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsDatasetVersionsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDatasetVersionsGetRequest object. Fields: name: Required. The resource name of the Dataset version to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}/data setVersions/{dataset_version}` readMask: Mask specifying which fields to read. """ name = _messages.StringField(1, required=True) readMask = _messages.StringField(2) class AiplatformProjectsLocationsDatasetsDatasetVersionsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDatasetVersionsListRequest object. Fields: filter: Optional. The standard list filter. orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. parent: Required. The resource name of the Dataset to list DatasetVersions from. Format: `projects/{project}/locations/{location}/datasets/{dataset}` readMask: Optional. Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsDatasetsDatasetVersionsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDatasetVersionsPatchRequest object. Fields: googleCloudAiplatformV1beta1DatasetVersion: A GoogleCloudAiplatformV1beta1DatasetVersion resource to be passed as the request body. name: Output only. Identifier. The resource name of the DatasetVersion. Format: `projects/{project}/locations/{location}/datasets/{dataset}/data setVersions/{dataset_version}` updateMask: Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name` """ googleCloudAiplatformV1beta1DatasetVersion = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetVersion', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsDatasetsDatasetVersionsRestoreRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDatasetVersionsRestoreRequest object. Fields: name: Required. The name of the DatasetVersion resource. Format: `projects /{project}/locations/{location}/datasets/{dataset}/datasetVersions/{data set_version}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsDeleteRequest object. Fields: name: Required. The resource name of the Dataset to delete. Format: `projects/{project}/locations/{location}/datasets/{dataset}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsExportRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsExportRequest object. Fields: googleCloudAiplatformV1beta1ExportDataRequest: A GoogleCloudAiplatformV1beta1ExportDataRequest resource to be passed as the request body. name: Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}` """ googleCloudAiplatformV1beta1ExportDataRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ExportDataRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsDatasetsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsGetRequest object. Fields: name: Required. The name of the Dataset resource. readMask: Mask specifying which fields to read. """ name = _messages.StringField(1, required=True) readMask = _messages.StringField(2) class AiplatformProjectsLocationsDatasetsImportRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsImportRequest object. Fields: googleCloudAiplatformV1beta1ImportDataRequest: A GoogleCloudAiplatformV1beta1ImportDataRequest resource to be passed as the request body. name: Required. The name of the Dataset resource. Format: `projects/{project}/locations/{location}/datasets/{dataset}` """ googleCloudAiplatformV1beta1ImportDataRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportDataRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsDatasetsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsListRequest object. Fields: filter: An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `display_name`: supports = and != * `metadata_schema_uri`: supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels."a key"`. Some examples: * `displayName="myDisplayName"` * `labels.myKey="myValue"` orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` pageSize: The standard list page size. pageToken: The standard list page token. parent: Required. The name of the Dataset's parent resource. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsDatasetsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsDatasetsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsDatasetsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsPatchRequest object. Fields: googleCloudAiplatformV1beta1Dataset: A GoogleCloudAiplatformV1beta1Dataset resource to be passed as the request body. name: Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}` updateMask: Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Updatable fields: * `display_name` * `description` * `labels` """ googleCloudAiplatformV1beta1Dataset = _messages.MessageField('GoogleCloudAiplatformV1beta1Dataset', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsDatasetsSavedQueriesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsSavedQueriesDeleteRequest object. Fields: name: Required. The resource name of the SavedQuery to delete. Format: `pr ojects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{s aved_query}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsSavedQueriesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsSavedQueriesListRequest object. Fields: filter: The standard list filter. orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. pageSize: The standard list page size. pageToken: The standard list page token. parent: Required. The resource name of the Dataset to list SavedQueries from. Format: `projects/{project}/locations/{location}/datasets/{dataset}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsDatasetsSavedQueriesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsSavedQueriesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsSavedQueriesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsSavedQueriesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsSavedQueriesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsSavedQueriesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDatasetsSavedQueriesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsSavedQueriesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsDatasetsSavedQueriesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsSavedQueriesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsDatasetsSearchDataItemsRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsSearchDataItemsRequest object. Fields: annotationFilters: An expression that specifies what Annotations will be returned per DataItem. Annotations satisfied either of the conditions will be returned. * `annotation_spec_id` - for = or !=. Must specify `saved_query_id=` - saved query id that annotations should belong to. annotationsFilter: An expression for filtering the Annotations that will be returned per DataItem. * `annotation_spec_id` - for = or !=. annotationsLimit: If set, only up to this many of Annotations will be returned per DataItemView. The maximum value is 1000. If not set, the maximum value will be used. dataItemFilter: An expression for filtering the DataItem that will be returned. * `data_item_id` - for = or !=. * `labeled` - for = or !=. * `has_annotation(ANNOTATION_SPEC_ID)` - true only for DataItem that have at least one annotation with annotation_spec_id = `ANNOTATION_SPEC_ID` in the context of SavedQuery or DataLabelingJob. For example: * `data_item=1` * `has_annotation(5)` dataLabelingJob: The resource name of a DataLabelingJob. Format: `projects /{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}` If this field is set, all of the search will be done in the context of this DataLabelingJob. dataset: Required. The resource name of the Dataset from which to search DataItems. Format: `projects/{project}/locations/{location}/datasets/{dataset}` fieldMask: Mask specifying which fields of DataItemView to read. orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. orderByAnnotation_orderBy: A comma-separated list of annotation fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Must also specify saved_query. orderByAnnotation_savedQuery: Required. Saved query of the Annotation. Only Annotations belong to this saved query will be considered for ordering. orderByDataItem: A comma-separated list of data item fields to order by, sorted in ascending order. Use "desc" after a field name for descending. pageSize: Requested page size. Server may return fewer results than requested. Default and maximum page size is 100. pageToken: A token identifying a page of results for the server to return Typically obtained via SearchDataItemsResponse.next_page_token of the previous DatasetService.SearchDataItems call. savedQuery: The resource name of a SavedQuery(annotation set in UI). Format: `projects/{project}/locations/{location}/datasets/{dataset}/save dQueries/{saved_query}` All of the search will be done in the context of this SavedQuery. """ annotationFilters = _messages.StringField(1, repeated=True) annotationsFilter = _messages.StringField(2) annotationsLimit = _messages.IntegerField(3, variant=_messages.Variant.INT32) dataItemFilter = _messages.StringField(4) dataLabelingJob = _messages.StringField(5) dataset = _messages.StringField(6, required=True) fieldMask = _messages.StringField(7) orderBy = _messages.StringField(8) orderByAnnotation_orderBy = _messages.StringField(9) orderByAnnotation_savedQuery = _messages.StringField(10) orderByDataItem = _messages.StringField(11) pageSize = _messages.IntegerField(12, variant=_messages.Variant.INT32) pageToken = _messages.StringField(13) savedQuery = _messages.StringField(14) class AiplatformProjectsLocationsDatasetsSetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsSetIamPolicyRequest object. Fields: googleIamV1SetIamPolicyRequest: A GoogleIamV1SetIamPolicyRequest resource to be passed as the request body. resource: REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ googleIamV1SetIamPolicyRequest = _messages.MessageField('GoogleIamV1SetIamPolicyRequest', 1) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsDatasetsTestIamPermissionsRequest(_messages.Message): r"""A AiplatformProjectsLocationsDatasetsTestIamPermissionsRequest object. Fields: permissions: The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions). resource: REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ permissions = _messages.StringField(1, repeated=True) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsDeployPublisherModelRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeployPublisherModelRequest object. Fields: destination: Required. The resource name of the Location to deploy the model in. Format: `projects/{project}/locations/{location}` googleCloudAiplatformV1beta1DeployPublisherModelRequest: A GoogleCloudAiplatformV1beta1DeployPublisherModelRequest resource to be passed as the request body. """ destination = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1DeployPublisherModelRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployPublisherModelRequest', 2) class AiplatformProjectsLocationsDeployRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeployRequest object. Fields: destination: Required. The resource name of the Location to deploy the model in. Format: `projects/{project}/locations/{location}` googleCloudAiplatformV1beta1DeployRequest: A GoogleCloudAiplatformV1beta1DeployRequest resource to be passed as the request body. """ destination = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1DeployRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployRequest', 2) class AiplatformProjectsLocationsDeploymentResourcePoolsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeploymentResourcePoolsCreateRequest object. Fields: googleCloudAiplatformV1beta1CreateDeploymentResourcePoolRequest: A GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolRequest resource to be passed as the request body. parent: Required. The parent location resource where this DeploymentResourcePool will be created. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1CreateDeploymentResourcePoolRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsDeploymentResourcePoolsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeploymentResourcePoolsDeleteRequest object. Fields: name: Required. The name of the DeploymentResourcePool to delete. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deploy ment_resource_pool}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDeploymentResourcePoolsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeploymentResourcePoolsGetRequest object. Fields: name: Required. The name of the DeploymentResourcePool to retrieve. Format: `projects/{project}/locations/{location}/deploymentResourcePools /{deployment_resource_pool}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDeploymentResourcePoolsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeploymentResourcePoolsListRequest object. Fields: pageSize: The maximum number of DeploymentResourcePools to return. The service may return fewer than this value. pageToken: A page token, received from a previous `ListDeploymentResourcePools` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `ListDeploymentResourcePools` must match the call that provided the page token. parent: Required. The parent Location which owns this collection of DeploymentResourcePools. Format: `projects/{project}/locations/{location}` """ pageSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) pageToken = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsDeploymentResourcePoolsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeploymentResourcePoolsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDeploymentResourcePoolsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeploymentResourcePoolsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDeploymentResourcePoolsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeploymentResourcePoolsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsDeploymentResourcePoolsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeploymentResourcePoolsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsDeploymentResourcePoolsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeploymentResourcePoolsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsDeploymentResourcePoolsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeploymentResourcePoolsPatchRequest object. Fields: googleCloudAiplatformV1beta1DeploymentResourcePool: A GoogleCloudAiplatformV1beta1DeploymentResourcePool resource to be passed as the request body. name: Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deploy ment_resource_pool}` updateMask: Required. The list of fields to update. """ googleCloudAiplatformV1beta1DeploymentResourcePool = _messages.MessageField('GoogleCloudAiplatformV1beta1DeploymentResourcePool', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsDeploymentResourcePoolsQueryDeployedModelsRequest(_messages.Message): r"""A AiplatformProjectsLocationsDeploymentResourcePoolsQueryDeployedModelsRequest object. Fields: deploymentResourcePool: Required. The name of the target DeploymentResourcePool to query. Format: `projects/{project}/locations/{ location}/deploymentResourcePools/{deployment_resource_pool}` pageSize: The maximum number of DeployedModels to return. The service may return fewer than this value. pageToken: A page token, received from a previous `QueryDeployedModels` call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to `QueryDeployedModels` must match the call that provided the page token. """ deploymentResourcePool = _messages.StringField(1, required=True) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) class AiplatformProjectsLocationsEdgeDevicesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsEdgeDevicesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEdgeDevicesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsEdgeDevicesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEdgeDevicesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsEdgeDevicesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEdgeDevicesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsEdgeDevicesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsEdgeDevicesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsEdgeDevicesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsEndpointsChatCompletionsRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsChatCompletionsRequest object. Fields: endpoint: Required. The name of the endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleApiHttpBody: A GoogleApiHttpBody resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleApiHttpBody = _messages.MessageField('GoogleApiHttpBody', 2) class AiplatformProjectsLocationsEndpointsComputeTokensRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsComputeTokensRequest object. Fields: endpoint: Required. The name of the Endpoint requested to get lists of tokens and token ids. googleCloudAiplatformV1beta1ComputeTokensRequest: A GoogleCloudAiplatformV1beta1ComputeTokensRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1ComputeTokensRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ComputeTokensRequest', 2) class AiplatformProjectsLocationsEndpointsCountTokensRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsCountTokensRequest object. Fields: endpoint: Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1CountTokensRequest: A GoogleCloudAiplatformV1beta1CountTokensRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1CountTokensRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CountTokensRequest', 2) class AiplatformProjectsLocationsEndpointsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsCreateRequest object. Fields: endpointId: Immutable. The ID to use for endpoint, which will become the final component of the endpoint resource name. If not provided, Vertex AI will generate a value for this ID. If the first character is a letter, this value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The last character must be a letter or number. If the first character is a number, this value may be up to 9 characters, and valid characters are `[0-9]` with no leading zeros. When using HTTP/JSON, this field is populated based on a query string argument, such as `?endpoint_id=12345`. This is the fallback for fields that are not included in either the URI or the body. googleCloudAiplatformV1beta1Endpoint: A GoogleCloudAiplatformV1beta1Endpoint resource to be passed as the request body. parent: Required. The resource name of the Location to create the Endpoint in. Format: `projects/{project}/locations/{location}` """ endpointId = _messages.StringField(1) googleCloudAiplatformV1beta1Endpoint = _messages.MessageField('GoogleCloudAiplatformV1beta1Endpoint', 2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsEndpointsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsDeleteRequest object. Fields: name: Required. The name of the Endpoint resource to be deleted. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEndpointsDeployModelRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsDeployModelRequest object. Fields: endpoint: Required. The name of the Endpoint resource into which to deploy a Model. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1DeployModelRequest: A GoogleCloudAiplatformV1beta1DeployModelRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1DeployModelRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployModelRequest', 2) class AiplatformProjectsLocationsEndpointsDeployedModelsInvokeInvokeRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsDeployedModelsInvokeInvokeRequest object. Fields: deployedModelId: ID of the DeployedModel that serves the invoke request. endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1InvokeRequest: A GoogleCloudAiplatformV1beta1InvokeRequest resource to be passed as the request body. invokeId: A string attribute. """ deployedModelId = _messages.StringField(1, required=True) endpoint = _messages.StringField(2, required=True) googleCloudAiplatformV1beta1InvokeRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1InvokeRequest', 3) invokeId = _messages.StringField(4, required=True) class AiplatformProjectsLocationsEndpointsDirectPredictRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsDirectPredictRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1DirectPredictRequest: A GoogleCloudAiplatformV1beta1DirectPredictRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1DirectPredictRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1DirectPredictRequest', 2) class AiplatformProjectsLocationsEndpointsDirectRawPredictRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsDirectRawPredictRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1DirectRawPredictRequest: A GoogleCloudAiplatformV1beta1DirectRawPredictRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1DirectRawPredictRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1DirectRawPredictRequest', 2) class AiplatformProjectsLocationsEndpointsExplainRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsExplainRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the explanation. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1ExplainRequest: A GoogleCloudAiplatformV1beta1ExplainRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1ExplainRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplainRequest', 2) class AiplatformProjectsLocationsEndpointsFetchPredictOperationRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsFetchPredictOperationRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `proje cts/{project}/locations/{location}/publishers/{publisher}/models/{model} ` googleCloudAiplatformV1beta1FetchPredictOperationRequest: A GoogleCloudAiplatformV1beta1FetchPredictOperationRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1FetchPredictOperationRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1FetchPredictOperationRequest', 2) class AiplatformProjectsLocationsEndpointsGenerateContentRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsGenerateContentRequest object. Fields: googleCloudAiplatformV1beta1GenerateContentRequest: A GoogleCloudAiplatformV1beta1GenerateContentRequest resource to be passed as the request body. model: Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` """ googleCloudAiplatformV1beta1GenerateContentRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateContentRequest', 1) model = _messages.StringField(2, required=True) class AiplatformProjectsLocationsEndpointsGetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsGetIamPolicyRequest object. Fields: options_requestedPolicyVersion: Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). resource: REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ options_requestedPolicyVersion = _messages.IntegerField(1, variant=_messages.Variant.INT32) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsEndpointsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsGetRequest object. Fields: name: Required. The name of the Endpoint resource. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEndpointsGoogleScienceInferenceRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsGoogleScienceInferenceRequest object. Fields: deployedModelId: ID of the DeployedModel that serves the invoke request. endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleApiHttpBody: A GoogleApiHttpBody resource to be passed as the request body. """ deployedModelId = _messages.StringField(1) endpoint = _messages.StringField(2, required=True) googleApiHttpBody = _messages.MessageField('GoogleApiHttpBody', 3) class AiplatformProjectsLocationsEndpointsInvokeInvokeRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsInvokeInvokeRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1InvokeRequest: A GoogleCloudAiplatformV1beta1InvokeRequest resource to be passed as the request body. invokeId: A string attribute. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1InvokeRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1InvokeRequest', 2) invokeId = _messages.StringField(3, required=True) class AiplatformProjectsLocationsEndpointsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsListRequest object. Fields: filter: Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `endpoint` supports `=` and `!=`. `endpoint` represents the Endpoint ID, i.e. the last segment of the Endpoint's resource name. * `display_name` supports `=` and `!=`. * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:*` or `labels:key` - key existence * A key including a space must be quoted. `labels."a key"`. * `base_model_name` only supports `=`. Some examples: * `endpoint=1` * `displayName="myDisplayName"` * `labels.myKey="myValue"` * `baseModelName="text-bison"` gdcZone: Optional. Configures the Google Distributed Cloud (GDC) environment for online prediction. Only set this field when the Endpoint is to be deployed in a GDC environment. pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. Typically obtained via ListEndpointsResponse.next_page_token of the previous EndpointService.ListEndpoints call. parent: Required. The resource name of the Location from which to list the Endpoints. Format: `projects/{project}/locations/{location}` readMask: Optional. Mask specifying which fields to read. """ filter = _messages.StringField(1) gdcZone = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsEndpointsMutateDeployedModelRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsMutateDeployedModelRequest object. Fields: endpoint: Required. The name of the Endpoint resource into which to mutate a DeployedModel. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1MutateDeployedModelRequest: A GoogleCloudAiplatformV1beta1MutateDeployedModelRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1MutateDeployedModelRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1MutateDeployedModelRequest', 2) class AiplatformProjectsLocationsEndpointsOpenapiEmbeddingsRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsOpenapiEmbeddingsRequest object. Fields: deployedModelId: ID of the DeployedModel that serves the invoke request. endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleApiHttpBody: A GoogleApiHttpBody resource to be passed as the request body. """ deployedModelId = _messages.StringField(1) endpoint = _messages.StringField(2, required=True) googleApiHttpBody = _messages.MessageField('GoogleApiHttpBody', 3) class AiplatformProjectsLocationsEndpointsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEndpointsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEndpointsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEndpointsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsEndpointsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsEndpointsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsPatchRequest object. Fields: googleCloudAiplatformV1beta1Endpoint: A GoogleCloudAiplatformV1beta1Endpoint resource to be passed as the request body. name: Output only. The resource name of the Endpoint. updateMask: Required. The update mask applies to the resource. See google.protobuf.FieldMask. """ googleCloudAiplatformV1beta1Endpoint = _messages.MessageField('GoogleCloudAiplatformV1beta1Endpoint', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsEndpointsPredictLongRunningRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsPredictLongRunningRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `proje cts/{project}/locations/{location}/publishers/{publisher}/models/{model} ` googleCloudAiplatformV1beta1PredictLongRunningRequest: A GoogleCloudAiplatformV1beta1PredictLongRunningRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1PredictLongRunningRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictLongRunningRequest', 2) class AiplatformProjectsLocationsEndpointsPredictRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsPredictRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1PredictRequest: A GoogleCloudAiplatformV1beta1PredictRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1PredictRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictRequest', 2) class AiplatformProjectsLocationsEndpointsRawPredictRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsRawPredictRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1RawPredictRequest: A GoogleCloudAiplatformV1beta1RawPredictRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1RawPredictRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RawPredictRequest', 2) class AiplatformProjectsLocationsEndpointsServerStreamingPredictRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsServerStreamingPredictRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1StreamingPredictRequest: A GoogleCloudAiplatformV1beta1StreamingPredictRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1StreamingPredictRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1StreamingPredictRequest', 2) class AiplatformProjectsLocationsEndpointsSetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsSetIamPolicyRequest object. Fields: googleIamV1SetIamPolicyRequest: A GoogleIamV1SetIamPolicyRequest resource to be passed as the request body. resource: REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ googleIamV1SetIamPolicyRequest = _messages.MessageField('GoogleIamV1SetIamPolicyRequest', 1) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsEndpointsStreamGenerateContentRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsStreamGenerateContentRequest object. Fields: googleCloudAiplatformV1beta1GenerateContentRequest: A GoogleCloudAiplatformV1beta1GenerateContentRequest resource to be passed as the request body. model: Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` """ googleCloudAiplatformV1beta1GenerateContentRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateContentRequest', 1) model = _messages.StringField(2, required=True) class AiplatformProjectsLocationsEndpointsStreamRawPredictRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsStreamRawPredictRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1StreamRawPredictRequest: A GoogleCloudAiplatformV1beta1StreamRawPredictRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1StreamRawPredictRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1StreamRawPredictRequest', 2) class AiplatformProjectsLocationsEndpointsTestIamPermissionsRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsTestIamPermissionsRequest object. Fields: permissions: The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions). resource: REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ permissions = _messages.StringField(1, repeated=True) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsEndpointsUndeployModelRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsUndeployModelRequest object. Fields: endpoint: Required. The name of the Endpoint resource from which to undeploy a Model. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1UndeployModelRequest: A GoogleCloudAiplatformV1beta1UndeployModelRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1UndeployModelRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1UndeployModelRequest', 2) class AiplatformProjectsLocationsEndpointsUpdateRequest(_messages.Message): r"""A AiplatformProjectsLocationsEndpointsUpdateRequest object. Fields: googleCloudAiplatformV1beta1UpdateEndpointLongRunningRequest: A GoogleCloudAiplatformV1beta1UpdateEndpointLongRunningRequest resource to be passed as the request body. name: Output only. The resource name of the Endpoint. """ googleCloudAiplatformV1beta1UpdateEndpointLongRunningRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1UpdateEndpointLongRunningRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsEvaluateDatasetRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluateDatasetRequest object. Fields: googleCloudAiplatformV1beta1EvaluateDatasetRequest: A GoogleCloudAiplatformV1beta1EvaluateDatasetRequest resource to be passed as the request body. location: Required. The resource name of the Location to evaluate the dataset. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1EvaluateDatasetRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluateDatasetRequest', 1) location = _messages.StringField(2, required=True) class AiplatformProjectsLocationsEvaluateInstancesRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluateInstancesRequest object. Fields: googleCloudAiplatformV1beta1EvaluateInstancesRequest: A GoogleCloudAiplatformV1beta1EvaluateInstancesRequest resource to be passed as the request body. location: Required. The resource name of the Location to evaluate the instances. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1EvaluateInstancesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluateInstancesRequest', 1) location = _messages.StringField(2, required=True) class AiplatformProjectsLocationsEvaluationItemsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationItemsCreateRequest object. Fields: googleCloudAiplatformV1beta1EvaluationItem: A GoogleCloudAiplatformV1beta1EvaluationItem resource to be passed as the request body. parent: Required. The resource name of the Location to create the Evaluation Item in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1EvaluationItem = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationItem', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsEvaluationItemsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationItemsDeleteRequest object. Fields: name: Required. The name of the EvaluationItem resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationItems/{evalua tion_item}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationItemsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationItemsGetRequest object. Fields: name: Required. The name of the EvaluationItem resource. Format: `projects /{project}/locations/{location}/evaluationItems/{evaluation_item}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationItemsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationItemsListRequest object. Fields: filter: Optional. Filter expression that matches a subset of the EvaluationItems to show. For field names both snake_case and camelCase are supported. For more information about filter syntax, see [AIP-160](https://google.aip.dev/160). orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending. pageSize: Optional. The maximum number of Evaluation Items to return. pageToken: Optional. A page token, received from a previous `ListEvaluationItems` call. Provide this to retrieve the subsequent page. parent: Required. The resource name of the Location from which to list the Evaluation Items. Format: `projects/{project}/locations/{location}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsEvaluationItemsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationItemsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationItemsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationItemsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationItemsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationItemsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsEvaluationItemsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationItemsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsEvaluationRunsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationRunsCancelRequest object. Fields: googleCloudAiplatformV1beta1CancelEvaluationRunRequest: A GoogleCloudAiplatformV1beta1CancelEvaluationRunRequest resource to be passed as the request body. name: Required. The name of the EvaluationRun resource to be cancelled. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluat ion_run}` """ googleCloudAiplatformV1beta1CancelEvaluationRunRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CancelEvaluationRunRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsEvaluationRunsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationRunsCreateRequest object. Fields: googleCloudAiplatformV1beta1EvaluationRun: A GoogleCloudAiplatformV1beta1EvaluationRun resource to be passed as the request body. parent: Required. The resource name of the Location to create the Evaluation Run in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1EvaluationRun = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRun', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsEvaluationRunsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationRunsDeleteRequest object. Fields: name: Required. The name of the EvaluationRun resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluat ion_run}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationRunsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationRunsGetRequest object. Fields: name: Required. The name of the EvaluationRun resource. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluation_run} ` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationRunsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationRunsListRequest object. Fields: filter: Optional. Filter expression that matches a subset of the EvaluationRuns to show. For field names both snake_case and camelCase are supported. For more information about filter syntax, see [AIP-160](https://google.aip.dev/160). orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending. pageSize: Optional. The maximum number of Evaluation Runs to return. pageToken: Optional. A page token, received from a previous `ListEvaluationRuns` call. Provide this to retrieve the subsequent page. parent: Required. The resource name of the Location from which to list the Evaluation Runs. Format: `projects/{project}/locations/{location}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsEvaluationRunsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationRunsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationRunsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationRunsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationRunsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationRunsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsEvaluationRunsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationRunsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsEvaluationSetsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationSetsCreateRequest object. Fields: googleCloudAiplatformV1beta1EvaluationSet: A GoogleCloudAiplatformV1beta1EvaluationSet resource to be passed as the request body. parent: Required. The resource name of the Location to create the Evaluation Set in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1EvaluationSet = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationSet', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsEvaluationSetsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationSetsDeleteRequest object. Fields: name: Required. The name of the EvaluationSet resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluat ion_set}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationSetsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationSetsGetRequest object. Fields: name: Required. The name of the EvaluationSet resource. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set} ` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationSetsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationSetsListRequest object. Fields: filter: Optional. Filter expression that matches a subset of the EvaluationSets to show. For field names both snake_case and camelCase are supported. For more information about filter syntax, see [AIP-160](https://google.aip.dev/160). orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending. pageSize: Optional. The maximum number of Evaluation Sets to return. pageToken: Optional. A page token, received from a previous `ListEvaluationSets` call. Provide this to retrieve the subsequent page. parent: Required. The resource name of the Location from which to list the Evaluation Sets. Format: `projects/{project}/locations/{location}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsEvaluationSetsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationSetsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationSetsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationSetsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationSetsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationSetsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsEvaluationSetsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationSetsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsEvaluationSetsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationSetsPatchRequest object. Fields: googleCloudAiplatformV1beta1EvaluationSet: A GoogleCloudAiplatformV1beta1EvaluationSet resource to be passed as the request body. name: Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set} ` updateMask: Optional. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. """ googleCloudAiplatformV1beta1EvaluationSet = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationSet', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsEvaluationTasksOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationTasksOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationTasksOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationTasksOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsEvaluationTasksOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationTasksOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsEvaluationTasksOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsEvaluationTasksOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsExampleStoresCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresCreateRequest object. Fields: exampleStore_createTime: Output only. Timestamp when this ExampleStore was created. exampleStore_description: Optional. Description of the ExampleStore. exampleStore_displayName: Required. Display name of the ExampleStore. exampleStore_exampleStoreConfig_vertexEmbeddingModel: Required. The embedding model to be used for vector embedding. Immutable. Supported models: * "text-embedding-005" * "text-multilingual-embedding-002" exampleStore_name: Identifier. The resource name of the ExampleStore. This is a unique identifier. Format: projects/{project}/locations/{location}/exampleStores/{example_store} exampleStore_updateTime: Output only. Timestamp when this ExampleStore was most recently updated. parent: Required. The resource name of the Location to create the ExampleStore in. Format: `projects/{project}/locations/{location}` """ exampleStore_createTime = _messages.StringField(1) exampleStore_description = _messages.StringField(2) exampleStore_displayName = _messages.StringField(3) exampleStore_exampleStoreConfig_vertexEmbeddingModel = _messages.StringField(4) exampleStore_name = _messages.StringField(5) exampleStore_updateTime = _messages.StringField(6) parent = _messages.StringField(7, required=True) class AiplatformProjectsLocationsExampleStoresDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresDeleteRequest object. Fields: name: Required. The resource name of the ExampleStore to be deleted. Format: `projects/{project}/locations/{location}/exampleStores/{example_store}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExampleStoresFetchExamplesRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresFetchExamplesRequest object. Fields: exampleStore: Required. The name of the ExampleStore resource that the examples should be fetched from. Format: `projects/{project}/locations/{location}/exampleStores/{example_store}` googleCloudAiplatformV1beta1FetchExamplesRequest: A GoogleCloudAiplatformV1beta1FetchExamplesRequest resource to be passed as the request body. """ exampleStore = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1FetchExamplesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1FetchExamplesRequest', 2) class AiplatformProjectsLocationsExampleStoresGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresGetRequest object. Fields: name: Required. The resource name of the ExampleStore. Format: `projects/{project}/locations/{location}/exampleStores/{example_store}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExampleStoresListRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresListRequest object. Fields: filter: Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. parent: Required. The resource name of the Location to list the ExampleStores from. Format: `projects/{project}/locations/{location}` """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) class AiplatformProjectsLocationsExampleStoresOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExampleStoresOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExampleStoresOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExampleStoresOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsExampleStoresOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsExampleStoresPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresPatchRequest object. Fields: googleCloudAiplatformV1beta1ExampleStore: A GoogleCloudAiplatformV1beta1ExampleStore resource to be passed as the request body. name: Identifier. The resource name of the ExampleStore. This is a unique identifier. Format: projects/{project}/locations/{location}/exampleStores/{example_store} updateMask: Optional. Mask specifying which fields to update. Supported fields: * `display_name` * `description` """ googleCloudAiplatformV1beta1ExampleStore = _messages.MessageField('GoogleCloudAiplatformV1beta1ExampleStore', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsExampleStoresRemoveExamplesRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresRemoveExamplesRequest object. Fields: exampleStore: Required. The name of the ExampleStore resource that the examples should be removed from. Format: `projects/{project}/locations/{location}/exampleStores/{example_store}` googleCloudAiplatformV1beta1RemoveExamplesRequest: A GoogleCloudAiplatformV1beta1RemoveExamplesRequest resource to be passed as the request body. """ exampleStore = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1RemoveExamplesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RemoveExamplesRequest', 2) class AiplatformProjectsLocationsExampleStoresSearchExamplesRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresSearchExamplesRequest object. Fields: exampleStore: Required. The name of the ExampleStore resource that examples are retrieved from. Format: `projects/{project}/locations/{location}/exampleStores/{example_store}` googleCloudAiplatformV1beta1SearchExamplesRequest: A GoogleCloudAiplatformV1beta1SearchExamplesRequest resource to be passed as the request body. """ exampleStore = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1SearchExamplesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1SearchExamplesRequest', 2) class AiplatformProjectsLocationsExampleStoresUpsertExamplesRequest(_messages.Message): r"""A AiplatformProjectsLocationsExampleStoresUpsertExamplesRequest object. Fields: exampleStore: Required. The name of the ExampleStore resource that examples are added to or updated in. Format: `projects/{project}/locations/{location}/exampleStores/{example_store}` googleCloudAiplatformV1beta1UpsertExamplesRequest: A GoogleCloudAiplatformV1beta1UpsertExamplesRequest resource to be passed as the request body. """ exampleStore = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1UpsertExamplesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1UpsertExamplesRequest', 2) class AiplatformProjectsLocationsExtensionControllersOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionControllersOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExtensionControllersOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionControllersOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExtensionControllersOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionControllersOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExtensionControllersOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionControllersOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsExtensionControllersOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionControllersOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsExtensionsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionsDeleteRequest object. Fields: name: Required. The name of the Extension resource to be deleted. Format: `projects/{project}/locations/{location}/extensions/{extension}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExtensionsExecuteRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionsExecuteRequest object. Fields: googleCloudAiplatformV1beta1ExecuteExtensionRequest: A GoogleCloudAiplatformV1beta1ExecuteExtensionRequest resource to be passed as the request body. name: Required. Name (identifier) of the extension; Format: `projects/{project}/locations/{location}/extensions/{extension}` """ googleCloudAiplatformV1beta1ExecuteExtensionRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ExecuteExtensionRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsExtensionsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionsGetRequest object. Fields: name: Required. The name of the Extension resource. Format: `projects/{project}/locations/{location}/extensions/{extension}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExtensionsImportRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionsImportRequest object. Fields: googleCloudAiplatformV1beta1Extension: A GoogleCloudAiplatformV1beta1Extension resource to be passed as the request body. parent: Required. The resource name of the Location to import the Extension in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1Extension = _messages.MessageField('GoogleCloudAiplatformV1beta1Extension', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsExtensionsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionsListRequest object. Fields: filter: Optional. The standard list filter. Supported fields: * `display_name` * `create_time` * `update_time` More detail in [AIP-160](https://google.aip.dev/160). orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`. pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. parent: Required. The resource name of the Location to list the Extensions from. Format: `projects/{project}/locations/{location}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsExtensionsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExtensionsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExtensionsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsExtensionsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsExtensionsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsExtensionsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionsPatchRequest object. Fields: googleCloudAiplatformV1beta1Extension: A GoogleCloudAiplatformV1beta1Extension resource to be passed as the request body. name: Identifier. The resource name of the Extension. updateMask: Required. Mask specifying which fields to update. Supported fields: * `display_name` * `description` * `runtime_config` * `tool_use_examples` * `manifest.description` """ googleCloudAiplatformV1beta1Extension = _messages.MessageField('GoogleCloudAiplatformV1beta1Extension', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsExtensionsQueryRequest(_messages.Message): r"""A AiplatformProjectsLocationsExtensionsQueryRequest object. Fields: googleCloudAiplatformV1beta1QueryExtensionRequest: A GoogleCloudAiplatformV1beta1QueryExtensionRequest resource to be passed as the request body. name: Required. Name (identifier) of the extension; Format: `projects/{project}/locations/{location}/extensions/{extension}` """ googleCloudAiplatformV1beta1QueryExtensionRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1QueryExtensionRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeatureGroupsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsCreateRequest object. Fields: featureGroupId: Required. The ID to use for this FeatureGroup, which will become the final component of the FeatureGroup's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location. googleCloudAiplatformV1beta1FeatureGroup: A GoogleCloudAiplatformV1beta1FeatureGroup resource to be passed as the request body. parent: Required. The resource name of the Location to create FeatureGroups. Format: `projects/{project}/locations/{location}` """ featureGroupId = _messages.StringField(1) googleCloudAiplatformV1beta1FeatureGroup = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureGroup', 2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsFeatureGroupsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsDeleteRequest object. Fields: force: If set to true, any Features under this FeatureGroup will also be deleted. (Otherwise, the request will only work if the FeatureGroup has no Features.) name: Required. The name of the FeatureGroup to be deleted. Format: `projects/{project}/locations/{location}/featureGroups/{feature_group}` """ force = _messages.BooleanField(1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsCreateRequest object. Fields: featureMonitorId: Required. The ID to use for this FeatureMonitor, which will become the final component of the FeatureGroup's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the FeatureGroup. googleCloudAiplatformV1beta1FeatureMonitor: A GoogleCloudAiplatformV1beta1FeatureMonitor resource to be passed as the request body. parent: Required. The resource name of FeatureGroup to create FeatureMonitor. Format: `projects/{project}/locations/{location}/featureGroups/{featuregroup}` """ featureMonitorId = _messages.StringField(1) googleCloudAiplatformV1beta1FeatureMonitor = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureMonitor', 2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsDeleteRequest object. Fields: name: Required. The name of the FeatureMonitor to be deleted. Format: `pro jects/{project}/locations/{location}/featureGroups/{feature_group}/featu reMonitors/{feature_monitor}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsFeatureMonitorJobsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsFeatureMonitorJ obsCreateRequest object. Fields: featureMonitorJobId: Optional. Output only. System-generated ID for feature monitor job. googleCloudAiplatformV1beta1FeatureMonitorJob: A GoogleCloudAiplatformV1beta1FeatureMonitorJob resource to be passed as the request body. parent: Required. The resource name of FeatureMonitor to create FeatureMonitorJob. Format: `projects/{project}/locations/{location}/feat ureGroups/{feature_group}/featureMonitors/{feature_monitor}` """ featureMonitorJobId = _messages.IntegerField(1) googleCloudAiplatformV1beta1FeatureMonitorJob = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureMonitorJob', 2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsFeatureMonitorJobsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsFeatureMonitorJ obsGetRequest object. Fields: name: Required. The name of the FeatureMonitorJob resource. Format: `proje cts/{project}/locations/{location}/featureGroups/{feature_group}/feature Monitors/{feature_monitor}/featureMonitorJobs/{feature_monitor_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsFeatureMonitorJobsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsFeatureMonitorJ obsListRequest object. Fields: filter: Optional. Lists the FeatureMonitorJobs that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be Examples: * `create_time > "2020-01-01"` FeatureMonitorJobs created after 2020-01-01. orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported Fields: * `create_time` pageSize: Optional. The maximum number of FeatureMonitorJobs to return. The service may return fewer than this value. If unspecified, at most 100 FeatureMonitorJobs will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100. pageToken: Optional. A page token, received from a previous FeatureRegistryService.ListFeatureMonitorJobs call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureRegistryService.ListFeatureMonitorJobs must match the call that provided the page token. parent: Required. The resource name of the FeatureMonitor to list FeatureMonitorJobs. Format: `projects/{project}/locations/{location}/fea tureGroups/{feature_group}/featureMonitors/{feature_monitor}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsGetRequest object. Fields: name: Required. The name of the FeatureMonitor resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsListRequest object. Fields: filter: Optional. Lists the FeatureMonitors that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. Examples: * `create_time > "2020-01-01" OR update_time > "2020-01-01"` FeatureMonitors created or updated after 2020-01-01. * `labels.env = "prod"` FeatureGroups with label "env" set to "prod". orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported Fields: * `create_time` * `update_time` pageSize: Optional. The maximum number of FeatureGroups to return. The service may return fewer than this value. If unspecified, at most 100 FeatureMonitors will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100. pageToken: Optional. A page token, received from a previous FeatureRegistryService.ListFeatureMonitors call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureRegistryService.ListFeatureMonitors must match the call that provided the page token. parent: Required. The resource name of the FeatureGroup to list FeatureMonitors. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsOperationsDelet eRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeatureMonitorsPatchRequest object. Fields: googleCloudAiplatformV1beta1FeatureMonitor: A GoogleCloudAiplatformV1beta1FeatureMonitor resource to be passed as the request body. name: Identifier. Name of the FeatureMonitor. Format: `projects/{project}/ locations/{location}/featureGroups/{featureGroup}/featureMonitors/{featu reMonitor}` updateMask: Optional. Field mask is used to specify the fields to be overwritten in the FeatureMonitor resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `description` * `schedule_config` * `feature_selection_config` """ googleCloudAiplatformV1beta1FeatureMonitor = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureMonitor', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsFeatureGroupsFeaturesBatchCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeaturesBatchCreateRequest object. Fields: googleCloudAiplatformV1beta1BatchCreateFeaturesRequest: A GoogleCloudAiplatformV1beta1BatchCreateFeaturesRequest resource to be passed as the request body. parent: Required. The resource name of the EntityType/FeatureGroup to create the batch of Features under. Format: `projects/{project}/location s/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` `projects/{project}/locations/{location}/featureGroups/{feature_group}` """ googleCloudAiplatformV1beta1BatchCreateFeaturesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchCreateFeaturesRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeatureGroupsFeaturesCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeaturesCreateRequest object. Fields: featureId: Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup. googleCloudAiplatformV1beta1Feature: A GoogleCloudAiplatformV1beta1Feature resource to be passed as the request body. parent: Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/ locations/{location}/featurestores/{featurestore}/entityTypes/{entity_ty pe}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}` """ featureId = _messages.StringField(1) googleCloudAiplatformV1beta1Feature = _messages.MessageField('GoogleCloudAiplatformV1beta1Feature', 2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsFeatureGroupsFeaturesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeaturesDeleteRequest object. Fields: name: Required. The name of the Features to be deleted. Format: `projects/ {project}/locations/{location}/featurestores/{featurestore}/entityTypes/ {entity_type}/features/{feature}` `projects/{project}/locations/{locatio n}/featureGroups/{feature_group}/features/{feature}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureGroupsFeaturesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeaturesGetRequest object. Fields: featureStatsAndAnomalySpec_latestStatsCount: Optional. If set, returns the most recent count of stats. Valid value is [0, 100]. If stats_time_range is set, return most recent count of stats within the stats_time_range. featureStatsAndAnomalySpec_statsTimeRange_endTime: Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end. featureStatsAndAnomalySpec_statsTimeRange_startTime: Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start. name: Required. The name of the Feature resource. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featu restore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}` """ featureStatsAndAnomalySpec_latestStatsCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) featureStatsAndAnomalySpec_statsTimeRange_endTime = _messages.StringField(2) featureStatsAndAnomalySpec_statsTimeRange_startTime = _messages.StringField(3) name = _messages.StringField(4, required=True) class AiplatformProjectsLocationsFeatureGroupsFeaturesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeaturesListRequest object. Fields: filter: Lists the Features that match the filter expression. The following filters are supported: * `value_type`: Supports = and != comparisons. * `create_time`: Supports =, !=, <, >, >=, and <= comparisons. Values must be in RFC 3339 format. * `update_time`: Supports =, !=, <, >, >=, and <= comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `value_type = DOUBLE` --> Features whose type is DOUBLE. * `create_time > \"2020-01-31T15:30:00.000000Z\" OR update_time > \"2020-01-31T15:30:00.000000Z\"` --> EntityTypes created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --> Features having both (active: yes) and (env: prod) labels. * `labels.env: *` --> Any Feature which has a label with 'env' as the key. latestStatsCount: Only applicable for Vertex AI Feature Store (Legacy). If set, return the most recent ListFeaturesRequest.latest_stats_count of stats for each Feature in response. Valid value is [0, 10]. If number of stats exists < ListFeaturesRequest.latest_stats_count, return all existing stats. orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `feature_id` * `value_type` (Not supported for FeatureRegistry Feature) * `create_time` * `update_time` pageSize: The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 1000 Features will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000. pageToken: A page token, received from a previous FeaturestoreService.ListFeatures call or FeatureRegistryService.ListFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeatures or FeatureRegistryService.ListFeatures must match the call that provided the page token. parent: Required. The resource name of the Location to list Features. Format for entity_type as parent: `projects/{project}/locations/{locatio n}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) latestStatsCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) orderBy = _messages.StringField(3) pageSize = _messages.IntegerField(4, variant=_messages.Variant.INT32) pageToken = _messages.StringField(5) parent = _messages.StringField(6, required=True) readMask = _messages.StringField(7) class AiplatformProjectsLocationsFeatureGroupsFeaturesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeaturesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureGroupsFeaturesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeaturesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureGroupsFeaturesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeaturesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsFeatureGroupsFeaturesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeaturesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsFeatureGroupsFeaturesPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsFeaturesPatchRequest object. Fields: googleCloudAiplatformV1beta1Feature: A GoogleCloudAiplatformV1beta1Feature resource to be passed as the request body. name: Immutable. Name of the Feature. Format: `projects/{project}/location s/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/feat ures/{feature}` `projects/{project}/locations/{location}/featureGroups/{ feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type. updateMask: Field mask is used to specify the fields to be overwritten in the Features resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `disable_monitoring` (Not supported for FeatureRegistryService Feature) * `point_of_contact` (Not supported for FeaturestoreService FeatureStore) """ googleCloudAiplatformV1beta1Feature = _messages.MessageField('GoogleCloudAiplatformV1beta1Feature', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsFeatureGroupsGetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsGetIamPolicyRequest object. Fields: options_requestedPolicyVersion: Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). resource: REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ options_requestedPolicyVersion = _messages.IntegerField(1, variant=_messages.Variant.INT32) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeatureGroupsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsGetRequest object. Fields: name: Required. The name of the FeatureGroup resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureGroupsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsListRequest object. Fields: filter: Lists the FeatureGroups that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. Examples: * `create_time > "2020-01-01" OR update_time > "2020-01-01"` FeatureGroups created or updated after 2020-01-01. * `labels.env = "prod"` FeatureGroups with label "env" set to "prod". orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported Fields: * `create_time` * `update_time` pageSize: The maximum number of FeatureGroups to return. The service may return fewer than this value. If unspecified, at most 100 FeatureGroups will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100. pageToken: A page token, received from a previous FeatureRegistryService.ListFeatureGroups call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureRegistryService.ListFeatureGroups must match the call that provided the page token. parent: Required. The resource name of the Location to list FeatureGroups. Format: `projects/{project}/locations/{location}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsFeatureGroupsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureGroupsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureGroupsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsFeatureGroupsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsFeatureGroupsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsPatchRequest object. Fields: googleCloudAiplatformV1beta1FeatureGroup: A GoogleCloudAiplatformV1beta1FeatureGroup resource to be passed as the request body. name: Identifier. Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}` updateMask: Field mask is used to specify the fields to be overwritten in the FeatureGroup resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `description` * `big_query` * `big_query.entity_id_columns` * `service_agent_type` """ googleCloudAiplatformV1beta1FeatureGroup = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureGroup', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsFeatureGroupsSetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsSetIamPolicyRequest object. Fields: googleIamV1SetIamPolicyRequest: A GoogleIamV1SetIamPolicyRequest resource to be passed as the request body. resource: REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ googleIamV1SetIamPolicyRequest = _messages.MessageField('GoogleIamV1SetIamPolicyRequest', 1) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeatureGroupsTestIamPermissionsRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureGroupsTestIamPermissionsRequest object. Fields: permissions: The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions). resource: REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ permissions = _messages.StringField(1, repeated=True) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresCreateRequest object. Fields: featureOnlineStoreId: Required. The ID to use for this FeatureOnlineStore, which will become the final component of the FeatureOnlineStore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location. googleCloudAiplatformV1beta1FeatureOnlineStore: A GoogleCloudAiplatformV1beta1FeatureOnlineStore resource to be passed as the request body. parent: Required. The resource name of the Location to create FeatureOnlineStores. Format: `projects/{project}/locations/{location}` """ featureOnlineStoreId = _messages.StringField(1) googleCloudAiplatformV1beta1FeatureOnlineStore = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureOnlineStore', 2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresDeleteRequest object. Fields: force: If set to true, any FeatureViews and Features for this FeatureOnlineStore will also be deleted. (Otherwise, the request will only work if the FeatureOnlineStore has no FeatureViews.) name: Required. The name of the FeatureOnlineStore to be deleted. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_on line_store}` """ force = _messages.BooleanField(1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsCreateRequest object. Fields: featureViewId: Required. The ID to use for the FeatureView, which will become the final component of the FeatureView's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a FeatureOnlineStore. googleCloudAiplatformV1beta1FeatureView: A GoogleCloudAiplatformV1beta1FeatureView resource to be passed as the request body. parent: Required. The resource name of the FeatureOnlineStore to create FeatureViews. Format: `projects/{project}/locations/{location}/featureOn lineStores/{feature_online_store}` runSyncImmediately: Immutable. If set to true, one on demand sync will be run immediately, regardless whether the FeatureView.sync_config is configured or not. """ featureViewId = _messages.StringField(1) googleCloudAiplatformV1beta1FeatureView = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureView', 2) parent = _messages.StringField(3, required=True) runSyncImmediately = _messages.BooleanField(4) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsDeleteRequest object. Fields: name: Required. The name of the FeatureView to be deleted. Format: `projec ts/{project}/locations/{location}/featureOnlineStores/{feature_online_st ore}/featureViews/{feature_view}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsDirectWriteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsDirectWriteRequest object. Fields: featureView: FeatureView resource format `projects/{project}/locations/{lo cation}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureVi ew}` googleCloudAiplatformV1beta1FeatureViewDirectWriteRequest: A GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequest resource to be passed as the request body. """ featureView = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1FeatureViewDirectWriteRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequest', 2) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsFeatureViewSyncsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsFeatureViewS yncsGetRequest object. Fields: name: Required. The name of the FeatureViewSync resource. Format: `project s/{project}/locations/{location}/featureOnlineStores/{feature_online_sto re}/featureViews/{feature_view}/featureViewSyncs/{feature_view_sync}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsFeatureViewSyncsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsFeatureViewS yncsListRequest object. Fields: filter: Lists the FeatureViewSyncs that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `<`, `>`, `>=`, and `<=` comparisons. Values must be in RFC 3339 format. Examples: * `create_time > \"2020-01-31T15:30:00.000000Z\"` --> FeatureViewSyncs created after 2020-01-31T15:30:00.000000Z. orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `create_time` pageSize: The maximum number of FeatureViewSyncs to return. The service may return fewer than this value. If unspecified, at most 1000 FeatureViewSyncs will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000. pageToken: A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureViewSyncs call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureViewSyncs must match the call that provided the page token. parent: Required. The resource name of the FeatureView to list FeatureViewSyncs. Format: `projects/{project}/locations/{location}/featu reOnlineStores/{feature_online_store}/featureViews/{feature_view}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsFetchFeatureValuesRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsFetchFeature ValuesRequest object. Fields: featureView: Required. FeatureView resource format `projects/{project}/loc ations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/ {featureView}` googleCloudAiplatformV1beta1FetchFeatureValuesRequest: A GoogleCloudAiplatformV1beta1FetchFeatureValuesRequest resource to be passed as the request body. """ featureView = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1FetchFeatureValuesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1FetchFeatureValuesRequest', 2) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsGenerateFetchAccessTokenRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsGenerateFetc hAccessTokenRequest object. Fields: featureView: FeatureView resource format `projects/{project}/locations/{lo cation}/featureOnlineStores/{featureOnlineStore}/featureViews/{featureVi ew}` googleCloudAiplatformV1beta1GenerateFetchAccessTokenRequest: A GoogleCloudAiplatformV1beta1GenerateFetchAccessTokenRequest resource to be passed as the request body. """ featureView = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1GenerateFetchAccessTokenRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateFetchAccessTokenRequest', 2) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsGetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsGetIamPolicy Request object. Fields: options_requestedPolicyVersion: Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). resource: REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ options_requestedPolicyVersion = _messages.IntegerField(1, variant=_messages.Variant.INT32) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsGetRequest object. Fields: name: Required. The name of the FeatureView resource. Format: `projects/{p roject}/locations/{location}/featureOnlineStores/{feature_online_store}/ featureViews/{feature_view}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsListRequest object. Fields: filter: Lists the FeatureViews that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `<`, `>`, `>=`, and `<=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `<`, `>`, `>=`, and `<=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `create_time > \"2020-01-31T15:30:00.000000Z\" OR update_time > \"2020-01-31T15:30:00.000000Z\"` --> FeatureViews created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --> FeatureViews having both (active: yes) and (env: prod) labels. * `labels.env: *` --> Any FeatureView which has a label with 'env' as the key. orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `feature_view_id` * `create_time` * `update_time` pageSize: The maximum number of FeatureViews to return. The service may return fewer than this value. If unspecified, at most 1000 FeatureViews will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000. pageToken: A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureViews call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureViews must match the call that provided the page token. parent: Required. The resource name of the FeatureOnlineStore to list FeatureViews. Format: `projects/{project}/locations/{location}/featureOn lineStores/{feature_online_store}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsOperationsDe leteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsOperationsGe tRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsOperationsLi stRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsOperationsWa itRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsPatchRequest object. Fields: googleCloudAiplatformV1beta1FeatureView: A GoogleCloudAiplatformV1beta1FeatureView resource to be passed as the request body. name: Identifier. Name of the FeatureView. Format: `projects/{project}/loc ations/{location}/featureOnlineStores/{feature_online_store}/featureView s/{feature_view}` updateMask: Field mask is used to specify the fields to be overwritten in the FeatureView resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `service_agent_type` * `big_query_source` * `big_query_source.uri` * `big_query_source.entity_id_columns` * `feature_registry_source` * `feature_registry_source.feature_groups` * `sync_config` * `sync_config.cron` * `optimized_config.automatic_resources` """ googleCloudAiplatformV1beta1FeatureView = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureView', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsSearchNearestEntitiesRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsSearchNeares tEntitiesRequest object. Fields: featureView: Required. FeatureView resource format `projects/{project}/loc ations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/ {featureView}` googleCloudAiplatformV1beta1SearchNearestEntitiesRequest: A GoogleCloudAiplatformV1beta1SearchNearestEntitiesRequest resource to be passed as the request body. """ featureView = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1SearchNearestEntitiesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1SearchNearestEntitiesRequest', 2) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsSetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsSetIamPolicy Request object. Fields: googleIamV1SetIamPolicyRequest: A GoogleIamV1SetIamPolicyRequest resource to be passed as the request body. resource: REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ googleIamV1SetIamPolicyRequest = _messages.MessageField('GoogleIamV1SetIamPolicyRequest', 1) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsStreamingFetchFeatureValuesRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsStreamingFet chFeatureValuesRequest object. Fields: featureView: Required. FeatureView resource format `projects/{project}/loc ations/{location}/featureOnlineStores/{featureOnlineStore}/featureViews/ {featureView}` googleCloudAiplatformV1beta1StreamingFetchFeatureValuesRequest: A GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesRequest resource to be passed as the request body. """ featureView = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1StreamingFetchFeatureValuesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesRequest', 2) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsSyncRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsSyncRequest object. Fields: featureView: Required. Format: `projects/{project}/locations/{location}/fe atureOnlineStores/{feature_online_store}/featureViews/{feature_view}` googleCloudAiplatformV1beta1SyncFeatureViewRequest: A GoogleCloudAiplatformV1beta1SyncFeatureViewRequest resource to be passed as the request body. """ featureView = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1SyncFeatureViewRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1SyncFeatureViewRequest', 2) class AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsTestIamPermissionsRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsTestIamPermi ssionsRequest object. Fields: permissions: The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions). resource: REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ permissions = _messages.StringField(1, repeated=True) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresGetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresGetIamPolicyRequest object. Fields: options_requestedPolicyVersion: Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). resource: REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ options_requestedPolicyVersion = _messages.IntegerField(1, variant=_messages.Variant.INT32) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresGetRequest object. Fields: name: Required. The name of the FeatureOnlineStore resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresListRequest object. Fields: filter: Lists the FeatureOnlineStores that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. Examples: * `create_time > "2020-01-01" OR update_time > "2020-01-01"` FeatureOnlineStores created or updated after 2020-01-01. * `labels.env = "prod"` FeatureOnlineStores with label "env" set to "prod". orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported Fields: * `create_time` * `update_time` pageSize: The maximum number of FeatureOnlineStores to return. The service may return fewer than this value. If unspecified, at most 100 FeatureOnlineStores will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100. pageToken: A page token, received from a previous FeatureOnlineStoreAdminService.ListFeatureOnlineStores call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeatureOnlineStoreAdminService.ListFeatureOnlineStores must match the call that provided the page token. parent: Required. The resource name of the Location to list FeatureOnlineStores. Format: `projects/{project}/locations/{location}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsFeatureOnlineStoresOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsFeatureOnlineStoresPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresPatchRequest object. Fields: googleCloudAiplatformV1beta1FeatureOnlineStore: A GoogleCloudAiplatformV1beta1FeatureOnlineStore resource to be passed as the request body. name: Identifier. Name of the FeatureOnlineStore. Format: `projects/{proje ct}/locations/{location}/featureOnlineStores/{featureOnlineStore}` updateMask: Field mask is used to specify the fields to be overwritten in the FeatureOnlineStore resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `description` * `bigtable` * `bigtable.auto_scaling` * `bigtable.enable_multi_region_replica` """ googleCloudAiplatformV1beta1FeatureOnlineStore = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureOnlineStore', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsFeatureOnlineStoresSetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresSetIamPolicyRequest object. Fields: googleIamV1SetIamPolicyRequest: A GoogleIamV1SetIamPolicyRequest resource to be passed as the request body. resource: REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ googleIamV1SetIamPolicyRequest = _messages.MessageField('GoogleIamV1SetIamPolicyRequest', 1) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeatureOnlineStoresTestIamPermissionsRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeatureOnlineStoresTestIamPermissionsRequest object. Fields: permissions: The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions). resource: REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ permissions = _messages.StringField(1, repeated=True) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeaturestoresBatchReadFeatureValuesRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresBatchReadFeatureValuesRequest object. Fields: featurestore: Required. The resource name of the Featurestore from which to query Feature values. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}` googleCloudAiplatformV1beta1BatchReadFeatureValuesRequest: A GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequest resource to be passed as the request body. """ featurestore = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1BatchReadFeatureValuesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequest', 2) class AiplatformProjectsLocationsFeaturestoresCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresCreateRequest object. Fields: featurestoreId: Required. The ID to use for this Featurestore, which will become the final component of the Featurestore's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within the project and location. googleCloudAiplatformV1beta1Featurestore: A GoogleCloudAiplatformV1beta1Featurestore resource to be passed as the request body. parent: Required. The resource name of the Location to create Featurestores. Format: `projects/{project}/locations/{location}` """ featurestoreId = _messages.StringField(1) googleCloudAiplatformV1beta1Featurestore = _messages.MessageField('GoogleCloudAiplatformV1beta1Featurestore', 2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsFeaturestoresDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresDeleteRequest object. Fields: force: If set to true, any EntityTypes and Features for this Featurestore will also be deleted. (Otherwise, the request will only work if the Featurestore has no EntityTypes.) name: Required. The name of the Featurestore to be deleted. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}` """ force = _messages.BooleanField(1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesCreateRequest object. Fields: entityTypeId: Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within a featurestore. googleCloudAiplatformV1beta1EntityType: A GoogleCloudAiplatformV1beta1EntityType resource to be passed as the request body. parent: Required. The resource name of the Featurestore to create EntityTypes. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}` """ entityTypeId = _messages.StringField(1) googleCloudAiplatformV1beta1EntityType = _messages.MessageField('GoogleCloudAiplatformV1beta1EntityType', 2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesDeleteFeatureValuesRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesDeleteFeatureValues Request object. Fields: entityType: Required. The resource name of the EntityType grouping the Features for which values are being deleted from. Format: `projects/{pro ject}/locations/{location}/featurestores/{featurestore}/entityTypes/{ent ityType}` googleCloudAiplatformV1beta1DeleteFeatureValuesRequest: A GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequest resource to be passed as the request body. """ entityType = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1DeleteFeatureValuesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequest', 2) class AiplatformProjectsLocationsFeaturestoresEntityTypesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesDeleteRequest object. Fields: force: If set to true, any Features for this EntityType will also be deleted. (Otherwise, the request will only work if the EntityType has no Features.) name: Required. The name of the EntityType to be deleted. Format: `project s/{project}/locations/{location}/featurestores/{featurestore}/entityType s/{entity_type}` """ force = _messages.BooleanField(1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesExportFeatureValuesRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesExportFeatureValues Request object. Fields: entityType: Required. The resource name of the EntityType from which to export Feature values. Format: `projects/{project}/locations/{location}/ featurestores/{featurestore}/entityTypes/{entity_type}` googleCloudAiplatformV1beta1ExportFeatureValuesRequest: A GoogleCloudAiplatformV1beta1ExportFeatureValuesRequest resource to be passed as the request body. """ entityType = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1ExportFeatureValuesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ExportFeatureValuesRequest', 2) class AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesBatchCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesBatchCreate Request object. Fields: googleCloudAiplatformV1beta1BatchCreateFeaturesRequest: A GoogleCloudAiplatformV1beta1BatchCreateFeaturesRequest resource to be passed as the request body. parent: Required. The resource name of the EntityType/FeatureGroup to create the batch of Features under. Format: `projects/{project}/location s/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` `projects/{project}/locations/{location}/featureGroups/{feature_group}` """ googleCloudAiplatformV1beta1BatchCreateFeaturesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchCreateFeaturesRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesCreateRequest object. Fields: featureId: Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup. googleCloudAiplatformV1beta1Feature: A GoogleCloudAiplatformV1beta1Feature resource to be passed as the request body. parent: Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/ locations/{location}/featurestores/{featurestore}/entityTypes/{entity_ty pe}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}` """ featureId = _messages.StringField(1) googleCloudAiplatformV1beta1Feature = _messages.MessageField('GoogleCloudAiplatformV1beta1Feature', 2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesDeleteRequest object. Fields: name: Required. The name of the Features to be deleted. Format: `projects/ {project}/locations/{location}/featurestores/{featurestore}/entityTypes/ {entity_type}/features/{feature}` `projects/{project}/locations/{locatio n}/featureGroups/{feature_group}/features/{feature}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesGetRequest object. Fields: featureStatsAndAnomalySpec_latestStatsCount: Optional. If set, returns the most recent count of stats. Valid value is [0, 100]. If stats_time_range is set, return most recent count of stats within the stats_time_range. featureStatsAndAnomalySpec_statsTimeRange_endTime: Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end. featureStatsAndAnomalySpec_statsTimeRange_startTime: Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start. name: Required. The name of the Feature resource. Format for entity_type as parent: `projects/{project}/locations/{location}/featurestores/{featu restore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}` """ featureStatsAndAnomalySpec_latestStatsCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) featureStatsAndAnomalySpec_statsTimeRange_endTime = _messages.StringField(2) featureStatsAndAnomalySpec_statsTimeRange_startTime = _messages.StringField(3) name = _messages.StringField(4, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesListRequest object. Fields: filter: Lists the Features that match the filter expression. The following filters are supported: * `value_type`: Supports = and != comparisons. * `create_time`: Supports =, !=, <, >, >=, and <= comparisons. Values must be in RFC 3339 format. * `update_time`: Supports =, !=, <, >, >=, and <= comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `value_type = DOUBLE` --> Features whose type is DOUBLE. * `create_time > \"2020-01-31T15:30:00.000000Z\" OR update_time > \"2020-01-31T15:30:00.000000Z\"` --> EntityTypes created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --> Features having both (active: yes) and (env: prod) labels. * `labels.env: *` --> Any Feature which has a label with 'env' as the key. latestStatsCount: Only applicable for Vertex AI Feature Store (Legacy). If set, return the most recent ListFeaturesRequest.latest_stats_count of stats for each Feature in response. Valid value is [0, 10]. If number of stats exists < ListFeaturesRequest.latest_stats_count, return all existing stats. orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `feature_id` * `value_type` (Not supported for FeatureRegistry Feature) * `create_time` * `update_time` pageSize: The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 1000 Features will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000. pageToken: A page token, received from a previous FeaturestoreService.ListFeatures call or FeatureRegistryService.ListFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeatures or FeatureRegistryService.ListFeatures must match the call that provided the page token. parent: Required. The resource name of the Location to list Features. Format for entity_type as parent: `projects/{project}/locations/{locatio n}/featurestores/{featurestore}/entityTypes/{entity_type}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) latestStatsCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) orderBy = _messages.StringField(3) pageSize = _messages.IntegerField(4, variant=_messages.Variant.INT32) pageToken = _messages.StringField(5) parent = _messages.StringField(6, required=True) readMask = _messages.StringField(7) class AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesOperationsC ancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesOperationsD eleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesOperationsG etRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesOperationsL istRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesOperationsW aitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesPatchRequest object. Fields: googleCloudAiplatformV1beta1Feature: A GoogleCloudAiplatformV1beta1Feature resource to be passed as the request body. name: Immutable. Name of the Feature. Format: `projects/{project}/location s/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/feat ures/{feature}` `projects/{project}/locations/{location}/featureGroups/{ feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type. updateMask: Field mask is used to specify the fields to be overwritten in the Features resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `disable_monitoring` (Not supported for FeatureRegistryService Feature) * `point_of_contact` (Not supported for FeaturestoreService FeatureStore) """ googleCloudAiplatformV1beta1Feature = _messages.MessageField('GoogleCloudAiplatformV1beta1Feature', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsFeaturestoresEntityTypesGetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesGetIamPolicyRequest object. Fields: options_requestedPolicyVersion: Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). resource: REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ options_requestedPolicyVersion = _messages.IntegerField(1, variant=_messages.Variant.INT32) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesGetRequest object. Fields: name: Required. The name of the EntityType resource. Format: `projects/{pr oject}/locations/{location}/featurestores/{featurestore}/entityTypes/{en tity_type}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesImportFeatureValuesRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesImportFeatureValues Request object. Fields: entityType: Required. The resource name of the EntityType grouping the Features for which values are being imported. Format: `projects/{project }/locations/{location}/featurestores/{featurestore}/entityTypes/{entityT ype}` googleCloudAiplatformV1beta1ImportFeatureValuesRequest: A GoogleCloudAiplatformV1beta1ImportFeatureValuesRequest resource to be passed as the request body. """ entityType = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1ImportFeatureValuesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportFeatureValuesRequest', 2) class AiplatformProjectsLocationsFeaturestoresEntityTypesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesListRequest object. Fields: filter: Lists the EntityTypes that match the filter expression. The following filters are supported: * `create_time`: Supports `=`, `!=`, `<`, `>`, `>=`, and `<=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `<`, `>`, `>=`, and `<=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality as well as key presence. Examples: * `create_time > \"2020-01-31T15:30:00.000000Z\" OR update_time > \"2020-01-31T15:30:00.000000Z\"` --> EntityTypes created or updated after 2020-01-31T15:30:00.000000Z. * `labels.active = yes AND labels.env = prod` --> EntityTypes having both (active: yes) and (env: prod) labels. * `labels.env: *` --> Any EntityType which has a label with 'env' as the key. orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `entity_type_id` * `create_time` * `update_time` pageSize: The maximum number of EntityTypes to return. The service may return fewer than this value. If unspecified, at most 1000 EntityTypes will be returned. The maximum value is 1000; any value greater than 1000 will be coerced to 1000. pageToken: A page token, received from a previous FeaturestoreService.ListEntityTypes call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListEntityTypes must match the call that provided the page token. parent: Required. The resource name of the Featurestore to list EntityTypes. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsFeaturestoresEntityTypesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsFeaturestoresEntityTypesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsFeaturestoresEntityTypesPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesPatchRequest object. Fields: googleCloudAiplatformV1beta1EntityType: A GoogleCloudAiplatformV1beta1EntityType resource to be passed as the request body. name: Immutable. Name of the EntityType. Format: `projects/{project}/locat ions/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore. updateMask: Field mask is used to specify the fields to be overwritten in the EntityType resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `description` * `labels` * `monitoring_config.snapshot_analysis.disabled` * `monitoring_config.snapshot_analysis.monitoring_interval_days` * `monitoring_config.snapshot_analysis.staleness_days` * `monitoring_config.import_features_analysis.state` * `monitoring_config.import_features_analysis.anomaly_detection_baseline` * `monitoring_config.numerical_threshold_config.value` * `monitoring_config.categorical_threshold_config.value` * `offline_storage_ttl_days` """ googleCloudAiplatformV1beta1EntityType = _messages.MessageField('GoogleCloudAiplatformV1beta1EntityType', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsFeaturestoresEntityTypesReadFeatureValuesRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesReadFeatureValuesRequest object. Fields: entityType: Required. The resource name of the EntityType for the entity being read. Value format: `projects/{project}/locations/{location}/featu restores/{featurestore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`. googleCloudAiplatformV1beta1ReadFeatureValuesRequest: A GoogleCloudAiplatformV1beta1ReadFeatureValuesRequest resource to be passed as the request body. """ entityType = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1ReadFeatureValuesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ReadFeatureValuesRequest', 2) class AiplatformProjectsLocationsFeaturestoresEntityTypesSetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesSetIamPolicyRequest object. Fields: googleIamV1SetIamPolicyRequest: A GoogleIamV1SetIamPolicyRequest resource to be passed as the request body. resource: REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ googleIamV1SetIamPolicyRequest = _messages.MessageField('GoogleIamV1SetIamPolicyRequest', 1) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesStreamingReadFeatureValuesRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesStreamingReadFeatur eValuesRequest object. Fields: entityType: Required. The resource name of the entities' type. Value format: `projects/{project}/locations/{location}/featurestores/{features tore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`. googleCloudAiplatformV1beta1StreamingReadFeatureValuesRequest: A GoogleCloudAiplatformV1beta1StreamingReadFeatureValuesRequest resource to be passed as the request body. """ entityType = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1StreamingReadFeatureValuesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1StreamingReadFeatureValuesRequest', 2) class AiplatformProjectsLocationsFeaturestoresEntityTypesTestIamPermissionsRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesTestIamPermissionsRequest object. Fields: permissions: The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions). resource: REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ permissions = _messages.StringField(1, repeated=True) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeaturestoresEntityTypesWriteFeatureValuesRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresEntityTypesWriteFeatureValuesRequest object. Fields: entityType: Required. The resource name of the EntityType for the entities being written. Value format: `projects/{project}/locations/{location}/featurestores/ {featurestore}/entityTypes/{entityType}`. For example, for a machine learning model predicting user clicks on a website, an EntityType ID could be `user`. googleCloudAiplatformV1beta1WriteFeatureValuesRequest: A GoogleCloudAiplatformV1beta1WriteFeatureValuesRequest resource to be passed as the request body. """ entityType = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1WriteFeatureValuesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1WriteFeatureValuesRequest', 2) class AiplatformProjectsLocationsFeaturestoresGetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresGetIamPolicyRequest object. Fields: googleIamV1GetIamPolicyRequest: A GoogleIamV1GetIamPolicyRequest resource to be passed as the request body. resource: REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ googleIamV1GetIamPolicyRequest = _messages.MessageField('GoogleIamV1GetIamPolicyRequest', 1) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeaturestoresGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresGetRequest object. Fields: name: Required. The name of the Featurestore resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeaturestoresListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresListRequest object. Fields: filter: Lists the featurestores that match the filter expression. The following fields are supported: * `create_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `online_serving_config.fixed_node_count`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. * `labels`: Supports key-value equality and key presence. Examples: * `create_time > "2020-01-01" OR update_time > "2020-01-01"` Featurestores created or updated after 2020-01-01. * `labels.env = "prod"` Featurestores with label "env" set to "prod". orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported Fields: * `create_time` * `update_time` * `online_serving_config.fixed_node_count` pageSize: The maximum number of Featurestores to return. The service may return fewer than this value. If unspecified, at most 100 Featurestores will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100. pageToken: A page token, received from a previous FeaturestoreService.ListFeaturestores call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.ListFeaturestores must match the call that provided the page token. parent: Required. The resource name of the Location to list Featurestores. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsFeaturestoresOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeaturestoresOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeaturestoresOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsFeaturestoresOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsFeaturestoresOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsFeaturestoresPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresPatchRequest object. Fields: googleCloudAiplatformV1beta1Featurestore: A GoogleCloudAiplatformV1beta1Featurestore resource to be passed as the request body. name: Output only. Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}` updateMask: Field mask is used to specify the fields to be overwritten in the Featurestore resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. Updatable fields: * `labels` * `online_serving_config.fixed_node_count` * `online_serving_config.scaling` * `online_storage_ttl_days` """ googleCloudAiplatformV1beta1Featurestore = _messages.MessageField('GoogleCloudAiplatformV1beta1Featurestore', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsFeaturestoresSearchFeaturesRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresSearchFeaturesRequest object. Fields: location: Required. The resource name of the Location to search Features. Format: `projects/{project}/locations/{location}` pageSize: The maximum number of Features to return. The service may return fewer than this value. If unspecified, at most 100 Features will be returned. The maximum value is 100; any value greater than 100 will be coerced to 100. pageToken: A page token, received from a previous FeaturestoreService.SearchFeatures call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to FeaturestoreService.SearchFeatures, except `page_size`, must match the call that provided the page token. query: Query string that is a conjunction of field-restricted queries and/or field-restricted filters. Field-restricted queries and filters can be combined using `AND` to form a conjunction. A field query is in the form FIELD:QUERY. This implicitly checks if QUERY exists as a substring within Feature's FIELD. The QUERY and the FIELD are converted to a sequence of words (i.e. tokens) for comparison. This is done by: * Removing leading/trailing whitespace and tokenizing the search value. Characters that are not one of alphanumeric `[a-zA-Z0-9]`, underscore `_`, or asterisk `*` are treated as delimiters for tokens. `*` is treated as a wildcard that matches characters within a token. * Ignoring case. * Prepending an asterisk to the first and appending an asterisk to the last token in QUERY. A QUERY must be either a singular token or a phrase. A phrase is one or multiple words enclosed in double quotation marks ("). With phrases, the order of the words is important. Words in the phrase must be matching in order and consecutively. Supported FIELDs for field-restricted queries: * `feature_id` * `description` * `entity_type_id` Examples: * `feature_id: foo` --> Matches a Feature with ID containing the substring `foo` (eg. `foo`, `foofeature`, `barfoo`). * `feature_id: foo*feature` --> Matches a Feature with ID containing the substring `foo*feature` (eg. `foobarfeature`). * `feature_id: foo AND description: bar` --> Matches a Feature with ID containing the substring `foo` and description containing the substring `bar`. Besides field queries, the following exact-match filters are supported. The exact-match filters do not support wildcards. Unlike field-restricted queries, exact-match filters are case-sensitive. * `feature_id`: Supports = comparisons. * `description`: Supports = comparisons. Multi-token filters should be enclosed in quotes. * `entity_type_id`: Supports = comparisons. * `value_type`: Supports = and != comparisons. * `labels`: Supports key-value equality as well as key presence. * `featurestore_id`: Supports = comparisons. Examples: * `description = "foo bar"` --> Any Feature with description exactly equal to `foo bar` * `value_type = DOUBLE` --> Features whose type is DOUBLE. * `labels.active = yes AND labels.env = prod` --> Features having both (active: yes) and (env: prod) labels. * `labels.env: *` --> Any Feature which has a label with `env` as the key. """ location = _messages.StringField(1, required=True) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) query = _messages.StringField(4) class AiplatformProjectsLocationsFeaturestoresSetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresSetIamPolicyRequest object. Fields: googleIamV1SetIamPolicyRequest: A GoogleIamV1SetIamPolicyRequest resource to be passed as the request body. resource: REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ googleIamV1SetIamPolicyRequest = _messages.MessageField('GoogleIamV1SetIamPolicyRequest', 1) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsFeaturestoresTestIamPermissionsRequest(_messages.Message): r"""A AiplatformProjectsLocationsFeaturestoresTestIamPermissionsRequest object. Fields: googleIamV1TestIamPermissionsRequest: A GoogleIamV1TestIamPermissionsRequest resource to be passed as the request body. resource: REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ googleIamV1TestIamPermissionsRequest = _messages.MessageField('GoogleIamV1TestIamPermissionsRequest', 1) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsGenerateInstanceRubricsRequest(_messages.Message): r"""A AiplatformProjectsLocationsGenerateInstanceRubricsRequest object. Fields: googleCloudAiplatformV1beta1GenerateInstanceRubricsRequest: A GoogleCloudAiplatformV1beta1GenerateInstanceRubricsRequest resource to be passed as the request body. location: Required. The resource name of the Location to generate rubrics from. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1GenerateInstanceRubricsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateInstanceRubricsRequest', 1) location = _messages.StringField(2, required=True) class AiplatformProjectsLocationsGenerateSyntheticDataRequest(_messages.Message): r"""A AiplatformProjectsLocationsGenerateSyntheticDataRequest object. Fields: googleCloudAiplatformV1beta1GenerateSyntheticDataRequest: A GoogleCloudAiplatformV1beta1GenerateSyntheticDataRequest resource to be passed as the request body. location: Required. The resource name of the Location to run the job. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1GenerateSyntheticDataRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateSyntheticDataRequest', 1) location = _messages.StringField(2, required=True) class AiplatformProjectsLocationsGetRagEngineConfigRequest(_messages.Message): r"""A AiplatformProjectsLocationsGetRagEngineConfigRequest object. Fields: name: Required. The name of the RagEngineConfig resource. Format: `projects/{project}/locations/{location}/ragEngineConfig` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsGetRequest object. Fields: name: Resource name for the location. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsHyperparameterTuningJobsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsHyperparameterTuningJobsCancelRequest object. Fields: googleCloudAiplatformV1beta1CancelHyperparameterTuningJobRequest: A GoogleCloudAiplatformV1beta1CancelHyperparameterTuningJobRequest resource to be passed as the request body. name: Required. The name of the HyperparameterTuningJob to cancel. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyper parameter_tuning_job}` """ googleCloudAiplatformV1beta1CancelHyperparameterTuningJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CancelHyperparameterTuningJobRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsHyperparameterTuningJobsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsHyperparameterTuningJobsCreateRequest object. Fields: googleCloudAiplatformV1beta1HyperparameterTuningJob: A GoogleCloudAiplatformV1beta1HyperparameterTuningJob resource to be passed as the request body. parent: Required. The resource name of the Location to create the HyperparameterTuningJob in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1HyperparameterTuningJob = _messages.MessageField('GoogleCloudAiplatformV1beta1HyperparameterTuningJob', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsHyperparameterTuningJobsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsHyperparameterTuningJobsDeleteRequest object. Fields: name: Required. The name of the HyperparameterTuningJob resource to be deleted. Format: `projects/{project}/locations/{location}/hyperparameter TuningJobs/{hyperparameter_tuning_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsHyperparameterTuningJobsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsHyperparameterTuningJobsGetRequest object. Fields: name: Required. The name of the HyperparameterTuningJob resource. Format: `projects/{project}/locations/{location}/hyperparameterTuningJobs/{hyper parameter_tuning_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsHyperparameterTuningJobsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsHyperparameterTuningJobsListRequest object. Fields: filter: The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`<`, `<=`,`>`, `>=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state="JOB_STATE_SUCCEEDED" AND display_name:"my_job_*"` * `state!="JOB_STATE_FAILED" OR display_name="my_job"` * `NOT display_name="my_job"` * `create_time>"2021-05-18T00:00:00Z"` * `labels.keyA=valueA` * `labels.keyB:*` pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via ListHyperparameterTuningJobsResponse.next_page_token of the previous JobService.ListHyperparameterTuningJobs call. parent: Required. The resource name of the Location to list the HyperparameterTuningJobs from. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsHyperparameterTuningJobsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsHyperparameterTuningJobsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsHyperparameterTuningJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsHyperparameterTuningJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsHyperparameterTuningJobsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsHyperparameterTuningJobsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsHyperparameterTuningJobsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsHyperparameterTuningJobsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsHyperparameterTuningJobsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsHyperparameterTuningJobsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsIndexEndpointsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsCreateRequest object. Fields: googleCloudAiplatformV1beta1IndexEndpoint: A GoogleCloudAiplatformV1beta1IndexEndpoint resource to be passed as the request body. parent: Required. The resource name of the Location to create the IndexEndpoint in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1IndexEndpoint = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexEndpoint', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsIndexEndpointsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsDeleteRequest object. Fields: name: Required. The name of the IndexEndpoint resource to be deleted. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_e ndpoint}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsIndexEndpointsDeployIndexRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsDeployIndexRequest object. Fields: googleCloudAiplatformV1beta1DeployIndexRequest: A GoogleCloudAiplatformV1beta1DeployIndexRequest resource to be passed as the request body. indexEndpoint: Required. The name of the IndexEndpoint resource into which to deploy an Index. Format: `projects/{project}/locations/{location}/ind exEndpoints/{index_endpoint}` """ googleCloudAiplatformV1beta1DeployIndexRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployIndexRequest', 1) indexEndpoint = _messages.StringField(2, required=True) class AiplatformProjectsLocationsIndexEndpointsFindNeighborsRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsFindNeighborsRequest object. Fields: googleCloudAiplatformV1beta1FindNeighborsRequest: A GoogleCloudAiplatformV1beta1FindNeighborsRequest resource to be passed as the request body. indexEndpoint: Required. The name of the index endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint} ` """ googleCloudAiplatformV1beta1FindNeighborsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1FindNeighborsRequest', 1) indexEndpoint = _messages.StringField(2, required=True) class AiplatformProjectsLocationsIndexEndpointsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsGetRequest object. Fields: name: Required. The name of the IndexEndpoint resource. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint} ` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsIndexEndpointsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsListRequest object. Fields: filter: Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `index_endpoint` supports = and !=. `index_endpoint` represents the IndexEndpoint ID, ie. the last segment of the IndexEndpoint's resourcename. * `display_name` supports =, != and regex() (uses [re2](https://github.com/google/re2/wiki/Syntax) syntax) * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* or labels:key - key existence A key including a space must be quoted. `labels."a key"`. Some examples: * `index_endpoint="1"` * `display_name="myDisplayName"` * `regex(display_name, "^A") -> The display name starts with an A. * `labels.myKey="myValue"` pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. Typically obtained via ListIndexEndpointsResponse.next_page_token of the previous IndexEndpointService.ListIndexEndpoints call. parent: Required. The resource name of the Location from which to list the IndexEndpoints. Format: `projects/{project}/locations/{location}` readMask: Optional. Mask specifying which fields to read. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsIndexEndpointsMutateDeployedIndexRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsMutateDeployedIndexRequest object. Fields: googleCloudAiplatformV1beta1DeployedIndex: A GoogleCloudAiplatformV1beta1DeployedIndex resource to be passed as the request body. indexEndpoint: Required. The name of the IndexEndpoint resource into which to deploy an Index. Format: `projects/{project}/locations/{location}/ind exEndpoints/{index_endpoint}` """ googleCloudAiplatformV1beta1DeployedIndex = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedIndex', 1) indexEndpoint = _messages.StringField(2, required=True) class AiplatformProjectsLocationsIndexEndpointsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsIndexEndpointsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsIndexEndpointsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsIndexEndpointsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsIndexEndpointsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsIndexEndpointsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsPatchRequest object. Fields: googleCloudAiplatformV1beta1IndexEndpoint: A GoogleCloudAiplatformV1beta1IndexEndpoint resource to be passed as the request body. name: Output only. The resource name of the IndexEndpoint. updateMask: Required. The update mask applies to the resource. See google.protobuf.FieldMask. """ googleCloudAiplatformV1beta1IndexEndpoint = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexEndpoint', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsIndexEndpointsReadIndexDatapointsRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsReadIndexDatapointsRequest object. Fields: googleCloudAiplatformV1beta1ReadIndexDatapointsRequest: A GoogleCloudAiplatformV1beta1ReadIndexDatapointsRequest resource to be passed as the request body. indexEndpoint: Required. The name of the index endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint} ` """ googleCloudAiplatformV1beta1ReadIndexDatapointsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ReadIndexDatapointsRequest', 1) indexEndpoint = _messages.StringField(2, required=True) class AiplatformProjectsLocationsIndexEndpointsUndeployIndexRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexEndpointsUndeployIndexRequest object. Fields: googleCloudAiplatformV1beta1UndeployIndexRequest: A GoogleCloudAiplatformV1beta1UndeployIndexRequest resource to be passed as the request body. indexEndpoint: Required. The name of the IndexEndpoint resource from which to undeploy an Index. Format: `projects/{project}/locations/{location}/i ndexEndpoints/{index_endpoint}` """ googleCloudAiplatformV1beta1UndeployIndexRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1UndeployIndexRequest', 1) indexEndpoint = _messages.StringField(2, required=True) class AiplatformProjectsLocationsIndexesCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesCreateRequest object. Fields: googleCloudAiplatformV1beta1Index: A GoogleCloudAiplatformV1beta1Index resource to be passed as the request body. parent: Required. The resource name of the Location to create the Index in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1Index = _messages.MessageField('GoogleCloudAiplatformV1beta1Index', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsIndexesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesDeleteRequest object. Fields: name: Required. The name of the Index resource to be deleted. Format: `projects/{project}/locations/{location}/indexes/{index}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsIndexesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesGetRequest object. Fields: name: Required. The name of the Index resource. Format: `projects/{project}/locations/{location}/indexes/{index}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsIndexesImportRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesImportRequest object. Fields: googleCloudAiplatformV1beta1ImportIndexRequest: A GoogleCloudAiplatformV1beta1ImportIndexRequest resource to be passed as the request body. name: Required. The name of the Index resource to import data to. Format: `projects/{project}/locations/{location}/indexes/{index}` """ googleCloudAiplatformV1beta1ImportIndexRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportIndexRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsIndexesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesListRequest object. Fields: filter: The standard list filter. pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via ListIndexesResponse.next_page_token of the previous IndexService.ListIndexes call. parent: Required. The resource name of the Location from which to list the Indexes. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsIndexesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsIndexesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsIndexesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsIndexesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsIndexesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsIndexesPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesPatchRequest object. Fields: googleCloudAiplatformV1beta1Index: A GoogleCloudAiplatformV1beta1Index resource to be passed as the request body. name: Output only. The resource name of the Index. updateMask: The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. """ googleCloudAiplatformV1beta1Index = _messages.MessageField('GoogleCloudAiplatformV1beta1Index', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsIndexesRemoveDatapointsRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesRemoveDatapointsRequest object. Fields: googleCloudAiplatformV1beta1RemoveDatapointsRequest: A GoogleCloudAiplatformV1beta1RemoveDatapointsRequest resource to be passed as the request body. index: Required. The name of the Index resource to be updated. Format: `projects/{project}/locations/{location}/indexes/{index}` """ googleCloudAiplatformV1beta1RemoveDatapointsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RemoveDatapointsRequest', 1) index = _messages.StringField(2, required=True) class AiplatformProjectsLocationsIndexesUpsertDatapointsRequest(_messages.Message): r"""A AiplatformProjectsLocationsIndexesUpsertDatapointsRequest object. Fields: googleCloudAiplatformV1beta1UpsertDatapointsRequest: A GoogleCloudAiplatformV1beta1UpsertDatapointsRequest resource to be passed as the request body. index: Required. The name of the Index resource to be updated. Format: `projects/{project}/locations/{location}/indexes/{index}` """ googleCloudAiplatformV1beta1UpsertDatapointsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1UpsertDatapointsRequest', 1) index = _messages.StringField(2, required=True) class AiplatformProjectsLocationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsListRequest object. Fields: extraLocationTypes: Optional. Do not use this field. It is unsupported and is ignored unless explicitly documented otherwise. This is primarily for internal usage. filter: A filter to narrow down results to a preferred subset. The filtering language accepts strings like `"displayName=tokyo"`, and is documented in more detail in [AIP-160](https://google.aip.dev/160). name: The resource that owns the locations collection, if applicable. pageSize: The maximum number of results to return. If not set, the service selects a default. pageToken: A page token received from the `next_page_token` field in the response. Send that page token to receive the subsequent page. """ extraLocationTypes = _messages.StringField(1, repeated=True) filter = _messages.StringField(2) name = _messages.StringField(3, required=True) pageSize = _messages.IntegerField(4, variant=_messages.Variant.INT32) pageToken = _messages.StringField(5) class AiplatformProjectsLocationsMetadataStoresArtifactsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresArtifactsCreateRequest object. Fields: artifactId: The {artifact} portion of the resource name with the format: ` projects/{project}/locations/{location}/metadataStores/{metadatastore}/a rtifacts/{artifact}` If not provided, the Artifact's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Artifacts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Artifact.) googleCloudAiplatformV1beta1Artifact: A GoogleCloudAiplatformV1beta1Artifact resource to be passed as the request body. parent: Required. The resource name of the MetadataStore where the Artifact should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ artifactId = _messages.StringField(1) googleCloudAiplatformV1beta1Artifact = _messages.MessageField('GoogleCloudAiplatformV1beta1Artifact', 2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsMetadataStoresArtifactsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresArtifactsDeleteRequest object. Fields: etag: Optional. The etag of the Artifact to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION. name: Required. The resource name of the Artifact to delete. Format: `proj ects/{project}/locations/{location}/metadataStores/{metadatastore}/artif acts/{artifact}` """ etag = _messages.StringField(1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsMetadataStoresArtifactsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresArtifactsGetRequest object. Fields: name: Required. The resource name of the Artifact to retrieve. Format: `pr ojects/{project}/locations/{location}/metadataStores/{metadatastore}/art ifacts/{artifact}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresArtifactsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresArtifactsListRequest object. Fields: filter: Filter specifying the boolean condition for the Artifacts to satisfy in order to be part of the result set. The syntax to define filter query is based on https://google.aip.dev/160. The supported set of filters include the following: * **Attribute filtering**: For example: `display_name = "test"`. Supported fields include: `name`, `display_name`, `uri`, `state`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = "2020-11-19T11:30:00-04:00"` * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..`. For example: `metadata.field_1.number_value = 10.0` In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata."field:1".number_value = 10.0` * **Context based filtering**: To filter Artifacts based on the contexts to which they belong, use the function operator with the full resource name `in_context()`. For example: `in_context("projects//locations//metadataStores//contexts/")` Each of the above supported filter types can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = "test" AND metadata.field1.bool_value = true`. orderBy: How the list of messages is ordered. Specify the values to order by and an ordering operation. The default sorting order is ascending. To specify descending order for a field, users append a " desc" suffix; for example: "foo desc, bar". Subfields are specified with a `.` character, such as foo.bar. see https://google.aip.dev/132#ordering for more details. pageSize: The maximum number of Artifacts to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100. pageToken: A page token, received from a previous MetadataService.ListArtifacts call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.) parent: Required. The MetadataStore whose Artifacts should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsMetadataStoresArtifactsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresArtifactsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresArtifactsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresArtifactsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresArtifactsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresArtifactsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresArtifactsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresArtifactsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsMetadataStoresArtifactsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresArtifactsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsMetadataStoresArtifactsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresArtifactsPatchRequest object. Fields: allowMissing: If set to true, and the Artifact is not found, a new Artifact is created. googleCloudAiplatformV1beta1Artifact: A GoogleCloudAiplatformV1beta1Artifact resource to be passed as the request body. name: Output only. The resource name of the Artifact. updateMask: Optional. A FieldMask indicating which fields should be updated. """ allowMissing = _messages.BooleanField(1) googleCloudAiplatformV1beta1Artifact = _messages.MessageField('GoogleCloudAiplatformV1beta1Artifact', 2) name = _messages.StringField(3, required=True) updateMask = _messages.StringField(4) class AiplatformProjectsLocationsMetadataStoresArtifactsPurgeRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresArtifactsPurgeRequest object. Fields: googleCloudAiplatformV1beta1PurgeArtifactsRequest: A GoogleCloudAiplatformV1beta1PurgeArtifactsRequest resource to be passed as the request body. parent: Required. The metadata store to purge Artifacts from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ googleCloudAiplatformV1beta1PurgeArtifactsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PurgeArtifactsRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsMetadataStoresArtifactsQueryArtifactLineageSubgraphRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresArtifactsQueryArtifactLineage SubgraphRequest object. Fields: artifact: Required. The resource name of the Artifact whose Lineage needs to be retrieved as a LineageSubgraph. Format: `projects/{project}/locati ons/{location}/metadataStores/{metadatastore}/artifacts/{artifact}` The request may error with FAILED_PRECONDITION if the number of Artifacts, the number of Executions, or the number of Events that would be returned for the Context exceeds 1000. filter: Filter specifying the boolean condition for the Artifacts to satisfy in order to be part of the Lineage Subgraph. The syntax to define filter query is based on https://google.aip.dev/160. The supported set of filters include the following: * **Attribute filtering**: For example: `display_name = "test"` Supported fields include: `name`, `display_name`, `uri`, `state`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = "2020-11-19T11:30:00-04:00"` * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..`. For example: `metadata.field_1.number_value = 10.0` In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata."field:1".number_value = 10.0` Each of the above supported filter types can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = "test" AND metadata.field1.bool_value = true`. maxHops: Specifies the size of the lineage graph in terms of number of hops from the specified artifact. Negative Value: INVALID_ARGUMENT error is returned 0: Only input artifact is returned. No value: Transitive closure is performed to return the complete graph. """ artifact = _messages.StringField(1, required=True) filter = _messages.StringField(2) maxHops = _messages.IntegerField(3, variant=_messages.Variant.INT32) class AiplatformProjectsLocationsMetadataStoresContextsAddContextArtifactsAndExecutionsRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsAddContextArtifactsAn dExecutionsRequest object. Fields: context: Required. The resource name of the Context that the Artifacts and Executions belong to. Format: `projects/{project}/locations/{location}/m etadataStores/{metadatastore}/contexts/{context}` googleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsRequest: A GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsRequest resource to be passed as the request body. """ context = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsRequest', 2) class AiplatformProjectsLocationsMetadataStoresContextsAddContextChildrenRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsAddContextChildrenRequest object. Fields: context: Required. The resource name of the parent Context. Format: `proje cts/{project}/locations/{location}/metadataStores/{metadatastore}/contex ts/{context}` googleCloudAiplatformV1beta1AddContextChildrenRequest: A GoogleCloudAiplatformV1beta1AddContextChildrenRequest resource to be passed as the request body. """ context = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1AddContextChildrenRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1AddContextChildrenRequest', 2) class AiplatformProjectsLocationsMetadataStoresContextsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsCreateRequest object. Fields: contextId: The {context} portion of the resource name with the format: `pr ojects/{project}/locations/{location}/metadataStores/{metadatastore}/con texts/{context}`. If not provided, the Context's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Contexts in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Context.) googleCloudAiplatformV1beta1Context: A GoogleCloudAiplatformV1beta1Context resource to be passed as the request body. parent: Required. The resource name of the MetadataStore where the Context should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ contextId = _messages.StringField(1) googleCloudAiplatformV1beta1Context = _messages.MessageField('GoogleCloudAiplatformV1beta1Context', 2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsMetadataStoresContextsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsDeleteRequest object. Fields: etag: Optional. The etag of the Context to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION. force: The force deletion semantics is still undefined. Users should not use this field. name: Required. The resource name of the Context to delete. Format: `proje cts/{project}/locations/{location}/metadataStores/{metadatastore}/contex ts/{context}` """ etag = _messages.StringField(1) force = _messages.BooleanField(2) name = _messages.StringField(3, required=True) class AiplatformProjectsLocationsMetadataStoresContextsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsGetRequest object. Fields: name: Required. The resource name of the Context to retrieve. Format: `pro jects/{project}/locations/{location}/metadataStores/{metadatastore}/cont exts/{context}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresContextsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsListRequest object. Fields: filter: Filter specifying the boolean condition for the Contexts to satisfy in order to be part of the result set. The syntax to define filter query is based on https://google.aip.dev/160. Following are the supported set of filters: * **Attribute filtering**: For example: `display_name = "test"`. Supported fields include: `name`, `display_name`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = "2020-11-19T11:30:00-04:00"`. * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..`. For example: `metadata.field_1.number_value = 10.0`. In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata."field:1".number_value = 10.0` * **Parent Child filtering**: To filter Contexts based on parent-child relationship use the HAS operator as follows: ``` parent_contexts: "projects//locations//metadataStores//contexts/" child_contexts: "projects//locations//metadataStores//contexts/" ``` Each of the above supported filters can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = "test" AND metadata.field1.bool_value = true`. orderBy: How the list of messages is ordered. Specify the values to order by and an ordering operation. The default sorting order is ascending. To specify descending order for a field, users append a " desc" suffix; for example: "foo desc, bar". Subfields are specified with a `.` character, such as foo.bar. see https://google.aip.dev/132#ordering for more details. pageSize: The maximum number of Contexts to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100. pageToken: A page token, received from a previous MetadataService.ListContexts call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.) parent: Required. The MetadataStore whose Contexts should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsMetadataStoresContextsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresContextsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresContextsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresContextsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsMetadataStoresContextsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsMetadataStoresContextsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsPatchRequest object. Fields: allowMissing: If set to true, and the Context is not found, a new Context is created. googleCloudAiplatformV1beta1Context: A GoogleCloudAiplatformV1beta1Context resource to be passed as the request body. name: Immutable. The resource name of the Context. updateMask: Optional. A FieldMask indicating which fields should be updated. """ allowMissing = _messages.BooleanField(1) googleCloudAiplatformV1beta1Context = _messages.MessageField('GoogleCloudAiplatformV1beta1Context', 2) name = _messages.StringField(3, required=True) updateMask = _messages.StringField(4) class AiplatformProjectsLocationsMetadataStoresContextsPurgeRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsPurgeRequest object. Fields: googleCloudAiplatformV1beta1PurgeContextsRequest: A GoogleCloudAiplatformV1beta1PurgeContextsRequest resource to be passed as the request body. parent: Required. The metadata store to purge Contexts from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ googleCloudAiplatformV1beta1PurgeContextsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PurgeContextsRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsMetadataStoresContextsQueryContextLineageSubgraphRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsQueryContextLineageSu bgraphRequest object. Fields: context: Required. The resource name of the Context whose Artifacts and Executions should be retrieved as a LineageSubgraph. Format: `projects/{ project}/locations/{location}/metadataStores/{metadatastore}/contexts/{c ontext}` The request may error with FAILED_PRECONDITION if the number of Artifacts, the number of Executions, or the number of Events that would be returned for the Context exceeds 1000. """ context = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresContextsRemoveContextChildrenRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresContextsRemoveContextChildren Request object. Fields: context: Required. The resource name of the parent Context. Format: `proje cts/{project}/locations/{location}/metadataStores/{metadatastore}/contex ts/{context}` googleCloudAiplatformV1beta1RemoveContextChildrenRequest: A GoogleCloudAiplatformV1beta1RemoveContextChildrenRequest resource to be passed as the request body. """ context = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1RemoveContextChildrenRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RemoveContextChildrenRequest', 2) class AiplatformProjectsLocationsMetadataStoresCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresCreateRequest object. Fields: googleCloudAiplatformV1beta1MetadataStore: A GoogleCloudAiplatformV1beta1MetadataStore resource to be passed as the request body. metadataStoreId: The {metadatastore} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataStores in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataStore.) parent: Required. The resource name of the Location where the MetadataStore should be created. Format: `projects/{project}/locations/{location}/` """ googleCloudAiplatformV1beta1MetadataStore = _messages.MessageField('GoogleCloudAiplatformV1beta1MetadataStore', 1) metadataStoreId = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsMetadataStoresDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresDeleteRequest object. Fields: force: Deprecated: Field is no longer supported. name: Required. The resource name of the MetadataStore to delete. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ force = _messages.BooleanField(1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsMetadataStoresExecutionsAddExecutionEventsRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsAddExecutionEventsRequest object. Fields: execution: Required. The resource name of the Execution that the Events connect Artifacts with. Format: `projects/{project}/locations/{location} /metadataStores/{metadatastore}/executions/{execution}` googleCloudAiplatformV1beta1AddExecutionEventsRequest: A GoogleCloudAiplatformV1beta1AddExecutionEventsRequest resource to be passed as the request body. """ execution = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1AddExecutionEventsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1AddExecutionEventsRequest', 2) class AiplatformProjectsLocationsMetadataStoresExecutionsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsCreateRequest object. Fields: executionId: The {execution} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/ executions/{execution}` If not provided, the Execution's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all Executions in the parent MetadataStore. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting Execution.) googleCloudAiplatformV1beta1Execution: A GoogleCloudAiplatformV1beta1Execution resource to be passed as the request body. parent: Required. The resource name of the MetadataStore where the Execution should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ executionId = _messages.StringField(1) googleCloudAiplatformV1beta1Execution = _messages.MessageField('GoogleCloudAiplatformV1beta1Execution', 2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsMetadataStoresExecutionsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsDeleteRequest object. Fields: etag: Optional. The etag of the Execution to delete. If this is provided, it must match the server's etag. Otherwise, the request will fail with a FAILED_PRECONDITION. name: Required. The resource name of the Execution to delete. Format: `pro jects/{project}/locations/{location}/metadataStores/{metadatastore}/exec utions/{execution}` """ etag = _messages.StringField(1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsMetadataStoresExecutionsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsGetRequest object. Fields: name: Required. The resource name of the Execution to retrieve. Format: `p rojects/{project}/locations/{location}/metadataStores/{metadatastore}/ex ecutions/{execution}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresExecutionsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsListRequest object. Fields: filter: Filter specifying the boolean condition for the Executions to satisfy in order to be part of the result set. The syntax to define filter query is based on https://google.aip.dev/160. Following are the supported set of filters: * **Attribute filtering**: For example: `display_name = "test"`. Supported fields include: `name`, `display_name`, `state`, `schema_title`, `create_time`, and `update_time`. Time fields, such as `create_time` and `update_time`, require values specified in RFC-3339 format. For example: `create_time = "2020-11-19T11:30:00-04:00"`. * **Metadata field**: To filter on metadata fields use traversal operation as follows: `metadata..` For example: `metadata.field_1.number_value = 10.0` In case the field name contains special characters (such as colon), one can embed it inside double quote. For example: `metadata."field:1".number_value = 10.0` * **Context based filtering**: To filter Executions based on the contexts to which they belong use the function operator with the full resource name: `in_context()`. For example: `in_context("projects//locations//metadataStores//contexts/")` Each of the above supported filters can be combined together using logical operators (`AND` & `OR`). Maximum nested expression depth allowed is 5. For example: `display_name = "test" AND metadata.field1.bool_value = true`. orderBy: How the list of messages is ordered. Specify the values to order by and an ordering operation. The default sorting order is ascending. To specify descending order for a field, users append a " desc" suffix; for example: "foo desc, bar". Subfields are specified with a `.` character, such as foo.bar. see https://google.aip.dev/132#ordering for more details. pageSize: The maximum number of Executions to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100. pageToken: A page token, received from a previous MetadataService.ListExecutions call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with an INVALID_ARGUMENT error.) parent: Required. The MetadataStore whose Executions should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsMetadataStoresExecutionsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresExecutionsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresExecutionsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresExecutionsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsMetadataStoresExecutionsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsMetadataStoresExecutionsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsPatchRequest object. Fields: allowMissing: If set to true, and the Execution is not found, a new Execution is created. googleCloudAiplatformV1beta1Execution: A GoogleCloudAiplatformV1beta1Execution resource to be passed as the request body. name: Output only. The resource name of the Execution. updateMask: Optional. A FieldMask indicating which fields should be updated. """ allowMissing = _messages.BooleanField(1) googleCloudAiplatformV1beta1Execution = _messages.MessageField('GoogleCloudAiplatformV1beta1Execution', 2) name = _messages.StringField(3, required=True) updateMask = _messages.StringField(4) class AiplatformProjectsLocationsMetadataStoresExecutionsPurgeRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsPurgeRequest object. Fields: googleCloudAiplatformV1beta1PurgeExecutionsRequest: A GoogleCloudAiplatformV1beta1PurgeExecutionsRequest resource to be passed as the request body. parent: Required. The metadata store to purge Executions from. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ googleCloudAiplatformV1beta1PurgeExecutionsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PurgeExecutionsRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsMetadataStoresExecutionsQueryExecutionInputsAndOutputsRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresExecutionsQueryExecutionInput sAndOutputsRequest object. Fields: execution: Required. The resource name of the Execution whose input and output Artifacts should be retrieved as a LineageSubgraph. Format: `proj ects/{project}/locations/{location}/metadataStores/{metadatastore}/execu tions/{execution}` """ execution = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresGetRequest object. Fields: name: Required. The resource name of the MetadataStore to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresListRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresListRequest object. Fields: pageSize: The maximum number of Metadata Stores to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100. pageToken: A page token, received from a previous MetadataService.ListMetadataStores call. Provide this to retrieve the subsequent page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.) parent: Required. The Location whose MetadataStores should be listed. Format: `projects/{project}/locations/{location}` """ pageSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) pageToken = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsMetadataStoresMetadataSchemasCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresMetadataSchemasCreateRequest object. Fields: googleCloudAiplatformV1beta1MetadataSchema: A GoogleCloudAiplatformV1beta1MetadataSchema resource to be passed as the request body. metadataSchemaId: The {metadata_schema} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{met adatastore}/metadataSchemas/{metadataschema}` If not provided, the MetadataStore's ID will be a UUID generated by the service. Must be 4-128 characters in length. Valid characters are `/a-z-/`. Must be unique across all MetadataSchemas in the parent Location. (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the caller can't view the preexisting MetadataSchema.) parent: Required. The resource name of the MetadataStore where the MetadataSchema should be created. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ googleCloudAiplatformV1beta1MetadataSchema = _messages.MessageField('GoogleCloudAiplatformV1beta1MetadataSchema', 1) metadataSchemaId = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsMetadataStoresMetadataSchemasGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresMetadataSchemasGetRequest object. Fields: name: Required. The resource name of the MetadataSchema to retrieve. Format: `projects/{project}/locations/{location}/metadataStores/{metadat astore}/metadataSchemas/{metadataschema}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresMetadataSchemasListRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresMetadataSchemasListRequest object. Fields: filter: A query to filter available MetadataSchemas for matching results. pageSize: The maximum number of MetadataSchemas to return. The service may return fewer. Must be in range 1-100, inclusive. Defaults to 100. pageToken: A page token, received from a previous MetadataService.ListMetadataSchemas call. Provide this to retrieve the next page. When paginating, all other provided parameters must match the call that provided the page token. (Otherwise the request will fail with INVALID_ARGUMENT error.) parent: Required. The MetadataStore whose MetadataSchemas should be listed. Format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}` """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) class AiplatformProjectsLocationsMetadataStoresOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMetadataStoresOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsMetadataStoresOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsMetadataStoresOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsMigratableResourcesBatchMigrateRequest(_messages.Message): r"""A AiplatformProjectsLocationsMigratableResourcesBatchMigrateRequest object. Fields: googleCloudAiplatformV1beta1BatchMigrateResourcesRequest: A GoogleCloudAiplatformV1beta1BatchMigrateResourcesRequest resource to be passed as the request body. parent: Required. The location of the migrated resource will live in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1BatchMigrateResourcesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchMigrateResourcesRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsMigratableResourcesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsMigratableResourcesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMigratableResourcesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsMigratableResourcesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMigratableResourcesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsMigratableResourcesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsMigratableResourcesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsMigratableResourcesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsMigratableResourcesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsMigratableResourcesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsMigratableResourcesSearchRequest(_messages.Message): r"""A AiplatformProjectsLocationsMigratableResourcesSearchRequest object. Fields: googleCloudAiplatformV1beta1SearchMigratableResourcesRequest: A GoogleCloudAiplatformV1beta1SearchMigratableResourcesRequest resource to be passed as the request body. parent: Required. The location that the migratable resources should be searched from. It's the Vertex AI location that the resources can be migrated to, not the resources' original location. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1SearchMigratableResourcesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1SearchMigratableResourcesRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsCreateRequest object. Fields: googleCloudAiplatformV1beta1ModelDeploymentMonitoringJob: A GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob resource to be passed as the request body. parent: Required. The parent of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1ModelDeploymentMonitoringJob = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsDeleteRequest object. Fields: name: Required. The resource name of the model monitoring job to delete. Format: `projects/{project}/locations/{location}/modelDeploymentMonitori ngJobs/{model_deployment_monitoring_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsGetRequest object. Fields: name: Required. The resource name of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}/modelDeploymentMonitori ngJobs/{model_deployment_monitoring_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsListRequest object. Fields: filter: The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`<`, `<=`,`>`, `>=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state="JOB_STATE_SUCCEEDED" AND display_name:"my_job_*"` * `state!="JOB_STATE_FAILED" OR display_name="my_job"` * `NOT display_name="my_job"` * `create_time>"2021-05-18T00:00:00Z"` * `labels.keyA=valueA` * `labels.keyB:*` pageSize: The standard list page size. pageToken: The standard list page token. parent: Required. The parent of the ModelDeploymentMonitoringJob. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsOperationsCanc elRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsOperationsDele teRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsOperationsList Request object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsOperationsWait Request object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsPatchRequest object. Fields: googleCloudAiplatformV1beta1ModelDeploymentMonitoringJob: A GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob resource to be passed as the request body. name: Output only. Resource name of a ModelDeploymentMonitoringJob. updateMask: Required. The update mask is used to specify the fields to be overwritten in the ModelDeploymentMonitoringJob resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to `*` to override all fields. For the objective config, the user can either provide the update mask for model_deployment_monitoring_objective_configs or any combination of its nested fields, such as: model_deployment_monitoring_objective_configs.ob jective_config.training_dataset. Updatable fields: * `display_name` * `model_deployment_monitoring_schedule_config` * `model_monitoring_alert_config` * `logging_sampling_strategy` * `labels` * `log_ttl` * `enable_monitoring_pipeline_logs` . and * `model_deployment_monitoring_objective_configs` . or * `model_deployment _monitoring_objective_configs.objective_config.training_dataset` * `mode l_deployment_monitoring_objective_configs.objective_config.training_pred iction_skew_detection_config` * `model_deployment_monitoring_objective_c onfigs.objective_config.prediction_drift_detection_config` """ googleCloudAiplatformV1beta1ModelDeploymentMonitoringJob = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsPauseRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsPauseRequest object. Fields: googleCloudAiplatformV1beta1PauseModelDeploymentMonitoringJobRequest: A GoogleCloudAiplatformV1beta1PauseModelDeploymentMonitoringJobRequest resource to be passed as the request body. name: Required. The resource name of the ModelDeploymentMonitoringJob to pause. Format: `projects/{project}/locations/{location}/modelDeploymentM onitoringJobs/{model_deployment_monitoring_job}` """ googleCloudAiplatformV1beta1PauseModelDeploymentMonitoringJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PauseModelDeploymentMonitoringJobRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsResumeRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsResumeRequest object. Fields: googleCloudAiplatformV1beta1ResumeModelDeploymentMonitoringJobRequest: A GoogleCloudAiplatformV1beta1ResumeModelDeploymentMonitoringJobRequest resource to be passed as the request body. name: Required. The resource name of the ModelDeploymentMonitoringJob to resume. Format: `projects/{project}/locations/{location}/modelDeployment MonitoringJobs/{model_deployment_monitoring_job}` """ googleCloudAiplatformV1beta1ResumeModelDeploymentMonitoringJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ResumeModelDeploymentMonitoringJobRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelDeploymentMonitoringJobsSearchModelDeploymentMonitoringStatsAnomaliesRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelDeploymentMonitoringJobsSearchModelDep loymentMonitoringStatsAnomaliesRequest object. Fields: googleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesR equest: A GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringSta tsAnomaliesRequest resource to be passed as the request body. modelDeploymentMonitoringJob: Required. ModelDeploymentMonitoring Job resource name. Format: `projects/{project}/locations/{location}/modelDep loymentMonitoringJobs/{model_deployment_monitoring_job}` """ googleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequest', 1) modelDeploymentMonitoringJob = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelMonitorsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsCreateRequest object. Fields: googleCloudAiplatformV1beta1ModelMonitor: A GoogleCloudAiplatformV1beta1ModelMonitor resource to be passed as the request body. modelMonitorId: Optional. The ID to use for the Model Monitor, which will become the final component of the model monitor resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`. parent: Required. The resource name of the Location to create the ModelMonitor in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1ModelMonitor = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitor', 1) modelMonitorId = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsModelMonitorsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsDeleteRequest object. Fields: force: Optional. Force delete the model monitor with schedules. name: Required. The name of the ModelMonitor resource to be deleted. Format: `projects/{project}/locations/{location}/modelMonitords/{model_monitor}` """ force = _messages.BooleanField(1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelMonitorsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsGetRequest object. Fields: name: Required. The name of the ModelMonitor resource. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelMonitorsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsListRequest object. Fields: filter: The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). pageSize: The standard list page size. pageToken: The standard list page token. parent: Required. The resource name of the Location to list the ModelMonitors from. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsModelMonitorsModelMonitoringJobsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsModelMonitoringJobsCreateRequest object. Fields: googleCloudAiplatformV1beta1ModelMonitoringJob: A GoogleCloudAiplatformV1beta1ModelMonitoringJob resource to be passed as the request body. modelMonitoringJobId: Optional. The ID to use for the Model Monitoring Job, which will become the final component of the model monitoring job resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`. parent: Required. The parent of the ModelMonitoringJob. Format: `projects/{project}/locations/{location}/modelMoniitors/{model_monitor}` """ googleCloudAiplatformV1beta1ModelMonitoringJob = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringJob', 1) modelMonitoringJobId = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsModelMonitorsModelMonitoringJobsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsModelMonitoringJobsDeleteRequest object. Fields: name: Required. The resource name of the model monitoring job to delete. Format: `projects/{project}/locations/{location}/modelMonitors/{model_mo nitor}/modelMonitoringJobs/{model_monitoring_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelMonitorsModelMonitoringJobsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsModelMonitoringJobsGetRequest object. Fields: name: Required. The resource name of the ModelMonitoringJob. Format: `proj ects/{project}/locations/{location}/modelMonitors/{model_monitor}/modelM onitoringJobs/{model_monitoring_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelMonitorsModelMonitoringJobsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsModelMonitoringJobsListRequest object. Fields: filter: The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). pageSize: The standard list page size. pageToken: The standard list page token. parent: Required. The parent of the ModelMonitoringJob. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}` readMask: Mask specifying which fields to read """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsModelMonitorsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelMonitorsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelMonitorsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelMonitorsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsModelMonitorsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsModelMonitorsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsPatchRequest object. Fields: googleCloudAiplatformV1beta1ModelMonitor: A GoogleCloudAiplatformV1beta1ModelMonitor resource to be passed as the request body. name: Immutable. Resource name of the ModelMonitor. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`. updateMask: Required. Mask specifying which fields to update. """ googleCloudAiplatformV1beta1ModelMonitor = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitor', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsModelMonitorsSearchModelMonitoringAlertsRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsSearchModelMonitoringAlertsRequest object. Fields: googleCloudAiplatformV1beta1SearchModelMonitoringAlertsRequest: A GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsRequest resource to be passed as the request body. modelMonitor: Required. ModelMonitor resource name. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}` """ googleCloudAiplatformV1beta1SearchModelMonitoringAlertsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsRequest', 1) modelMonitor = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelMonitorsSearchModelMonitoringStatsRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelMonitorsSearchModelMonitoringStatsRequest object. Fields: googleCloudAiplatformV1beta1SearchModelMonitoringStatsRequest: A GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsRequest resource to be passed as the request body. modelMonitor: Required. ModelMonitor resource name. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}` """ googleCloudAiplatformV1beta1SearchModelMonitoringStatsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsRequest', 1) modelMonitor = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelsCopyRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsCopyRequest object. Fields: googleCloudAiplatformV1beta1CopyModelRequest: A GoogleCloudAiplatformV1beta1CopyModelRequest resource to be passed as the request body. parent: Required. The resource name of the Location into which to copy the Model. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1CopyModelRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CopyModelRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsDeleteRequest object. Fields: name: Required. The name of the Model resource to be deleted. Format: `projects/{project}/locations/{location}/models/{model}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelsDeleteVersionRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsDeleteVersionRequest object. Fields: name: Required. The name of the model version to be deleted, with a version ID explicitly included. Example: `projects/{project}/locations/{location}/models/{model}@1234` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelsEvaluationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsEvaluationsGetRequest object. Fields: name: Required. The name of the ModelEvaluation resource. Format: `project s/{project}/locations/{location}/models/{model}/evaluations/{evaluation} ` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelsEvaluationsImportRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsEvaluationsImportRequest object. Fields: googleCloudAiplatformV1beta1ImportModelEvaluationRequest: A GoogleCloudAiplatformV1beta1ImportModelEvaluationRequest resource to be passed as the request body. parent: Required. The name of the parent model resource. Format: `projects/{project}/locations/{location}/models/{model}` """ googleCloudAiplatformV1beta1ImportModelEvaluationRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportModelEvaluationRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelsEvaluationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsEvaluationsListRequest object. Fields: filter: The standard list filter. pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via ListModelEvaluationsResponse.next_page_token of the previous ModelService.ListModelEvaluations call. parent: Required. The resource name of the Model to list the ModelEvaluations from. Format: `projects/{project}/locations/{location}/models/{model}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsModelsEvaluationsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsEvaluationsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelsEvaluationsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsEvaluationsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelsEvaluationsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsEvaluationsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelsEvaluationsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsEvaluationsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsModelsEvaluationsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsEvaluationsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsModelsEvaluationsSlicesBatchImportRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsEvaluationsSlicesBatchImportRequest object. Fields: googleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest: A GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest resource to be passed as the request body. parent: Required. The name of the parent ModelEvaluationSlice resource. Format: `projects/{project}/locations/{location}/models/{model}/evaluati ons/{evaluation}/slices/{slice}` """ googleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelsEvaluationsSlicesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsEvaluationsSlicesGetRequest object. Fields: name: Required. The name of the ModelEvaluationSlice resource. Format: `pr ojects/{project}/locations/{location}/models/{model}/evaluations/{evalua tion}/slices/{slice}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelsEvaluationsSlicesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsEvaluationsSlicesListRequest object. Fields: filter: The standard list filter. * `slice.dimension` - for =. pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via ListModelEvaluationSlicesResponse.next_page_token of the previous ModelService.ListModelEvaluationSlices call. parent: Required. The resource name of the ModelEvaluation to list the ModelEvaluationSlices from. Format: `projects/{project}/locations/{locat ion}/models/{model}/evaluations/{evaluation}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsModelsExportRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsExportRequest object. Fields: googleCloudAiplatformV1beta1ExportModelRequest: A GoogleCloudAiplatformV1beta1ExportModelRequest resource to be passed as the request body. name: Required. The resource name of the Model to export. The resource name may contain version id or version alias to specify the version, if no version is specified, the default version will be exported. """ googleCloudAiplatformV1beta1ExportModelRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ExportModelRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelsGetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsGetIamPolicyRequest object. Fields: options_requestedPolicyVersion: Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). resource: REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ options_requestedPolicyVersion = _messages.IntegerField(1, variant=_messages.Variant.INT32) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsGetRequest object. Fields: name: Required. The name of the Model resource. Format: `projects/{project}/locations/{location}/models/{model}` In order to retrieve a specific version of the model, also provide the version ID or version alias. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` If no version ID or alias is specified, the "default" version will be returned. The "default" version alias is created for the first version of the model, and can be moved to other versions later on. There will be exactly one default version. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelsListCheckpointsRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsListCheckpointsRequest object. Fields: name: Required. The name of the model version to list checkpoints for. `projects/{project}/locations/{location}/models/{model}@{version}` Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` If no version ID or alias is specified, the latest version will be used. pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. Typically obtained via next_page_token of the previous ListModelVersionCheckpoints call. """ name = _messages.StringField(1, required=True) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) class AiplatformProjectsLocationsModelsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsListRequest object. Fields: filter: An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `model` supports = and !=. `model` represents the Model ID, i.e. the last segment of the Model's resource name. * `display_name` supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels."a key"`. * `base_model_name` only supports = Some examples: * `model=1234` * `displayName="myDisplayName"` * `labels.myKey="myValue"` * `baseModelName="text-bison"` pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via ListModelsResponse.next_page_token of the previous ModelService.ListModels call. parent: Required. The resource name of the Location to list the Models from. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsModelsListVersionsRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsListVersionsRequest object. Fields: filter: An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels."a key"`. Some examples: * `labels.myKey="myValue"` name: Required. The name of the model to list versions for. orderBy: A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `create_time` * `update_time` Example: `update_time asc, create_time desc`. pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via next_page_token of the previous ListModelVersions call. readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) orderBy = _messages.StringField(3) pageSize = _messages.IntegerField(4, variant=_messages.Variant.INT32) pageToken = _messages.StringField(5) readMask = _messages.StringField(6) class AiplatformProjectsLocationsModelsMergeVersionAliasesRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsMergeVersionAliasesRequest object. Fields: googleCloudAiplatformV1beta1MergeVersionAliasesRequest: A GoogleCloudAiplatformV1beta1MergeVersionAliasesRequest resource to be passed as the request body. name: Required. The name of the model version to merge aliases, with a version ID explicitly included. Example: `projects/{project}/locations/{location}/models/{model}@1234` """ googleCloudAiplatformV1beta1MergeVersionAliasesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1MergeVersionAliasesRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsModelsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsModelsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsModelsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsPatchRequest object. Fields: googleCloudAiplatformV1beta1Model: A GoogleCloudAiplatformV1beta1Model resource to be passed as the request body. name: The resource name of the Model. updateMask: Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. """ googleCloudAiplatformV1beta1Model = _messages.MessageField('GoogleCloudAiplatformV1beta1Model', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsModelsSetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsSetIamPolicyRequest object. Fields: googleIamV1SetIamPolicyRequest: A GoogleIamV1SetIamPolicyRequest resource to be passed as the request body. resource: REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ googleIamV1SetIamPolicyRequest = _messages.MessageField('GoogleIamV1SetIamPolicyRequest', 1) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelsTestIamPermissionsRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsTestIamPermissionsRequest object. Fields: permissions: The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions). resource: REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ permissions = _messages.StringField(1, repeated=True) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelsUpdateExplanationDatasetRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsUpdateExplanationDatasetRequest object. Fields: googleCloudAiplatformV1beta1UpdateExplanationDatasetRequest: A GoogleCloudAiplatformV1beta1UpdateExplanationDatasetRequest resource to be passed as the request body. model: Required. The resource name of the Model to update. Format: `projects/{project}/locations/{location}/models/{model}` """ googleCloudAiplatformV1beta1UpdateExplanationDatasetRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1UpdateExplanationDatasetRequest', 1) model = _messages.StringField(2, required=True) class AiplatformProjectsLocationsModelsUploadRequest(_messages.Message): r"""A AiplatformProjectsLocationsModelsUploadRequest object. Fields: googleCloudAiplatformV1beta1UploadModelRequest: A GoogleCloudAiplatformV1beta1UploadModelRequest resource to be passed as the request body. parent: Required. The resource name of the Location into which to upload the Model. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1UploadModelRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1UploadModelRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNasJobsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsNasJobsCancelRequest object. Fields: googleCloudAiplatformV1beta1CancelNasJobRequest: A GoogleCloudAiplatformV1beta1CancelNasJobRequest resource to be passed as the request body. name: Required. The name of the NasJob to cancel. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}` """ googleCloudAiplatformV1beta1CancelNasJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CancelNasJobRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNasJobsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsNasJobsCreateRequest object. Fields: googleCloudAiplatformV1beta1NasJob: A GoogleCloudAiplatformV1beta1NasJob resource to be passed as the request body. parent: Required. The resource name of the Location to create the NasJob in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1NasJob = _messages.MessageField('GoogleCloudAiplatformV1beta1NasJob', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNasJobsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsNasJobsDeleteRequest object. Fields: name: Required. The name of the NasJob resource to be deleted. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNasJobsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsNasJobsGetRequest object. Fields: name: Required. The name of the NasJob resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNasJobsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsNasJobsListRequest object. Fields: filter: The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `create_time` supports `=`, `!=`,`<`, `<=`,`>`, `>=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state="JOB_STATE_SUCCEEDED" AND display_name:"my_job_*"` * `state!="JOB_STATE_FAILED" OR display_name="my_job"` * `NOT display_name="my_job"` * `create_time>"2021-05-18T00:00:00Z"` * `labels.keyA=valueA` * `labels.keyB:*` pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via ListNasJobsResponse.next_page_token of the previous JobService.ListNasJobs call. parent: Required. The resource name of the Location to list the NasJobs from. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsNasJobsNasTrialDetailsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsNasJobsNasTrialDetailsGetRequest object. Fields: name: Required. The name of the NasTrialDetail resource. Format: `projects /{project}/locations/{location}/nasJobs/{nas_job}/nasTrialDetails/{nas_t rial_detail}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNasJobsNasTrialDetailsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsNasJobsNasTrialDetailsListRequest object. Fields: pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via ListNasTrialDetailsResponse.next_page_token of the previous JobService.ListNasTrialDetails call. parent: Required. The name of the NasJob resource. Format: `projects/{project}/locations/{location}/nasJobs/{nas_job}` """ pageSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) pageToken = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsNotebookExecutionJobsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookExecutionJobsCreateRequest object. Fields: googleCloudAiplatformV1beta1NotebookExecutionJob: A GoogleCloudAiplatformV1beta1NotebookExecutionJob resource to be passed as the request body. notebookExecutionJobId: Optional. User specified ID for the NotebookExecutionJob. parent: Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1NotebookExecutionJob = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookExecutionJob', 1) notebookExecutionJobId = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsNotebookExecutionJobsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookExecutionJobsDeleteRequest object. Fields: name: Required. The name of the NotebookExecutionJob resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookExecutionJobsGenerateAccessTokenRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookExecutionJobsGenerateAccessTokenRequest object. Fields: googleCloudAiplatformV1beta1GenerateAccessTokenRequest: A GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest resource to be passed as the request body. name: Required. The name of the resource requesting the OAuth2 token. Format: `projects/{project}/locations/{location}/notebookRuntimes/{noteb ook_runtime}` `projects/{project}/locations/{location}/notebookExecution Jobs/{notebook_execution_job}` """ googleCloudAiplatformV1beta1GenerateAccessTokenRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNotebookExecutionJobsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookExecutionJobsGetRequest object. Enums: ViewValueValuesEnum: Optional. The NotebookExecutionJob view. Defaults to BASIC. Fields: name: Required. The name of the NotebookExecutionJob resource. view: Optional. The NotebookExecutionJob view. Defaults to BASIC. """ class ViewValueValuesEnum(_messages.Enum): r"""Optional. The NotebookExecutionJob view. Defaults to BASIC. Values: NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED: When unspecified, the API defaults to the BASIC view. NOTEBOOK_EXECUTION_JOB_VIEW_BASIC: Includes all fields except for direct notebook inputs. NOTEBOOK_EXECUTION_JOB_VIEW_FULL: Includes all fields. """ NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED = 0 NOTEBOOK_EXECUTION_JOB_VIEW_BASIC = 1 NOTEBOOK_EXECUTION_JOB_VIEW_FULL = 2 name = _messages.StringField(1, required=True) view = _messages.EnumField('ViewValueValuesEnum', 2) class AiplatformProjectsLocationsNotebookExecutionJobsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookExecutionJobsListRequest object. Enums: ViewValueValuesEnum: Optional. The NotebookExecutionJob view. Defaults to BASIC. Fields: filter: Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookExecutionJob` supports = and !=. `notebookExecutionJob` represents the NotebookExecutionJob ID. * `displayName` supports = and != and regex. * `schedule` supports = and != and regex. Some examples: * `notebookExecutionJob="123"` * `notebookExecutionJob="my-execution-job"` * `displayName="myDisplayName"` and `displayName=~"myDisplayNameRegex"` orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`. pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. Typically obtained via ListNotebookExecutionJobsResponse.next_page_token of the previous NotebookService.ListNotebookExecutionJobs call. parent: Required. The resource name of the Location from which to list the NotebookExecutionJobs. Format: `projects/{project}/locations/{location}` view: Optional. The NotebookExecutionJob view. Defaults to BASIC. """ class ViewValueValuesEnum(_messages.Enum): r"""Optional. The NotebookExecutionJob view. Defaults to BASIC. Values: NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED: When unspecified, the API defaults to the BASIC view. NOTEBOOK_EXECUTION_JOB_VIEW_BASIC: Includes all fields except for direct notebook inputs. NOTEBOOK_EXECUTION_JOB_VIEW_FULL: Includes all fields. """ NOTEBOOK_EXECUTION_JOB_VIEW_UNSPECIFIED = 0 NOTEBOOK_EXECUTION_JOB_VIEW_BASIC = 1 NOTEBOOK_EXECUTION_JOB_VIEW_FULL = 2 filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) view = _messages.EnumField('ViewValueValuesEnum', 6) class AiplatformProjectsLocationsNotebookExecutionJobsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookExecutionJobsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookExecutionJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookExecutionJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookExecutionJobsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookExecutionJobsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookExecutionJobsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookExecutionJobsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsNotebookExecutionJobsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookExecutionJobsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsNotebookExecutionJobsReportEventRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookExecutionJobsReportEventRequest object. Fields: googleCloudAiplatformV1beta1ReportExecutionEventRequest: A GoogleCloudAiplatformV1beta1ReportExecutionEventRequest resource to be passed as the request body. name: Required. The name of the NotebookExecutionJob resource. Format: `pr ojects/{project}/locations/{location}/notebookExecutionJobs/{notebook_ex ecution_jobs}` """ googleCloudAiplatformV1beta1ReportExecutionEventRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ReportExecutionEventRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNotebookRuntimeTemplatesCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesCreateRequest object. Fields: googleCloudAiplatformV1beta1NotebookRuntimeTemplate: A GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate resource to be passed as the request body. notebookRuntimeTemplateId: Optional. User specified ID for the notebook runtime template. parent: Required. The resource name of the Location to create the NotebookRuntimeTemplate. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1NotebookRuntimeTemplate = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate', 1) notebookRuntimeTemplateId = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsNotebookRuntimeTemplatesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesDeleteRequest object. Fields: name: Required. The name of the NotebookRuntimeTemplate resource to be deleted. Format: `projects/{project}/locations/{location}/notebookRuntim eTemplates/{notebook_runtime_template}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookRuntimeTemplatesGetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesGetIamPolicyRequest object. Fields: options_requestedPolicyVersion: Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). resource: REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ options_requestedPolicyVersion = _messages.IntegerField(1, variant=_messages.Variant.INT32) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNotebookRuntimeTemplatesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesGetRequest object. Fields: name: Required. The name of the NotebookRuntimeTemplate resource. Format: `projects/{project}/locations/{location}/notebookRuntimeTemplates/{noteb ook_runtime_template}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookRuntimeTemplatesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesListRequest object. Fields: filter: Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookRuntimeTemplate` supports = and !=. `notebookRuntimeTemplate` represents the NotebookRuntimeTemplate ID, i.e. the last segment of the NotebookRuntimeTemplate's resource name. * `display_name` supports = and != * `labels` supports general map functions that is: * `labels.key=value` - key:value equality * `labels.key:* or labels:key - key existence * A key including a space must be quoted. `labels."a key"`. * `notebookRuntimeType` supports = and !=. notebookRuntimeType enum: [USER_DEFINED, ONE_CLICK]. * `machineType` supports = and !=. * `acceleratorType` supports = and !=. Some examples: * `notebookRuntimeTemplate=notebookRuntimeTemplate123` * `displayName="myDisplayName"` * `labels.myKey="myValue"` * `notebookRuntimeType=USER_DEFINED` * `machineType=e2-standard-4` * `acceleratorType=NVIDIA_TESLA_T4` orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`. pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. Typically obtained via ListNotebookRuntimeTemplatesResponse.next_page_token of the previous NotebookService.ListNotebookRuntimeTemplates call. parent: Required. The resource name of the Location from which to list the NotebookRuntimeTemplates. Format: `projects/{project}/locations/{location}` readMask: Optional. Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsNotebookRuntimeTemplatesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookRuntimeTemplatesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookRuntimeTemplatesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookRuntimeTemplatesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsNotebookRuntimeTemplatesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsNotebookRuntimeTemplatesPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesPatchRequest object. Fields: googleCloudAiplatformV1beta1NotebookRuntimeTemplate: A GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate resource to be passed as the request body. name: The resource name of the NotebookRuntimeTemplate. updateMask: Required. The update mask applies to the resource. For the `FieldMask` definition, see google.protobuf.FieldMask. Input format: `{paths: "${updated_filed}"}` Updatable fields: * `encryption_spec.kms_key_name` """ googleCloudAiplatformV1beta1NotebookRuntimeTemplate = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsNotebookRuntimeTemplatesSetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesSetIamPolicyRequest object. Fields: googleIamV1SetIamPolicyRequest: A GoogleIamV1SetIamPolicyRequest resource to be passed as the request body. resource: REQUIRED: The resource for which the policy is being specified. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ googleIamV1SetIamPolicyRequest = _messages.MessageField('GoogleIamV1SetIamPolicyRequest', 1) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNotebookRuntimeTemplatesTestIamPermissionsRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimeTemplatesTestIamPermissionsRequest object. Fields: permissions: The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions). resource: REQUIRED: The resource for which the policy detail is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ permissions = _messages.StringField(1, repeated=True) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNotebookRuntimesAssignRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesAssignRequest object. Fields: googleCloudAiplatformV1beta1AssignNotebookRuntimeRequest: A GoogleCloudAiplatformV1beta1AssignNotebookRuntimeRequest resource to be passed as the request body. parent: Required. The resource name of the Location to get the NotebookRuntime assignment. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1AssignNotebookRuntimeRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1AssignNotebookRuntimeRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNotebookRuntimesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesDeleteRequest object. Fields: name: Required. The name of the NotebookRuntime resource to be deleted. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookRuntimesGenerateAccessTokenRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesGenerateAccessTokenRequest object. Fields: googleCloudAiplatformV1beta1GenerateAccessTokenRequest: A GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest resource to be passed as the request body. name: Required. The name of the resource requesting the OAuth2 token. Format: `projects/{project}/locations/{location}/notebookRuntimes/{noteb ook_runtime}` `projects/{project}/locations/{location}/notebookExecution Jobs/{notebook_execution_job}` """ googleCloudAiplatformV1beta1GenerateAccessTokenRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNotebookRuntimesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesGetRequest object. Fields: name: Required. The name of the NotebookRuntime resource. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookRuntimesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesListRequest object. Fields: filter: Optional. An expression for filtering the results of the request. For field names both snake_case and camelCase are supported. * `notebookRuntime` supports = and !=. `notebookRuntime` represents the NotebookRuntime ID, i.e. the last segment of the NotebookRuntime's resource name. * `displayName` supports = and != and regex. * `notebookRuntimeTemplate` supports = and !=. `notebookRuntimeTemplate` represents the NotebookRuntimeTemplate ID, i.e. the last segment of the NotebookRuntimeTemplate's resource name. * `healthState` supports = and !=. healthState enum: [HEALTHY, UNHEALTHY, HEALTH_STATE_UNSPECIFIED]. * `runtimeState` supports = and !=. runtimeState enum: [RUNTIME_STATE_UNSPECIFIED, RUNNING, BEING_STARTED, BEING_STOPPED, STOPPED, BEING_UPGRADED, ERROR, INVALID]. * `runtimeUser` supports = and !=. * API version is UI only: `uiState` supports = and !=. uiState enum: [UI_RESOURCE_STATE_UNSPECIFIED, UI_RESOURCE_STATE_BEING_CREATED, UI_RESOURCE_STATE_ACTIVE, UI_RESOURCE_STATE_BEING_DELETED, UI_RESOURCE_STATE_CREATION_FAILED]. * `notebookRuntimeType` supports = and !=. notebookRuntimeType enum: [USER_DEFINED, ONE_CLICK]. * `machineType` supports = and !=. * `acceleratorType` supports = and !=. Some examples: * `notebookRuntime="notebookRuntime123"` * `displayName="myDisplayName"` and `displayName=~"myDisplayNameRegex"` * `notebookRuntimeTemplate="notebookRuntimeTemplate321"` * `healthState=HEALTHY` * `runtimeState=RUNNING` * `runtimeUser="test@google.com"` * `uiState=UI_RESOURCE_STATE_BEING_DELETED` * `notebookRuntimeType=USER_DEFINED` * `machineType=e2-standard-4` * `acceleratorType=NVIDIA_TESLA_T4` orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `display_name` * `create_time` * `update_time` Example: `display_name, create_time desc`. pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. Typically obtained via ListNotebookRuntimesResponse.next_page_token of the previous NotebookService.ListNotebookRuntimes call. parent: Required. The resource name of the Location from which to list the NotebookRuntimes. Format: `projects/{project}/locations/{location}` readMask: Optional. Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsNotebookRuntimesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookRuntimesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookRuntimesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsNotebookRuntimesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsNotebookRuntimesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsNotebookRuntimesReportEventRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesReportEventRequest object. Fields: googleCloudAiplatformV1beta1ReportRuntimeEventRequest: A GoogleCloudAiplatformV1beta1ReportRuntimeEventRequest resource to be passed as the request body. name: Required. The name of the NotebookRuntime resource. Format: `project s/{project}/locations/{location}/notebookRuntimes/{notebook_runtime}` """ googleCloudAiplatformV1beta1ReportRuntimeEventRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ReportRuntimeEventRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNotebookRuntimesStartRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesStartRequest object. Fields: googleCloudAiplatformV1beta1StartNotebookRuntimeRequest: A GoogleCloudAiplatformV1beta1StartNotebookRuntimeRequest resource to be passed as the request body. name: Required. The name of the NotebookRuntime resource to be started. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner. """ googleCloudAiplatformV1beta1StartNotebookRuntimeRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1StartNotebookRuntimeRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNotebookRuntimesStopRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesStopRequest object. Fields: googleCloudAiplatformV1beta1StopNotebookRuntimeRequest: A GoogleCloudAiplatformV1beta1StopNotebookRuntimeRequest resource to be passed as the request body. name: Required. The name of the NotebookRuntime resource to be stopped. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner. """ googleCloudAiplatformV1beta1StopNotebookRuntimeRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1StopNotebookRuntimeRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsNotebookRuntimesUpgradeRequest(_messages.Message): r"""A AiplatformProjectsLocationsNotebookRuntimesUpgradeRequest object. Fields: googleCloudAiplatformV1beta1UpgradeNotebookRuntimeRequest: A GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeRequest resource to be passed as the request body. name: Required. The name of the NotebookRuntime resource to be upgrade. Instead of checking whether the name is in valid NotebookRuntime resource name format, directly throw NotFound exception if there is no such NotebookRuntime in spanner. """ googleCloudAiplatformV1beta1UpgradeNotebookRuntimeRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsPersistentResourcesCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsPersistentResourcesCreateRequest object. Fields: googleCloudAiplatformV1beta1PersistentResource: A GoogleCloudAiplatformV1beta1PersistentResource resource to be passed as the request body. parent: Required. The resource name of the Location to create the PersistentResource in. Format: `projects/{project}/locations/{location}` persistentResourceId: Required. The ID to use for the PersistentResource, which become the final component of the PersistentResource's resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`. """ googleCloudAiplatformV1beta1PersistentResource = _messages.MessageField('GoogleCloudAiplatformV1beta1PersistentResource', 1) parent = _messages.StringField(2, required=True) persistentResourceId = _messages.StringField(3) class AiplatformProjectsLocationsPersistentResourcesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsPersistentResourcesDeleteRequest object. Fields: name: Required. The name of the PersistentResource to be deleted. Format: `projects/{project}/locations/{location}/persistentResources/{persistent _resource}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsPersistentResourcesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsPersistentResourcesGetRequest object. Fields: name: Required. The name of the PersistentResource resource. Format: `proj ects/{project_id_or_number}/locations/{location_id}/persistentResources/ {persistent_resource_id}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsPersistentResourcesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsPersistentResourcesListRequest object. Fields: pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. Typically obtained via ListPersistentResourcesResponse.next_page_token of the previous PersistentResourceService.ListPersistentResource call. parent: Required. The resource name of the Location to list the PersistentResources from. Format: `projects/{project}/locations/{location}` """ pageSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) pageToken = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsPersistentResourcesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsPersistentResourcesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsPersistentResourcesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsPersistentResourcesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsPersistentResourcesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsPersistentResourcesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsPersistentResourcesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsPersistentResourcesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsPersistentResourcesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsPersistentResourcesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsPersistentResourcesPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsPersistentResourcesPatchRequest object. Fields: googleCloudAiplatformV1beta1PersistentResource: A GoogleCloudAiplatformV1beta1PersistentResource resource to be passed as the request body. name: Immutable. Resource name of a PersistentResource. updateMask: Required. Specify the fields to be overwritten in the PersistentResource by the update method. """ googleCloudAiplatformV1beta1PersistentResource = _messages.MessageField('GoogleCloudAiplatformV1beta1PersistentResource', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsPersistentResourcesRebootRequest(_messages.Message): r"""A AiplatformProjectsLocationsPersistentResourcesRebootRequest object. Fields: googleCloudAiplatformV1beta1RebootPersistentResourceRequest: A GoogleCloudAiplatformV1beta1RebootPersistentResourceRequest resource to be passed as the request body. name: Required. The name of the PersistentResource resource. Format: `proj ects/{project_id_or_number}/locations/{location_id}/persistentResources/ {persistent_resource_id}` """ googleCloudAiplatformV1beta1RebootPersistentResourceRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RebootPersistentResourceRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsPipelineJobsBatchCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsPipelineJobsBatchCancelRequest object. Fields: googleCloudAiplatformV1beta1BatchCancelPipelineJobsRequest: A GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsRequest resource to be passed as the request body. parent: Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1BatchCancelPipelineJobsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsPipelineJobsBatchDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsPipelineJobsBatchDeleteRequest object. Fields: googleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest: A GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest resource to be passed as the request body. parent: Required. The name of the PipelineJobs' parent resource. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsPipelineJobsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsPipelineJobsCancelRequest object. Fields: googleCloudAiplatformV1beta1CancelPipelineJobRequest: A GoogleCloudAiplatformV1beta1CancelPipelineJobRequest resource to be passed as the request body. name: Required. The name of the PipelineJob to cancel. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}` """ googleCloudAiplatformV1beta1CancelPipelineJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CancelPipelineJobRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsPipelineJobsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsPipelineJobsCreateRequest object. Fields: googleCloudAiplatformV1beta1PipelineJob: A GoogleCloudAiplatformV1beta1PipelineJob resource to be passed as the request body. parent: Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}` pipelineJobId: The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`. """ googleCloudAiplatformV1beta1PipelineJob = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineJob', 1) parent = _messages.StringField(2, required=True) pipelineJobId = _messages.StringField(3) class AiplatformProjectsLocationsPipelineJobsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsPipelineJobsDeleteRequest object. Fields: name: Required. The name of the PipelineJob resource to be deleted. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsPipelineJobsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsPipelineJobsGetRequest object. Fields: name: Required. The name of the PipelineJob resource. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsPipelineJobsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsPipelineJobsListRequest object. Fields: filter: Lists the PipelineJobs that match the filter expression. The following fields are supported: * `pipeline_name`: Supports `=` and `!=` comparisons. * `display_name`: Supports `=`, `!=` comparisons, and `:` wildcard. * `pipeline_job_user_id`: Supports `=`, `!=` comparisons, and `:` wildcard. for example, can check if pipeline's display_name contains *step* by doing display_name:\"*step*\" * `state`: Supports `=` and `!=` comparisons. * `create_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `update_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `end_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `labels`: Supports key-value equality and key presence. * `template_uri`: Supports `=`, `!=` comparisons, and `:` wildcard. * `template_metadata.version`: Supports `=`, `!=` comparisons, and `:` wildcard. Filter expressions can be combined together using logical operators (`AND` & `OR`). For example: `pipeline_name="test" AND create_time>"2020-05-18T13:30:00Z"`. The syntax to define filter expression is based on https://google.aip.dev/160. Examples: * `create_time>"2021-05-18T00:00:00Z" OR update_time>"2020-05-18T00:00:00Z"` PipelineJobs created or updated after 2020-05-18 00:00:00 UTC. * `labels.env = "prod"` PipelineJobs with label "env" set to "prod". orderBy: A comma-separated list of fields to order by. The default sort order is in ascending order. Use "desc" after a field name for descending. You can have multiple order_by fields provided e.g. "create_time desc, end_time", "end_time, start_time, update_time" For example, using "create_time desc, end_time" will order results by create time in descending order, and if there are multiple jobs having the same create time, order them by the end time in ascending order. if order_by is not specified, it will order by default order is create time in descending order. Supported fields: * `create_time` * `update_time` * `end_time` * `start_time` pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via ListPipelineJobsResponse.next_page_token of the previous PipelineService.ListPipelineJobs call. parent: Required. The resource name of the Location to list the PipelineJobs from. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsPipelineJobsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsPipelineJobsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsPipelineJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsPipelineJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsPipelineJobsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsPipelineJobsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsPipelineJobsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsPipelineJobsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsPipelineJobsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsPipelineJobsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsPublishersModelsComputeTokensRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsComputeTokensRequest object. Fields: endpoint: Required. The name of the Endpoint requested to get lists of tokens and token ids. googleCloudAiplatformV1beta1ComputeTokensRequest: A GoogleCloudAiplatformV1beta1ComputeTokensRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1ComputeTokensRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ComputeTokensRequest', 2) class AiplatformProjectsLocationsPublishersModelsCountTokensRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsCountTokensRequest object. Fields: endpoint: Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1CountTokensRequest: A GoogleCloudAiplatformV1beta1CountTokensRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1CountTokensRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CountTokensRequest', 2) class AiplatformProjectsLocationsPublishersModelsEmbedContentRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsEmbedContentRequest object. Fields: googleCloudAiplatformV1beta1EmbedContentRequest: A GoogleCloudAiplatformV1beta1EmbedContentRequest resource to be passed as the request body. model: Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*` """ googleCloudAiplatformV1beta1EmbedContentRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1EmbedContentRequest', 1) model = _messages.StringField(2, required=True) class AiplatformProjectsLocationsPublishersModelsExportRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsExportRequest object. Fields: googleCloudAiplatformV1beta1ExportPublisherModelRequest: A GoogleCloudAiplatformV1beta1ExportPublisherModelRequest resource to be passed as the request body. name: Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}@{version_id}`, or `publishers/hf-{hugging-face-author}/models/{hugging-face-model- name}@001` parent: Required. The Location to export the model weights from Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1ExportPublisherModelRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ExportPublisherModelRequest', 1) name = _messages.StringField(2, required=True) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsPublishersModelsFetchPredictOperationRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsFetchPredictOperationRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `proje cts/{project}/locations/{location}/publishers/{publisher}/models/{model} ` googleCloudAiplatformV1beta1FetchPredictOperationRequest: A GoogleCloudAiplatformV1beta1FetchPredictOperationRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1FetchPredictOperationRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1FetchPredictOperationRequest', 2) class AiplatformProjectsLocationsPublishersModelsFetchPublisherModelConfigRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsFetchPublisherModelConfigRequest object. Fields: name: Required. The name of the publisher model, in the format of `project s/{project}/locations/{location}/publishers/{publisher}/models/{model}`. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsPublishersModelsGenerateContentRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsGenerateContentRequest object. Fields: googleCloudAiplatformV1beta1GenerateContentRequest: A GoogleCloudAiplatformV1beta1GenerateContentRequest resource to be passed as the request body. model: Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` """ googleCloudAiplatformV1beta1GenerateContentRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateContentRequest', 1) model = _messages.StringField(2, required=True) class AiplatformProjectsLocationsPublishersModelsGetIamPolicyRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsGetIamPolicyRequest object. Fields: options_requestedPolicyVersion: Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). resource: REQUIRED: The resource for which the policy is being requested. See [Resource names](https://cloud.google.com/apis/design/resource_names) for the appropriate value for this field. """ options_requestedPolicyVersion = _messages.IntegerField(1, variant=_messages.Variant.INT32) resource = _messages.StringField(2, required=True) class AiplatformProjectsLocationsPublishersModelsPredictLongRunningRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsPredictLongRunningRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `proje cts/{project}/locations/{location}/publishers/{publisher}/models/{model} ` googleCloudAiplatformV1beta1PredictLongRunningRequest: A GoogleCloudAiplatformV1beta1PredictLongRunningRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1PredictLongRunningRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictLongRunningRequest', 2) class AiplatformProjectsLocationsPublishersModelsPredictRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsPredictRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1PredictRequest: A GoogleCloudAiplatformV1beta1PredictRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1PredictRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictRequest', 2) class AiplatformProjectsLocationsPublishersModelsRawPredictRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsRawPredictRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1RawPredictRequest: A GoogleCloudAiplatformV1beta1RawPredictRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1RawPredictRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RawPredictRequest', 2) class AiplatformProjectsLocationsPublishersModelsServerStreamingPredictRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsServerStreamingPredictRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1StreamingPredictRequest: A GoogleCloudAiplatformV1beta1StreamingPredictRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1StreamingPredictRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1StreamingPredictRequest', 2) class AiplatformProjectsLocationsPublishersModelsSetPublisherModelConfigRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsSetPublisherModelConfigRequest object. Fields: googleCloudAiplatformV1beta1SetPublisherModelConfigRequest: A GoogleCloudAiplatformV1beta1SetPublisherModelConfigRequest resource to be passed as the request body. name: Required. The name of the publisher model, in the format of `project s/{project}/locations/{location}/publishers/{publisher}/models/{model}`. """ googleCloudAiplatformV1beta1SetPublisherModelConfigRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1SetPublisherModelConfigRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsPublishersModelsStreamGenerateContentRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsStreamGenerateContentRequest object. Fields: googleCloudAiplatformV1beta1GenerateContentRequest: A GoogleCloudAiplatformV1beta1GenerateContentRequest resource to be passed as the request body. model: Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` """ googleCloudAiplatformV1beta1GenerateContentRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateContentRequest', 1) model = _messages.StringField(2, required=True) class AiplatformProjectsLocationsPublishersModelsStreamRawPredictRequest(_messages.Message): r"""A AiplatformProjectsLocationsPublishersModelsStreamRawPredictRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1StreamRawPredictRequest: A GoogleCloudAiplatformV1beta1StreamRawPredictRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1StreamRawPredictRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1StreamRawPredictRequest', 2) class AiplatformProjectsLocationsRagCorporaCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaCreateRequest object. Fields: googleCloudAiplatformV1beta1RagCorpus: A GoogleCloudAiplatformV1beta1RagCorpus resource to be passed as the request body. parent: Required. The resource name of the Location to create the RagCorpus in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1RagCorpus = _messages.MessageField('GoogleCloudAiplatformV1beta1RagCorpus', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsRagCorporaDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaDeleteRequest object. Fields: force: Optional. If set to true, any RagFiles in this RagCorpus will also be deleted. Otherwise, the request will only work if the RagCorpus has no RagFiles. name: Required. The name of the RagCorpus resource to be deleted. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}` """ force = _messages.BooleanField(1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsRagCorporaGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaGetRequest object. Fields: name: Required. The name of the RagCorpus resource. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsRagCorporaListRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaListRequest object. Fields: pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. Typically obtained via ListRagCorporaResponse.next_page_token of the previous VertexRagDataService.ListRagCorpora call. parent: Required. The resource name of the Location from which to list the RagCorpora. Format: `projects/{project}/locations/{location}` """ pageSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) pageToken = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsRagCorporaOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsRagCorporaOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsRagCorporaOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsRagCorporaOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsRagCorporaOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsRagCorporaRagFilesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaRagFilesDeleteRequest object. Fields: forceDelete: Optional. If set to true, any errors generated by external vector database during the deletion will be ignored. The default value is false. name: Required. The name of the RagFile resource to be deleted. Format: `p rojects/{project}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/ {rag_file}` """ forceDelete = _messages.BooleanField(1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsRagCorporaRagFilesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaRagFilesGetRequest object. Fields: name: Required. The name of the RagFile resource. Format: `projects/{proje ct}/locations/{location}/ragCorpora/{rag_corpus}/ragFiles/{rag_file}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsRagCorporaRagFilesImportRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaRagFilesImportRequest object. Fields: googleCloudAiplatformV1beta1ImportRagFilesRequest: A GoogleCloudAiplatformV1beta1ImportRagFilesRequest resource to be passed as the request body. parent: Required. The name of the RagCorpus resource into which to import files. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}` """ googleCloudAiplatformV1beta1ImportRagFilesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportRagFilesRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsRagCorporaRagFilesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaRagFilesListRequest object. Fields: pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. Typically obtained via ListRagFilesResponse.next_page_token of the previous VertexRagDataService.ListRagFiles call. parent: Required. The resource name of the RagCorpus from which to list the RagFiles. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}` """ pageSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) pageToken = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsRagCorporaRagFilesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaRagFilesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsRagCorporaRagFilesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaRagFilesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsRagCorporaRagFilesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaRagFilesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsRagCorporaRagFilesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaRagFilesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsRagCorporaRagFilesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagCorporaRagFilesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsRagEngineConfigOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagEngineConfigOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsRagEngineConfigOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagEngineConfigOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsRagEngineConfigOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagEngineConfigOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsRagEngineConfigOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagEngineConfigOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsRagEngineConfigOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsRagEngineConfigOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsReasoningEnginesCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesCreateRequest object. Fields: googleCloudAiplatformV1beta1ReasoningEngine: A GoogleCloudAiplatformV1beta1ReasoningEngine resource to be passed as the request body. parent: Required. The resource name of the Location to create the ReasoningEngine in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1ReasoningEngine = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngine', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsReasoningEnginesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesDeleteRequest object. Fields: force: Optional. If set to true, child resources of this reasoning engine will also be deleted. Otherwise, the request will fail with FAILED_PRECONDITION error when the reasoning engine has undeleted child resources. name: Required. The name of the ReasoningEngine resource to be deleted. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}` """ force = _messages.BooleanField(1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsReasoningEnginesExamplesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesExamplesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesExamplesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesExamplesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesExamplesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesExamplesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesExamplesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesExamplesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsReasoningEnginesExecuteCodeRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesExecuteCodeRequest object. Fields: googleCloudAiplatformV1beta1ExecuteCodeRequest: A GoogleCloudAiplatformV1beta1ExecuteCodeRequest resource to be passed as the request body. name: Required. The resource name of the sandbox environment to execute. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}` """ googleCloudAiplatformV1beta1ExecuteCodeRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ExecuteCodeRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsReasoningEnginesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesGetRequest object. Fields: name: Required. The name of the ReasoningEngine resource. Format: `project s/{project}/locations/{location}/reasoningEngines/{reasoning_engine}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesListRequest object. Fields: filter: Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. parent: Required. The resource name of the Location to list the ReasoningEngines from. Format: `projects/{project}/locations/{location}` """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesCreateRequest object. Fields: googleCloudAiplatformV1beta1Memory: A GoogleCloudAiplatformV1beta1Memory resource to be passed as the request body. parent: Required. The resource name of the ReasoningEngine to create the Memory under. Format: `projects/{project}/locations/{location}/reasoning Engines/{reasoning_engine}` """ googleCloudAiplatformV1beta1Memory = _messages.MessageField('GoogleCloudAiplatformV1beta1Memory', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesDeleteRequest object. Fields: name: Required. The resource name of the Memory to delete. Format: `projec ts/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/me mories/{memory}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesGenerateRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesGenerateRequest object. Fields: googleCloudAiplatformV1beta1GenerateMemoriesRequest: A GoogleCloudAiplatformV1beta1GenerateMemoriesRequest resource to be passed as the request body. parent: Required. The resource name of the ReasoningEngine to generate memories for. Format: `projects/{project}/locations/{location}/reasoning Engines/{reasoning_engine}` """ googleCloudAiplatformV1beta1GenerateMemoriesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateMemoriesRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesGetRequest object. Fields: name: Required. The resource name of the Memory. Format: `projects/{projec t}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{me mory}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesListRequest object. Fields: filter: Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). Supported fields: * `scope` (as a JSON string with equality match only) * `topics` (i.e. `topics.custom_memory_topic_label: "example topic" OR topics.managed_memory_topic: USER_PREFERENCES`) orderBy: Optional. The standard list order by string. If not specified, the default order is `create_time desc`. If specified, the default sorting order of provided fields is ascending. More detail in [AIP-132](https://google.aip.dev/132). Supported fields: * `create_time` * `update_time` pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. parent: Required. The resource name of the ReasoningEngine to list the Memories under. Format: `projects/{project}/locations/{location}/reasoni ngEngines/{reasoning_engine}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsReasoningEnginesMemoriesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsReasoningEnginesMemoriesPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesPatchRequest object. Fields: googleCloudAiplatformV1beta1Memory: A GoogleCloudAiplatformV1beta1Memory resource to be passed as the request body. name: Identifier. The resource name of the Memory. Format: `projects/{proj ect}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{ memory}` updateMask: Optional. Mask specifying which fields to update. Supported fields: * `display_name` * `description` * `fact` """ googleCloudAiplatformV1beta1Memory = _messages.MessageField('GoogleCloudAiplatformV1beta1Memory', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsReasoningEnginesMemoriesPurgeRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesPurgeRequest object. Fields: googleCloudAiplatformV1beta1PurgeMemoriesRequest: A GoogleCloudAiplatformV1beta1PurgeMemoriesRequest resource to be passed as the request body. parent: Required. The resource name of the ReasoningEngine to purge memories from. Format: `projects/{project}/locations/{location}/reasonin gEngines/{reasoning_engine}` """ googleCloudAiplatformV1beta1PurgeMemoriesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PurgeMemoriesRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesRetrieveRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesRetrieveRequest object. Fields: googleCloudAiplatformV1beta1RetrieveMemoriesRequest: A GoogleCloudAiplatformV1beta1RetrieveMemoriesRequest resource to be passed as the request body. parent: Required. The resource name of the ReasoningEngine to retrieve memories from. Format: `projects/{project}/locations/{location}/reasonin gEngines/{reasoning_engine}` """ googleCloudAiplatformV1beta1RetrieveMemoriesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RetrieveMemoriesRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesRevisionsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesRevisionsGetRequest object. Fields: name: Required. The resource name of the Memory Revision to retrieve. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}/memories/{memory}/revisions/{revision}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesRevisionsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesRevisionsListRequest object. Fields: filter: Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). Supported fields (equality match only): * `labels` pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. parent: Required. The resource name of the Memory to list revisions for. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}/memories/{memory}` """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) class AiplatformProjectsLocationsReasoningEnginesMemoriesRollbackRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesMemoriesRollbackRequest object. Fields: googleCloudAiplatformV1beta1RollbackMemoryRequest: A GoogleCloudAiplatformV1beta1RollbackMemoryRequest resource to be passed as the request body. name: Required. The resource name of the Memory to rollback. Format: `proj ects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/ memories/{memory}` """ googleCloudAiplatformV1beta1RollbackMemoryRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RollbackMemoryRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsReasoningEnginesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsReasoningEnginesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsReasoningEnginesPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesPatchRequest object. Fields: googleCloudAiplatformV1beta1ReasoningEngine: A GoogleCloudAiplatformV1beta1ReasoningEngine resource to be passed as the request body. name: Identifier. The resource name of the ReasoningEngine. Format: `proje cts/{project}/locations/{location}/reasoningEngines/{reasoning_engine}` updateMask: Optional. Mask specifying which fields to update. """ googleCloudAiplatformV1beta1ReasoningEngine = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngine', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsReasoningEnginesQueryRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesQueryRequest object. Fields: googleCloudAiplatformV1beta1QueryReasoningEngineRequest: A GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest resource to be passed as the request body. name: Required. The name of the ReasoningEngine resource to use. Format: ` projects/{project}/locations/{location}/reasoningEngines/{reasoning_engi ne}` """ googleCloudAiplatformV1beta1QueryReasoningEngineRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsCreateRequest object. Fields: googleCloudAiplatformV1beta1SandboxEnvironment: A GoogleCloudAiplatformV1beta1SandboxEnvironment resource to be passed as the request body. parent: Required. The resource name of the reasoning engine to create the SandboxEnvironment in. Format: `projects/{project}/locations/{location}/ reasoningEngines/{reasoning_engine}`. """ googleCloudAiplatformV1beta1SandboxEnvironment = _messages.MessageField('GoogleCloudAiplatformV1beta1SandboxEnvironment', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsDeleteRequest object. Fields: name: Required. The resource name of the SandboxEnvironment to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}/sandboxEnvironments/{sandbox_environment}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsExecuteRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsExecuteRequest object. Fields: googleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest: A GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest resource to be passed as the request body. name: Required. The resource name of the sandbox environment to execute. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}/sandboxEnvironments/{sandbox_environment}` """ googleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsGetRequest object. Fields: name: Required. The resource name of the sandbox environment. Format: `pro jects/{project}/locations/{location}/reasoningEngines/{reasoning_engine} /sandboxEnvironments/{sandbox_environment}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsListRequest object. Fields: filter: Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). pageSize: Optional. The maximum number of SandboxEnvironments to return. The service may return fewer than this value. If unspecified, at most 100 SandboxEnvironments will be returned. pageToken: Optional. The standard list page token, received from a previous `ListSandboxEnvironments` call. Provide this to retrieve the subsequent page. parent: Required. The resource name of the reasoning engine to list sandbox environments from. Format: `projects/{project}/locations/{locati on}/reasoningEngines/{reasoning_engine}` """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) class AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsOperatio nsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsOperatio nsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsOperatio nsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsOperatio nsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSandboxEnvironmentsOperatio nsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsReasoningEnginesSessionsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSessionsCreateRequest object. Fields: googleCloudAiplatformV1beta1Session: A GoogleCloudAiplatformV1beta1Session resource to be passed as the request body. parent: Required. The resource name of the location to create the session in. Format: `projects/{project}/locations/{location}/reasoningEngines/{r easoning_engine}` """ googleCloudAiplatformV1beta1Session = _messages.MessageField('GoogleCloudAiplatformV1beta1Session', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsReasoningEnginesSessionsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSessionsDeleteRequest object. Fields: name: Required. The resource name of the session. Format: `projects/{proje ct}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{s ession}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesSessionsEventsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSessionsEventsListRequest object. Fields: filter: Optional. The standard list filter. Supported fields: * `timestamp` range (i.e. `timestamp>="2025-01-31T11:30:00-04:00"` where the timestamp is in RFC 3339 format) More detail in [AIP-160](https://google.aip.dev/160). orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `timestamp` Example: `timestamp desc`. pageSize: Optional. The maximum number of events to return. The service may return fewer than this value. If unspecified, at most 100 events will be returned. These events are ordered by timestamp in ascending order. pageToken: Optional. The next_page_token value returned from a previous list SessionService.ListEvents call. parent: Required. The resource name of the session to list events from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}/sessions/{session}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsReasoningEnginesSessionsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSessionsGetRequest object. Fields: name: Required. The resource name of the session. Format: `projects/{proje ct}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{s ession}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesSessionsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSessionsListRequest object. Fields: filter: Optional. The standard list filter. Supported fields: * `display_name` * `user_id` * `labels` Example: `display_name="abc"`, `user_id="123"`, `labels.key="value"`. orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `create_time` * `update_time` Example: `create_time desc`. pageSize: Optional. The maximum number of sessions to return. The service may return fewer than this value. If unspecified, at most 100 sessions will be returned. pageToken: Optional. The next_page_token value returned from a previous list SessionService.ListSessions call. parent: Required. The resource name of the location to list sessions from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsReasoningEnginesSessionsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSessionsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesSessionsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSessionsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesSessionsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSessionsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsReasoningEnginesSessionsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSessionsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsReasoningEnginesSessionsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSessionsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsReasoningEnginesSessionsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesSessionsPatchRequest object. Fields: googleCloudAiplatformV1beta1Session: A GoogleCloudAiplatformV1beta1Session resource to be passed as the request body. name: Identifier. The resource name of the session. Format: 'projects/{pro ject}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/ {session}'. updateMask: Optional. Field mask is used to control which fields get updated. If the mask is not present, all fields will be updated. """ googleCloudAiplatformV1beta1Session = _messages.MessageField('GoogleCloudAiplatformV1beta1Session', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsReasoningEnginesStreamQueryRequest(_messages.Message): r"""A AiplatformProjectsLocationsReasoningEnginesStreamQueryRequest object. Fields: googleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest: A GoogleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest resource to be passed as the request body. name: Required. The name of the ReasoningEngine resource to use. Format: ` projects/{project}/locations/{location}/reasoningEngines/{reasoning_engi ne}` """ googleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsRecommendSpecRequest(_messages.Message): r"""A AiplatformProjectsLocationsRecommendSpecRequest object. Fields: googleCloudAiplatformV1beta1RecommendSpecRequest: A GoogleCloudAiplatformV1beta1RecommendSpecRequest resource to be passed as the request body. parent: Required. The resource name of the Location from which to recommend specs. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`. """ googleCloudAiplatformV1beta1RecommendSpecRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RecommendSpecRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsRetrieveContextsRequest(_messages.Message): r"""A AiplatformProjectsLocationsRetrieveContextsRequest object. Fields: googleCloudAiplatformV1beta1RetrieveContextsRequest: A GoogleCloudAiplatformV1beta1RetrieveContextsRequest resource to be passed as the request body. parent: Required. The resource name of the Location from which to retrieve RagContexts. The users must have permission to make a call in the project. Format: `projects/{project}/locations/{location}`. """ googleCloudAiplatformV1beta1RetrieveContextsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RetrieveContextsRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsSchedulesCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsSchedulesCreateRequest object. Fields: googleCloudAiplatformV1beta1Schedule: A GoogleCloudAiplatformV1beta1Schedule resource to be passed as the request body. parent: Required. The resource name of the Location to create the Schedule in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1Schedule = _messages.MessageField('GoogleCloudAiplatformV1beta1Schedule', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsSchedulesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsSchedulesDeleteRequest object. Fields: name: Required. The name of the Schedule resource to be deleted. Format: `projects/{project}/locations/{location}/schedules/{schedule}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsSchedulesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsSchedulesGetRequest object. Fields: name: Required. The name of the Schedule resource. Format: `projects/{project}/locations/{location}/schedules/{schedule}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsSchedulesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsSchedulesListRequest object. Fields: filter: Lists the Schedules that match the filter expression. The following fields are supported: * `display_name`: Supports `=`, `!=` comparisons, and `:` wildcard. * `state`: Supports `=` and `!=` comparisons. * `request`: Supports existence of the check. (e.g. `create_pipeline_job_request:*` --> Schedule has create_pipeline_job_request). * `create_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `start_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. * `end_time`: Supports `=`, `!=`, `<`, `>`, `<=`, `>=` comparisons and `:*` existence check. Values must be in RFC 3339 format. * `next_run_time`: Supports `=`, `!=`, `<`, `>`, `<=`, and `>=` comparisons. Values must be in RFC 3339 format. Filter expressions can be combined together using logical operators (`NOT`, `AND` & `OR`). The syntax to define filter expression is based on https://google.aip.dev/160. Examples: * `state="ACTIVE" AND display_name:"my_schedule_*"` * `NOT display_name="my_schedule"` * `create_time>"2021-05-18T00:00:00Z"` * `end_time>"2021-05-18T00:00:00Z" OR NOT end_time:*` * `create_pipeline_job_request:*` orderBy: A comma-separated list of fields to order by. The default sort order is in ascending order. Use "desc" after a field name for descending. You can have multiple order_by fields provided. For example, using "create_time desc, end_time" will order results by create time in descending order, and if there are multiple schedules having the same create time, order them by the end time in ascending order. If order_by is not specified, it will order by default with create_time in descending order. Supported fields: * `create_time` * `start_time` * `end_time` * `next_run_time` pageSize: The standard list page size. Default to 100 if not specified. pageToken: The standard list page token. Typically obtained via ListSchedulesResponse.next_page_token of the previous ScheduleService.ListSchedules call. parent: Required. The resource name of the Location to list the Schedules from. Format: `projects/{project}/locations/{location}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformProjectsLocationsSchedulesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsSchedulesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsSchedulesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsSchedulesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsSchedulesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsSchedulesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsSchedulesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsSchedulesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsSchedulesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsSchedulesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsSchedulesPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsSchedulesPatchRequest object. Fields: googleCloudAiplatformV1beta1Schedule: A GoogleCloudAiplatformV1beta1Schedule resource to be passed as the request body. name: Immutable. The resource name of the Schedule. updateMask: Required. The update mask applies to the resource. See google.protobuf.FieldMask. """ googleCloudAiplatformV1beta1Schedule = _messages.MessageField('GoogleCloudAiplatformV1beta1Schedule', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsSchedulesPauseRequest(_messages.Message): r"""A AiplatformProjectsLocationsSchedulesPauseRequest object. Fields: googleCloudAiplatformV1beta1PauseScheduleRequest: A GoogleCloudAiplatformV1beta1PauseScheduleRequest resource to be passed as the request body. name: Required. The name of the Schedule resource to be paused. Format: `projects/{project}/locations/{location}/schedules/{schedule}` """ googleCloudAiplatformV1beta1PauseScheduleRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PauseScheduleRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsSchedulesResumeRequest(_messages.Message): r"""A AiplatformProjectsLocationsSchedulesResumeRequest object. Fields: googleCloudAiplatformV1beta1ResumeScheduleRequest: A GoogleCloudAiplatformV1beta1ResumeScheduleRequest resource to be passed as the request body. name: Required. The name of the Schedule resource to be resumed. Format: `projects/{project}/locations/{location}/schedules/{schedule}` """ googleCloudAiplatformV1beta1ResumeScheduleRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ResumeScheduleRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsServerlessRayJobsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsServerlessRayJobsCancelRequest object. Fields: googleCloudAiplatformV1beta1CancelServerlessRayJobRequest: A GoogleCloudAiplatformV1beta1CancelServerlessRayJobRequest resource to be passed as the request body. name: Required. The name of the ServerlessRayJob to cancel. Format: `proje cts/{project}/locations/{location}/ServerlessRayJobs/{serverless_ray_job }` """ googleCloudAiplatformV1beta1CancelServerlessRayJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CancelServerlessRayJobRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsServerlessRayJobsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsServerlessRayJobsCreateRequest object. Fields: googleCloudAiplatformV1beta1ServerlessRayJob: A GoogleCloudAiplatformV1beta1ServerlessRayJob resource to be passed as the request body. parent: Required. The resource name of the Location to create the ServerlessRayJob in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1ServerlessRayJob = _messages.MessageField('GoogleCloudAiplatformV1beta1ServerlessRayJob', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsServerlessRayJobsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsServerlessRayJobsDeleteRequest object. Fields: name: Required. The name of the ServerlessRayJob resource to be deleted. Format: `projects/{project}/locations/{location}/ServerlessRayJobs/{serv erless_ray_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsServerlessRayJobsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsServerlessRayJobsGetRequest object. Fields: name: Required. The name of the ServerlessRayJob resource. Format: `projec ts/{project}/locations/{location}/serverlessRayJobs/{serverless_ray_job} ` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsServerlessRayJobsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsServerlessRayJobsListRequest object. Fields: filter: Optional. The standard list filter. Supported fields: * `serverless_ray_job_id` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. Typically obtained via ListServerlessRayJobsResponse.next_page_token of the previous JobService.ListServerlessRayJobs call. parent: Required. The resource name of the Location to list the ServerlessRayJobs from. Format: `projects/{project}/locations/{location}` """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) class AiplatformProjectsLocationsSolversOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsSolversOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsSolversOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsSolversOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsSolversOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsSolversOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsSpecialistPoolsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsSpecialistPoolsCreateRequest object. Fields: googleCloudAiplatformV1beta1SpecialistPool: A GoogleCloudAiplatformV1beta1SpecialistPool resource to be passed as the request body. parent: Required. The parent Project name for the new SpecialistPool. The form is `projects/{project}/locations/{location}`. """ googleCloudAiplatformV1beta1SpecialistPool = _messages.MessageField('GoogleCloudAiplatformV1beta1SpecialistPool', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsSpecialistPoolsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsSpecialistPoolsDeleteRequest object. Fields: force: If set to true, any specialist managers in this SpecialistPool will also be deleted. (Otherwise, the request will only work if the SpecialistPool has no specialist managers.) name: Required. The resource name of the SpecialistPool to delete. Format: `projects/{project}/locations/{location}/specialistPools/{specialist_poo l}` """ force = _messages.BooleanField(1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsSpecialistPoolsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsSpecialistPoolsGetRequest object. Fields: name: Required. The name of the SpecialistPool resource. The form is `proj ects/{project}/locations/{location}/specialistPools/{specialist_pool}`. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsSpecialistPoolsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsSpecialistPoolsListRequest object. Fields: pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained by ListSpecialistPoolsResponse.next_page_token of the previous SpecialistPoolService.ListSpecialistPools call. Return first page if empty. parent: Required. The name of the SpecialistPool's parent resource. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. FieldMask represents a set of """ pageSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) pageToken = _messages.StringField(2) parent = _messages.StringField(3, required=True) readMask = _messages.StringField(4) class AiplatformProjectsLocationsSpecialistPoolsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsSpecialistPoolsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsSpecialistPoolsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsSpecialistPoolsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsSpecialistPoolsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsSpecialistPoolsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsSpecialistPoolsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsSpecialistPoolsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsSpecialistPoolsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsSpecialistPoolsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsSpecialistPoolsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsSpecialistPoolsPatchRequest object. Fields: googleCloudAiplatformV1beta1SpecialistPool: A GoogleCloudAiplatformV1beta1SpecialistPool resource to be passed as the request body. name: Required. The resource name of the SpecialistPool. updateMask: Required. The update mask applies to the resource. """ googleCloudAiplatformV1beta1SpecialistPool = _messages.MessageField('GoogleCloudAiplatformV1beta1SpecialistPool', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsStudiesCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesCreateRequest object. Fields: googleCloudAiplatformV1beta1Study: A GoogleCloudAiplatformV1beta1Study resource to be passed as the request body. parent: Required. The resource name of the Location to create the CustomJob in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1Study = _messages.MessageField('GoogleCloudAiplatformV1beta1Study', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsStudiesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesDeleteRequest object. Fields: name: Required. The name of the Study resource to be deleted. Format: `projects/{project}/locations/{location}/studies/{study}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsStudiesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesGetRequest object. Fields: name: Required. The name of the Study resource. Format: `projects/{project}/locations/{location}/studies/{study}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsStudiesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesListRequest object. Fields: pageSize: Optional. The maximum number of studies to return per "page" of results. If unspecified, service will pick an appropriate default. pageToken: Optional. A page token to request the next page of results. If unspecified, there are no subsequent pages. parent: Required. The resource name of the Location to list the Study from. Format: `projects/{project}/locations/{location}` """ pageSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) pageToken = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsStudiesLookupRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesLookupRequest object. Fields: googleCloudAiplatformV1beta1LookupStudyRequest: A GoogleCloudAiplatformV1beta1LookupStudyRequest resource to be passed as the request body. parent: Required. The resource name of the Location to get the Study from. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1LookupStudyRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1LookupStudyRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsStudiesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsStudiesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsStudiesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsStudiesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsStudiesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsStudiesTrialsAddTrialMeasurementRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsAddTrialMeasurementRequest object. Fields: googleCloudAiplatformV1beta1AddTrialMeasurementRequest: A GoogleCloudAiplatformV1beta1AddTrialMeasurementRequest resource to be passed as the request body. trialName: Required. The name of the trial to add measurement. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}` """ googleCloudAiplatformV1beta1AddTrialMeasurementRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1AddTrialMeasurementRequest', 1) trialName = _messages.StringField(2, required=True) class AiplatformProjectsLocationsStudiesTrialsCheckTrialEarlyStoppingStateRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsCheckTrialEarlyStoppingStateRequest object. Fields: googleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateRequest: A GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateRequest resource to be passed as the request body. trialName: Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}` """ googleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateRequest', 1) trialName = _messages.StringField(2, required=True) class AiplatformProjectsLocationsStudiesTrialsCompleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsCompleteRequest object. Fields: googleCloudAiplatformV1beta1CompleteTrialRequest: A GoogleCloudAiplatformV1beta1CompleteTrialRequest resource to be passed as the request body. name: Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}` """ googleCloudAiplatformV1beta1CompleteTrialRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CompleteTrialRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsStudiesTrialsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsCreateRequest object. Fields: googleCloudAiplatformV1beta1Trial: A GoogleCloudAiplatformV1beta1Trial resource to be passed as the request body. parent: Required. The resource name of the Study to create the Trial in. Format: `projects/{project}/locations/{location}/studies/{study}` """ googleCloudAiplatformV1beta1Trial = _messages.MessageField('GoogleCloudAiplatformV1beta1Trial', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsStudiesTrialsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsDeleteRequest object. Fields: name: Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsStudiesTrialsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsGetRequest object. Fields: name: Required. The name of the Trial resource. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsStudiesTrialsListOptimalTrialsRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsListOptimalTrialsRequest object. Fields: googleCloudAiplatformV1beta1ListOptimalTrialsRequest: A GoogleCloudAiplatformV1beta1ListOptimalTrialsRequest resource to be passed as the request body. parent: Required. The name of the Study that the optimal Trial belongs to. """ googleCloudAiplatformV1beta1ListOptimalTrialsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ListOptimalTrialsRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsStudiesTrialsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsListRequest object. Fields: pageSize: Optional. The number of Trials to retrieve per "page" of results. If unspecified, the service will pick an appropriate default. pageToken: Optional. A page token to request the next page of results. If unspecified, there are no subsequent pages. parent: Required. The resource name of the Study to list the Trial from. Format: `projects/{project}/locations/{location}/studies/{study}` """ pageSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) pageToken = _messages.StringField(2) parent = _messages.StringField(3, required=True) class AiplatformProjectsLocationsStudiesTrialsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsStudiesTrialsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsStudiesTrialsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsStudiesTrialsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsStudiesTrialsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsStudiesTrialsStopRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsStopRequest object. Fields: googleCloudAiplatformV1beta1StopTrialRequest: A GoogleCloudAiplatformV1beta1StopTrialRequest resource to be passed as the request body. name: Required. The Trial's name. Format: `projects/{project}/locations/{location}/studies/{study}/trials/{trial}` """ googleCloudAiplatformV1beta1StopTrialRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1StopTrialRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsStudiesTrialsSuggestRequest(_messages.Message): r"""A AiplatformProjectsLocationsStudiesTrialsSuggestRequest object. Fields: googleCloudAiplatformV1beta1SuggestTrialsRequest: A GoogleCloudAiplatformV1beta1SuggestTrialsRequest resource to be passed as the request body. parent: Required. The project and location that the Study belongs to. Format: `projects/{project}/locations/{location}/studies/{study}` """ googleCloudAiplatformV1beta1SuggestTrialsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1SuggestTrialsRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsTensorboardsBatchReadRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsBatchReadRequest object. Fields: tensorboard: Required. The resource name of the Tensorboard containing TensorboardTimeSeries to read data from. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}`. The TensorboardTimeSeries referenced by time_series must be sub resources of this Tensorboard. timeSeries: Required. The resource names of the TensorboardTimeSeries to read data from. Format: `projects/{project}/locations/{location}/tensorb oards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time _series}` """ tensorboard = _messages.StringField(1, required=True) timeSeries = _messages.StringField(2, repeated=True) class AiplatformProjectsLocationsTensorboardsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsCreateRequest object. Fields: googleCloudAiplatformV1beta1Tensorboard: A GoogleCloudAiplatformV1beta1Tensorboard resource to be passed as the request body. parent: Required. The resource name of the Location to create the Tensorboard in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1Tensorboard = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensorboard', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsTensorboardsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsDeleteRequest object. Fields: name: Required. The name of the Tensorboard to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsBatchCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsBatchCreateRequest object. Fields: googleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesRequest: A GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesRequest resource to be passed as the request body. parent: Required. The resource name of the TensorboardExperiment to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{loc ation}/tensorboards/{tensorboard}/experiments/{experiment}` The TensorboardRuns referenced by the parent fields in the CreateTensorboardTimeSeriesRequest messages must be sub resources of this TensorboardExperiment. """ googleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsCreateRequest object. Fields: googleCloudAiplatformV1beta1TensorboardExperiment: A GoogleCloudAiplatformV1beta1TensorboardExperiment resource to be passed as the request body. parent: Required. The resource name of the Tensorboard to create the TensorboardExperiment in. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}` tensorboardExperimentId: Required. The ID to use for the Tensorboard experiment, which becomes the final component of the Tensorboard experiment's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`. """ googleCloudAiplatformV1beta1TensorboardExperiment = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardExperiment', 1) parent = _messages.StringField(2, required=True) tensorboardExperimentId = _messages.StringField(3) class AiplatformProjectsLocationsTensorboardsExperimentsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsDeleteRequest object. Fields: name: Required. The name of the TensorboardExperiment to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboa rd}/experiments/{experiment}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsGetRequest object. Fields: name: Required. The name of the TensorboardExperiment resource. Format: `p rojects/{project}/locations/{location}/tensorboards/{tensorboard}/experi ments/{experiment}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsListRequest object. Fields: filter: Lists the TensorboardExperiments that match the filter expression. orderBy: Field to use to sort the list. pageSize: The maximum number of TensorboardExperiments to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardExperiments are returned. The maximum value is 1000; values above 1000 are coerced to 1000. pageToken: A page token, received from a previous TensorboardService.ListTensorboardExperiments call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardExperiments must match the call that provided the page token. parent: Required. The resource name of the Tensorboard to list TensorboardExperiments. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsTensorboardsExperimentsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsTensorboardsExperimentsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsTensorboardsExperimentsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsPatchRequest object. Fields: googleCloudAiplatformV1beta1TensorboardExperiment: A GoogleCloudAiplatformV1beta1TensorboardExperiment resource to be passed as the request body. name: Output only. Name of the TensorboardExperiment. Format: `projects/{p roject}/locations/{location}/tensorboards/{tensorboard}/experiments/{exp eriment}` updateMask: Required. Field mask is used to specify the fields to be overwritten in the TensorboardExperiment resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified. """ googleCloudAiplatformV1beta1TensorboardExperiment = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardExperiment', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsTensorboardsExperimentsRunsBatchCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsBatchCreateRequest object. Fields: googleCloudAiplatformV1beta1BatchCreateTensorboardRunsRequest: A GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsRequest resource to be passed as the request body. parent: Required. The resource name of the TensorboardExperiment to create the TensorboardRuns in. Format: `projects/{project}/locations/{location} /tensorboards/{tensorboard}/experiments/{experiment}` The parent field in the CreateTensorboardRunRequest messages must match this field. """ googleCloudAiplatformV1beta1BatchCreateTensorboardRunsRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsCreateRequest object. Fields: googleCloudAiplatformV1beta1TensorboardRun: A GoogleCloudAiplatformV1beta1TensorboardRun resource to be passed as the request body. parent: Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: `projects/{project}/locations/{location}/ tensorboards/{tensorboard}/experiments/{experiment}` tensorboardRunId: Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`. """ googleCloudAiplatformV1beta1TensorboardRun = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardRun', 1) parent = _messages.StringField(2, required=True) tensorboardRunId = _messages.StringField(3) class AiplatformProjectsLocationsTensorboardsExperimentsRunsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsDeleteRequest object. Fields: name: Required. The name of the TensorboardRun to be deleted. Format: `pro jects/{project}/locations/{location}/tensorboards/{tensorboard}/experime nts/{experiment}/runs/{run}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsGetRequest object. Fields: name: Required. The name of the TensorboardRun resource. Format: `projects /{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{ experiment}/runs/{run}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsListRequest object. Fields: filter: Lists the TensorboardRuns that match the filter expression. orderBy: Field to use to sort the list. pageSize: The maximum number of TensorboardRuns to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardRuns are returned. The maximum value is 1000; values above 1000 are coerced to 1000. pageToken: A page token, received from a previous TensorboardService.ListTensorboardRuns call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardRuns must match the call that provided the page token. parent: Required. The resource name of the TensorboardExperiment to list TensorboardRuns. Format: `projects/{project}/locations/{location}/tensor boards/{tensorboard}/experiments/{experiment}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsTensorboardsExperimentsRunsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsOperationsCancel Request object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsOperationsDelete Request object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsTensorboardsExperimentsRunsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsTensorboardsExperimentsRunsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsPatchRequest object. Fields: googleCloudAiplatformV1beta1TensorboardRun: A GoogleCloudAiplatformV1beta1TensorboardRun resource to be passed as the request body. name: Output only. Name of the TensorboardRun. Format: `projects/{project} /locations/{location}/tensorboards/{tensorboard}/experiments/{experiment }/runs/{run}` updateMask: Required. Field mask is used to specify the fields to be overwritten in the TensorboardRun resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified. """ googleCloudAiplatformV1beta1TensorboardRun = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardRun', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesCreate Request object. Fields: googleCloudAiplatformV1beta1TensorboardTimeSeries: A GoogleCloudAiplatformV1beta1TensorboardTimeSeries resource to be passed as the request body. parent: Required. The resource name of the TensorboardRun to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{locatio n}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}` tensorboardTimeSeriesId: Optional. The user specified unique ID to use for the TensorboardTimeSeries, which becomes the final component of the TensorboardTimeSeries's resource name. This value should match "a-z0-9{0, 127}" """ googleCloudAiplatformV1beta1TensorboardTimeSeries = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardTimeSeries', 1) parent = _messages.StringField(2, required=True) tensorboardTimeSeriesId = _messages.StringField(3) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesDelete Request object. Fields: name: Required. The name of the TensorboardTimeSeries to be deleted. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboa rd}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesExportTensorboardTimeSeriesRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesExport TensorboardTimeSeriesRequest object. Fields: googleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataRequest: A GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataRequest resource to be passed as the request body. tensorboardTimeSeries: Required. The resource name of the TensorboardTimeSeries to export data from. Format: `projects/{project}/l ocations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/ runs/{run}/timeSeries/{time_series}` """ googleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataRequest', 1) tensorboardTimeSeries = _messages.StringField(2, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesGetRequest object. Fields: name: Required. The name of the TensorboardTimeSeries resource. Format: `p rojects/{project}/locations/{location}/tensorboards/{tensorboard}/experi ments/{experiment}/runs/{run}/timeSeries/{time_series}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesListRequest object. Fields: filter: Lists the TensorboardTimeSeries that match the filter expression. orderBy: Field to use to sort the list. pageSize: The maximum number of TensorboardTimeSeries to return. The service may return fewer than this value. If unspecified, at most 50 TensorboardTimeSeries are returned. The maximum value is 1000; values above 1000 are coerced to 1000. pageToken: A page token, received from a previous TensorboardService.ListTensorboardTimeSeries call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboardTimeSeries must match the call that provided the page token. parent: Required. The resource name of the TensorboardRun to list TensorboardTimeSeries. Format: `projects/{project}/locations/{location}/ tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesOperat ionsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesOperat ionsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesOperat ionsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesOperat ionsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesOperat ionsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesPatchRequest object. Fields: googleCloudAiplatformV1beta1TensorboardTimeSeries: A GoogleCloudAiplatformV1beta1TensorboardTimeSeries resource to be passed as the request body. name: Output only. Name of the TensorboardTimeSeries. updateMask: Required. Field mask is used to specify the fields to be overwritten in the TensorboardTimeSeries resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified. """ googleCloudAiplatformV1beta1TensorboardTimeSeries = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardTimeSeries', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesReadBlobDataRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesReadBl obDataRequest object. Fields: blobIds: IDs of the blobs to read. timeSeries: Required. The resource name of the TensorboardTimeSeries to list Blobs. Format: `projects/{project}/locations/{location}/tensorboard s/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_ser ies}` """ blobIds = _messages.StringField(1, repeated=True) timeSeries = _messages.StringField(2, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesReadRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesReadRequest object. Fields: filter: Reads the TensorboardTimeSeries' data that match the filter expression. maxDataPoints: The maximum number of TensorboardTimeSeries' data to return. This value should be a positive integer. This value can be set to -1 to return all data. tensorboardTimeSeries: Required. The resource name of the TensorboardTimeSeries to read data from. Format: `projects/{project}/loc ations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/ru ns/{run}/timeSeries/{time_series}` """ filter = _messages.StringField(1) maxDataPoints = _messages.IntegerField(2, variant=_messages.Variant.INT32) tensorboardTimeSeries = _messages.StringField(3, required=True) class AiplatformProjectsLocationsTensorboardsExperimentsWriteRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsExperimentsWriteRequest object. Fields: googleCloudAiplatformV1beta1WriteTensorboardExperimentDataRequest: A GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataRequest resource to be passed as the request body. tensorboardExperiment: Required. The resource name of the TensorboardExperiment to write data to. Format: `projects/{project}/loca tions/{location}/tensorboards/{tensorboard}/experiments/{experiment}` """ googleCloudAiplatformV1beta1WriteTensorboardExperimentDataRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataRequest', 1) tensorboardExperiment = _messages.StringField(2, required=True) class AiplatformProjectsLocationsTensorboardsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsGetRequest object. Fields: name: Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsListRequest object. Fields: filter: Lists the Tensorboards that match the filter expression. orderBy: Field to use to sort the list. pageSize: The maximum number of Tensorboards to return. The service may return fewer than this value. If unspecified, at most 100 Tensorboards are returned. The maximum value is 100; values above 100 are coerced to 100. pageToken: A page token, received from a previous TensorboardService.ListTensorboards call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to TensorboardService.ListTensorboards must match the call that provided the page token. parent: Required. The resource name of the Location to list Tensorboards. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) readMask = _messages.StringField(6) class AiplatformProjectsLocationsTensorboardsOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsTensorboardsOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsTensorboardsPatchRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsPatchRequest object. Fields: googleCloudAiplatformV1beta1Tensorboard: A GoogleCloudAiplatformV1beta1Tensorboard resource to be passed as the request body. name: Output only. Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}` updateMask: Required. Field mask is used to specify the fields to be overwritten in the Tensorboard resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field is overwritten if it's in the mask. If the user does not provide a mask then all fields are overwritten if new values are specified. """ googleCloudAiplatformV1beta1Tensorboard = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensorboard', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformProjectsLocationsTensorboardsReadSizeRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsReadSizeRequest object. Fields: tensorboard: Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}` """ tensorboard = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTensorboardsReadUsageRequest(_messages.Message): r"""A AiplatformProjectsLocationsTensorboardsReadUsageRequest object. Fields: tensorboard: Required. The name of the Tensorboard resource. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}` """ tensorboard = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTrainingPipelinesCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsTrainingPipelinesCancelRequest object. Fields: googleCloudAiplatformV1beta1CancelTrainingPipelineRequest: A GoogleCloudAiplatformV1beta1CancelTrainingPipelineRequest resource to be passed as the request body. name: Required. The name of the TrainingPipeline to cancel. Format: `proje cts/{project}/locations/{location}/trainingPipelines/{training_pipeline} ` """ googleCloudAiplatformV1beta1CancelTrainingPipelineRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CancelTrainingPipelineRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsTrainingPipelinesCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsTrainingPipelinesCreateRequest object. Fields: googleCloudAiplatformV1beta1TrainingPipeline: A GoogleCloudAiplatformV1beta1TrainingPipeline resource to be passed as the request body. parent: Required. The resource name of the Location to create the TrainingPipeline in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1TrainingPipeline = _messages.MessageField('GoogleCloudAiplatformV1beta1TrainingPipeline', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsTrainingPipelinesDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsTrainingPipelinesDeleteRequest object. Fields: name: Required. The name of the TrainingPipeline resource to be deleted. Format: `projects/{project}/locations/{location}/trainingPipelines/{trai ning_pipeline}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTrainingPipelinesGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsTrainingPipelinesGetRequest object. Fields: name: Required. The name of the TrainingPipeline resource. Format: `projec ts/{project}/locations/{location}/trainingPipelines/{training_pipeline}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTrainingPipelinesListRequest(_messages.Message): r"""A AiplatformProjectsLocationsTrainingPipelinesListRequest object. Fields: filter: The standard list filter. Supported fields: * `display_name` supports `=`, `!=` comparisons, and `:` wildcard. * `state` supports `=`, `!=` comparisons. * `training_task_definition` `=`, `!=` comparisons, and `:` wildcard. * `create_time` supports `=`, `!=`,`<`, `<=`,`>`, `>=` comparisons. `create_time` must be in RFC 3339 format. * `labels` supports general map functions that is: `labels.key=value` - key:value equality `labels.key:* - key existence Some examples of using the filter are: * `state="PIPELINE_STATE_SUCCEEDED" AND display_name:"my_pipeline_*"` * `state!="PIPELINE_STATE_FAILED" OR display_name="my_pipeline"` * `NOT display_name="my_pipeline"` * `create_time>"2021-05-18T00:00:00Z"` * `training_task_definition:"*automl_text_classification*"` pageSize: The standard list page size. pageToken: The standard list page token. Typically obtained via ListTrainingPipelinesResponse.next_page_token of the previous PipelineService.ListTrainingPipelines call. parent: Required. The resource name of the Location to list the TrainingPipelines from. Format: `projects/{project}/locations/{location}` readMask: Mask specifying which fields to read. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) readMask = _messages.StringField(5) class AiplatformProjectsLocationsTrainingPipelinesOperationsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsTrainingPipelinesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTrainingPipelinesOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsTrainingPipelinesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTrainingPipelinesOperationsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsTrainingPipelinesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTrainingPipelinesOperationsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsTrainingPipelinesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformProjectsLocationsTrainingPipelinesOperationsWaitRequest(_messages.Message): r"""A AiplatformProjectsLocationsTrainingPipelinesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformProjectsLocationsTuningJobsCancelRequest(_messages.Message): r"""A AiplatformProjectsLocationsTuningJobsCancelRequest object. Fields: googleCloudAiplatformV1beta1CancelTuningJobRequest: A GoogleCloudAiplatformV1beta1CancelTuningJobRequest resource to be passed as the request body. name: Required. The name of the TuningJob to cancel. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}` """ googleCloudAiplatformV1beta1CancelTuningJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CancelTuningJobRequest', 1) name = _messages.StringField(2, required=True) class AiplatformProjectsLocationsTuningJobsCreateRequest(_messages.Message): r"""A AiplatformProjectsLocationsTuningJobsCreateRequest object. Fields: googleCloudAiplatformV1beta1TuningJob: A GoogleCloudAiplatformV1beta1TuningJob resource to be passed as the request body. parent: Required. The resource name of the Location to create the TuningJob in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1TuningJob = _messages.MessageField('GoogleCloudAiplatformV1beta1TuningJob', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsTuningJobsGetRequest(_messages.Message): r"""A AiplatformProjectsLocationsTuningJobsGetRequest object. Fields: name: Required. The name of the TuningJob resource. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}` """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTuningJobsListRequest(_messages.Message): r"""A AiplatformProjectsLocationsTuningJobsListRequest object. Fields: filter: Optional. The standard list filter. pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. Typically obtained via ListTuningJobsResponse.next_page_token of the previous GenAiTuningService.ListTuningJob][] call. parent: Required. The resource name of the Location to list the TuningJobs from. Format: `projects/{project}/locations/{location}` """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) class AiplatformProjectsLocationsTuningJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformProjectsLocationsTuningJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformProjectsLocationsTuningJobsOptimizePromptRequest(_messages.Message): r"""A AiplatformProjectsLocationsTuningJobsOptimizePromptRequest object. Fields: googleCloudAiplatformV1beta1OptimizePromptRequest: A GoogleCloudAiplatformV1beta1OptimizePromptRequest resource to be passed as the request body. parent: Required. The resource name of the Location to optimize the prompt in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1OptimizePromptRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1OptimizePromptRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsLocationsTuningJobsRebaseTunedModelRequest(_messages.Message): r"""A AiplatformProjectsLocationsTuningJobsRebaseTunedModelRequest object. Fields: googleCloudAiplatformV1beta1RebaseTunedModelRequest: A GoogleCloudAiplatformV1beta1RebaseTunedModelRequest resource to be passed as the request body. parent: Required. The resource name of the Location into which to rebase the Model. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1RebaseTunedModelRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RebaseTunedModelRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsModelGardenEulaAcceptRequest(_messages.Message): r"""A AiplatformProjectsModelGardenEulaAcceptRequest object. Fields: googleCloudAiplatformV1beta1AcceptPublisherModelEulaRequest: A GoogleCloudAiplatformV1beta1AcceptPublisherModelEulaRequest resource to be passed as the request body. parent: Required. The project requesting access for named model. The format is `projects/{project}`. """ googleCloudAiplatformV1beta1AcceptPublisherModelEulaRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1AcceptPublisherModelEulaRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsModelGardenEulaCheckRequest(_messages.Message): r"""A AiplatformProjectsModelGardenEulaCheckRequest object. Fields: googleCloudAiplatformV1beta1CheckPublisherModelEulaAcceptanceRequest: A GoogleCloudAiplatformV1beta1CheckPublisherModelEulaAcceptanceRequest resource to be passed as the request body. parent: Required. The project requesting access for named model. The format is `projects/{project}`. """ googleCloudAiplatformV1beta1CheckPublisherModelEulaAcceptanceRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CheckPublisherModelEulaAcceptanceRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformProjectsPublishersModelsEnableModelRequest(_messages.Message): r"""A AiplatformProjectsPublishersModelsEnableModelRequest object. Fields: googleCloudAiplatformV1beta1EnableModelRequest: A GoogleCloudAiplatformV1beta1EnableModelRequest resource to be passed as the request body. name: Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}` parent: Required. The project requesting access for named model. Format: `projects/{project}` """ googleCloudAiplatformV1beta1EnableModelRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1EnableModelRequest', 1) name = _messages.StringField(2, required=True) parent = _messages.StringField(3, required=True) class AiplatformProjectsSetPublisherModelConfigRequest(_messages.Message): r"""A AiplatformProjectsSetPublisherModelConfigRequest object. Fields: googleCloudAiplatformV1beta1SetPublisherModelConfigRequest: A GoogleCloudAiplatformV1beta1SetPublisherModelConfigRequest resource to be passed as the request body. name: Required. The name of the publisher model, in the format of `project s/{project}/locations/{location}/publishers/{publisher}/models/{model}`. """ googleCloudAiplatformV1beta1SetPublisherModelConfigRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1SetPublisherModelConfigRequest', 1) name = _messages.StringField(2, required=True) class AiplatformPublishersModelsComputeTokensRequest(_messages.Message): r"""A AiplatformPublishersModelsComputeTokensRequest object. Fields: endpoint: Required. The name of the Endpoint requested to get lists of tokens and token ids. googleCloudAiplatformV1beta1ComputeTokensRequest: A GoogleCloudAiplatformV1beta1ComputeTokensRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1ComputeTokensRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ComputeTokensRequest', 2) class AiplatformPublishersModelsCountTokensRequest(_messages.Message): r"""A AiplatformPublishersModelsCountTokensRequest object. Fields: endpoint: Required. The name of the Endpoint requested to perform token counting. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1CountTokensRequest: A GoogleCloudAiplatformV1beta1CountTokensRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1CountTokensRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CountTokensRequest', 2) class AiplatformPublishersModelsFetchPredictOperationRequest(_messages.Message): r"""A AiplatformPublishersModelsFetchPredictOperationRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `proje cts/{project}/locations/{location}/publishers/{publisher}/models/{model} ` googleCloudAiplatformV1beta1FetchPredictOperationRequest: A GoogleCloudAiplatformV1beta1FetchPredictOperationRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1FetchPredictOperationRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1FetchPredictOperationRequest', 2) class AiplatformPublishersModelsGenerateContentRequest(_messages.Message): r"""A AiplatformPublishersModelsGenerateContentRequest object. Fields: googleCloudAiplatformV1beta1GenerateContentRequest: A GoogleCloudAiplatformV1beta1GenerateContentRequest resource to be passed as the request body. model: Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` """ googleCloudAiplatformV1beta1GenerateContentRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateContentRequest', 1) model = _messages.StringField(2, required=True) class AiplatformPublishersModelsGetRequest(_messages.Message): r"""A AiplatformPublishersModelsGetRequest object. Enums: ViewValueValuesEnum: Optional. PublisherModel view specifying which fields to read. Fields: huggingFaceToken: Optional. Token used to access Hugging Face gated models. includeEquivalentModelGardenModelDeploymentConfigs: Optional. Whether to cnclude the deployment configs from the equivalent Model Garden model if the requested model is a Hugging Face model. isHuggingFaceModel: Optional. Boolean indicates whether the requested model is a Hugging Face model. languageCode: Optional. The IETF BCP-47 language code representing the language in which the publisher model's text information should be written in. name: Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}` view: Optional. PublisherModel view specifying which fields to read. """ class ViewValueValuesEnum(_messages.Enum): r"""Optional. PublisherModel view specifying which fields to read. Values: PUBLISHER_MODEL_VIEW_UNSPECIFIED: The default / unset value. The API will default to the BASIC view. PUBLISHER_MODEL_VIEW_BASIC: Include basic metadata about the publisher model, but not the full contents. PUBLISHER_MODEL_VIEW_FULL: Include everything. PUBLISHER_MODEL_VERSION_VIEW_BASIC: Include: VersionId, ModelVersionExternalName, and SupportedActions. """ PUBLISHER_MODEL_VIEW_UNSPECIFIED = 0 PUBLISHER_MODEL_VIEW_BASIC = 1 PUBLISHER_MODEL_VIEW_FULL = 2 PUBLISHER_MODEL_VERSION_VIEW_BASIC = 3 huggingFaceToken = _messages.StringField(1) includeEquivalentModelGardenModelDeploymentConfigs = _messages.BooleanField(2) isHuggingFaceModel = _messages.BooleanField(3) languageCode = _messages.StringField(4) name = _messages.StringField(5, required=True) view = _messages.EnumField('ViewValueValuesEnum', 6) class AiplatformPublishersModelsListRequest(_messages.Message): r"""A AiplatformPublishersModelsListRequest object. Enums: ViewValueValuesEnum: Optional. PublisherModel view specifying which fields to read. Fields: filter: Optional. The standard list filter. languageCode: Optional. The IETF BCP-47 language code representing the language in which the publisher models' text information should be written in. If not set, by default English (en). listAllVersions: Optional. List all publisher model versions if the flag is set to true. orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. Typically obtained via ListPublisherModelsResponse.next_page_token of the previous ModelGardenService.ListPublisherModels call. parent: Required. The name of the Publisher from which to list the PublisherModels. Format: `publishers/{publisher}` view: Optional. PublisherModel view specifying which fields to read. """ class ViewValueValuesEnum(_messages.Enum): r"""Optional. PublisherModel view specifying which fields to read. Values: PUBLISHER_MODEL_VIEW_UNSPECIFIED: The default / unset value. The API will default to the BASIC view. PUBLISHER_MODEL_VIEW_BASIC: Include basic metadata about the publisher model, but not the full contents. PUBLISHER_MODEL_VIEW_FULL: Include everything. PUBLISHER_MODEL_VERSION_VIEW_BASIC: Include: VersionId, ModelVersionExternalName, and SupportedActions. """ PUBLISHER_MODEL_VIEW_UNSPECIFIED = 0 PUBLISHER_MODEL_VIEW_BASIC = 1 PUBLISHER_MODEL_VIEW_FULL = 2 PUBLISHER_MODEL_VERSION_VIEW_BASIC = 3 filter = _messages.StringField(1) languageCode = _messages.StringField(2) listAllVersions = _messages.BooleanField(3) orderBy = _messages.StringField(4) pageSize = _messages.IntegerField(5, variant=_messages.Variant.INT32) pageToken = _messages.StringField(6) parent = _messages.StringField(7, required=True) view = _messages.EnumField('ViewValueValuesEnum', 8) class AiplatformPublishersModelsPredictLongRunningRequest(_messages.Message): r"""A AiplatformPublishersModelsPredictLongRunningRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` or `proje cts/{project}/locations/{location}/publishers/{publisher}/models/{model} ` googleCloudAiplatformV1beta1PredictLongRunningRequest: A GoogleCloudAiplatformV1beta1PredictLongRunningRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1PredictLongRunningRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictLongRunningRequest', 2) class AiplatformPublishersModelsPredictRequest(_messages.Message): r"""A AiplatformPublishersModelsPredictRequest object. Fields: endpoint: Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` googleCloudAiplatformV1beta1PredictRequest: A GoogleCloudAiplatformV1beta1PredictRequest resource to be passed as the request body. """ endpoint = _messages.StringField(1, required=True) googleCloudAiplatformV1beta1PredictRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictRequest', 2) class AiplatformPublishersModelsStreamGenerateContentRequest(_messages.Message): r"""A AiplatformPublishersModelsStreamGenerateContentRequest object. Fields: googleCloudAiplatformV1beta1GenerateContentRequest: A GoogleCloudAiplatformV1beta1GenerateContentRequest resource to be passed as the request body. model: Required. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` """ googleCloudAiplatformV1beta1GenerateContentRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateContentRequest', 1) model = _messages.StringField(2, required=True) class AiplatformRagCorporaOperationsCancelRequest(_messages.Message): r"""A AiplatformRagCorporaOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformRagCorporaOperationsDeleteRequest(_messages.Message): r"""A AiplatformRagCorporaOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformRagCorporaOperationsGetRequest(_messages.Message): r"""A AiplatformRagCorporaOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformRagCorporaOperationsListRequest(_messages.Message): r"""A AiplatformRagCorporaOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformRagCorporaOperationsWaitRequest(_messages.Message): r"""A AiplatformRagCorporaOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformRagCorporaRagFilesOperationsCancelRequest(_messages.Message): r"""A AiplatformRagCorporaRagFilesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformRagCorporaRagFilesOperationsDeleteRequest(_messages.Message): r"""A AiplatformRagCorporaRagFilesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformRagCorporaRagFilesOperationsGetRequest(_messages.Message): r"""A AiplatformRagCorporaRagFilesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformRagCorporaRagFilesOperationsListRequest(_messages.Message): r"""A AiplatformRagCorporaRagFilesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformRagCorporaRagFilesOperationsWaitRequest(_messages.Message): r"""A AiplatformRagCorporaRagFilesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformRagEngineConfigOperationsCancelRequest(_messages.Message): r"""A AiplatformRagEngineConfigOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformRagEngineConfigOperationsDeleteRequest(_messages.Message): r"""A AiplatformRagEngineConfigOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformRagEngineConfigOperationsGetRequest(_messages.Message): r"""A AiplatformRagEngineConfigOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformRagEngineConfigOperationsListRequest(_messages.Message): r"""A AiplatformRagEngineConfigOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformRagEngineConfigOperationsWaitRequest(_messages.Message): r"""A AiplatformRagEngineConfigOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformReasoningEnginesCreateRequest(_messages.Message): r"""A AiplatformReasoningEnginesCreateRequest object. Fields: googleCloudAiplatformV1beta1ReasoningEngine: A GoogleCloudAiplatformV1beta1ReasoningEngine resource to be passed as the request body. parent: Required. The resource name of the Location to create the ReasoningEngine in. Format: `projects/{project}/locations/{location}` """ googleCloudAiplatformV1beta1ReasoningEngine = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngine', 1) parent = _messages.StringField(2) class AiplatformReasoningEnginesDeleteRequest(_messages.Message): r"""A AiplatformReasoningEnginesDeleteRequest object. Fields: force: Optional. If set to true, child resources of this reasoning engine will also be deleted. Otherwise, the request will fail with FAILED_PRECONDITION error when the reasoning engine has undeleted child resources. name: Required. The name of the ReasoningEngine resource to be deleted. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}` """ force = _messages.BooleanField(1) name = _messages.StringField(2, required=True) class AiplatformReasoningEnginesExamplesOperationsCancelRequest(_messages.Message): r"""A AiplatformReasoningEnginesExamplesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesExamplesOperationsDeleteRequest(_messages.Message): r"""A AiplatformReasoningEnginesExamplesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesExamplesOperationsGetRequest(_messages.Message): r"""A AiplatformReasoningEnginesExamplesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesExamplesOperationsWaitRequest(_messages.Message): r"""A AiplatformReasoningEnginesExamplesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformReasoningEnginesExecuteCodeRequest(_messages.Message): r"""A AiplatformReasoningEnginesExecuteCodeRequest object. Fields: googleCloudAiplatformV1beta1ExecuteCodeRequest: A GoogleCloudAiplatformV1beta1ExecuteCodeRequest resource to be passed as the request body. name: Required. The resource name of the sandbox environment to execute. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}` """ googleCloudAiplatformV1beta1ExecuteCodeRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ExecuteCodeRequest', 1) name = _messages.StringField(2, required=True) class AiplatformReasoningEnginesGetRequest(_messages.Message): r"""A AiplatformReasoningEnginesGetRequest object. Fields: name: Required. The name of the ReasoningEngine resource. Format: `project s/{project}/locations/{location}/reasoningEngines/{reasoning_engine}` """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesListRequest(_messages.Message): r"""A AiplatformReasoningEnginesListRequest object. Fields: filter: Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. parent: Required. The resource name of the Location to list the ReasoningEngines from. Format: `projects/{project}/locations/{location}` """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4) class AiplatformReasoningEnginesMemoriesCreateRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesCreateRequest object. Fields: googleCloudAiplatformV1beta1Memory: A GoogleCloudAiplatformV1beta1Memory resource to be passed as the request body. parent: Required. The resource name of the ReasoningEngine to create the Memory under. Format: `projects/{project}/locations/{location}/reasoning Engines/{reasoning_engine}` """ googleCloudAiplatformV1beta1Memory = _messages.MessageField('GoogleCloudAiplatformV1beta1Memory', 1) parent = _messages.StringField(2, required=True) class AiplatformReasoningEnginesMemoriesDeleteRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesDeleteRequest object. Fields: name: Required. The resource name of the Memory to delete. Format: `projec ts/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/me mories/{memory}` """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesMemoriesGenerateRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesGenerateRequest object. Fields: googleCloudAiplatformV1beta1GenerateMemoriesRequest: A GoogleCloudAiplatformV1beta1GenerateMemoriesRequest resource to be passed as the request body. parent: Required. The resource name of the ReasoningEngine to generate memories for. Format: `projects/{project}/locations/{location}/reasoning Engines/{reasoning_engine}` """ googleCloudAiplatformV1beta1GenerateMemoriesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateMemoriesRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformReasoningEnginesMemoriesGetRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesGetRequest object. Fields: name: Required. The resource name of the Memory. Format: `projects/{projec t}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{me mory}` """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesMemoriesListRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesListRequest object. Fields: filter: Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). Supported fields: * `scope` (as a JSON string with equality match only) * `topics` (i.e. `topics.custom_memory_topic_label: "example topic" OR topics.managed_memory_topic: USER_PREFERENCES`) orderBy: Optional. The standard list order by string. If not specified, the default order is `create_time desc`. If specified, the default sorting order of provided fields is ascending. More detail in [AIP-132](https://google.aip.dev/132). Supported fields: * `create_time` * `update_time` pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. parent: Required. The resource name of the ReasoningEngine to list the Memories under. Format: `projects/{project}/locations/{location}/reasoni ngEngines/{reasoning_engine}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformReasoningEnginesMemoriesOperationsCancelRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesMemoriesOperationsDeleteRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesMemoriesOperationsGetRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesMemoriesOperationsListRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformReasoningEnginesMemoriesOperationsWaitRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformReasoningEnginesMemoriesPatchRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesPatchRequest object. Fields: googleCloudAiplatformV1beta1Memory: A GoogleCloudAiplatformV1beta1Memory resource to be passed as the request body. name: Identifier. The resource name of the Memory. Format: `projects/{proj ect}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{ memory}` updateMask: Optional. Mask specifying which fields to update. Supported fields: * `display_name` * `description` * `fact` """ googleCloudAiplatformV1beta1Memory = _messages.MessageField('GoogleCloudAiplatformV1beta1Memory', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformReasoningEnginesMemoriesPurgeRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesPurgeRequest object. Fields: googleCloudAiplatformV1beta1PurgeMemoriesRequest: A GoogleCloudAiplatformV1beta1PurgeMemoriesRequest resource to be passed as the request body. parent: Required. The resource name of the ReasoningEngine to purge memories from. Format: `projects/{project}/locations/{location}/reasonin gEngines/{reasoning_engine}` """ googleCloudAiplatformV1beta1PurgeMemoriesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1PurgeMemoriesRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformReasoningEnginesMemoriesRetrieveRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesRetrieveRequest object. Fields: googleCloudAiplatformV1beta1RetrieveMemoriesRequest: A GoogleCloudAiplatformV1beta1RetrieveMemoriesRequest resource to be passed as the request body. parent: Required. The resource name of the ReasoningEngine to retrieve memories from. Format: `projects/{project}/locations/{location}/reasonin gEngines/{reasoning_engine}` """ googleCloudAiplatformV1beta1RetrieveMemoriesRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RetrieveMemoriesRequest', 1) parent = _messages.StringField(2, required=True) class AiplatformReasoningEnginesMemoriesRevisionsGetRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesRevisionsGetRequest object. Fields: name: Required. The resource name of the Memory Revision to retrieve. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}/memories/{memory}/revisions/{revision}` """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesMemoriesRevisionsListRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesRevisionsListRequest object. Fields: filter: Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). Supported fields (equality match only): * `labels` pageSize: Optional. The standard list page size. pageToken: Optional. The standard list page token. parent: Required. The resource name of the Memory to list revisions for. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}/memories/{memory}` """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) class AiplatformReasoningEnginesMemoriesRollbackRequest(_messages.Message): r"""A AiplatformReasoningEnginesMemoriesRollbackRequest object. Fields: googleCloudAiplatformV1beta1RollbackMemoryRequest: A GoogleCloudAiplatformV1beta1RollbackMemoryRequest resource to be passed as the request body. name: Required. The resource name of the Memory to rollback. Format: `proj ects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/ memories/{memory}` """ googleCloudAiplatformV1beta1RollbackMemoryRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1RollbackMemoryRequest', 1) name = _messages.StringField(2, required=True) class AiplatformReasoningEnginesOperationsCancelRequest(_messages.Message): r"""A AiplatformReasoningEnginesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesOperationsDeleteRequest(_messages.Message): r"""A AiplatformReasoningEnginesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesOperationsGetRequest(_messages.Message): r"""A AiplatformReasoningEnginesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesOperationsListRequest(_messages.Message): r"""A AiplatformReasoningEnginesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformReasoningEnginesOperationsWaitRequest(_messages.Message): r"""A AiplatformReasoningEnginesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformReasoningEnginesPatchRequest(_messages.Message): r"""A AiplatformReasoningEnginesPatchRequest object. Fields: googleCloudAiplatformV1beta1ReasoningEngine: A GoogleCloudAiplatformV1beta1ReasoningEngine resource to be passed as the request body. name: Identifier. The resource name of the ReasoningEngine. Format: `proje cts/{project}/locations/{location}/reasoningEngines/{reasoning_engine}` updateMask: Optional. Mask specifying which fields to update. """ googleCloudAiplatformV1beta1ReasoningEngine = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngine', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformReasoningEnginesQueryRequest(_messages.Message): r"""A AiplatformReasoningEnginesQueryRequest object. Fields: googleCloudAiplatformV1beta1QueryReasoningEngineRequest: A GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest resource to be passed as the request body. name: Required. The name of the ReasoningEngine resource to use. Format: ` projects/{project}/locations/{location}/reasoningEngines/{reasoning_engi ne}` """ googleCloudAiplatformV1beta1QueryReasoningEngineRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest', 1) name = _messages.StringField(2, required=True) class AiplatformReasoningEnginesSandboxEnvironmentsCreateRequest(_messages.Message): r"""A AiplatformReasoningEnginesSandboxEnvironmentsCreateRequest object. Fields: googleCloudAiplatformV1beta1SandboxEnvironment: A GoogleCloudAiplatformV1beta1SandboxEnvironment resource to be passed as the request body. parent: Required. The resource name of the reasoning engine to create the SandboxEnvironment in. Format: `projects/{project}/locations/{location}/ reasoningEngines/{reasoning_engine}`. """ googleCloudAiplatformV1beta1SandboxEnvironment = _messages.MessageField('GoogleCloudAiplatformV1beta1SandboxEnvironment', 1) parent = _messages.StringField(2, required=True) class AiplatformReasoningEnginesSandboxEnvironmentsDeleteRequest(_messages.Message): r"""A AiplatformReasoningEnginesSandboxEnvironmentsDeleteRequest object. Fields: name: Required. The resource name of the SandboxEnvironment to delete. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}/sandboxEnvironments/{sandbox_environment}` """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesSandboxEnvironmentsExecuteRequest(_messages.Message): r"""A AiplatformReasoningEnginesSandboxEnvironmentsExecuteRequest object. Fields: googleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest: A GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest resource to be passed as the request body. name: Required. The resource name of the sandbox environment to execute. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}/sandboxEnvironments/{sandbox_environment}` """ googleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest', 1) name = _messages.StringField(2, required=True) class AiplatformReasoningEnginesSandboxEnvironmentsGetRequest(_messages.Message): r"""A AiplatformReasoningEnginesSandboxEnvironmentsGetRequest object. Fields: name: Required. The resource name of the sandbox environment. Format: `pro jects/{project}/locations/{location}/reasoningEngines/{reasoning_engine} /sandboxEnvironments/{sandbox_environment}` """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesSandboxEnvironmentsListRequest(_messages.Message): r"""A AiplatformReasoningEnginesSandboxEnvironmentsListRequest object. Fields: filter: Optional. The standard list filter. More detail in [AIP-160](https://google.aip.dev/160). pageSize: Optional. The maximum number of SandboxEnvironments to return. The service may return fewer than this value. If unspecified, at most 100 SandboxEnvironments will be returned. pageToken: Optional. The standard list page token, received from a previous `ListSandboxEnvironments` call. Provide this to retrieve the subsequent page. parent: Required. The resource name of the reasoning engine to list sandbox environments from. Format: `projects/{project}/locations/{locati on}/reasoningEngines/{reasoning_engine}` """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) parent = _messages.StringField(4, required=True) class AiplatformReasoningEnginesSandboxEnvironmentsOperationsCancelRequest(_messages.Message): r"""A AiplatformReasoningEnginesSandboxEnvironmentsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesSandboxEnvironmentsOperationsDeleteRequest(_messages.Message): r"""A AiplatformReasoningEnginesSandboxEnvironmentsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesSandboxEnvironmentsOperationsGetRequest(_messages.Message): r"""A AiplatformReasoningEnginesSandboxEnvironmentsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesSandboxEnvironmentsOperationsListRequest(_messages.Message): r"""A AiplatformReasoningEnginesSandboxEnvironmentsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformReasoningEnginesSandboxEnvironmentsOperationsWaitRequest(_messages.Message): r"""A AiplatformReasoningEnginesSandboxEnvironmentsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformReasoningEnginesSessionsCreateRequest(_messages.Message): r"""A AiplatformReasoningEnginesSessionsCreateRequest object. Fields: googleCloudAiplatformV1beta1Session: A GoogleCloudAiplatformV1beta1Session resource to be passed as the request body. parent: Required. The resource name of the location to create the session in. Format: `projects/{project}/locations/{location}/reasoningEngines/{r easoning_engine}` """ googleCloudAiplatformV1beta1Session = _messages.MessageField('GoogleCloudAiplatformV1beta1Session', 1) parent = _messages.StringField(2, required=True) class AiplatformReasoningEnginesSessionsDeleteRequest(_messages.Message): r"""A AiplatformReasoningEnginesSessionsDeleteRequest object. Fields: name: Required. The resource name of the session. Format: `projects/{proje ct}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{s ession}` """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesSessionsEventsListRequest(_messages.Message): r"""A AiplatformReasoningEnginesSessionsEventsListRequest object. Fields: filter: Optional. The standard list filter. Supported fields: * `timestamp` range (i.e. `timestamp>="2025-01-31T11:30:00-04:00"` where the timestamp is in RFC 3339 format) More detail in [AIP-160](https://google.aip.dev/160). orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `timestamp` Example: `timestamp desc`. pageSize: Optional. The maximum number of events to return. The service may return fewer than this value. If unspecified, at most 100 events will be returned. These events are ordered by timestamp in ascending order. pageToken: Optional. The next_page_token value returned from a previous list SessionService.ListEvents call. parent: Required. The resource name of the session to list events from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}/sessions/{session}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformReasoningEnginesSessionsGetRequest(_messages.Message): r"""A AiplatformReasoningEnginesSessionsGetRequest object. Fields: name: Required. The resource name of the session. Format: `projects/{proje ct}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{s ession}` """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesSessionsListRequest(_messages.Message): r"""A AiplatformReasoningEnginesSessionsListRequest object. Fields: filter: Optional. The standard list filter. Supported fields: * `display_name` * `user_id` * `labels` Example: `display_name="abc"`, `user_id="123"`, `labels.key="value"`. orderBy: Optional. A comma-separated list of fields to order by, sorted in ascending order. Use "desc" after a field name for descending. Supported fields: * `create_time` * `update_time` Example: `create_time desc`. pageSize: Optional. The maximum number of sessions to return. The service may return fewer than this value. If unspecified, at most 100 sessions will be returned. pageToken: Optional. The next_page_token value returned from a previous list SessionService.ListSessions call. parent: Required. The resource name of the location to list sessions from. Format: `projects/{project}/locations/{location}/reasoningEngines/{reaso ning_engine}` """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) parent = _messages.StringField(5, required=True) class AiplatformReasoningEnginesSessionsOperationsCancelRequest(_messages.Message): r"""A AiplatformReasoningEnginesSessionsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesSessionsOperationsDeleteRequest(_messages.Message): r"""A AiplatformReasoningEnginesSessionsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesSessionsOperationsGetRequest(_messages.Message): r"""A AiplatformReasoningEnginesSessionsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformReasoningEnginesSessionsOperationsListRequest(_messages.Message): r"""A AiplatformReasoningEnginesSessionsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformReasoningEnginesSessionsOperationsWaitRequest(_messages.Message): r"""A AiplatformReasoningEnginesSessionsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformReasoningEnginesSessionsPatchRequest(_messages.Message): r"""A AiplatformReasoningEnginesSessionsPatchRequest object. Fields: googleCloudAiplatformV1beta1Session: A GoogleCloudAiplatformV1beta1Session resource to be passed as the request body. name: Identifier. The resource name of the session. Format: 'projects/{pro ject}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/ {session}'. updateMask: Optional. Field mask is used to control which fields get updated. If the mask is not present, all fields will be updated. """ googleCloudAiplatformV1beta1Session = _messages.MessageField('GoogleCloudAiplatformV1beta1Session', 1) name = _messages.StringField(2, required=True) updateMask = _messages.StringField(3) class AiplatformReasoningEnginesStreamQueryRequest(_messages.Message): r"""A AiplatformReasoningEnginesStreamQueryRequest object. Fields: googleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest: A GoogleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest resource to be passed as the request body. name: Required. The name of the ReasoningEngine resource to use. Format: ` projects/{project}/locations/{location}/reasoningEngines/{reasoning_engi ne}` """ googleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest', 1) name = _messages.StringField(2, required=True) class AiplatformSchedulesOperationsCancelRequest(_messages.Message): r"""A AiplatformSchedulesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformSchedulesOperationsDeleteRequest(_messages.Message): r"""A AiplatformSchedulesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformSchedulesOperationsGetRequest(_messages.Message): r"""A AiplatformSchedulesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformSchedulesOperationsListRequest(_messages.Message): r"""A AiplatformSchedulesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformSchedulesOperationsWaitRequest(_messages.Message): r"""A AiplatformSchedulesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformSolversOperationsDeleteRequest(_messages.Message): r"""A AiplatformSolversOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformSolversOperationsGetRequest(_messages.Message): r"""A AiplatformSolversOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformSolversOperationsListRequest(_messages.Message): r"""A AiplatformSolversOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformSpecialistPoolsOperationsCancelRequest(_messages.Message): r"""A AiplatformSpecialistPoolsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformSpecialistPoolsOperationsDeleteRequest(_messages.Message): r"""A AiplatformSpecialistPoolsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformSpecialistPoolsOperationsGetRequest(_messages.Message): r"""A AiplatformSpecialistPoolsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformSpecialistPoolsOperationsListRequest(_messages.Message): r"""A AiplatformSpecialistPoolsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformSpecialistPoolsOperationsWaitRequest(_messages.Message): r"""A AiplatformSpecialistPoolsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformStudiesOperationsCancelRequest(_messages.Message): r"""A AiplatformStudiesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformStudiesOperationsDeleteRequest(_messages.Message): r"""A AiplatformStudiesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformStudiesOperationsGetRequest(_messages.Message): r"""A AiplatformStudiesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformStudiesOperationsListRequest(_messages.Message): r"""A AiplatformStudiesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformStudiesOperationsWaitRequest(_messages.Message): r"""A AiplatformStudiesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformStudiesTrialsOperationsCancelRequest(_messages.Message): r"""A AiplatformStudiesTrialsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformStudiesTrialsOperationsDeleteRequest(_messages.Message): r"""A AiplatformStudiesTrialsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformStudiesTrialsOperationsGetRequest(_messages.Message): r"""A AiplatformStudiesTrialsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformStudiesTrialsOperationsListRequest(_messages.Message): r"""A AiplatformStudiesTrialsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformStudiesTrialsOperationsWaitRequest(_messages.Message): r"""A AiplatformStudiesTrialsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformTensorboardsExperimentsOperationsCancelRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformTensorboardsExperimentsOperationsDeleteRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformTensorboardsExperimentsOperationsGetRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformTensorboardsExperimentsOperationsListRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformTensorboardsExperimentsOperationsWaitRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformTensorboardsExperimentsRunsOperationsCancelRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsRunsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformTensorboardsExperimentsRunsOperationsDeleteRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsRunsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformTensorboardsExperimentsRunsOperationsGetRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsRunsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformTensorboardsExperimentsRunsOperationsListRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsRunsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformTensorboardsExperimentsRunsOperationsWaitRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsRunsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformTensorboardsExperimentsRunsTimeSeriesOperationsCancelRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsRunsTimeSeriesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformTensorboardsExperimentsRunsTimeSeriesOperationsDeleteRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsRunsTimeSeriesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformTensorboardsExperimentsRunsTimeSeriesOperationsGetRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsRunsTimeSeriesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformTensorboardsExperimentsRunsTimeSeriesOperationsListRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsRunsTimeSeriesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformTensorboardsExperimentsRunsTimeSeriesOperationsWaitRequest(_messages.Message): r"""A AiplatformTensorboardsExperimentsRunsTimeSeriesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformTensorboardsOperationsCancelRequest(_messages.Message): r"""A AiplatformTensorboardsOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformTensorboardsOperationsDeleteRequest(_messages.Message): r"""A AiplatformTensorboardsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformTensorboardsOperationsGetRequest(_messages.Message): r"""A AiplatformTensorboardsOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformTensorboardsOperationsListRequest(_messages.Message): r"""A AiplatformTensorboardsOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformTensorboardsOperationsWaitRequest(_messages.Message): r"""A AiplatformTensorboardsOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformTrainingPipelinesOperationsCancelRequest(_messages.Message): r"""A AiplatformTrainingPipelinesOperationsCancelRequest object. Fields: name: The name of the operation resource to be cancelled. """ name = _messages.StringField(1, required=True) class AiplatformTrainingPipelinesOperationsDeleteRequest(_messages.Message): r"""A AiplatformTrainingPipelinesOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class AiplatformTrainingPipelinesOperationsGetRequest(_messages.Message): r"""A AiplatformTrainingPipelinesOperationsGetRequest object. Fields: name: The name of the operation resource. """ name = _messages.StringField(1, required=True) class AiplatformTrainingPipelinesOperationsListRequest(_messages.Message): r"""A AiplatformTrainingPipelinesOperationsListRequest object. Fields: filter: The standard list filter. name: The name of the operation's parent resource. pageSize: The standard list page size. pageToken: The standard list page token. returnPartialSuccess: When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the [ListOperationsResponse.unreachable] field. This can only be `true` when reading across collections e.g. when `parent` is set to `"projects/example/locations/-"`. This field is not by default supported and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation. """ filter = _messages.StringField(1) name = _messages.StringField(2, required=True) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) returnPartialSuccess = _messages.BooleanField(5) class AiplatformTrainingPipelinesOperationsWaitRequest(_messages.Message): r"""A AiplatformTrainingPipelinesOperationsWaitRequest object. Fields: name: The name of the operation resource to wait on. timeout: The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used. """ name = _messages.StringField(1, required=True) timeout = _messages.StringField(2) class AiplatformTuningJobsOperationsDeleteRequest(_messages.Message): r"""A AiplatformTuningJobsOperationsDeleteRequest object. Fields: name: The name of the operation resource to be deleted. """ name = _messages.StringField(1, required=True) class CloudAiLargeModelsVisionGenerateVideoResponse(_messages.Message): r"""Generate video response. Fields: generatedSamples: The generates samples. raiMediaFilteredCount: Returns if any videos were filtered due to RAI policies. raiMediaFilteredReasons: Returns rai failure reasons if any. videos: List of videos, used to align naming with the external response. """ generatedSamples = _messages.MessageField('CloudAiLargeModelsVisionMedia', 1, repeated=True) raiMediaFilteredCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) raiMediaFilteredReasons = _messages.StringField(3, repeated=True) videos = _messages.MessageField('CloudAiLargeModelsVisionGenerateVideoResponseVideo', 4, repeated=True) class CloudAiLargeModelsVisionGenerateVideoResponseVideo(_messages.Message): r"""A CloudAiLargeModelsVisionGenerateVideoResponseVideo object. Fields: bytesBase64Encoded: Base64 encoded bytes string representing the video. gcsUri: Cloud Storage URI where the generated video is written. mimeType: The MIME type of the content of the video. - video/mp4 """ bytesBase64Encoded = _messages.StringField(1) gcsUri = _messages.StringField(2) mimeType = _messages.StringField(3) class CloudAiLargeModelsVisionImage(_messages.Message): r"""Image. Fields: encoding: Image encoding, encoded as "image/png" or "image/jpg". generationSeed: Generation seed for the sampled image. This parameter is exposed to the user only if one of the following is true: 1. The user specified per-example seeds in the request. 2. The user doesn't specify the generation seed in the request. image: Raw bytes. imageRaiScores: RAI scores for generated image. imageSize: Image size. The size of the image. Can be self reported, or computed from the image bytes. raiInfo: RAI info for image. semanticFilterResponse: Semantic filter info for image. text: Text/Expanded text input for imagen. uri: Path to another storage (typically Google Cloud Storage). """ encoding = _messages.StringField(1) generationSeed = _messages.IntegerField(2, variant=_messages.Variant.INT32) image = _messages.BytesField(3) imageRaiScores = _messages.MessageField('CloudAiLargeModelsVisionImageRAIScores', 4) imageSize = _messages.MessageField('CloudAiLargeModelsVisionImageImageSize', 5) raiInfo = _messages.MessageField('CloudAiLargeModelsVisionRaiInfo', 6) semanticFilterResponse = _messages.MessageField('CloudAiLargeModelsVisionSemanticFilterResponse', 7) text = _messages.StringField(8) uri = _messages.StringField(9) class CloudAiLargeModelsVisionImageImageSize(_messages.Message): r"""Image size. Fields: channels: A integer attribute. height: A integer attribute. width: A integer attribute. """ channels = _messages.IntegerField(1, variant=_messages.Variant.INT32) height = _messages.IntegerField(2, variant=_messages.Variant.INT32) width = _messages.IntegerField(3, variant=_messages.Variant.INT32) class CloudAiLargeModelsVisionImageRAIScores(_messages.Message): r"""RAI scores for generated image returned. Fields: agileWatermarkDetectionScore: Agile watermark score for image. """ agileWatermarkDetectionScore = _messages.FloatField(1) class CloudAiLargeModelsVisionMedia(_messages.Message): r"""Media. Fields: image: Image. video: Video """ image = _messages.MessageField('CloudAiLargeModelsVisionImage', 1) video = _messages.MessageField('CloudAiLargeModelsVisionVideo', 2) class CloudAiLargeModelsVisionNamedBoundingBox(_messages.Message): r"""A CloudAiLargeModelsVisionNamedBoundingBox object. Fields: classes: A string attribute. entities: A string attribute. scores: A number attribute. x1: A number attribute. x2: A number attribute. y1: A number attribute. y2: A number attribute. """ classes = _messages.StringField(1, repeated=True) entities = _messages.StringField(2, repeated=True) scores = _messages.FloatField(3, repeated=True, variant=_messages.Variant.FLOAT) x1 = _messages.FloatField(4, variant=_messages.Variant.FLOAT) x2 = _messages.FloatField(5, variant=_messages.Variant.FLOAT) y1 = _messages.FloatField(6, variant=_messages.Variant.FLOAT) y2 = _messages.FloatField(7, variant=_messages.Variant.FLOAT) class CloudAiLargeModelsVisionRaiInfo(_messages.Message): r"""Next ID: 6 Fields: blockedEntities: List of blocked entities from the blocklist if it is detected. detectedLabels: The list of detected labels for different rai categories. modelName: The model name used to indexing into the RaiFilterConfig map. Would either be one of imagegeneration@002-006, imagen-3.0-... api endpoint names, or internal names used for mapping to different filter configs (genselfie, ai_watermark) than its api endpoint. raiCategories: List of rai categories' information to return scores: List of rai scores mapping to the rai categories. Rounded to 1 decimal place. """ blockedEntities = _messages.StringField(1, repeated=True) detectedLabels = _messages.MessageField('CloudAiLargeModelsVisionRaiInfoDetectedLabels', 2, repeated=True) modelName = _messages.StringField(3) raiCategories = _messages.StringField(4, repeated=True) scores = _messages.FloatField(5, repeated=True, variant=_messages.Variant.FLOAT) class CloudAiLargeModelsVisionRaiInfoDetectedLabels(_messages.Message): r"""Filters returning list of deteceted labels, scores, and bounding boxes. Fields: entities: The list of detected entities for the rai signal. raiCategory: The RAI category for the deteceted labels. """ entities = _messages.MessageField('CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity', 1, repeated=True) raiCategory = _messages.StringField(2) class CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox(_messages.Message): r"""An integer bounding box of original pixels of the image for the detected labels. Fields: x1: The X coordinate of the top-left corner, in pixels. x2: The X coordinate of the bottom-right corner, in pixels. y1: The Y coordinate of the top-left corner, in pixels. y2: The Y coordinate of the bottom-right corner, in pixels. """ x1 = _messages.IntegerField(1, variant=_messages.Variant.INT32) x2 = _messages.IntegerField(2, variant=_messages.Variant.INT32) y1 = _messages.IntegerField(3, variant=_messages.Variant.INT32) y2 = _messages.IntegerField(4, variant=_messages.Variant.INT32) class CloudAiLargeModelsVisionRaiInfoDetectedLabelsEntity(_messages.Message): r"""The properties for a detected entity from the rai signal. Fields: boundingBox: Bounding box of the label description: Description of the label iouScore: The intersection ratio between the detection bounding box and the mask. mid: MID of the label score: Confidence score of the label """ boundingBox = _messages.MessageField('CloudAiLargeModelsVisionRaiInfoDetectedLabelsBoundingBox', 1) description = _messages.StringField(2) iouScore = _messages.FloatField(3, variant=_messages.Variant.FLOAT) mid = _messages.StringField(4) score = _messages.FloatField(5, variant=_messages.Variant.FLOAT) class CloudAiLargeModelsVisionSemanticFilterResponse(_messages.Message): r"""A CloudAiLargeModelsVisionSemanticFilterResponse object. Fields: namedBoundingBoxes: Class labels of the bounding boxes that failed the semantic filtering. Bounding box coordinates. passedSemanticFilter: This response is added when semantic filter config is turned on in EditConfig. It reports if this image is passed semantic filter response. If passed_semantic_filter is false, the bounding box information will be populated for user to check what caused the semantic filter to fail. """ namedBoundingBoxes = _messages.MessageField('CloudAiLargeModelsVisionNamedBoundingBox', 1, repeated=True) passedSemanticFilter = _messages.BooleanField(2) class CloudAiLargeModelsVisionVideo(_messages.Message): r"""Video Fields: encodedVideo: Base 64 encoded video bytes. encoding: Video encoding, for example "video/mp4". text: Text/Expanded text input for Help Me Write. uri: Path to another storage (typically Google Cloud Storage). video: Raw bytes. """ encodedVideo = _messages.StringField(1) encoding = _messages.StringField(2) text = _messages.StringField(3) uri = _messages.StringField(4) video = _messages.BytesField(5) class CloudAiPlatformCommonCreatePipelineJobApiErrorDetail(_messages.Message): r"""Create API error message for Vertex Pipeline. Enums: ErrorCauseValueValuesEnum: The error root cause returned by CreatePipelineJob API. Fields: errorCause: The error root cause returned by CreatePipelineJob API. publicMessage: Public messages contains actionable items for the error cause. """ class ErrorCauseValueValuesEnum(_messages.Enum): r"""The error root cause returned by CreatePipelineJob API. Values: ERROR_CAUSE_UNSPECIFIED: Should never be used. INVALID_PIPELINE_SPEC_FORMAT: IR Pipeline Spec can not been parsed to yaml or json format. INVALID_PIPELINE_SPEC: A pipeline spec is invalid. INVALID_DEPLOYMENT_CONFIG: A deployment config is invalid. INVALID_DEPLOYMENT_SPEC: A deployment spec is invalid. INVALID_INSTANCE_SCHEMA: An instance schema is invalid. INVALID_CUSTOM_JOB: A custom job is invalid. INVALID_CONTAINER_SPEC: A container spec is invalid. INVALID_NOTIFICATION_EMAIL_SETUP: Notification email setup is invalid. INVALID_SERVICE_ACCOUNT_SETUP: Service account setup is invalid. INVALID_KMS_SETUP: KMS setup is invalid. INVALID_NETWORK_SETUP: Network setup is invalid. INVALID_PIPELINE_TASK_SPEC: Task spec is invalid. INVALID_PIPELINE_TASK_ARTIFACT: Task artifact is invalid. INVALID_IMPORTER_SPEC: Importer spec is invalid. INVALID_RESOLVER_SPEC: Resolver spec is invalid. INVALID_RUNTIME_PARAMETERS: Runtime Parameters are invalid. CLOUD_API_NOT_ENABLED: Cloud API not enabled. INVALID_GCS_INPUT_URI: Invalid Cloud Storage input uri INVALID_GCS_OUTPUT_URI: Invalid Cloud Storage output uri INVALID_COMPONENT_SPEC: Component spec of pipeline is invalid. INVALID_DAG_OUTPUTS_SPEC: DagOutputsSpec is invalid. INVALID_DAG_SPEC: DagSpec is invalid. INSUFFICIENT_QUOTA: Project does not have enough quota. INTERNAL: An internal error with unknown cause. """ ERROR_CAUSE_UNSPECIFIED = 0 INVALID_PIPELINE_SPEC_FORMAT = 1 INVALID_PIPELINE_SPEC = 2 INVALID_DEPLOYMENT_CONFIG = 3 INVALID_DEPLOYMENT_SPEC = 4 INVALID_INSTANCE_SCHEMA = 5 INVALID_CUSTOM_JOB = 6 INVALID_CONTAINER_SPEC = 7 INVALID_NOTIFICATION_EMAIL_SETUP = 8 INVALID_SERVICE_ACCOUNT_SETUP = 9 INVALID_KMS_SETUP = 10 INVALID_NETWORK_SETUP = 11 INVALID_PIPELINE_TASK_SPEC = 12 INVALID_PIPELINE_TASK_ARTIFACT = 13 INVALID_IMPORTER_SPEC = 14 INVALID_RESOLVER_SPEC = 15 INVALID_RUNTIME_PARAMETERS = 16 CLOUD_API_NOT_ENABLED = 17 INVALID_GCS_INPUT_URI = 18 INVALID_GCS_OUTPUT_URI = 19 INVALID_COMPONENT_SPEC = 20 INVALID_DAG_OUTPUTS_SPEC = 21 INVALID_DAG_SPEC = 22 INSUFFICIENT_QUOTA = 23 INTERNAL = 24 errorCause = _messages.EnumField('ErrorCauseValueValuesEnum', 1) publicMessage = _messages.StringField(2) class GoogleApiHttpBody(_messages.Message): r"""Message that represents an arbitrary HTTP body. It should only be used for payload formats that can't be represented as JSON, such as raw binary or an HTML page. This message can be used both in streaming and non-streaming API methods in the request as well as the response. It can be used as a top- level request field, which is convenient if one wants to extract parameters from either the URL or HTTP template into the request fields and also want access to the raw HTTP body. Example: message GetResourceRequest { // A unique request id. string request_id = 1; // The raw HTTP body is bound to this field. google.api.HttpBody http_body = 2; } service ResourceService { rpc GetResource(GetResourceRequest) returns (google.api.HttpBody); rpc UpdateResource(google.api.HttpBody) returns (google.protobuf.Empty); } Example with streaming methods: service CaldavService { rpc GetCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); rpc UpdateCalendar(stream google.api.HttpBody) returns (stream google.api.HttpBody); } Use of this type only changes how the request and response bodies are handled, all other features will continue to work unchanged. Messages: ExtensionsValueListEntry: A ExtensionsValueListEntry object. Fields: contentType: The HTTP Content-Type header value specifying the content type of the body. data: The HTTP request/response body as raw binary. extensions: Application specific response metadata. Must be set in the first response for streaming APIs. """ @encoding.MapUnrecognizedFields('additionalProperties') class ExtensionsValueListEntry(_messages.Message): r"""A ExtensionsValueListEntry object. Messages: AdditionalProperty: An additional property for a ExtensionsValueListEntry object. Fields: additionalProperties: Properties of the object. Contains field @type with type URL. """ class AdditionalProperty(_messages.Message): r"""An additional property for a ExtensionsValueListEntry object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) contentType = _messages.StringField(1) data = _messages.BytesField(2) extensions = _messages.MessageField('ExtensionsValueListEntry', 3, repeated=True) class GoogleCloudAiplatformV1beta1AcceptPublisherModelEulaRequest(_messages.Message): r"""Request message for ModelGardenService.AcceptPublisherModelEula. Fields: publisherModel: Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}`, or `publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}` """ publisherModel = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ActiveLearningConfig(_messages.Message): r"""Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy. Fields: maxDataItemCount: Max number of human labeled DataItems. maxDataItemPercentage: Max percent of total DataItems for human labeling. sampleConfig: Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy. trainingConfig: CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems. """ maxDataItemCount = _messages.IntegerField(1) maxDataItemPercentage = _messages.IntegerField(2, variant=_messages.Variant.INT32) sampleConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SampleConfig', 3) trainingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1TrainingConfig', 4) class GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsRequest(_messages.Message): r"""Request message for MetadataService.AddContextArtifactsAndExecutions. Fields: artifacts: The resource names of the Artifacts to attribute to the Context. Format: `projects/{project}/locations/{location}/metadataStores /{metadatastore}/artifacts/{artifact}` executions: The resource names of the Executions to associate with the Context. Format: `projects/{project}/locations/{location}/metadataStores /{metadatastore}/executions/{execution}` """ artifacts = _messages.StringField(1, repeated=True) executions = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1AddContextArtifactsAndExecutionsResponse(_messages.Message): r"""Response message for MetadataService.AddContextArtifactsAndExecutions. """ class GoogleCloudAiplatformV1beta1AddContextChildrenRequest(_messages.Message): r"""Request message for MetadataService.AddContextChildren. Fields: childContexts: The resource names of the child Contexts. """ childContexts = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1AddContextChildrenResponse(_messages.Message): r"""Response message for MetadataService.AddContextChildren.""" class GoogleCloudAiplatformV1beta1AddExecutionEventsRequest(_messages.Message): r"""Request message for MetadataService.AddExecutionEvents. Fields: events: The Events to create and add. """ events = _messages.MessageField('GoogleCloudAiplatformV1beta1Event', 1, repeated=True) class GoogleCloudAiplatformV1beta1AddExecutionEventsResponse(_messages.Message): r"""Response message for MetadataService.AddExecutionEvents.""" class GoogleCloudAiplatformV1beta1AddTrialMeasurementRequest(_messages.Message): r"""Request message for VizierService.AddTrialMeasurement. Fields: measurement: Required. The measurement to be added to a Trial. """ measurement = _messages.MessageField('GoogleCloudAiplatformV1beta1Measurement', 1) class GoogleCloudAiplatformV1beta1AggregationOutput(_messages.Message): r"""The aggregation result for the entire dataset and all metrics. Fields: aggregationResults: One AggregationResult per metric. dataset: The dataset used for evaluation & aggregation. """ aggregationResults = _messages.MessageField('GoogleCloudAiplatformV1beta1AggregationResult', 1, repeated=True) dataset = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationDataset', 2) class GoogleCloudAiplatformV1beta1AggregationResult(_messages.Message): r"""The aggregation result for a single metric. Enums: AggregationMetricValueValuesEnum: Aggregation metric. Fields: aggregationMetric: Aggregation metric. bleuMetricValue: Results for bleu metric. customCodeExecutionResult: Result for code execution metric. exactMatchMetricValue: Results for exact match metric. pairwiseMetricResult: Result for pairwise metric. pointwiseMetricResult: Result for pointwise metric. rougeMetricValue: Results for rouge metric. """ class AggregationMetricValueValuesEnum(_messages.Enum): r"""Aggregation metric. Values: AGGREGATION_METRIC_UNSPECIFIED: Unspecified aggregation metric. AVERAGE: Average aggregation metric. Not supported for Pairwise metric. MODE: Mode aggregation metric. STANDARD_DEVIATION: Standard deviation aggregation metric. Not supported for pairwise metric. VARIANCE: Variance aggregation metric. Not supported for pairwise metric. MINIMUM: Minimum aggregation metric. Not supported for pairwise metric. MAXIMUM: Maximum aggregation metric. Not supported for pairwise metric. MEDIAN: Median aggregation metric. Not supported for pairwise metric. PERCENTILE_P90: 90th percentile aggregation metric. Not supported for pairwise metric. PERCENTILE_P95: 95th percentile aggregation metric. Not supported for pairwise metric. PERCENTILE_P99: 99th percentile aggregation metric. Not supported for pairwise metric. """ AGGREGATION_METRIC_UNSPECIFIED = 0 AVERAGE = 1 MODE = 2 STANDARD_DEVIATION = 3 VARIANCE = 4 MINIMUM = 5 MAXIMUM = 6 MEDIAN = 7 PERCENTILE_P90 = 8 PERCENTILE_P95 = 9 PERCENTILE_P99 = 10 aggregationMetric = _messages.EnumField('AggregationMetricValueValuesEnum', 1) bleuMetricValue = _messages.MessageField('GoogleCloudAiplatformV1beta1BleuMetricValue', 2) customCodeExecutionResult = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomCodeExecutionResult', 3) exactMatchMetricValue = _messages.MessageField('GoogleCloudAiplatformV1beta1ExactMatchMetricValue', 4) pairwiseMetricResult = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseMetricResult', 5) pointwiseMetricResult = _messages.MessageField('GoogleCloudAiplatformV1beta1PointwiseMetricResult', 6) rougeMetricValue = _messages.MessageField('GoogleCloudAiplatformV1beta1RougeMetricValue', 7) class GoogleCloudAiplatformV1beta1Annotation(_messages.Message): r"""Used to assign specific AnnotationSpec to a particular area of a DataItem or the whole part of the DataItem. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize your Annotations. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Annotation(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Annotation: * "aiplatform.googleapis.com/annotation_set_name": optional, name of the UI's annotation set this Annotation belongs to. If not set, the Annotation is not visible in the UI. * "aiplatform.googleapis.com/payload_schema": output only, its value is the payload_schema's title. Fields: annotationSource: Output only. The source of the Annotation. createTime: Output only. Timestamp when this Annotation was created. etag: Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: Optional. The labels with user-defined metadata to organize your Annotations. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Annotation(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Annotation: * "aiplatform.googleapis.com/annotation_set_name": optional, name of the UI's annotation set this Annotation belongs to. If not set, the Annotation is not visible in the UI. * "aiplatform.googleapis.com/payload_schema": output only, its value is the payload_schema's title. name: Output only. Resource name of the Annotation. payload: Required. The schema of the payload can be found in payload_schema. payloadSchemaUri: Required. Google Cloud Storage URI points to a YAML file describing payload. The schema is defined as an [OpenAPI 3.0.2 Schema Object](https://github.com/OAI/OpenAPI- Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud- aiplatform/schema/dataset/annotation/, note that the chosen schema must be consistent with the parent Dataset's metadata. updateTime: Output only. Timestamp when this Annotation was last updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize your Annotations. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Annotation(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Annotation: * "aiplatform.googleapis.com/annotation_set_name": optional, name of the UI's annotation set this Annotation belongs to. If not set, the Annotation is not visible in the UI. * "aiplatform.googleapis.com/payload_schema": output only, its value is the payload_schema's title. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) annotationSource = _messages.MessageField('GoogleCloudAiplatformV1beta1UserActionReference', 1) createTime = _messages.StringField(2) etag = _messages.StringField(3) labels = _messages.MessageField('LabelsValue', 4) name = _messages.StringField(5) payload = _messages.MessageField('extra_types.JsonValue', 6) payloadSchemaUri = _messages.StringField(7) updateTime = _messages.StringField(8) class GoogleCloudAiplatformV1beta1AnnotationSpec(_messages.Message): r"""Identifies a concept with which DataItems may be annotated with. Fields: createTime: Output only. Timestamp when this AnnotationSpec was created. displayName: Required. The user-defined name of the AnnotationSpec. The name can be up to 128 characters long and can consist of any UTF-8 characters. etag: Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. name: Output only. Resource name of the AnnotationSpec. updateTime: Output only. Timestamp when AnnotationSpec was last updated. """ createTime = _messages.StringField(1) displayName = _messages.StringField(2) etag = _messages.StringField(3) name = _messages.StringField(4) updateTime = _messages.StringField(5) class GoogleCloudAiplatformV1beta1ApiAuth(_messages.Message): r"""The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. Fields: apiKeyConfig: The API secret. """ apiKeyConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig', 1) class GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig(_messages.Message): r"""The API secret. Fields: apiKeySecretVersion: Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version} apiKeyString: The API key string. Either this or `api_key_secret_version` must be set. """ apiKeySecretVersion = _messages.StringField(1) apiKeyString = _messages.StringField(2) class GoogleCloudAiplatformV1beta1AppendEventResponse(_messages.Message): r"""Response message for SessionService.AppendEvent.""" class GoogleCloudAiplatformV1beta1Artifact(_messages.Message): r"""Instance of a general artifact. Enums: StateValueValuesEnum: The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions. Messages: LabelsValue: The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded). MetadataValue: Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB. Fields: createTime: Output only. Timestamp when this Artifact was created. description: Description of the Artifact displayName: User provided display name of the Artifact. May be up to 128 Unicode characters. etag: An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded). metadata: Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB. name: Output only. The resource name of the Artifact. schemaTitle: The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store. schemaVersion: The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store. state: The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions. updateTime: Output only. Timestamp when this Artifact was last updated. uri: The uniform resource identifier of the artifact file. May be empty if there is no actual artifact file. """ class StateValueValuesEnum(_messages.Enum): r"""The state of this Artifact. This is a property of the Artifact, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines), and the system does not prescribe or check the validity of state transitions. Values: STATE_UNSPECIFIED: Unspecified state for the Artifact. PENDING: A state used by systems like Vertex AI Pipelines to indicate that the underlying data item represented by this Artifact is being created. LIVE: A state indicating that the Artifact should exist, unless something external to the system deletes it. """ STATE_UNSPECIFIED = 0 PENDING = 1 LIVE = 2 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your Artifacts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Artifact (System labels are excluded). Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class MetadataValue(_messages.Message): r"""Properties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB. Messages: AdditionalProperty: An additional property for a MetadataValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a MetadataValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) description = _messages.StringField(2) displayName = _messages.StringField(3) etag = _messages.StringField(4) labels = _messages.MessageField('LabelsValue', 5) metadata = _messages.MessageField('MetadataValue', 6) name = _messages.StringField(7) schemaTitle = _messages.StringField(8) schemaVersion = _messages.StringField(9) state = _messages.EnumField('StateValueValuesEnum', 10) updateTime = _messages.StringField(11) uri = _messages.StringField(12) class GoogleCloudAiplatformV1beta1ArtifactTypeSchema(_messages.Message): r"""The definition of a artifact type in MLMD. Fields: instanceSchema: Contains a raw YAML string, describing the format of the properties of the type. schemaTitle: The name of the type. The format of the title must be: `.`. Examples: - `aiplatform.Model` - `acme.CustomModel` When this field is set, the type must be pre-registered in the MLMD store. schemaUri: Points to a YAML file stored on Cloud Storage describing the format. Deprecated. Use PipelineArtifactTypeSchema.schema_title or PipelineArtifactTypeSchema.instance_schema instead. schemaVersion: The schema version of the artifact. If the value is not set, it defaults to the latest version in the system. """ instanceSchema = _messages.StringField(1) schemaTitle = _messages.StringField(2) schemaUri = _messages.StringField(3) schemaVersion = _messages.StringField(4) class GoogleCloudAiplatformV1beta1AssembleDataRequest(_messages.Message): r"""Request message for DatasetService.AssembleData. Used only for MULTIMODAL datasets. Fields: geminiRequestReadConfig: Optional. The read config for the dataset. """ geminiRequestReadConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GeminiRequestReadConfig', 1) class GoogleCloudAiplatformV1beta1AssessDataRequest(_messages.Message): r"""Request message for DatasetService.AssessData. Used only for MULTIMODAL datasets. Fields: batchPredictionResourceUsageAssessmentConfig: Optional. Configuration for the batch prediction resource usage assessment. batchPredictionValidationAssessmentConfig: Optional. Configuration for the batch prediction validation assessment. geminiRequestReadConfig: Optional. The Gemini request read config for the dataset. tuningResourceUsageAssessmentConfig: Optional. Configuration for the tuning resource usage assessment. tuningValidationAssessmentConfig: Optional. Configuration for the tuning validation assessment. """ batchPredictionResourceUsageAssessmentConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AssessDataRequestBatchPredictionResourceUsageAssessmentConfig', 1) batchPredictionValidationAssessmentConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AssessDataRequestBatchPredictionValidationAssessmentConfig', 2) geminiRequestReadConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GeminiRequestReadConfig', 3) tuningResourceUsageAssessmentConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AssessDataRequestTuningResourceUsageAssessmentConfig', 4) tuningValidationAssessmentConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AssessDataRequestTuningValidationAssessmentConfig', 5) class GoogleCloudAiplatformV1beta1AssessDataRequestBatchPredictionResourceUsageAssessmentConfig(_messages.Message): r"""Configuration for the batch prediction resource usage assessment. Fields: modelName: Required. The name of the model used for batch prediction. """ modelName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1AssessDataRequestBatchPredictionValidationAssessmentConfig(_messages.Message): r"""Configuration for the batch prediction validation assessment. Fields: modelName: Required. The name of the model used for batch prediction. """ modelName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1AssessDataRequestTuningResourceUsageAssessmentConfig(_messages.Message): r"""Configuration for the tuning resource usage assessment. Fields: modelName: Required. The name of the model used for tuning. """ modelName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1AssessDataRequestTuningValidationAssessmentConfig(_messages.Message): r"""Configuration for the tuning validation assessment. Enums: DatasetUsageValueValuesEnum: Required. The dataset usage (e.g. training/validation). Fields: datasetUsage: Required. The dataset usage (e.g. training/validation). modelName: Required. The name of the model used for tuning. """ class DatasetUsageValueValuesEnum(_messages.Enum): r"""Required. The dataset usage (e.g. training/validation). Values: DATASET_USAGE_UNSPECIFIED: Default value. Should not be used. SFT_TRAINING: Supervised fine-tuning training dataset. SFT_VALIDATION: Supervised fine-tuning validation dataset. """ DATASET_USAGE_UNSPECIFIED = 0 SFT_TRAINING = 1 SFT_VALIDATION = 2 datasetUsage = _messages.EnumField('DatasetUsageValueValuesEnum', 1) modelName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1AssignNotebookRuntimeOperationMetadata(_messages.Message): r"""Metadata information for NotebookService.AssignNotebookRuntime. Fields: genericMetadata: The operation generic information. progressMessage: A human-readable message that shows the intermediate progress details of NotebookRuntime. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) progressMessage = _messages.StringField(2) class GoogleCloudAiplatformV1beta1AssignNotebookRuntimeRequest(_messages.Message): r"""Request message for NotebookService.AssignNotebookRuntime. Fields: notebookRuntime: Required. Provide runtime specific information (e.g. runtime owner, notebook id) used for NotebookRuntime assignment. notebookRuntimeId: Optional. User specified ID for the notebook runtime. notebookRuntimeTemplate: Required. The resource name of the NotebookRuntimeTemplate based on which a NotebookRuntime will be assigned (reuse or create a new one). """ notebookRuntime = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookRuntime', 1) notebookRuntimeId = _messages.StringField(2) notebookRuntimeTemplate = _messages.StringField(3) class GoogleCloudAiplatformV1beta1Attribution(_messages.Message): r"""Attribution that explains a particular prediction output. Fields: approximationError: Output only. Error of feature_attributions caused by approximation used in the explanation method. Lower value means more precise attributions. * For Sampled Shapley attribution, increasing path_count might reduce the error. * For Integrated Gradients attribution, increasing step_count might reduce the error. * For XRAI attribution, increasing step_count might reduce the error. See [this introduction](/vertex-ai/docs/explainable-ai/overview) for more information. baselineOutputValue: Output only. Model predicted output if the input instance is constructed from the baselines of all the features defined in ExplanationMetadata.inputs. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model's predicted output has multiple dimensions (rank > 1), this is the value in the output located by output_index. If there are multiple baselines, their output values are averaged. featureAttributions: Output only. Attributions of each explained feature. Features are extracted from the prediction instances according to explanation metadata for inputs. The value is a struct, whose keys are the name of the feature. The values are how much the feature in the instance contributed to the predicted result. The format of the value is determined by the feature's input format: * If the feature is a scalar value, the attribution value is a floating number. * If the feature is an array of scalar values, the attribution value is an array. * If the feature is a struct, the attribution value is a struct. The keys in the attribution value struct are the same as the keys in the feature struct. The formats of the values in the attribution struct are determined by the formats of the values in the feature struct. The ExplanationMetadata.feature_attributions_schema_uri field, pointed to by the ExplanationSpec field of the Endpoint.deployed_models object, points to the schema file that describes the features and their attribution values (if it is populated). instanceOutputValue: Output only. Model predicted output on the corresponding explanation instance. The field name of the output is determined by the key in ExplanationMetadata.outputs. If the Model predicted output has multiple dimensions, this is the value in the output located by output_index. outputDisplayName: Output only. The display name of the output identified by output_index. For example, the predicted class name by a multi- classification Model. This field is only populated iff the Model predicts display names as a separate field along with the explained output. The predicted display name must has the same shape of the explained output, and can be located using output_index. outputIndex: Output only. The index that locates the explained prediction output. If the prediction output is a scalar value, output_index is not populated. If the prediction output has multiple dimensions, the length of the output_index list is the same as the number of dimensions of the output. The i-th element in output_index is the element index of the i-th dimension of the output vector. Indices start from 0. outputName: Output only. Name of the explain output. Specified as the key in ExplanationMetadata.outputs. """ approximationError = _messages.FloatField(1) baselineOutputValue = _messages.FloatField(2) featureAttributions = _messages.MessageField('extra_types.JsonValue', 3) instanceOutputValue = _messages.FloatField(4) outputDisplayName = _messages.StringField(5) outputIndex = _messages.IntegerField(6, repeated=True, variant=_messages.Variant.INT32) outputName = _messages.StringField(7) class GoogleCloudAiplatformV1beta1AugmentPromptRequest(_messages.Message): r"""Request message for AugmentPrompt. Fields: contents: Optional. Input content to augment, only text format is supported for now. model: Optional. Metadata of the backend deployed model. vertexRagStore: Optional. Retrieves contexts from the Vertex RagStore. """ contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1, repeated=True) model = _messages.MessageField('GoogleCloudAiplatformV1beta1AugmentPromptRequestModel', 2) vertexRagStore = _messages.MessageField('GoogleCloudAiplatformV1beta1VertexRagStore', 3) class GoogleCloudAiplatformV1beta1AugmentPromptRequestModel(_messages.Message): r"""Metadata of the backend deployed model. Fields: model: Optional. The model that the user will send the augmented prompt for content generation. modelVersion: Optional. The model version of the backend deployed model. """ model = _messages.StringField(1) modelVersion = _messages.StringField(2) class GoogleCloudAiplatformV1beta1AugmentPromptResponse(_messages.Message): r"""Response message for AugmentPrompt. Fields: augmentedPrompt: Augmented prompt, only text format is supported for now. facts: Retrieved facts from RAG data sources. """ augmentedPrompt = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1, repeated=True) facts = _messages.MessageField('GoogleCloudAiplatformV1beta1Fact', 2, repeated=True) class GoogleCloudAiplatformV1beta1AuthConfig(_messages.Message): r"""Auth configuration to run the extension. Enums: AuthTypeValueValuesEnum: Type of auth scheme. Fields: apiKeyConfig: Config for API key auth. authType: Type of auth scheme. googleServiceAccountConfig: Config for Google Service Account auth. httpBasicAuthConfig: Config for HTTP Basic auth. oauthConfig: Config for user oauth. oidcConfig: Config for user OIDC auth. """ class AuthTypeValueValuesEnum(_messages.Enum): r"""Type of auth scheme. Values: AUTH_TYPE_UNSPECIFIED: NO_AUTH: No Auth. API_KEY_AUTH: API Key Auth. HTTP_BASIC_AUTH: HTTP Basic Auth. GOOGLE_SERVICE_ACCOUNT_AUTH: Google Service Account Auth. OAUTH: OAuth auth. OIDC_AUTH: OpenID Connect (OIDC) Auth. """ AUTH_TYPE_UNSPECIFIED = 0 NO_AUTH = 1 API_KEY_AUTH = 2 HTTP_BASIC_AUTH = 3 GOOGLE_SERVICE_ACCOUNT_AUTH = 4 OAUTH = 5 OIDC_AUTH = 6 apiKeyConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig', 1) authType = _messages.EnumField('AuthTypeValueValuesEnum', 2) googleServiceAccountConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig', 3) httpBasicAuthConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig', 4) oauthConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AuthConfigOauthConfig', 5) oidcConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AuthConfigOidcConfig', 6) class GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig(_messages.Message): r"""Config for authentication with API key. Enums: HttpElementLocationValueValuesEnum: Optional. The location of the API key. Fields: apiKeySecret: Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex- ai/docs/general/access-control#service-agents) on the specified resource. apiKeyString: Optional. The API key to be used in the request directly. httpElementLocation: Optional. The location of the API key. name: Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name. """ class HttpElementLocationValueValuesEnum(_messages.Enum): r"""Optional. The location of the API key. Values: HTTP_IN_UNSPECIFIED: HTTP_IN_QUERY: Element is in the HTTP request query. HTTP_IN_HEADER: Element is in the HTTP request header. HTTP_IN_PATH: Element is in the HTTP request path. HTTP_IN_BODY: Element is in the HTTP request body. HTTP_IN_COOKIE: Element is in the HTTP request cookie. """ HTTP_IN_UNSPECIFIED = 0 HTTP_IN_QUERY = 1 HTTP_IN_HEADER = 2 HTTP_IN_PATH = 3 HTTP_IN_BODY = 4 HTTP_IN_COOKIE = 5 apiKeySecret = _messages.StringField(1) apiKeyString = _messages.StringField(2) httpElementLocation = _messages.EnumField('HttpElementLocationValueValuesEnum', 3) name = _messages.StringField(4) class GoogleCloudAiplatformV1beta1AuthConfigGoogleServiceAccountConfig(_messages.Message): r"""Config for Google Service Account Authentication. Fields: serviceAccount: Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex- ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension. """ serviceAccount = _messages.StringField(1) class GoogleCloudAiplatformV1beta1AuthConfigHttpBasicAuthConfig(_messages.Message): r"""Config for HTTP Basic Authentication. Fields: credentialSecret: Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service- agents) on the specified resource. """ credentialSecret = _messages.StringField(1) class GoogleCloudAiplatformV1beta1AuthConfigOauthConfig(_messages.Message): r"""Config for user oauth. Fields: accessToken: Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time. serviceAccount: The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex- ai/docs/general/access-control#service-agents) on the provided service account. """ accessToken = _messages.StringField(1) serviceAccount = _messages.StringField(2) class GoogleCloudAiplatformV1beta1AuthConfigOidcConfig(_messages.Message): r"""Config for user OIDC auth. Fields: idToken: OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time. serviceAccount: The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials- direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access- control#service-agents). """ idToken = _messages.StringField(1) serviceAccount = _messages.StringField(2) class GoogleCloudAiplatformV1beta1AutomaticResources(_messages.Message): r"""A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. Each Model supporting these resources documents its specific guidelines. Fields: maxReplicaCount: Immutable. The maximum number of replicas that may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale to that many replicas is guaranteed (barring service outages). If traffic increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, a no upper bound for scaling under heavy traffic will be assume, though Vertex AI may be unable to scale beyond certain replica number. minReplicaCount: Immutable. The minimum number of replicas that will be always deployed on. If traffic against it increases, it may dynamically be deployed onto more replicas up to max_replica_count, and as traffic decreases, some of these extra replicas may be freed. If the requested value is too large, the deployment will error. """ maxReplicaCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) minReplicaCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1AutoraterConfig(_messages.Message): r"""The configs for autorater. This is applicable to both EvaluateInstances and EvaluateDataset. Fields: autoraterModel: Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` flipEnabled: Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias. generationConfig: Optional. Configuration options for model generation and outputs. samplingCount: Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32. """ autoraterModel = _messages.StringField(1) flipEnabled = _messages.BooleanField(2) generationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerationConfig', 3) samplingCount = _messages.IntegerField(4, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1AutoscalingMetricSpec(_messages.Message): r"""The metric specification that defines the target resource utilization (CPU utilization, accelerator's duty cycle, and so on) for calculating the desired replica count. Messages: MonitoredResourceLabelsValue: Optional. The Cloud Monitoring monitored resource labels as key value pairs used for metrics filtering. See Cloud Monitoring Labels https://cloud.google.com/monitoring/api/v3/metric- model#generic-label-info Fields: metricName: Required. The resource metric name. Supported metrics: * For Online Prediction: * `aiplatform.googleapis.com/prediction/online/accelerator/duty_cycle` * `aiplatform.googleapis.com/prediction/online/cpu/utilization` * `aiplatform.googleapis.com/prediction/online/request_count` * `pubsub.googleapis.com/subscription/num_undelivered_messages` monitoredResourceLabels: Optional. The Cloud Monitoring monitored resource labels as key value pairs used for metrics filtering. See Cloud Monitoring Labels https://cloud.google.com/monitoring/api/v3/metric- model#generic-label-info target: The target resource utilization in percentage (1% - 100%) for the given metric; once the real usage deviates from the target by a certain percentage, the machine replicas change. The default value is 60 (representing 60%) if not provided. """ @encoding.MapUnrecognizedFields('additionalProperties') class MonitoredResourceLabelsValue(_messages.Message): r"""Optional. The Cloud Monitoring monitored resource labels as key value pairs used for metrics filtering. See Cloud Monitoring Labels https://cloud.google.com/monitoring/api/v3/metric-model#generic-label-info Messages: AdditionalProperty: An additional property for a MonitoredResourceLabelsValue object. Fields: additionalProperties: Additional properties of type MonitoredResourceLabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a MonitoredResourceLabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) metricName = _messages.StringField(1) monitoredResourceLabels = _messages.MessageField('MonitoredResourceLabelsValue', 2) target = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1AvroSource(_messages.Message): r"""The storage details for Avro input content. Fields: gcsSource: Required. Google Cloud Storage location. """ gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsSource', 1) class GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsRequest(_messages.Message): r"""Request message for PipelineService.BatchCancelPipelineJobs. Fields: names: Required. The names of the PipelineJobs to cancel. A maximum of 32 PipelineJobs can be cancelled in a batch. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}` """ names = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1BatchCancelPipelineJobsResponse(_messages.Message): r"""Response message for PipelineService.BatchCancelPipelineJobs. Fields: pipelineJobs: PipelineJobs cancelled. """ pipelineJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineJob', 1, repeated=True) class GoogleCloudAiplatformV1beta1BatchCreateFeaturesOperationMetadata(_messages.Message): r"""Details of operations that perform batch create Features. Fields: genericMetadata: Operation metadata for Feature. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1BatchCreateFeaturesRequest(_messages.Message): r"""Request message for FeaturestoreService.BatchCreateFeatures. Request message for FeatureRegistryService.BatchCreateFeatures. Fields: requests: Required. The request message specifying the Features to create. All Features must be created under the same parent EntityType / FeatureGroup. The `parent` field in each child request message can be omitted. If `parent` is set in a child request, then the value must match the `parent` value in this request message. """ requests = _messages.MessageField('GoogleCloudAiplatformV1beta1CreateFeatureRequest', 1, repeated=True) class GoogleCloudAiplatformV1beta1BatchCreateFeaturesResponse(_messages.Message): r"""Response message for FeaturestoreService.BatchCreateFeatures. Fields: features: The Features created. """ features = _messages.MessageField('GoogleCloudAiplatformV1beta1Feature', 1, repeated=True) class GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsRequest(_messages.Message): r"""Request message for TensorboardService.BatchCreateTensorboardRuns. Fields: requests: Required. The request message specifying the TensorboardRuns to create. A maximum of 1000 TensorboardRuns can be created in a batch. """ requests = _messages.MessageField('GoogleCloudAiplatformV1beta1CreateTensorboardRunRequest', 1, repeated=True) class GoogleCloudAiplatformV1beta1BatchCreateTensorboardRunsResponse(_messages.Message): r"""Response message for TensorboardService.BatchCreateTensorboardRuns. Fields: tensorboardRuns: The created TensorboardRuns. """ tensorboardRuns = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardRun', 1, repeated=True) class GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesRequest(_messages.Message): r"""Request message for TensorboardService.BatchCreateTensorboardTimeSeries. Fields: requests: Required. The request message specifying the TensorboardTimeSeries to create. A maximum of 1000 TensorboardTimeSeries can be created in a batch. """ requests = _messages.MessageField('GoogleCloudAiplatformV1beta1CreateTensorboardTimeSeriesRequest', 1, repeated=True) class GoogleCloudAiplatformV1beta1BatchCreateTensorboardTimeSeriesResponse(_messages.Message): r"""Response message for TensorboardService.BatchCreateTensorboardTimeSeries. Fields: tensorboardTimeSeries: The created TensorboardTimeSeries. """ tensorboardTimeSeries = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardTimeSeries', 1, repeated=True) class GoogleCloudAiplatformV1beta1BatchDedicatedResources(_messages.Message): r"""A description of resources that are used for performing batch operations, are dedicated to a Model, and need manual configuration. Fields: flexStart: Optional. Immutable. If set, use DWS resource to schedule the deployment workload. reference: (https://cloud.google.com/blog/products/compute/introducing-dynamic- workload-scheduler) machineSpec: Required. Immutable. The specification of a single machine. maxReplicaCount: Immutable. The maximum number of machine replicas the batch operation may be scaled to. The default value is 10. spot: Optional. If true, schedule the deployment workload on [spot VMs](https://cloud.google.com/kubernetes-engine/docs/concepts/spot-vms). startingReplicaCount: Immutable. The number of machine replicas used at the start of the batch operation. If not set, Vertex AI decides starting number, not greater than max_replica_count """ flexStart = _messages.MessageField('GoogleCloudAiplatformV1beta1FlexStart', 1) machineSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1MachineSpec', 2) maxReplicaCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) spot = _messages.BooleanField(4) startingReplicaCount = _messages.IntegerField(5, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsRequest(_messages.Message): r"""Request message for PipelineService.BatchDeletePipelineJobs. Fields: names: Required. The names of the PipelineJobs to delete. A maximum of 32 PipelineJobs can be deleted in a batch. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipelineJob}` """ names = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1BatchDeletePipelineJobsResponse(_messages.Message): r"""Response message for PipelineService.BatchDeletePipelineJobs. Fields: pipelineJobs: PipelineJobs deleted. """ pipelineJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineJob', 1, repeated=True) class GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsRequest(_messages.Message): r"""Request message for ModelService.BatchImportEvaluatedAnnotations Fields: evaluatedAnnotations: Required. Evaluated annotations resource to be imported. """ evaluatedAnnotations = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluatedAnnotation', 1, repeated=True) class GoogleCloudAiplatformV1beta1BatchImportEvaluatedAnnotationsResponse(_messages.Message): r"""Response message for ModelService.BatchImportEvaluatedAnnotations Fields: importedEvaluatedAnnotationsCount: Output only. Number of EvaluatedAnnotations imported. """ importedEvaluatedAnnotationsCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1BatchImportModelEvaluationSlicesRequest(_messages.Message): r"""Request message for ModelService.BatchImportModelEvaluationSlices Fields: modelEvaluationSlices: Required. Model evaluation slice resource to be imported. """ modelEvaluationSlices = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelEvaluationSlice', 1, repeated=True) class GoogleCloudAiplatformV1beta1BatchImportModelEvaluationSlicesResponse(_messages.Message): r"""Response message for ModelService.BatchImportModelEvaluationSlices Fields: importedModelEvaluationSlices: Output only. List of imported ModelEvaluationSlice.name. """ importedModelEvaluationSlices = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadata(_messages.Message): r"""Runtime operation information for MigrationService.BatchMigrateResources. Fields: genericMetadata: The common part of the operation metadata. partialResults: Partial results that reflect the latest migration operation progress. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) partialResults = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadataPartialResult', 2, repeated=True) class GoogleCloudAiplatformV1beta1BatchMigrateResourcesOperationMetadataPartialResult(_messages.Message): r"""Represents a partial result in batch migration operation for one MigrateResourceRequest. Fields: dataset: Migrated dataset resource name. error: The error result of the migration request in case of failure. model: Migrated model resource name. request: It's the same as the value in BatchMigrateResourcesRequest.migrate_resource_requests. """ dataset = _messages.StringField(1) error = _messages.MessageField('GoogleRpcStatus', 2) model = _messages.StringField(3) request = _messages.MessageField('GoogleCloudAiplatformV1beta1MigrateResourceRequest', 4) class GoogleCloudAiplatformV1beta1BatchMigrateResourcesRequest(_messages.Message): r"""Request message for MigrationService.BatchMigrateResources. Fields: migrateResourceRequests: Required. The request messages specifying the resources to migrate. They must be in the same location as the destination. Up to 50 resources can be migrated in one batch. """ migrateResourceRequests = _messages.MessageField('GoogleCloudAiplatformV1beta1MigrateResourceRequest', 1, repeated=True) class GoogleCloudAiplatformV1beta1BatchMigrateResourcesResponse(_messages.Message): r"""Response message for MigrationService.BatchMigrateResources. Fields: migrateResourceResponses: Successfully migrated resources. """ migrateResourceResponses = _messages.MessageField('GoogleCloudAiplatformV1beta1MigrateResourceResponse', 1, repeated=True) class GoogleCloudAiplatformV1beta1BatchPredictionJob(_messages.Message): r"""A job that uses a Model to produce predictions on multiple input instances. If predictions for significant portion of the instances fail, the job may finish without attempting predictions for all remaining instances. Enums: StateValueValuesEnum: Output only. The detailed state of the job. Messages: LabelsValue: The labels with user-defined metadata to organize BatchPredictionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: completionStats: Output only. Statistics on completed and failed prediction instances. createTime: Output only. Time when the BatchPredictionJob was created. dedicatedResources: The config of resources used by the Model during the batch prediction. If the Model supports DEDICATED_RESOURCES this config may be provided (and the job will use these resources), if the Model doesn't support AUTOMATIC_RESOURCES, this config must be provided. disableContainerLogging: For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true. displayName: Required. The user-defined name of this BatchPredictionJob. encryptionSpec: Customer-managed encryption key options for a BatchPredictionJob. If this is set, then all resources created by the BatchPredictionJob will be encrypted with the provided encryption key. endTime: Output only. Time when the BatchPredictionJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`. error: Output only. Only populated when the job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED. explanationSpec: Explanation configuration for this BatchPredictionJob. Can be specified only if generate_explanation is set to `true`. This value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of the explanation_spec object is not populated, the corresponding field of the Model.explanation_spec object is inherited. generateExplanation: Generate explanation with the batch prediction results. When set to `true`, the batch prediction output changes based on the `predictions_format` field of the BatchPredictionJob.output_config object: * `bigquery`: output includes a column named `explanation`. The value is a struct that conforms to the Explanation object. * `jsonl`: The JSON objects on each line include an additional entry keyed `explanation`. The value of the entry is a JSON object that conforms to the Explanation object. * `csv`: Generating explanations for CSV format is not supported. If this field is set to true, either the Model.explanation_spec or explanation_spec must be populated. inputConfig: Required. Input configuration of the instances on which predictions are performed. The schema of any single instance may be specified via the Model's PredictSchemata's instance_schema_uri. instanceConfig: Configuration for how to convert batch prediction input instances to the prediction instances that are sent to the Model. labels: The labels with user-defined metadata to organize BatchPredictionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. manualBatchTuningParameters: Immutable. Parameters configuring the batch behavior. Currently only applicable when dedicated_resources are used (in other cases Vertex AI does the tuning itself). model: The name of the Model resource that produces the predictions via this job, must share the same ancestor Location. Starting this job has no impact on any existing deployments of the Model and their resources. Exactly one of model and unmanaged_container_model must be set. The model resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. The model resource could also be a publisher model. Example: `publishers/{publisher}/models/{model}` or `projects/{project}/locations /{location}/publishers/{publisher}/models/{model}` modelMonitoringConfig: Model monitoring config will be used for analysis model behaviors, based on the input and output to the batch prediction job, as well as the provided training dataset. modelMonitoringStatsAnomalies: Get batch prediction job monitoring statistics. modelMonitoringStatus: Output only. The running status of the model monitoring pipeline. modelParameters: The parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri. modelVersionId: Output only. The version ID of the Model that produces the predictions via this job. name: Output only. Resource name of the BatchPredictionJob. outputConfig: Required. The Configuration specifying where output predictions should be written. The schema of any single prediction may be specified as a concatenation of Model's PredictSchemata's instance_schema_uri and prediction_schema_uri. outputInfo: Output only. Information further describing the output of this job. partialFailures: Output only. Partial failures encountered. For example, single files that can't be read. This field never exceeds 20 entries. Status details fields contain standard Google Cloud error details. resourcesConsumed: Output only. Information about resources that had been consumed by this job. Provided in real time at best effort basis, as well as a final value once the job completes. Note: This field currently may be not populated for batch predictions that use AutoML Models. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. serviceAccount: The service account that the DeployedModel's container runs as. If not specified, a system generated one will be used, which has minimal permissions and the custom container, if used, may not have enough permission to access other Google Cloud resources. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account. startTime: Output only. Time when the BatchPredictionJob for the first time entered the `JOB_STATE_RUNNING` state. state: Output only. The detailed state of the job. unmanagedContainerModel: Contains model information necessary to perform batch prediction without requiring uploading to model registry. Exactly one of model and unmanaged_container_model must be set. updateTime: Output only. Time when the BatchPredictionJob was most recently updated. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of the job. Values: JOB_STATE_UNSPECIFIED: The job state is unspecified. JOB_STATE_QUEUED: The job has been just created or resumed and processing has not yet begun. JOB_STATE_PENDING: The service is preparing to run the job. JOB_STATE_RUNNING: The job is in progress. JOB_STATE_SUCCEEDED: The job completed successfully. JOB_STATE_FAILED: The job failed. JOB_STATE_CANCELLING: The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. JOB_STATE_CANCELLED: The job has been cancelled. JOB_STATE_PAUSED: The job has been stopped, and can be resumed. JOB_STATE_EXPIRED: The job has expired. JOB_STATE_UPDATING: The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state. JOB_STATE_PARTIALLY_SUCCEEDED: The job is partially succeeded, some results may be missing due to errors. """ JOB_STATE_UNSPECIFIED = 0 JOB_STATE_QUEUED = 1 JOB_STATE_PENDING = 2 JOB_STATE_RUNNING = 3 JOB_STATE_SUCCEEDED = 4 JOB_STATE_FAILED = 5 JOB_STATE_CANCELLING = 6 JOB_STATE_CANCELLED = 7 JOB_STATE_PAUSED = 8 JOB_STATE_EXPIRED = 9 JOB_STATE_UPDATING = 10 JOB_STATE_PARTIALLY_SUCCEEDED = 11 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize BatchPredictionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) completionStats = _messages.MessageField('GoogleCloudAiplatformV1beta1CompletionStats', 1) createTime = _messages.StringField(2) dedicatedResources = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchDedicatedResources', 3) disableContainerLogging = _messages.BooleanField(4) displayName = _messages.StringField(5) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 6) endTime = _messages.StringField(7) error = _messages.MessageField('GoogleRpcStatus', 8) explanationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationSpec', 9) generateExplanation = _messages.BooleanField(10) inputConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchPredictionJobInputConfig', 11) instanceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchPredictionJobInstanceConfig', 12) labels = _messages.MessageField('LabelsValue', 13) manualBatchTuningParameters = _messages.MessageField('GoogleCloudAiplatformV1beta1ManualBatchTuningParameters', 14) model = _messages.StringField(15) modelMonitoringConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringConfig', 16) modelMonitoringStatsAnomalies = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies', 17, repeated=True) modelMonitoringStatus = _messages.MessageField('GoogleRpcStatus', 18) modelParameters = _messages.MessageField('extra_types.JsonValue', 19) modelVersionId = _messages.StringField(20) name = _messages.StringField(21) outputConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchPredictionJobOutputConfig', 22) outputInfo = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchPredictionJobOutputInfo', 23) partialFailures = _messages.MessageField('GoogleRpcStatus', 24, repeated=True) resourcesConsumed = _messages.MessageField('GoogleCloudAiplatformV1beta1ResourcesConsumed', 25) satisfiesPzi = _messages.BooleanField(26) satisfiesPzs = _messages.BooleanField(27) serviceAccount = _messages.StringField(28) startTime = _messages.StringField(29) state = _messages.EnumField('StateValueValuesEnum', 30) unmanagedContainerModel = _messages.MessageField('GoogleCloudAiplatformV1beta1UnmanagedContainerModel', 31) updateTime = _messages.StringField(32) class GoogleCloudAiplatformV1beta1BatchPredictionJobInputConfig(_messages.Message): r"""Configures the input to BatchPredictionJob. See Model.supported_input_storage_formats for Model's supported input formats, and how instances should be expressed via any of them. Fields: bigquerySource: The BigQuery location of the input table. The schema of the table should be in the format described by the given context OpenAPI Schema, if one is provided. The table may contain additional columns that are not described by the schema, and they will be ignored. gcsSource: The Cloud Storage location for the input instances. instancesFormat: Required. The format in which instances are given, must be one of the Model's supported_input_storage_formats. """ bigquerySource = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQuerySource', 1) gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsSource', 2) instancesFormat = _messages.StringField(3) class GoogleCloudAiplatformV1beta1BatchPredictionJobInstanceConfig(_messages.Message): r"""Configuration defining how to transform batch prediction input instances to the instances that the Model accepts. Fields: excludedFields: Fields that will be excluded in the prediction instance that is sent to the Model. Excluded will be attached to the batch prediction output if key_field is not specified. When excluded_fields is populated, included_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord. includedFields: Fields that will be included in the prediction instance that is sent to the Model. If instance_type is `array`, the order of field names in included_fields also determines the order of the values in the array. When included_fields is populated, excluded_fields must be empty. The input must be JSONL with objects at each line, BigQuery or TfRecord. instanceType: The format of the instance that the Model accepts. Vertex AI will convert compatible batch prediction input instance formats to the specified format. Supported values are: * `object`: Each input is converted to JSON object format. * For `bigquery`, each row is converted to an object. * For `jsonl`, each line of the JSONL input must be an object. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf- record-gzip`. * `array`: Each input is converted to JSON array format. * For `bigquery`, each row is converted to an array. The order of columns is determined by the BigQuery column order, unless included_fields is populated. included_fields must be populated for specifying field orders. * For `jsonl`, if each line of the JSONL input is an object, included_fields must be populated for specifying field orders. * Does not apply to `csv`, `file-list`, `tf-record`, or `tf-record-gzip`. If not specified, Vertex AI converts the batch prediction input as follows: * For `bigquery` and `csv`, the behavior is the same as `array`. The order of columns is the same as defined in the file or table, unless included_fields is populated. * For `jsonl`, the prediction instance format is determined by each line of the input. * For `tf-record`/`tf- record-gzip`, each record will be converted to an object in the format of `{"b64": }`, where `` is the Base64-encoded string of the content of the record. * For `file-list`, each file in the list will be converted to an object in the format of `{"b64": }`, where `` is the Base64-encoded string of the content of the file. keyField: The name of the field that is considered as a key. The values identified by the key field is not included in the transformed instances that is sent to the Model. This is similar to specifying this name of the field in excluded_fields. In addition, the batch prediction output will not include the instances. Instead the output will only include the value of the key field, in a field named `key` in the output: * For `jsonl` output format, the output will have a `key` field instead of the `instance` field. * For `csv`/`bigquery` output format, the output will have have a `key` column instead of the instance feature columns. The input must be JSONL with objects at each line, CSV, BigQuery or TfRecord. """ excludedFields = _messages.StringField(1, repeated=True) includedFields = _messages.StringField(2, repeated=True) instanceType = _messages.StringField(3) keyField = _messages.StringField(4) class GoogleCloudAiplatformV1beta1BatchPredictionJobOutputConfig(_messages.Message): r"""Configures the output of BatchPredictionJob. See Model.supported_output_storage_formats for supported output formats, and how predictions are expressed via any of them. Fields: bigqueryDestination: The BigQuery project or dataset location where the output is to be written to. If project is provided, a new dataset is created with name `prediction__` where is made BigQuery-dataset-name compatible (for example, most special characters become underscores), and timestamp is in YYYY_MM_DDThh_mm_ss_sssZ "based on ISO-8601" format. In the dataset two tables will be created, `predictions`, and `errors`. If the Model has both instance and prediction schemata defined then the tables have columns as follows: The `predictions` table contains instances for which the prediction succeeded, it has columns as per a concatenation of the Model's instance and prediction schemata. The `errors` table contains rows for which the prediction has failed, it has instance columns, as per the instance schema, followed by a single "errors" column, which as values has google.rpc.Status represented as a STRUCT, and containing only `code` and `message`. gcsDestination: The Cloud Storage location of the directory where the output is to be written to. In the given directory a new directory is created. Its name is `prediction--`, where timestamp is in YYYY-MM- DDThh:mm:ss.sssZ ISO-8601 format. Inside of it files `predictions_0001.`, `predictions_0002.`, ..., `predictions_N.` are created where `` depends on chosen predictions_format, and N may equal 0001 and depends on the total number of successfully predicted instances. If the Model has both instance and prediction schemata defined then each such file contains predictions as per the predictions_format. If prediction for any instance failed (partially or completely), then an additional `errors_0001.`, `errors_0002.`,..., `errors_N.` files are created (N depends on total number of failed predictions). These files contain the failed instances, as per their schema, followed by an additional `error` field which as value has google.rpc.Status containing only `code` and `message` fields. predictionsFormat: Required. The format in which Vertex AI gives the predictions, must be one of the Model's supported_output_storage_formats. """ bigqueryDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQueryDestination', 1) gcsDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 2) predictionsFormat = _messages.StringField(3) class GoogleCloudAiplatformV1beta1BatchPredictionJobOutputInfo(_messages.Message): r"""Further describes this job's output. Supplements output_config. Fields: bigqueryOutputDataset: Output only. The path of the BigQuery dataset created, in `bq://projectId.bqDatasetId` format, into which the prediction output is written. bigqueryOutputTable: Output only. The name of the BigQuery table created, in `predictions_` format, into which the prediction output is written. Can be used by UI to generate the BigQuery output path, for example. gcsOutputDirectory: Output only. The full path of the Cloud Storage directory created, into which the prediction output is written. """ bigqueryOutputDataset = _messages.StringField(1) bigqueryOutputTable = _messages.StringField(2) gcsOutputDirectory = _messages.StringField(3) class GoogleCloudAiplatformV1beta1BatchReadFeatureValuesOperationMetadata(_messages.Message): r"""Details of operations that batch reads Feature values. Fields: genericMetadata: Operation metadata for Featurestore batch read Features values. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequest(_messages.Message): r"""Request message for FeaturestoreService.BatchReadFeatureValues. Fields: bigqueryReadInstances: Similar to csv_read_instances, but from BigQuery source. csvReadInstances: Each read instance consists of exactly one read timestamp and one or more entity IDs identifying entities of the corresponding EntityTypes whose Features are requested. Each output instance contains Feature values of requested entities concatenated together as of the read time. An example read instance may be `foo_entity_id, bar_entity_id, 2020-01-01T10:00:00.123Z`. An example output instance may be `foo_entity_id, bar_entity_id, 2020-01-01T10:00:00.123Z, foo_entity_feature1_value, bar_entity_feature2_value`. Timestamp in each read instance must be millisecond-aligned. `csv_read_instances` are read instances stored in a plain-text CSV file. The header should be: [ENTITY_TYPE_ID1], [ENTITY_TYPE_ID2], ..., timestamp The columns can be in any order. Values in the timestamp column must use the RFC 3339 format, e.g. `2012-07-30T10:43:17.123Z`. destination: Required. Specifies output location and format. entityTypeSpecs: Required. Specifies EntityType grouping Features to read values of and settings. passThroughFields: When not empty, the specified fields in the *_read_instances source will be joined as-is in the output, in addition to those fields from the Featurestore Entity. For BigQuery source, the type of the pass-through values will be automatically inferred. For CSV source, the pass-through values will be passed as opaque bytes. startTime: Optional. Excludes Feature values with feature generation timestamp before this timestamp. If not set, retrieve oldest values kept in Feature Store. Timestamp, if present, must not have higher than millisecond precision. """ bigqueryReadInstances = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQuerySource', 1) csvReadInstances = _messages.MessageField('GoogleCloudAiplatformV1beta1CsvSource', 2) destination = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureValueDestination', 3) entityTypeSpecs = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestEntityTypeSpec', 4, repeated=True) passThroughFields = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestPassThroughField', 5, repeated=True) startTime = _messages.StringField(6) class GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestEntityTypeSpec(_messages.Message): r"""Selects Features of an EntityType to read values of and specifies read settings. Fields: entityTypeId: Required. ID of the EntityType to select Features. The EntityType id is the entity_type_id specified during EntityType creation. featureSelector: Required. Selectors choosing which Feature values to read from the EntityType. settings: Per-Feature settings for the batch read. """ entityTypeId = _messages.StringField(1) featureSelector = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureSelector', 2) settings = _messages.MessageField('GoogleCloudAiplatformV1beta1DestinationFeatureSetting', 3, repeated=True) class GoogleCloudAiplatformV1beta1BatchReadFeatureValuesRequestPassThroughField(_messages.Message): r"""Describe pass-through fields in read_instance source. Fields: fieldName: Required. The name of the field in the CSV header or the name of the column in BigQuery table. The naming restriction is the same as Feature.name. """ fieldName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1BatchReadFeatureValuesResponse(_messages.Message): r"""Response message for FeaturestoreService.BatchReadFeatureValues.""" class GoogleCloudAiplatformV1beta1BatchReadTensorboardTimeSeriesDataResponse(_messages.Message): r"""Response message for TensorboardService.BatchReadTensorboardTimeSeriesData. Fields: timeSeriesData: The returned time series data. """ timeSeriesData = _messages.MessageField('GoogleCloudAiplatformV1beta1TimeSeriesData', 1, repeated=True) class GoogleCloudAiplatformV1beta1BigQueryDestination(_messages.Message): r"""The BigQuery location for the output content. Fields: outputUri: Required. BigQuery URI to a project or table, up to 2000 characters long. When only the project is specified, the Dataset and Table is created. When the full table reference is specified, the Dataset must exist and table must not exist. Accepted forms: * BigQuery path. For example: `bq://projectId` or `bq://projectId.bqDatasetId` or `bq://projectId.bqDatasetId.bqTableId`. """ outputUri = _messages.StringField(1) class GoogleCloudAiplatformV1beta1BigQueryRequestSet(_messages.Message): r"""The request set for the evaluation run. Messages: CandidateResponseColumnsValue: Optional. Map of candidate name to candidate response column name. The column will be in evaluation_item.CandidateResponse format. Fields: candidateResponseColumns: Optional. Map of candidate name to candidate response column name. The column will be in evaluation_item.CandidateResponse format. promptColumn: Optional. The name of the column that contains the requests to evaluate. This will be in evaluation_item.EvalPrompt format. rubricsColumn: Optional. The name of the column that contains the rubrics. This is in evaluation_rubric.RubricGroup format. samplingConfig: Optional. The sampling config for the bigquery resource. uri: Required. The URI of a BigQuery table. e.g. bq://projectId.bqDatasetId.bqTableId """ @encoding.MapUnrecognizedFields('additionalProperties') class CandidateResponseColumnsValue(_messages.Message): r"""Optional. Map of candidate name to candidate response column name. The column will be in evaluation_item.CandidateResponse format. Messages: AdditionalProperty: An additional property for a CandidateResponseColumnsValue object. Fields: additionalProperties: Additional properties of type CandidateResponseColumnsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a CandidateResponseColumnsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) candidateResponseColumns = _messages.MessageField('CandidateResponseColumnsValue', 1) promptColumn = _messages.StringField(2) rubricsColumn = _messages.StringField(3) samplingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQueryRequestSetSamplingConfig', 4) uri = _messages.StringField(5) class GoogleCloudAiplatformV1beta1BigQueryRequestSetSamplingConfig(_messages.Message): r"""The sampling config. Enums: SamplingMethodValueValuesEnum: Optional. The sampling method to use. Fields: samplingCount: Optional. The total number of logged data to import. If available data is less than the sampling count, all data will be imported. Default is 100. samplingDuration: Optional. How long to wait before sampling data from the BigQuery table. If not specified, defaults to 0. samplingMethod: Optional. The sampling method to use. """ class SamplingMethodValueValuesEnum(_messages.Enum): r"""Optional. The sampling method to use. Values: SAMPLING_METHOD_UNSPECIFIED: Unspecified sampling method. RANDOM: Random sampling. """ SAMPLING_METHOD_UNSPECIFIED = 0 RANDOM = 1 samplingCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) samplingDuration = _messages.StringField(2) samplingMethod = _messages.EnumField('SamplingMethodValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1BigQuerySource(_messages.Message): r"""The BigQuery location for the input content. Fields: inputUri: Required. BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`. """ inputUri = _messages.StringField(1) class GoogleCloudAiplatformV1beta1BleuInput(_messages.Message): r"""Input for bleu metric. Fields: instances: Required. Repeated bleu instances. metricSpec: Required. Spec for bleu score metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1BleuInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1BleuSpec', 2) class GoogleCloudAiplatformV1beta1BleuInstance(_messages.Message): r"""Spec for bleu instance. Fields: prediction: Required. Output of the evaluated model. reference: Required. Ground truth used to compare against the prediction. """ prediction = _messages.StringField(1) reference = _messages.StringField(2) class GoogleCloudAiplatformV1beta1BleuMetricValue(_messages.Message): r"""Bleu metric value for an instance. Fields: score: Output only. Bleu score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1BleuResults(_messages.Message): r"""Results for bleu metric. Fields: bleuMetricValues: Output only. Bleu metric values. """ bleuMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1BleuMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1BleuSpec(_messages.Message): r"""Spec for bleu score metric - calculates the precision of n-grams in the prediction as compared to reference - returns a score ranging between 0 to 1. Fields: useEffectiveOrder: Optional. Whether to use_effective_order to compute bleu score. """ useEffectiveOrder = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1Blob(_messages.Message): r"""A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. Fields: data: Required. The raw bytes of the data. displayName: Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled. mimeType: Required. The IANA standard MIME type of the source data. """ data = _messages.BytesField(1) displayName = _messages.StringField(2) mimeType = _messages.StringField(3) class GoogleCloudAiplatformV1beta1BlurBaselineConfig(_messages.Message): r"""Config for blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383 Fields: maxBlurSigma: The standard deviation of the blur kernel for the blurred baseline. The same blurring parameter is used for both the height and the width dimension. If not set, the method defaults to the zero (i.e. black for images) baseline. """ maxBlurSigma = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1BoolArray(_messages.Message): r"""A list of boolean values. Fields: values: A list of bool values. """ values = _messages.BooleanField(1, repeated=True) class GoogleCloudAiplatformV1beta1CacheConfig(_messages.Message): r"""Config of GenAI caching features. This is a singleton resource. Fields: disableCache: If set to true, disables GenAI caching. Otherwise caching is enabled. name: Identifier. Name of the cache config. Format: - `projects/{project}/cacheConfig`. """ disableCache = _messages.BooleanField(1) name = _messages.StringField(2) class GoogleCloudAiplatformV1beta1CachedContent(_messages.Message): r"""A resource used in LLM queries for users to explicitly specify what to cache and how to cache. Fields: contents: Optional. Input only. Immutable. The content to cache createTime: Output only. Creation time of the cache entry. displayName: Optional. Immutable. The user-generated meaningful display name of the cached content. encryptionSpec: Input only. Immutable. Customer-managed encryption key spec for a `CachedContent`. If set, this `CachedContent` and all its sub-resources will be secured by this key. expireTime: Timestamp of when this resource is considered expired. This is *always* provided on output, regardless of what was sent on input. model: Immutable. The name of the `Model` to use for cached content. Currently, only the published Gemini base models are supported, in form of projects/{PROJECT}/locations/{LOCATION}/publishers/google/models/{MODEL} name: Immutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content} systemInstruction: Optional. Input only. Immutable. Developer set system instruction. Currently, text only toolConfig: Optional. Input only. Immutable. Tool config. This config is shared for all tools tools: Optional. Input only. Immutable. A list of `Tools` the model may use to generate the next response ttl: Input only. The TTL for this resource. The expiration time is computed: now + TTL. updateTime: Output only. When the cache entry was last updated in UTC time. usageMetadata: Output only. Metadata on the usage of the cached content. """ contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1, repeated=True) createTime = _messages.StringField(2) displayName = _messages.StringField(3) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 4) expireTime = _messages.StringField(5) model = _messages.StringField(6) name = _messages.StringField(7) systemInstruction = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 8) toolConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolConfig', 9) tools = _messages.MessageField('GoogleCloudAiplatformV1beta1Tool', 10, repeated=True) ttl = _messages.StringField(11) updateTime = _messages.StringField(12) usageMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1CachedContentUsageMetadata', 13) class GoogleCloudAiplatformV1beta1CachedContentUsageMetadata(_messages.Message): r"""Metadata on the usage of the cached content. Fields: audioDurationSeconds: Duration of audio in seconds. imageCount: Number of images. textCount: Number of text characters. totalTokenCount: Total number of tokens that the cached content consumes. videoDurationSeconds: Duration of video in seconds. """ audioDurationSeconds = _messages.IntegerField(1, variant=_messages.Variant.INT32) imageCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) textCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) totalTokenCount = _messages.IntegerField(4, variant=_messages.Variant.INT32) videoDurationSeconds = _messages.IntegerField(5, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1CancelBatchPredictionJobRequest(_messages.Message): r"""Request message for JobService.CancelBatchPredictionJob.""" class GoogleCloudAiplatformV1beta1CancelCustomJobRequest(_messages.Message): r"""Request message for JobService.CancelCustomJob.""" class GoogleCloudAiplatformV1beta1CancelDataLabelingJobRequest(_messages.Message): r"""Request message for JobService.CancelDataLabelingJob.""" class GoogleCloudAiplatformV1beta1CancelEvaluationRunRequest(_messages.Message): r"""Request message for EvaluationManagementService.CancelEvaluationRun.""" class GoogleCloudAiplatformV1beta1CancelHyperparameterTuningJobRequest(_messages.Message): r"""Request message for JobService.CancelHyperparameterTuningJob.""" class GoogleCloudAiplatformV1beta1CancelNasJobRequest(_messages.Message): r"""Request message for JobService.CancelNasJob.""" class GoogleCloudAiplatformV1beta1CancelPipelineJobRequest(_messages.Message): r"""Request message for PipelineService.CancelPipelineJob.""" class GoogleCloudAiplatformV1beta1CancelServerlessRayJobRequest(_messages.Message): r"""Request message for JobService.CancelServerlessRayJob.""" class GoogleCloudAiplatformV1beta1CancelServerlessRayJobResponse(_messages.Message): r"""Message for JobService.CancelServerlessRayJob response.""" class GoogleCloudAiplatformV1beta1CancelTrainingPipelineRequest(_messages.Message): r"""Request message for PipelineService.CancelTrainingPipeline.""" class GoogleCloudAiplatformV1beta1CancelTuningJobRequest(_messages.Message): r"""Request message for GenAiTuningService.CancelTuningJob.""" class GoogleCloudAiplatformV1beta1Candidate(_messages.Message): r"""A response candidate generated from the model. Enums: FinishReasonValueValuesEnum: Output only. The reason why the model stopped generating tokens. If empty, the model has not stopped generating. Fields: avgLogprobs: Output only. The average log probability of the tokens in this candidate. This is a length-normalized score that can be used to compare the quality of candidates of different lengths. A higher average log probability suggests a more confident and coherent response. citationMetadata: Output only. A collection of citations that apply to the generated content. content: Output only. The content of the candidate. finishMessage: Output only. Describes the reason the model stopped generating tokens in more detail. This field is returned only when `finish_reason` is set. finishReason: Output only. The reason why the model stopped generating tokens. If empty, the model has not stopped generating. groundingMetadata: Output only. Metadata returned when grounding is enabled. It contains the sources used to ground the generated content. index: Output only. The 0-based index of this candidate in the list of generated responses. This is useful for distinguishing between multiple candidates when `candidate_count` > 1. logprobsResult: Output only. The detailed log probability information for the tokens in this candidate. This is useful for debugging, understanding model uncertainty, and identifying potential "hallucinations". safetyRatings: Output only. A list of ratings for the safety of a response candidate. There is at most one rating per category. urlContextMetadata: Output only. Metadata returned when the model uses the `url_context` tool to get information from a user-provided URL. """ class FinishReasonValueValuesEnum(_messages.Enum): r"""Output only. The reason why the model stopped generating tokens. If empty, the model has not stopped generating. Values: FINISH_REASON_UNSPECIFIED: The finish reason is unspecified. STOP: The model reached a natural stopping point or a configured stop sequence. MAX_TOKENS: The model generated the maximum number of tokens allowed by the `max_output_tokens` parameter. SAFETY: The model stopped generating because the content potentially violates safety policies. NOTE: When streaming, the `content` field is empty if content filters block the output. RECITATION: The model stopped generating because the content may be a recitation from a source. OTHER: The model stopped generating for a reason not otherwise specified. BLOCKLIST: The model stopped generating because the content contains a term from a configured blocklist. PROHIBITED_CONTENT: The model stopped generating because the content may be prohibited. SPII: The model stopped generating because the content may contain sensitive personally identifiable information (SPII). MALFORMED_FUNCTION_CALL: The model generated a function call that is syntactically invalid and can't be parsed. MODEL_ARMOR: The model response was blocked by Model Armor. IMAGE_SAFETY: The generated image potentially violates safety policies. IMAGE_PROHIBITED_CONTENT: The generated image may contain prohibited content. IMAGE_RECITATION: The generated image may be a recitation from a source. IMAGE_OTHER: The image generation stopped for a reason not otherwise specified. UNEXPECTED_TOOL_CALL: The model generated a function call that is semantically invalid. This can happen, for example, if function calling is not enabled or the generated function is not in the function declaration. NO_IMAGE: The model was expected to generate an image, but didn't. """ FINISH_REASON_UNSPECIFIED = 0 STOP = 1 MAX_TOKENS = 2 SAFETY = 3 RECITATION = 4 OTHER = 5 BLOCKLIST = 6 PROHIBITED_CONTENT = 7 SPII = 8 MALFORMED_FUNCTION_CALL = 9 MODEL_ARMOR = 10 IMAGE_SAFETY = 11 IMAGE_PROHIBITED_CONTENT = 12 IMAGE_RECITATION = 13 IMAGE_OTHER = 14 UNEXPECTED_TOOL_CALL = 15 NO_IMAGE = 16 avgLogprobs = _messages.FloatField(1) citationMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1CitationMetadata', 2) content = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 3) finishMessage = _messages.StringField(4) finishReason = _messages.EnumField('FinishReasonValueValuesEnum', 5) groundingMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundingMetadata', 6) index = _messages.IntegerField(7, variant=_messages.Variant.INT32) logprobsResult = _messages.MessageField('GoogleCloudAiplatformV1beta1LogprobsResult', 8) safetyRatings = _messages.MessageField('GoogleCloudAiplatformV1beta1SafetyRating', 9, repeated=True) urlContextMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1UrlContextMetadata', 10) class GoogleCloudAiplatformV1beta1CandidateResponse(_messages.Message): r"""Responses from model or agent. Fields: candidate: Required. The name of the candidate that produced the response. events: Optional. Intermediate events (such as tool calls and responses) that led to the final response. text: Text response. value: Fields and values that can be used to populate the response template. """ candidate = _messages.StringField(1) events = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 2, repeated=True) text = _messages.StringField(3) value = _messages.MessageField('extra_types.JsonValue', 4) class GoogleCloudAiplatformV1beta1CandidateResult(_messages.Message): r"""Result for a single candidate. Fields: additionalResults: Optional. Additional results for the metric. candidate: Required. The candidate that is being evaluated. The value is the same as the candidate name in the EvaluationRequest. explanation: Optional. The explanation for the metric. metric: Required. The metric that was evaluated. rubricVerdicts: Optional. The rubric verdicts for the metric. score: Optional. The score for the metric. """ additionalResults = _messages.MessageField('extra_types.JsonValue', 1) candidate = _messages.StringField(2) explanation = _messages.StringField(3) metric = _messages.StringField(4) rubricVerdicts = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricVerdict', 5, repeated=True) score = _messages.FloatField(6, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1CheckPublisherModelEulaAcceptanceRequest(_messages.Message): r"""Request message for ModelGardenService.CheckPublisherModelEula. Fields: publisherModel: Required. The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}`, or `publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}` """ publisherModel = _messages.StringField(1) class GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateMetatdata(_messages.Message): r"""This message will be placed in the metadata field of a google.longrunning.Operation associated with a CheckTrialEarlyStoppingState request. Fields: genericMetadata: Operation metadata for suggesting Trials. study: The name of the Study that the Trial belongs to. trial: The Trial name. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) study = _messages.StringField(2) trial = _messages.StringField(3) class GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateRequest(_messages.Message): r"""Request message for VizierService.CheckTrialEarlyStoppingState.""" class GoogleCloudAiplatformV1beta1CheckTrialEarlyStoppingStateResponse(_messages.Message): r"""Response message for VizierService.CheckTrialEarlyStoppingState. Fields: shouldStop: True if the Trial should stop. """ shouldStop = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1Checkpoint(_messages.Message): r"""Describes the machine learning model version checkpoint. Fields: checkpointId: The ID of the checkpoint. epoch: The epoch of the checkpoint. step: The step of the checkpoint. """ checkpointId = _messages.StringField(1) epoch = _messages.IntegerField(2) step = _messages.IntegerField(3) class GoogleCloudAiplatformV1beta1Chunk(_messages.Message): r"""Container for bytes-encoded data such as video frame, audio sample, or a complete binary/text data. Fields: data: Required. The data in the chunk. metadata: Optional. Metadata that is associated with the data in the payload. mimeType: Required. Mime type of the chunk data. See https://www.iana.org/assignments/media-types/media-types.xhtml for the full list. """ data = _messages.BytesField(1) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1Metadata', 2) mimeType = _messages.StringField(3) class GoogleCloudAiplatformV1beta1Citation(_messages.Message): r"""A citation for a piece of generatedcontent. Fields: endIndex: Output only. The end index of the citation in the content. license: Output only. The license of the source of the citation. publicationDate: Output only. The publication date of the source of the citation. startIndex: Output only. The start index of the citation in the content. title: Output only. The title of the source of the citation. uri: Output only. The URI of the source of the citation. """ endIndex = _messages.IntegerField(1, variant=_messages.Variant.INT32) license = _messages.StringField(2) publicationDate = _messages.MessageField('GoogleTypeDate', 3) startIndex = _messages.IntegerField(4, variant=_messages.Variant.INT32) title = _messages.StringField(5) uri = _messages.StringField(6) class GoogleCloudAiplatformV1beta1CitationMetadata(_messages.Message): r"""A collection of citations that apply to a piece of generated content. Fields: citations: Output only. A list of citations for the content. """ citations = _messages.MessageField('GoogleCloudAiplatformV1beta1Citation', 1, repeated=True) class GoogleCloudAiplatformV1beta1Claim(_messages.Message): r"""Claim that is extracted from the input text and facts that support it. Fields: endIndex: Index in the input text where the claim ends (exclusive). factIndexes: Indexes of the facts supporting this claim. score: Confidence score of this corroboration. startIndex: Index in the input text where the claim starts (inclusive). """ endIndex = _messages.IntegerField(1, variant=_messages.Variant.INT32) factIndexes = _messages.IntegerField(2, repeated=True, variant=_messages.Variant.INT32) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) startIndex = _messages.IntegerField(4, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1ClientConnectionConfig(_messages.Message): r"""Configurations (e.g. inference timeout) that are applied on your endpoints. Fields: inferenceTimeout: Customizable online prediction request timeout. """ inferenceTimeout = _messages.StringField(1) class GoogleCloudAiplatformV1beta1CodeExecutionResult(_messages.Message): r"""Result of executing the [ExecutableCode]. Only generated when using the [CodeExecution] tool, and always follows a `part` containing the [ExecutableCode]. Enums: OutcomeValueValuesEnum: Required. Outcome of the code execution. Fields: outcome: Required. Outcome of the code execution. output: Optional. Contains stdout when code execution is successful, stderr or other description otherwise. """ class OutcomeValueValuesEnum(_messages.Enum): r"""Required. Outcome of the code execution. Values: OUTCOME_UNSPECIFIED: Unspecified status. This value should not be used. OUTCOME_OK: Code execution completed successfully. OUTCOME_FAILED: Code execution finished but with a failure. `stderr` should contain the reason. OUTCOME_DEADLINE_EXCEEDED: Code execution ran for too long, and was cancelled. There may or may not be a partial output present. """ OUTCOME_UNSPECIFIED = 0 OUTCOME_OK = 1 OUTCOME_FAILED = 2 OUTCOME_DEADLINE_EXCEEDED = 3 outcome = _messages.EnumField('OutcomeValueValuesEnum', 1) output = _messages.StringField(2) class GoogleCloudAiplatformV1beta1CoherenceInput(_messages.Message): r"""Input for coherence metric. Fields: instance: Required. Coherence instance. metricSpec: Required. Spec for coherence score metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1CoherenceInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1CoherenceSpec', 2) class GoogleCloudAiplatformV1beta1CoherenceInstance(_messages.Message): r"""Spec for coherence instance. Fields: prediction: Required. Output of the evaluated model. """ prediction = _messages.StringField(1) class GoogleCloudAiplatformV1beta1CoherenceResult(_messages.Message): r"""Spec for coherence result. Fields: confidence: Output only. Confidence for coherence score. explanation: Output only. Explanation for coherence score. score: Output only. Coherence score. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1CoherenceSpec(_messages.Message): r"""Spec for coherence score metric. Fields: version: Optional. Which version to use for evaluation. """ version = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1ColabImage(_messages.Message): r"""Colab image of the runtime. Fields: description: Output only. A human-readable description of the specified colab image release, populated by the system. Example: "Python 3.10", "Latest - current Python 3.11" releaseName: Optional. The release name of the NotebookRuntime Colab image, e.g. "py310". If not specified, detault to the latest release. """ description = _messages.StringField(1) releaseName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1CometInput(_messages.Message): r"""Input for Comet metric. Fields: instance: Required. Comet instance. metricSpec: Required. Spec for comet metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1CometInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1CometSpec', 2) class GoogleCloudAiplatformV1beta1CometInstance(_messages.Message): r"""Spec for Comet instance - The fields used for evaluation are dependent on the comet version. Fields: prediction: Required. Output of the evaluated model. reference: Optional. Ground truth used to compare against the prediction. source: Optional. Source text in original language. """ prediction = _messages.StringField(1) reference = _messages.StringField(2) source = _messages.StringField(3) class GoogleCloudAiplatformV1beta1CometResult(_messages.Message): r"""Spec for Comet result - calculates the comet score for the given instance using the version specified in the spec. Fields: score: Output only. Comet score. Range depends on version. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1CometSpec(_messages.Message): r"""Spec for Comet metric. Enums: VersionValueValuesEnum: Required. Which version to use for evaluation. Fields: sourceLanguage: Optional. Source language in BCP-47 format. targetLanguage: Optional. Target language in BCP-47 format. Covers both prediction and reference. version: Required. Which version to use for evaluation. """ class VersionValueValuesEnum(_messages.Enum): r"""Required. Which version to use for evaluation. Values: COMET_VERSION_UNSPECIFIED: Comet version unspecified. COMET_22_SRC_REF: Comet 22 for translation + source + reference (source- reference-combined). """ COMET_VERSION_UNSPECIFIED = 0 COMET_22_SRC_REF = 1 sourceLanguage = _messages.StringField(1) targetLanguage = _messages.StringField(2) version = _messages.EnumField('VersionValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1CompleteTrialRequest(_messages.Message): r"""Request message for VizierService.CompleteTrial. Fields: finalMeasurement: Optional. If provided, it will be used as the completed Trial's final_measurement; Otherwise, the service will auto-select a previously reported measurement as the final-measurement infeasibleReason: Optional. A human readable reason why the trial was infeasible. This should only be provided if `trial_infeasible` is true. trialInfeasible: Optional. True if the Trial cannot be run with the given Parameter, and final_measurement will be ignored. """ finalMeasurement = _messages.MessageField('GoogleCloudAiplatformV1beta1Measurement', 1) infeasibleReason = _messages.StringField(2) trialInfeasible = _messages.BooleanField(3) class GoogleCloudAiplatformV1beta1CompletionStats(_messages.Message): r"""Success and error statistics of processing multiple entities (for example, DataItems or structured data rows) in batch. Fields: failedCount: Output only. The number of entities for which any error was encountered. incompleteCount: Output only. In cases when enough errors are encountered a job, pipeline, or operation may be failed as a whole. Below is the number of entities for which the processing had not been finished (either in successful or failed state). Set to -1 if the number is unknown (for example, the operation failed before the total entity number could be collected). successfulCount: Output only. The number of entities that had been processed successfully. successfulForecastPointCount: Output only. The number of the successful forecast points that are generated by the forecasting model. This is ONLY used by the forecasting batch prediction. """ failedCount = _messages.IntegerField(1) incompleteCount = _messages.IntegerField(2) successfulCount = _messages.IntegerField(3) successfulForecastPointCount = _messages.IntegerField(4) class GoogleCloudAiplatformV1beta1ComputeTokensRequest(_messages.Message): r"""Request message for ComputeTokens RPC call. Fields: contents: Optional. Input content. instances: Optional. The instances that are the input to token computing API call. Schema is identical to the prediction schema of the text model, even for the non-text models, like chat models, or Codey models. model: Optional. The name of the publisher model requested to serve the prediction. Format: projects/{project}/locations/{location}/publishers/*/models/* """ contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1, repeated=True) instances = _messages.MessageField('extra_types.JsonValue', 2, repeated=True) model = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ComputeTokensResponse(_messages.Message): r"""Response message for ComputeTokens RPC call. Fields: tokensInfo: Lists of tokens info from the input. A ComputeTokensRequest could have multiple instances with a prompt in each instance. We also need to return lists of tokens info for the request with multiple instances. """ tokensInfo = _messages.MessageField('GoogleCloudAiplatformV1beta1TokensInfo', 1, repeated=True) class GoogleCloudAiplatformV1beta1ContainerRegistryDestination(_messages.Message): r"""The Container Registry location for the container image. Fields: outputUri: Required. Container Registry URI of a container image. Only Google Container Registry and Artifact Registry are supported now. Accepted forms: * Google Container Registry path. For example: `gcr.io/projectId/imageName:tag`. * Artifact Registry path. For example: `us-central1-docker.pkg.dev/projectId/repoName/imageName:tag`. If a tag is not specified, "latest" will be used as the default tag. """ outputUri = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ContainerSpec(_messages.Message): r"""The spec of a Container. Fields: args: The arguments to be passed when starting the container. command: The command to be invoked when the container is started. It overrides the entrypoint instruction in Dockerfile when provided. env: Environment variables to be passed to the container. Maximum limit is 100. imageUri: Required. The URI of a container image in the Container Registry that is to be run on each worker replica. """ args = _messages.StringField(1, repeated=True) command = _messages.StringField(2, repeated=True) env = _messages.MessageField('GoogleCloudAiplatformV1beta1EnvVar', 3, repeated=True) imageUri = _messages.StringField(4) class GoogleCloudAiplatformV1beta1Content(_messages.Message): r"""The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. Fields: parts: Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part. role: Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'. """ parts = _messages.MessageField('GoogleCloudAiplatformV1beta1Part', 1, repeated=True) role = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ContentMap(_messages.Message): r"""Map of placeholder in metric prompt template to contents of model input. Messages: ValuesValue: Optional. Map of placeholder to contents. Fields: values: Optional. Map of placeholder to contents. """ @encoding.MapUnrecognizedFields('additionalProperties') class ValuesValue(_messages.Message): r"""Optional. Map of placeholder to contents. Messages: AdditionalProperty: An additional property for a ValuesValue object. Fields: additionalProperties: Additional properties of type ValuesValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ValuesValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ContentMapContents attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ContentMapContents', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) values = _messages.MessageField('ValuesValue', 1) class GoogleCloudAiplatformV1beta1ContentMapContents(_messages.Message): r"""Repeated Content type. Fields: contents: Optional. Repeated contents. """ contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1, repeated=True) class GoogleCloudAiplatformV1beta1ContentsExample(_messages.Message): r"""A single example of a conversation with the model. Fields: contents: Required. The content of the conversation with the model that resulted in the expected output. expectedContents: Required. The expected output for the given `contents`. To represent multi-step reasoning, this is a repeated field that contains the iterative steps of the expected output. """ contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1, repeated=True) expectedContents = _messages.MessageField('GoogleCloudAiplatformV1beta1ContentsExampleExpectedContent', 2, repeated=True) class GoogleCloudAiplatformV1beta1ContentsExampleExpectedContent(_messages.Message): r"""A single step of the expected output. Fields: content: Required. A single step's content. """ content = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1) class GoogleCloudAiplatformV1beta1Context(_messages.Message): r"""Instance of a general context. Messages: LabelsValue: The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded). MetadataValue: Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB. Fields: createTime: Output only. Timestamp when this Context was created. description: Description of the Context displayName: User provided display name of the Context. May be up to 128 Unicode characters. etag: An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded). metadata: Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB. name: Immutable. The resource name of the Context. parentContexts: Output only. A list of resource names of Contexts that are parents of this Context. A Context may have at most 10 parent_contexts. schemaTitle: The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store. schemaVersion: The version of the schema in schema_name to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store. updateTime: Output only. Timestamp when this Context was last updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your Contexts. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Context (System labels are excluded). Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class MetadataValue(_messages.Message): r"""Properties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB. Messages: AdditionalProperty: An additional property for a MetadataValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a MetadataValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) description = _messages.StringField(2) displayName = _messages.StringField(3) etag = _messages.StringField(4) labels = _messages.MessageField('LabelsValue', 5) metadata = _messages.MessageField('MetadataValue', 6) name = _messages.StringField(7) parentContexts = _messages.StringField(8, repeated=True) schemaTitle = _messages.StringField(9) schemaVersion = _messages.StringField(10) updateTime = _messages.StringField(11) class GoogleCloudAiplatformV1beta1CopyModelOperationMetadata(_messages.Message): r"""Details of ModelService.CopyModel operation. Fields: genericMetadata: The common part of the operation metadata. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CopyModelRequest(_messages.Message): r"""Request message for ModelService.CopyModel. Fields: encryptionSpec: Customer-managed encryption key options. If this is set, then the Model copy will be encrypted with the provided encryption key. modelId: Optional. Copy source_model into a new Model with this ID. The ID will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen. parentModel: Optional. Specify this field to copy source_model into this existing Model as a new version. Format: `projects/{project}/locations/{location}/models/{model}` sourceModel: Required. The resource name of the Model to copy. That Model must be in the same Project. Format: `projects/{project}/locations/{location}/models/{model}` """ encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 1) modelId = _messages.StringField(2) parentModel = _messages.StringField(3) sourceModel = _messages.StringField(4) class GoogleCloudAiplatformV1beta1CopyModelResponse(_messages.Message): r"""Response message of ModelService.CopyModel operation. Fields: model: The name of the copied Model resource. Format: `projects/{project}/locations/{location}/models/{model}` modelVersionId: Output only. The version ID of the model that is copied. """ model = _messages.StringField(1) modelVersionId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1CorpusStatus(_messages.Message): r"""RagCorpus status. Enums: StateValueValuesEnum: Output only. RagCorpus life state. Fields: errorStatus: Output only. Only when the `state` field is ERROR. state: Output only. RagCorpus life state. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. RagCorpus life state. Values: UNKNOWN: This state is not supposed to happen. INITIALIZED: RagCorpus resource entry is initialized, but hasn't done validation. ACTIVE: RagCorpus is provisioned successfully and is ready to serve. ERROR: RagCorpus is in a problematic situation. See `error_message` field for details. """ UNKNOWN = 0 INITIALIZED = 1 ACTIVE = 2 ERROR = 3 errorStatus = _messages.StringField(1) state = _messages.EnumField('StateValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1CorroborateContentRequest(_messages.Message): r"""Request message for CorroborateContent. Fields: content: Optional. Input content to corroborate, only text format is supported for now. facts: Optional. Facts used to generate the text can also be used to corroborate the text. parameters: Optional. Parameters that can be set to override default settings per request. """ content = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1) facts = _messages.MessageField('GoogleCloudAiplatformV1beta1Fact', 2, repeated=True) parameters = _messages.MessageField('GoogleCloudAiplatformV1beta1CorroborateContentRequestParameters', 3) class GoogleCloudAiplatformV1beta1CorroborateContentRequestParameters(_messages.Message): r"""Parameters that can be overrided per request. Fields: citationThreshold: Optional. Only return claims with citation score larger than the threshold. """ citationThreshold = _messages.FloatField(1) class GoogleCloudAiplatformV1beta1CorroborateContentResponse(_messages.Message): r"""Response message for CorroborateContent. Fields: claims: Claims that are extracted from the input content and facts that support the claims. corroborationScore: Confidence score of corroborating content. Value is [0,1] with 1 is the most confidence. """ claims = _messages.MessageField('GoogleCloudAiplatformV1beta1Claim', 1, repeated=True) corroborationScore = _messages.FloatField(2, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1CountTokensRequest(_messages.Message): r"""Request message for PredictionService.CountTokens. Fields: contents: Optional. Input content. generationConfig: Optional. Generation config that the model will use to generate the response. instances: Optional. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model. model: Optional. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*` systemInstruction: Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph. tools: Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. """ contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1, repeated=True) generationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerationConfig', 2) instances = _messages.MessageField('extra_types.JsonValue', 3, repeated=True) model = _messages.StringField(4) systemInstruction = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 5) tools = _messages.MessageField('GoogleCloudAiplatformV1beta1Tool', 6, repeated=True) class GoogleCloudAiplatformV1beta1CountTokensResponse(_messages.Message): r"""Response message for PredictionService.CountTokens. Fields: promptTokensDetails: Output only. List of modalities that were processed in the request input. totalBillableCharacters: The total number of billable characters counted across all instances from the request. totalTokens: The total number of tokens counted across all instances from the request. """ promptTokensDetails = _messages.MessageField('GoogleCloudAiplatformV1beta1ModalityTokenCount', 1, repeated=True) totalBillableCharacters = _messages.IntegerField(2, variant=_messages.Variant.INT32) totalTokens = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1CreateDatasetOperationMetadata(_messages.Message): r"""Runtime operation information for DatasetService.CreateDataset. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateDatasetVersionOperationMetadata(_messages.Message): r"""Runtime operation information for DatasetService.CreateDatasetVersion. Fields: genericMetadata: The common part of the operation metadata. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolOperationMetadata(_messages.Message): r"""Runtime operation information for CreateDeploymentResourcePool method. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateDeploymentResourcePoolRequest(_messages.Message): r"""Request message for CreateDeploymentResourcePool method. Fields: deploymentResourcePool: Required. The DeploymentResourcePool to create. deploymentResourcePoolId: Required. The ID to use for the DeploymentResourcePool, which will become the final component of the DeploymentResourcePool's resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`. """ deploymentResourcePool = _messages.MessageField('GoogleCloudAiplatformV1beta1DeploymentResourcePool', 1) deploymentResourcePoolId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1CreateEndpointOperationMetadata(_messages.Message): r"""Runtime operation information for EndpointService.CreateEndpoint. Enums: DeploymentStageValueValuesEnum: Output only. The deployment stage of the model. Only populated if this CreateEndpoint request deploys a model at the same time. Fields: deploymentStage: Output only. The deployment stage of the model. Only populated if this CreateEndpoint request deploys a model at the same time. genericMetadata: The operation generic information. """ class DeploymentStageValueValuesEnum(_messages.Enum): r"""Output only. The deployment stage of the model. Only populated if this CreateEndpoint request deploys a model at the same time. Values: DEPLOYMENT_STAGE_UNSPECIFIED: Default value. This value is unused. STARTING_DEPLOYMENT: The deployment is initializing and setting up the environment. PREPARING_MODEL: The deployment is preparing the model assets. CREATING_SERVING_CLUSTER: The deployment is creating the underlying serving cluster. ADDING_NODES_TO_CLUSTER: The deployment is adding nodes to the serving cluster. GETTING_CONTAINER_IMAGE: The deployment is getting the container image for the model server. STARTING_MODEL_SERVER: The deployment is starting the model server. FINISHING_UP: The deployment is performing finalization steps. DEPLOYMENT_TERMINATED: The deployment has terminated. SUCCESSFULLY_DEPLOYED: The deployment has succeeded. FAILED_TO_DEPLOY: The deployment has failed. """ DEPLOYMENT_STAGE_UNSPECIFIED = 0 STARTING_DEPLOYMENT = 1 PREPARING_MODEL = 2 CREATING_SERVING_CLUSTER = 3 ADDING_NODES_TO_CLUSTER = 4 GETTING_CONTAINER_IMAGE = 5 STARTING_MODEL_SERVER = 6 FINISHING_UP = 7 DEPLOYMENT_TERMINATED = 8 SUCCESSFULLY_DEPLOYED = 9 FAILED_TO_DEPLOY = 10 deploymentStage = _messages.EnumField('DeploymentStageValueValuesEnum', 1) genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 2) class GoogleCloudAiplatformV1beta1CreateEntityTypeOperationMetadata(_messages.Message): r"""Details of operations that perform create EntityType. Fields: genericMetadata: Operation metadata for EntityType. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateExtensionControllerOperationMetadata(_messages.Message): r"""Details of ExtensionControllerService.CreateExtensionController operation. Fields: genericMetadata: The common part of the operation metadata. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateFeatureGroupOperationMetadata(_messages.Message): r"""Details of operations that perform create FeatureGroup. Fields: genericMetadata: Operation metadata for FeatureGroup. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateFeatureOnlineStoreOperationMetadata(_messages.Message): r"""Details of operations that perform create FeatureOnlineStore. Fields: genericMetadata: Operation metadata for FeatureOnlineStore. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateFeatureOperationMetadata(_messages.Message): r"""Details of operations that perform create Feature. Fields: genericMetadata: Operation metadata for Feature. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateFeatureRequest(_messages.Message): r"""Request message for FeaturestoreService.CreateFeature. Request message for FeatureRegistryService.CreateFeature. Fields: feature: Required. The Feature to create. featureId: Required. The ID to use for the Feature, which will become the final component of the Feature's resource name. This value may be up to 128 characters, and valid characters are `[a-z0-9_]`. The first character cannot be a number. The value must be unique within an EntityType/FeatureGroup. parent: Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: `projects/{project}/ locations/{location}/featurestores/{featurestore}/entityTypes/{entity_ty pe}` Format for feature_group as parent: `projects/{project}/locations/{location}/featureGroups/{feature_group}` """ feature = _messages.MessageField('GoogleCloudAiplatformV1beta1Feature', 1) featureId = _messages.StringField(2) parent = _messages.StringField(3) class GoogleCloudAiplatformV1beta1CreateFeatureViewOperationMetadata(_messages.Message): r"""Details of operations that perform create FeatureView. Fields: genericMetadata: Operation metadata for FeatureView Create. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateFeaturestoreOperationMetadata(_messages.Message): r"""Details of operations that perform create Featurestore. Fields: genericMetadata: Operation metadata for Featurestore. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateIndexEndpointOperationMetadata(_messages.Message): r"""Runtime operation information for IndexEndpointService.CreateIndexEndpoint. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateIndexOperationMetadata(_messages.Message): r"""Runtime operation information for IndexService.CreateIndex. Fields: genericMetadata: The operation generic information. nearestNeighborSearchOperationMetadata: The operation metadata with regard to Matching Engine Index operation. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) nearestNeighborSearchOperationMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadata', 2) class GoogleCloudAiplatformV1beta1CreateMetadataStoreOperationMetadata(_messages.Message): r"""Details of operations that perform MetadataService.CreateMetadataStore. Fields: genericMetadata: Operation metadata for creating a MetadataStore. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateModelMonitorOperationMetadata(_messages.Message): r"""Runtime operation information for ModelMonitoringService.CreateModelMonitor. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateModelMonitoringJobRequest(_messages.Message): r"""Request message for ModelMonitoringService.CreateModelMonitoringJob. Fields: modelMonitoringJob: Required. The ModelMonitoringJob to create modelMonitoringJobId: Optional. The ID to use for the Model Monitoring Job, which will become the final component of the model monitoring job resource name. The maximum length is 63 characters, and valid characters are `/^[a-z]([a-z0-9-]{0,61}[a-z0-9])?$/`. parent: Required. The parent of the ModelMonitoringJob. Format: `projects/{project}/locations/{location}/modelMoniitors/{model_monitor}` """ modelMonitoringJob = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringJob', 1) modelMonitoringJobId = _messages.StringField(2) parent = _messages.StringField(3) class GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobOperationMetadata(_messages.Message): r"""Metadata information for NotebookService.CreateNotebookExecutionJob. Fields: genericMetadata: The operation generic information. progressMessage: A human-readable message that shows the intermediate progress details of NotebookRuntime. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) progressMessage = _messages.StringField(2) class GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobRequest(_messages.Message): r"""Request message for [NotebookService.CreateNotebookExecutionJob] Fields: notebookExecutionJob: Required. The NotebookExecutionJob to create. notebookExecutionJobId: Optional. User specified ID for the NotebookExecutionJob. parent: Required. The resource name of the Location to create the NotebookExecutionJob. Format: `projects/{project}/locations/{location}` """ notebookExecutionJob = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookExecutionJob', 1) notebookExecutionJobId = _messages.StringField(2) parent = _messages.StringField(3) class GoogleCloudAiplatformV1beta1CreateNotebookRuntimeTemplateOperationMetadata(_messages.Message): r"""Metadata information for NotebookService.CreateNotebookRuntimeTemplate. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreatePersistentResourceOperationMetadata(_messages.Message): r"""Details of operations that perform create PersistentResource. Fields: genericMetadata: Operation metadata for PersistentResource. progressMessage: Progress Message for Create LRO """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) progressMessage = _messages.StringField(2) class GoogleCloudAiplatformV1beta1CreatePipelineJobRequest(_messages.Message): r"""Request message for PipelineService.CreatePipelineJob. Fields: parent: Required. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}` pipelineJob: Required. The PipelineJob to create. pipelineJobId: The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are `/a-z-/`. """ parent = _messages.StringField(1) pipelineJob = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineJob', 2) pipelineJobId = _messages.StringField(3) class GoogleCloudAiplatformV1beta1CreateRegistryFeatureOperationMetadata(_messages.Message): r"""Details of operations that perform create FeatureGroup. Fields: genericMetadata: Operation metadata for Feature. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateSolverOperationMetadata(_messages.Message): r"""Runtime operation information for SolverService.CreateSolver. Fields: genericMetadata: The generic operation information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateSpecialistPoolOperationMetadata(_messages.Message): r"""Runtime operation information for SpecialistPoolService.CreateSpecialistPool. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateTensorboardOperationMetadata(_messages.Message): r"""Details of operations that perform create Tensorboard. Fields: genericMetadata: Operation metadata for Tensorboard. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1CreateTensorboardRunRequest(_messages.Message): r"""Request message for TensorboardService.CreateTensorboardRun. Fields: parent: Required. The resource name of the TensorboardExperiment to create the TensorboardRun in. Format: `projects/{project}/locations/{location}/ tensorboards/{tensorboard}/experiments/{experiment}` tensorboardRun: Required. The TensorboardRun to create. tensorboardRunId: Required. The ID to use for the Tensorboard run, which becomes the final component of the Tensorboard run's resource name. This value should be 1-128 characters, and valid characters are `/a-z-/`. """ parent = _messages.StringField(1) tensorboardRun = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardRun', 2) tensorboardRunId = _messages.StringField(3) class GoogleCloudAiplatformV1beta1CreateTensorboardTimeSeriesRequest(_messages.Message): r"""Request message for TensorboardService.CreateTensorboardTimeSeries. Fields: parent: Required. The resource name of the TensorboardRun to create the TensorboardTimeSeries in. Format: `projects/{project}/locations/{locatio n}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}` tensorboardTimeSeries: Required. The TensorboardTimeSeries to create. tensorboardTimeSeriesId: Optional. The user specified unique ID to use for the TensorboardTimeSeries, which becomes the final component of the TensorboardTimeSeries's resource name. This value should match "a-z0-9{0, 127}" """ parent = _messages.StringField(1) tensorboardTimeSeries = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardTimeSeries', 2) tensorboardTimeSeriesId = _messages.StringField(3) class GoogleCloudAiplatformV1beta1CsvDestination(_messages.Message): r"""The storage details for CSV output content. Fields: gcsDestination: Required. Google Cloud Storage location. """ gcsDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 1) class GoogleCloudAiplatformV1beta1CsvSource(_messages.Message): r"""The storage details for CSV input content. Fields: gcsSource: Required. Google Cloud Storage location. """ gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsSource', 1) class GoogleCloudAiplatformV1beta1CustomCodeExecutionResult(_messages.Message): r"""Result for custom code execution metric. Fields: score: Output only. Custom code execution score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1CustomCodeExecutionSpec(_messages.Message): r"""Specificies a metric that is populated by evaluating user-defined Python code. Fields: evaluationFunction: Required. Python function. Expected user to define the following function, e.g.: def evaluate(instance: dict[str, Any]) -> float: Please include this function signature in the code snippet. Instance is the evaluation instance, any fields populated in the instance are available to the function as instance[field_name]. Example: Example input: ``` instance= EvaluationInstance( response=EvaluationInstance.InstanceData(text="The answer is 4."), reference=EvaluationInstance.InstanceData(text="4") ) ``` Example converted input: ``` { 'response': {'text': 'The answer is 4.'}, 'reference': {'text': '4'} } ``` Example python function: ``` def evaluate(instance: dict[str, Any]) -> float: if instance'response' == instance'reference': return 1.0 return 0.0 ``` CustomCodeExecutionSpec is also supported in Batch Evaluation (EvalDataset RPC) and Tuning Evaluation. Each line in the input jsonl file will be converted to dict[str, Any] and passed to the evaluation function. """ evaluationFunction = _messages.StringField(1) class GoogleCloudAiplatformV1beta1CustomJob(_messages.Message): r"""Represents a job that runs custom workloads such as a Docker container or a Python package. A CustomJob can have multiple worker pools and each worker pool can have its own machine and input spec. A CustomJob will be cleaned up once the job enters terminal state (failed or succeeded). Enums: StateValueValuesEnum: Output only. The detailed state of the job. Messages: LabelsValue: The labels with user-defined metadata to organize CustomJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. WebAccessUrisValue: Output only. URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug- interactive-shell) (one URI for each training node). Only available if job_spec.enable_web_access is `true`. The keys are names of each node in the training job; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell. Fields: createTime: Output only. Time when the CustomJob was created. displayName: Required. The display name of the CustomJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. encryptionSpec: Customer-managed encryption key options for a CustomJob. If this is set, then all resources created by the CustomJob will be encrypted with the provided encryption key. endTime: Output only. Time when the CustomJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`. error: Output only. Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. jobSpec: Required. Job spec. labels: The labels with user-defined metadata to organize CustomJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. name: Output only. Resource name of a CustomJob. pubsubTopic: Immutable. The `Topic.name` of the Pub/Sub topic to which to publish the update when this job finishes. Must be of the format: `projects/{project}/topics/{topic}`. If not provided, such an update won't be sent, but the job state can still be polled via JobService.GetCustomJob. If a non-existing topic, or a topic to which Vertex AI is not allowed to publish to is provided, the job creation will succeed, but the update still won't be sent. The update message contains as its data a JSON in the following format: ``` { "title": "Job state update", "type": "object", "properties": { "job": { "type": "string", "description": "The resource name of the job, in \"projects/{project}/locations/{location}/custom_jobs/{custom_job}\" format, this update pertains to." }, "status": { "type": "string", "enum": ["succeeded", "failed", "cancelled", "expired"], "description": "The status in which the job finished its execution." } } } ``` satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. startTime: Output only. Time when the CustomJob for the first time entered the `JOB_STATE_RUNNING` state. state: Output only. The detailed state of the job. updateTime: Output only. Time when the CustomJob was most recently updated. webAccessUris: Output only. URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug- interactive-shell) (one URI for each training node). Only available if job_spec.enable_web_access is `true`. The keys are names of each node in the training job; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of the job. Values: JOB_STATE_UNSPECIFIED: The job state is unspecified. JOB_STATE_QUEUED: The job has been just created or resumed and processing has not yet begun. JOB_STATE_PENDING: The service is preparing to run the job. JOB_STATE_RUNNING: The job is in progress. JOB_STATE_SUCCEEDED: The job completed successfully. JOB_STATE_FAILED: The job failed. JOB_STATE_CANCELLING: The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. JOB_STATE_CANCELLED: The job has been cancelled. JOB_STATE_PAUSED: The job has been stopped, and can be resumed. JOB_STATE_EXPIRED: The job has expired. JOB_STATE_UPDATING: The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state. JOB_STATE_PARTIALLY_SUCCEEDED: The job is partially succeeded, some results may be missing due to errors. """ JOB_STATE_UNSPECIFIED = 0 JOB_STATE_QUEUED = 1 JOB_STATE_PENDING = 2 JOB_STATE_RUNNING = 3 JOB_STATE_SUCCEEDED = 4 JOB_STATE_FAILED = 5 JOB_STATE_CANCELLING = 6 JOB_STATE_CANCELLED = 7 JOB_STATE_PAUSED = 8 JOB_STATE_EXPIRED = 9 JOB_STATE_UPDATING = 10 JOB_STATE_PARTIALLY_SUCCEEDED = 11 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize CustomJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class WebAccessUrisValue(_messages.Message): r"""Output only. URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug- interactive-shell) (one URI for each training node). Only available if job_spec.enable_web_access is `true`. The keys are names of each node in the training job; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell. Messages: AdditionalProperty: An additional property for a WebAccessUrisValue object. Fields: additionalProperties: Additional properties of type WebAccessUrisValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a WebAccessUrisValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) displayName = _messages.StringField(2) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 3) endTime = _messages.StringField(4) error = _messages.MessageField('GoogleRpcStatus', 5) jobSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomJobSpec', 6) labels = _messages.MessageField('LabelsValue', 7) name = _messages.StringField(8) pubsubTopic = _messages.StringField(9) satisfiesPzi = _messages.BooleanField(10) satisfiesPzs = _messages.BooleanField(11) startTime = _messages.StringField(12) state = _messages.EnumField('StateValueValuesEnum', 13) updateTime = _messages.StringField(14) webAccessUris = _messages.MessageField('WebAccessUrisValue', 15) class GoogleCloudAiplatformV1beta1CustomJobSpec(_messages.Message): r"""Represents the spec of a CustomJob. Fields: baseOutputDirectory: The Cloud Storage location to store the output of this CustomJob or HyperparameterTuningJob. For HyperparameterTuningJob, the baseOutputDirectory of each child CustomJob backing a Trial is set to a subdirectory of name id under its parent HyperparameterTuningJob's baseOutputDirectory. The following Vertex AI environment variables will be passed to containers or python modules when this field is set: For CustomJob: * AIP_MODEL_DIR = `/model/` * AIP_CHECKPOINT_DIR = `/checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `/logs/` For CustomJob backing a Trial of HyperparameterTuningJob: * AIP_MODEL_DIR = `//model/` * AIP_CHECKPOINT_DIR = `//checkpoints/` * AIP_TENSORBOARD_LOG_DIR = `//logs/` enableDashboardAccess: Optional. Whether you want Vertex AI to enable access to the customized dashboard in training chief container. If set to `true`, you can access the dashboard at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials). enableWebAccess: Optional. Whether you want Vertex AI to enable [interactive shell access](https://cloud.google.com/vertex- ai/docs/training/monitor-debug-interactive-shell) to training containers. If set to `true`, you can access interactive shells at the URIs given by CustomJob.web_access_uris or Trial.web_access_uris (within HyperparameterTuningJob.trials). experiment: Optional. The Experiment associated with this job. Format: `pr ojects/{project}/locations/{location}/metadataStores/{metadataStores}/co ntexts/{experiment-name}` experimentRun: Optional. The Experiment Run associated with this job. Format: `projects/{project}/locations/{location}/metadataStores/{metadat aStores}/contexts/{experiment-name}-{experiment-run-name}` models: Optional. The name of the Model resources for which to generate a mapping to artifact URIs. Applicable only to some of the Google-provided custom jobs. Format: `projects/{project}/locations/{location}/models/{model}` In order to retrieve a specific version of the model, also provide the version ID or version alias. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` If no version ID or alias is specified, the "default" version will be returned. The "default" version alias is created for the first version of the model, and can be moved to other versions later on. There will be exactly one default version. network: Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Job should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex- ai/docs/general/vpc-peering). If this field is left unspecified, the job is not peered with any network. persistentResourceId: Optional. The ID of the PersistentResource in the same Project and Location which to run If this is specified, the job will be run on existing machines held by the PersistentResource instead of on-demand short-live machines. The network and CMEK configs on the job should be consistent with those on the PersistentResource, otherwise, the job will be rejected. protectedArtifactLocationId: The ID of the location to store protected artifacts. e.g. us-central1. Populate only when the location is different than CustomJob location. List of supported locations: https://cloud.google.com/vertex-ai/docs/general/locations pscInterfaceConfig: Optional. Configuration for PSC-I for CustomJob. reservedIpRanges: Optional. A list of names for the reserved ip ranges under the VPC network that can be used for this job. If set, we will deploy the job within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range']. scheduling: Scheduling options for a CustomJob. serviceAccount: Specifies the service account for workload run-as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access- control#service-agents) for the CustomJob's project is used. tensorboard: Optional. The name of a Vertex AI Tensorboard resource to which this CustomJob will upload Tensorboard logs. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}` workerPoolSpecs: Required. The spec of the worker pools including machine type and Docker image. All worker pools except the first one are optional and can be skipped by providing an empty value. """ baseOutputDirectory = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 1) enableDashboardAccess = _messages.BooleanField(2) enableWebAccess = _messages.BooleanField(3) experiment = _messages.StringField(4) experimentRun = _messages.StringField(5) models = _messages.StringField(6, repeated=True) network = _messages.StringField(7) persistentResourceId = _messages.StringField(8) protectedArtifactLocationId = _messages.StringField(9) pscInterfaceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PscInterfaceConfig', 10) reservedIpRanges = _messages.StringField(11, repeated=True) scheduling = _messages.MessageField('GoogleCloudAiplatformV1beta1Scheduling', 12) serviceAccount = _messages.StringField(13) tensorboard = _messages.StringField(14) workerPoolSpecs = _messages.MessageField('GoogleCloudAiplatformV1beta1WorkerPoolSpec', 15, repeated=True) class GoogleCloudAiplatformV1beta1CustomOutput(_messages.Message): r"""Spec for custom output. Fields: rawOutputs: Output only. List of raw output strings. """ rawOutputs = _messages.MessageField('GoogleCloudAiplatformV1beta1RawOutput', 1) class GoogleCloudAiplatformV1beta1CustomOutputFormatConfig(_messages.Message): r"""Spec for custom output format configuration. Fields: returnRawOutput: Optional. Whether to return raw output. """ returnRawOutput = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1DataItem(_messages.Message): r"""A piece of data in a Dataset. Could be an image, a video, a document or plain text. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize your DataItems. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one DataItem(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: createTime: Output only. Timestamp when this DataItem was created. etag: Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: Optional. The labels with user-defined metadata to organize your DataItems. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one DataItem(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. name: Output only. The resource name of the DataItem. payload: Required. The data that the DataItem represents (for example, an image or a text snippet). The schema of the payload is stored in the parent Dataset's metadata schema's dataItemSchemaUri field. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. updateTime: Output only. Timestamp when this DataItem was last updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize your DataItems. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one DataItem(System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) etag = _messages.StringField(2) labels = _messages.MessageField('LabelsValue', 3) name = _messages.StringField(4) payload = _messages.MessageField('extra_types.JsonValue', 5) satisfiesPzi = _messages.BooleanField(6) satisfiesPzs = _messages.BooleanField(7) updateTime = _messages.StringField(8) class GoogleCloudAiplatformV1beta1DataItemView(_messages.Message): r"""A container for a single DataItem and Annotations on it. Fields: annotations: The Annotations on the DataItem. If too many Annotations should be returned for the DataItem, this field will be truncated per annotations_limit in request. If it was, then the has_truncated_annotations will be set to true. dataItem: The DataItem. hasTruncatedAnnotations: True if and only if the Annotations field has been truncated. It happens if more Annotations for this DataItem met the request's annotation_filter than are allowed to be returned by annotations_limit. Note that if Annotations field is not being returned due to field mask, then this field will not be set to true no matter how many Annotations are there. """ annotations = _messages.MessageField('GoogleCloudAiplatformV1beta1Annotation', 1, repeated=True) dataItem = _messages.MessageField('GoogleCloudAiplatformV1beta1DataItem', 2) hasTruncatedAnnotations = _messages.BooleanField(3) class GoogleCloudAiplatformV1beta1DataLabelingJob(_messages.Message): r"""DataLabelingJob is used to trigger a human labeling job on unlabeled data from the following Dataset: Enums: StateValueValuesEnum: Output only. The detailed state of the job. Messages: AnnotationLabelsValue: Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. LabelsValue: The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title. Fields: activeLearningConfig: Parameters that configure the active learning pipeline. Active learning will label the data incrementally via several iterations. For every iteration, it will select a batch of data based on the sampling strategy. annotationLabels: Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. createTime: Output only. Timestamp when this DataLabelingJob was created. currentSpend: Output only. Estimated cost(in US dollars) that the DataLabelingJob has incurred to date. datasets: Required. Dataset resource names. Right now we only support labeling from a single Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}` displayName: Required. The user-defined name of the DataLabelingJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a DataLabelingJob. encryptionSpec: Customer-managed encryption key spec for a DataLabelingJob. If set, this DataLabelingJob will be secured by this key. Note: Annotations created in the DataLabelingJob are associated with the EncryptionSpec of the Dataset they are exported to. error: Output only. DataLabelingJob errors. It is only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. inputs: Required. Input config parameters for the DataLabelingJob. inputsSchemaUri: Required. Points to a YAML file stored on Google Cloud Storage describing the config for a specific type of DataLabelingJob. The schema files that can be used here are found in the https://storage.googleapis.com/google-cloud-aiplatform bucket in the /schema/datalabelingjob/inputs/ folder. instructionUri: Required. The Google Cloud Storage location of the instruction pdf. This pdf is shared with labelers, and provides detailed description on how to label DataItems in Datasets. labelerCount: Required. Number of labelers to work on each DataItem. labelingProgress: Output only. Current labeling job progress percentage scaled in interval [0, 100], indicating the percentage of DataItems that has been finished. labels: The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title. name: Output only. Resource name of the DataLabelingJob. specialistPools: The SpecialistPools' resource names associated with this job. state: Output only. The detailed state of the job. updateTime: Output only. Timestamp when this DataLabelingJob was updated most recently. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of the job. Values: JOB_STATE_UNSPECIFIED: The job state is unspecified. JOB_STATE_QUEUED: The job has been just created or resumed and processing has not yet begun. JOB_STATE_PENDING: The service is preparing to run the job. JOB_STATE_RUNNING: The job is in progress. JOB_STATE_SUCCEEDED: The job completed successfully. JOB_STATE_FAILED: The job failed. JOB_STATE_CANCELLING: The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. JOB_STATE_CANCELLED: The job has been cancelled. JOB_STATE_PAUSED: The job has been stopped, and can be resumed. JOB_STATE_EXPIRED: The job has expired. JOB_STATE_UPDATING: The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state. JOB_STATE_PARTIALLY_SUCCEEDED: The job is partially succeeded, some results may be missing due to errors. """ JOB_STATE_UNSPECIFIED = 0 JOB_STATE_QUEUED = 1 JOB_STATE_PENDING = 2 JOB_STATE_RUNNING = 3 JOB_STATE_SUCCEEDED = 4 JOB_STATE_FAILED = 5 JOB_STATE_CANCELLING = 6 JOB_STATE_CANCELLED = 7 JOB_STATE_PAUSED = 8 JOB_STATE_EXPIRED = 9 JOB_STATE_UPDATING = 10 JOB_STATE_PARTIALLY_SUCCEEDED = 11 @encoding.MapUnrecognizedFields('additionalProperties') class AnnotationLabelsValue(_messages.Message): r"""Labels to assign to annotations generated by this DataLabelingJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a AnnotationLabelsValue object. Fields: additionalProperties: Additional properties of type AnnotationLabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a AnnotationLabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your DataLabelingJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each DataLabelingJob: * "aiplatform.googleapis.com/schema": output only, its value is the inputs_schema's title. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) activeLearningConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ActiveLearningConfig', 1) annotationLabels = _messages.MessageField('AnnotationLabelsValue', 2) createTime = _messages.StringField(3) currentSpend = _messages.MessageField('GoogleTypeMoney', 4) datasets = _messages.StringField(5, repeated=True) displayName = _messages.StringField(6) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 7) error = _messages.MessageField('GoogleRpcStatus', 8) inputs = _messages.MessageField('extra_types.JsonValue', 9) inputsSchemaUri = _messages.StringField(10) instructionUri = _messages.StringField(11) labelerCount = _messages.IntegerField(12, variant=_messages.Variant.INT32) labelingProgress = _messages.IntegerField(13, variant=_messages.Variant.INT32) labels = _messages.MessageField('LabelsValue', 14) name = _messages.StringField(15) specialistPools = _messages.StringField(16, repeated=True) state = _messages.EnumField('StateValueValuesEnum', 17) updateTime = _messages.StringField(18) class GoogleCloudAiplatformV1beta1Dataset(_messages.Message): r"""A collection of DataItems and Annotations on them. Messages: LabelsValue: The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title. Fields: createTime: Output only. Timestamp when this Dataset was created. dataItemCount: Output only. The number of DataItems in this Dataset. Only apply for non-structured Dataset. description: The description of the Dataset. displayName: Required. The user-defined name of the Dataset. The name can be up to 128 characters long and can consist of any UTF-8 characters. encryptionSpec: Customer-managed encryption key spec for a Dataset. If set, this Dataset and all sub-resources of this Dataset will be secured by this key. etag: Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title. metadata: Required. Additional information about the Dataset. metadataArtifact: Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metada taStores/{metadata_store}/artifacts/{artifact}`. metadataSchemaUri: Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud- aiplatform/schema/dataset/metadata/. modelReference: Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets. name: Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}` satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. savedQueries: All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec. updateTime: Output only. Timestamp when this Dataset was last updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your Datasets. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for each Dataset: * "aiplatform.googleapis.com/dataset_metadata_schema": output only, its value is the metadata_schema's title. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) dataItemCount = _messages.IntegerField(2) description = _messages.StringField(3) displayName = _messages.StringField(4) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 5) etag = _messages.StringField(6) labels = _messages.MessageField('LabelsValue', 7) metadata = _messages.MessageField('extra_types.JsonValue', 8) metadataArtifact = _messages.StringField(9) metadataSchemaUri = _messages.StringField(10) modelReference = _messages.StringField(11) name = _messages.StringField(12) satisfiesPzi = _messages.BooleanField(13) satisfiesPzs = _messages.BooleanField(14) savedQueries = _messages.MessageField('GoogleCloudAiplatformV1beta1SavedQuery', 15, repeated=True) updateTime = _messages.StringField(16) class GoogleCloudAiplatformV1beta1DatasetDistribution(_messages.Message): r"""Distribution computed over a tuning dataset. Fields: buckets: Output only. Defines the histogram bucket. max: Output only. The maximum of the population values. mean: Output only. The arithmetic mean of the values in the population. median: Output only. The median of the values in the population. min: Output only. The minimum of the population values. p5: Output only. The 5th percentile of the values in the population. p95: Output only. The 95th percentile of the values in the population. sum: Output only. Sum of a given population of values. """ buckets = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetDistributionDistributionBucket', 1, repeated=True) max = _messages.FloatField(2) mean = _messages.FloatField(3) median = _messages.FloatField(4) min = _messages.FloatField(5) p5 = _messages.FloatField(6) p95 = _messages.FloatField(7) sum = _messages.FloatField(8) class GoogleCloudAiplatformV1beta1DatasetDistributionDistributionBucket(_messages.Message): r"""Dataset bucket used to create a histogram for the distribution given a population of values. Fields: count: Output only. Number of values in the bucket. left: Output only. Left bound of the bucket. right: Output only. Right bound of the bucket. """ count = _messages.IntegerField(1) left = _messages.FloatField(2) right = _messages.FloatField(3) class GoogleCloudAiplatformV1beta1DatasetStats(_messages.Message): r"""Statistics computed over a tuning dataset. Fields: droppedExampleIndices: Output only. A partial sample of the indices (starting from 1) of the dropped examples. droppedExampleReasons: Output only. For each index in `dropped_example_indices`, the user-facing reason why the example was dropped. totalBillableCharacterCount: Output only. Number of billable characters in the tuning dataset. totalTuningCharacterCount: Output only. Number of tuning characters in the tuning dataset. tuningDatasetExampleCount: Output only. Number of examples in the tuning dataset. tuningStepCount: Output only. Number of tuning steps for this Tuning Job. userDatasetExamples: Output only. Sample user messages in the training dataset uri. userInputTokenDistribution: Output only. Dataset distributions for the user input tokens. userMessagePerExampleDistribution: Output only. Dataset distributions for the messages per example. userOutputTokenDistribution: Output only. Dataset distributions for the user output tokens. """ droppedExampleIndices = _messages.IntegerField(1, repeated=True) droppedExampleReasons = _messages.StringField(2, repeated=True) totalBillableCharacterCount = _messages.IntegerField(3) totalTuningCharacterCount = _messages.IntegerField(4) tuningDatasetExampleCount = _messages.IntegerField(5) tuningStepCount = _messages.IntegerField(6) userDatasetExamples = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 7, repeated=True) userInputTokenDistribution = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetDistribution', 8) userMessagePerExampleDistribution = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetDistribution', 9) userOutputTokenDistribution = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetDistribution', 10) class GoogleCloudAiplatformV1beta1DatasetVersion(_messages.Message): r"""Describes the dataset version. Fields: bigQueryDatasetName: Output only. Name of the associated BigQuery dataset. createTime: Output only. Timestamp when this DatasetVersion was created. displayName: The user-defined name of the DatasetVersion. The name can be up to 128 characters long and can consist of any UTF-8 characters. etag: Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. metadata: Required. Output only. Additional information about the DatasetVersion. modelReference: Output only. Reference to the public base model last used by the dataset version. Only set for prompt dataset versions. name: Output only. Identifier. The resource name of the DatasetVersion. Format: `projects/{project}/locations/{location}/datasets/{dataset}/data setVersions/{dataset_version}` satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. updateTime: Output only. Timestamp when this DatasetVersion was last updated. """ bigQueryDatasetName = _messages.StringField(1) createTime = _messages.StringField(2) displayName = _messages.StringField(3) etag = _messages.StringField(4) metadata = _messages.MessageField('extra_types.JsonValue', 5) modelReference = _messages.StringField(6) name = _messages.StringField(7) satisfiesPzi = _messages.BooleanField(8) satisfiesPzs = _messages.BooleanField(9) updateTime = _messages.StringField(10) class GoogleCloudAiplatformV1beta1DedicatedResources(_messages.Message): r"""A description of resources that are dedicated to a DeployedModel or DeployedIndex, and that need a higher degree of manual configuration. Fields: autoscalingMetricSpecs: Immutable. The metric specifications that overrides a resource utilization metric (CPU utilization, accelerator's duty cycle, and so on) target value (default to 60 if not set). At most one entry is allowed per metric. If machine_spec.accelerator_count is above 0, the autoscaling will be based on both CPU utilization and accelerator's duty cycle metrics and scale up when either metrics exceeds its target value while scale down if both metrics are under their target value. The default target value is 60 for both metrics. If machine_spec.accelerator_count is 0, the autoscaling will be based on CPU utilization metric only with default target value 60 if not explicitly set. For example, in the case of Online Prediction, if you want to override target CPU utilization to 80, you should set autoscaling_metric_specs.metric_name to `aiplatform.googleapis.com/prediction/online/cpu/utilization` and autoscaling_metric_specs.target to `80`. deploymentResourcePoolId: Optional. Immutable. Specifies the deployment resource pool to use for this deployment. This must refer to a deployment resource pool with a pool type of `RESOURCE_POOL_TYPE_RESERVED_CAPACITY`. If not specified, an internal deployment resource pool will be used. Format: `projects/{project}/locat ions/{location}/deploymentResourcePools/{deployment_resource_pool}` flexStart: Optional. Immutable. If set, use DWS resource to schedule the deployment workload. reference: (https://cloud.google.com/blog/products/compute/introducing-dynamic- workload-scheduler) initialReplicaCount: Immutable. Number of initial replicas being deployed on when scaling the workload up from zero or when creating the workload in case min_replica_count = 0. When min_replica_count > 0 (meaning that the scale-to-zero feature is not enabled), initial_replica_count should not be set. When min_replica_count = 0 (meaning that the scale-to-zero feature is enabled), initial_replica_count should be larger than zero, but no greater than max_replica_count. machineSpec: Required. Immutable. The specification of a single machine being used. maxReplicaCount: Immutable. The maximum number of replicas that may be deployed on when the traffic against it increases. If the requested value is too large, the deployment will error, but if deployment succeeds then the ability to scale to that many replicas is guaranteed (barring service outages). If traffic increases beyond what its replicas at maximum may handle, a portion of the traffic will be dropped. If this value is not provided, will use min_replica_count as the default value. The value of this field impacts the charge against Vertex CPU and GPU quotas. Specifically, you will be charged for (max_replica_count * number of cores in the selected machine type) and (max_replica_count * number of GPUs per replica in the selected machine type). minReplicaCount: Required. Immutable. The minimum number of machine replicas that will be always deployed on. This value must be greater than or equal to 1. If traffic increases, it may dynamically be deployed onto more replicas, and as traffic decreases, some of these extra replicas may be freed. requiredReplicaCount: Optional. Number of required available replicas for the deployment to succeed. This field is only needed when partial deployment/mutation is desired. If set, the deploy/mutate operation will succeed once available_replica_count reaches required_replica_count, and the rest of the replicas will be retried. If not set, the default required_replica_count will be min_replica_count. scaleToZeroSpec: Optional. Specification for scale-to-zero feature. spot: Optional. If true, schedule the deployment workload on [spot VMs](https://cloud.google.com/kubernetes-engine/docs/concepts/spot-vms). """ autoscalingMetricSpecs = _messages.MessageField('GoogleCloudAiplatformV1beta1AutoscalingMetricSpec', 1, repeated=True) deploymentResourcePoolId = _messages.StringField(2) flexStart = _messages.MessageField('GoogleCloudAiplatformV1beta1FlexStart', 3) initialReplicaCount = _messages.IntegerField(4, variant=_messages.Variant.INT32) machineSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1MachineSpec', 5) maxReplicaCount = _messages.IntegerField(6, variant=_messages.Variant.INT32) minReplicaCount = _messages.IntegerField(7, variant=_messages.Variant.INT32) requiredReplicaCount = _messages.IntegerField(8, variant=_messages.Variant.INT32) scaleToZeroSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1DedicatedResourcesScaleToZeroSpec', 9) spot = _messages.BooleanField(10) class GoogleCloudAiplatformV1beta1DedicatedResourcesScaleToZeroSpec(_messages.Message): r"""Specification for scale-to-zero feature. Fields: idleScaledownPeriod: Optional. Duration of no traffic before scaling to zero. [MinValue=300] (5 minutes) [MaxValue=28800] (8 hours) minScaleupPeriod: Optional. Minimum duration that a deployment will be scaled up before traffic is evaluated for potential scale-down. [MinValue=300] (5 minutes) [MaxValue=28800] (8 hours) """ idleScaledownPeriod = _messages.StringField(1) minScaleupPeriod = _messages.StringField(2) class GoogleCloudAiplatformV1beta1DeleteFeatureValuesOperationMetadata(_messages.Message): r"""Details of operations that delete Feature values. Fields: genericMetadata: Operation metadata for Featurestore delete Features values. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequest(_messages.Message): r"""Request message for FeaturestoreService.DeleteFeatureValues. Fields: selectEntity: Select feature values to be deleted by specifying entities. selectTimeRangeAndFeature: Select feature values to be deleted by specifying time range and features. """ selectEntity = _messages.MessageField('GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectEntity', 1) selectTimeRangeAndFeature = _messages.MessageField('GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectTimeRangeAndFeature', 2) class GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectEntity(_messages.Message): r"""Message to select entity. If an entity id is selected, all the feature values corresponding to the entity id will be deleted, including the entityId. Fields: entityIdSelector: Required. Selectors choosing feature values of which entity id to be deleted from the EntityType. """ entityIdSelector = _messages.MessageField('GoogleCloudAiplatformV1beta1EntityIdSelector', 1) class GoogleCloudAiplatformV1beta1DeleteFeatureValuesRequestSelectTimeRangeAndFeature(_messages.Message): r"""Message to select time range and feature. Values of the selected feature generated within an inclusive time range will be deleted. Using this option permanently deletes the feature values from the specified feature IDs within the specified time range. This might include data from the online storage. If you want to retain any deleted historical data in the online storage, you must re-ingest it. Fields: featureSelector: Required. Selectors choosing which feature values to be deleted from the EntityType. skipOnlineStorageDelete: If set, data will not be deleted from online storage. When time range is older than the data in online storage, setting this to be true will make the deletion have no impact on online serving. timeRange: Required. Select feature generated within a half-inclusive time range. The time range is lower inclusive and upper exclusive. """ featureSelector = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureSelector', 1) skipOnlineStorageDelete = _messages.BooleanField(2) timeRange = _messages.MessageField('GoogleTypeInterval', 3) class GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponse(_messages.Message): r"""Response message for FeaturestoreService.DeleteFeatureValues. Fields: selectEntity: Response for request specifying the entities to delete selectTimeRangeAndFeature: Response for request specifying time range and feature """ selectEntity = _messages.MessageField('GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectEntity', 1) selectTimeRangeAndFeature = _messages.MessageField('GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectTimeRangeAndFeature', 2) class GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectEntity(_messages.Message): r"""Response message if the request uses the SelectEntity option. Fields: offlineStorageDeletedEntityRowCount: The count of deleted entity rows in the offline storage. Each row corresponds to the combination of an entity ID and a timestamp. One entity ID can have multiple rows in the offline storage. onlineStorageDeletedEntityCount: The count of deleted entities in the online storage. Each entity ID corresponds to one entity. """ offlineStorageDeletedEntityRowCount = _messages.IntegerField(1) onlineStorageDeletedEntityCount = _messages.IntegerField(2) class GoogleCloudAiplatformV1beta1DeleteFeatureValuesResponseSelectTimeRangeAndFeature(_messages.Message): r"""Response message if the request uses the SelectTimeRangeAndFeature option. Fields: impactedFeatureCount: The count of the features or columns impacted. This is the same as the feature count in the request. offlineStorageModifiedEntityRowCount: The count of modified entity rows in the offline storage. Each row corresponds to the combination of an entity ID and a timestamp. One entity ID can have multiple rows in the offline storage. Within each row, only the features specified in the request are deleted. onlineStorageModifiedEntityCount: The count of modified entities in the online storage. Each entity ID corresponds to one entity. Within each entity, only the features specified in the request are deleted. """ impactedFeatureCount = _messages.IntegerField(1) offlineStorageModifiedEntityRowCount = _messages.IntegerField(2) onlineStorageModifiedEntityCount = _messages.IntegerField(3) class GoogleCloudAiplatformV1beta1DeleteMetadataStoreOperationMetadata(_messages.Message): r"""Details of operations that perform MetadataService.DeleteMetadataStore. Fields: genericMetadata: Operation metadata for deleting a MetadataStore. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1DeleteOperationMetadata(_messages.Message): r"""Details of operations that perform deletes of any entities. Fields: genericMetadata: The common part of the operation metadata. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1DeployIndexOperationMetadata(_messages.Message): r"""Runtime operation information for IndexEndpointService.DeployIndex. Fields: deployedIndexId: The unique index id specified by user genericMetadata: The operation generic information. """ deployedIndexId = _messages.StringField(1) genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 2) class GoogleCloudAiplatformV1beta1DeployIndexRequest(_messages.Message): r"""Request message for IndexEndpointService.DeployIndex. Fields: deployedIndex: Required. The DeployedIndex to be created within the IndexEndpoint. """ deployedIndex = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedIndex', 1) class GoogleCloudAiplatformV1beta1DeployIndexResponse(_messages.Message): r"""Response message for IndexEndpointService.DeployIndex. Fields: deployedIndex: The DeployedIndex that had been deployed in the IndexEndpoint. """ deployedIndex = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedIndex', 1) class GoogleCloudAiplatformV1beta1DeployModelOperationMetadata(_messages.Message): r"""Runtime operation information for EndpointService.DeployModel. Enums: DeploymentStageValueValuesEnum: Output only. The deployment stage of the model. Fields: deploymentStage: Output only. The deployment stage of the model. genericMetadata: The operation generic information. """ class DeploymentStageValueValuesEnum(_messages.Enum): r"""Output only. The deployment stage of the model. Values: DEPLOYMENT_STAGE_UNSPECIFIED: Default value. This value is unused. STARTING_DEPLOYMENT: The deployment is initializing and setting up the environment. PREPARING_MODEL: The deployment is preparing the model assets. CREATING_SERVING_CLUSTER: The deployment is creating the underlying serving cluster. ADDING_NODES_TO_CLUSTER: The deployment is adding nodes to the serving cluster. GETTING_CONTAINER_IMAGE: The deployment is getting the container image for the model server. STARTING_MODEL_SERVER: The deployment is starting the model server. FINISHING_UP: The deployment is performing finalization steps. DEPLOYMENT_TERMINATED: The deployment has terminated. SUCCESSFULLY_DEPLOYED: The deployment has succeeded. FAILED_TO_DEPLOY: The deployment has failed. """ DEPLOYMENT_STAGE_UNSPECIFIED = 0 STARTING_DEPLOYMENT = 1 PREPARING_MODEL = 2 CREATING_SERVING_CLUSTER = 3 ADDING_NODES_TO_CLUSTER = 4 GETTING_CONTAINER_IMAGE = 5 STARTING_MODEL_SERVER = 6 FINISHING_UP = 7 DEPLOYMENT_TERMINATED = 8 SUCCESSFULLY_DEPLOYED = 9 FAILED_TO_DEPLOY = 10 deploymentStage = _messages.EnumField('DeploymentStageValueValuesEnum', 1) genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 2) class GoogleCloudAiplatformV1beta1DeployModelRequest(_messages.Message): r"""Request message for EndpointService.DeployModel. Messages: TrafficSplitValue: A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If this field is non-empty, then the Endpoint's traffic_split will be overwritten with it. To refer to the ID of the just being deployed Model, a "0" should be used, and the actual ID of the new DeployedModel will be filled in its place by this method. The traffic percentage values must add up to 100. If this field is empty, then the Endpoint's traffic_split is not updated. Fields: deployedModel: Required. The DeployedModel to be created within the Endpoint. Note that Endpoint.traffic_split must be updated for the DeployedModel to start receiving traffic, either as part of this call, or via EndpointService.UpdateEndpoint. trafficSplit: A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If this field is non-empty, then the Endpoint's traffic_split will be overwritten with it. To refer to the ID of the just being deployed Model, a "0" should be used, and the actual ID of the new DeployedModel will be filled in its place by this method. The traffic percentage values must add up to 100. If this field is empty, then the Endpoint's traffic_split is not updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class TrafficSplitValue(_messages.Message): r"""A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If this field is non-empty, then the Endpoint's traffic_split will be overwritten with it. To refer to the ID of the just being deployed Model, a "0" should be used, and the actual ID of the new DeployedModel will be filled in its place by this method. The traffic percentage values must add up to 100. If this field is empty, then the Endpoint's traffic_split is not updated. Messages: AdditionalProperty: An additional property for a TrafficSplitValue object. Fields: additionalProperties: Additional properties of type TrafficSplitValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a TrafficSplitValue object. Fields: key: Name of the additional property. value: A integer attribute. """ key = _messages.StringField(1) value = _messages.IntegerField(2, variant=_messages.Variant.INT32) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) deployedModel = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedModel', 1) trafficSplit = _messages.MessageField('TrafficSplitValue', 2) class GoogleCloudAiplatformV1beta1DeployModelResponse(_messages.Message): r"""Response message for EndpointService.DeployModel. Fields: deployedModel: The DeployedModel that had been deployed in the Endpoint. """ deployedModel = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedModel', 1) class GoogleCloudAiplatformV1beta1DeployPublisherModelRequest(_messages.Message): r"""Request message for ModelGardenService.DeployPublisherModel. Fields: acceptEula: Optional. Whether the user accepts the End User License Agreement (EULA) for the model. dedicatedResources: Optional. The dedicated resources to use for the endpoint. If not set, the default resources will be used. endpointDisplayName: Optional. The user-specified display name of the endpoint. If not set, a default name will be used. huggingFaceAccessToken: Optional. The Hugging Face read access token used to access the model artifacts of gated models. model: Required. The model to deploy. Format: 1. `publishers/{publisher}/models/{publisher_model}@{version_id}`, or `publishers/hf-{hugging-face-author}/models/{hugging-face-model- name}@001`. 2. Hugging Face model ID like `google/gemma-2-2b-it`. 3. Custom model Google Cloud Storage URI like `gs://bucket`. 4. Custom model zip file like `https://example.com/a.zip`. modelDisplayName: Optional. The user-specified display name of the uploaded model. If not set, a default name will be used. """ acceptEula = _messages.BooleanField(1) dedicatedResources = _messages.MessageField('GoogleCloudAiplatformV1beta1DedicatedResources', 2) endpointDisplayName = _messages.StringField(3) huggingFaceAccessToken = _messages.StringField(4) model = _messages.StringField(5) modelDisplayName = _messages.StringField(6) class GoogleCloudAiplatformV1beta1DeployRequest(_messages.Message): r"""Request message for ModelGardenService.Deploy. Fields: customModel: The custom model to deploy from a Google Cloud Storage URI. deployConfig: Optional. The deploy config to use for the deployment. If not specified, the default deploy config will be used. endpointConfig: Optional. The endpoint config to use for the deployment. If not specified, the default endpoint config will be used. huggingFaceModelId: The Hugging Face model to deploy. Format: Hugging Face model ID like `google/gemma-2-2b-it`. modelConfig: Optional. The model config to use for the deployment. If not specified, the default model config will be used. publisherModelName: The Model Garden model to deploy. Format: `publishers/{publisher}/models/{publisher_model}@{version_id}`, or `publishers/hf-{hugging-face-author}/models/{hugging-face-model- name}@001`. """ customModel = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployRequestCustomModel', 1) deployConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployRequestDeployConfig', 2) endpointConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployRequestEndpointConfig', 3) huggingFaceModelId = _messages.StringField(4) modelConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployRequestModelConfig', 5) publisherModelName = _messages.StringField(6) class GoogleCloudAiplatformV1beta1DeployRequestCustomModel(_messages.Message): r"""The custom model to deploy from model weights in a Google Cloud Storage URI or Model Registry model. Fields: gcsUri: Immutable. The Google Cloud Storage URI of the custom model, storing weights and config files (which can be used to infer the base model). modelId: Optional. Deprecated. Use ModelConfig.model_user_id instead. """ gcsUri = _messages.StringField(1) modelId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1DeployRequestDeployConfig(_messages.Message): r"""The deploy config to use for the deployment. Messages: SystemLabelsValue: Optional. System labels for Model Garden deployments. These labels are managed by Google and for tracking purposes only. Fields: dedicatedResources: Optional. The dedicated resources to use for the endpoint. If not set, the default resources will be used. fastTryoutEnabled: Optional. If true, enable the QMT fast tryout feature for this model if possible. systemLabels: Optional. System labels for Model Garden deployments. These labels are managed by Google and for tracking purposes only. """ @encoding.MapUnrecognizedFields('additionalProperties') class SystemLabelsValue(_messages.Message): r"""Optional. System labels for Model Garden deployments. These labels are managed by Google and for tracking purposes only. Messages: AdditionalProperty: An additional property for a SystemLabelsValue object. Fields: additionalProperties: Additional properties of type SystemLabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a SystemLabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) dedicatedResources = _messages.MessageField('GoogleCloudAiplatformV1beta1DedicatedResources', 1) fastTryoutEnabled = _messages.BooleanField(2) systemLabels = _messages.MessageField('SystemLabelsValue', 3) class GoogleCloudAiplatformV1beta1DeployRequestEndpointConfig(_messages.Message): r"""The endpoint config to use for the deployment. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: dedicatedEndpointDisabled: Optional. By default, if dedicated endpoint is enabled and private service connect config is not set, the endpoint will be exposed through a dedicated DNS [Endpoint.dedicated_endpoint_dns]. If private service connect config is set, the endpoint will be exposed through private service connect. Your request to the dedicated DNS will be isolated from other users' traffic and will have better performance and reliability. Note: Once you enabled dedicated endpoint, you won't be able to send request to the shared DNS {region}-aiplatform.googleapis.com. The limitations will be removed soon. If this field is set to true, the dedicated endpoint will be disabled and the deployed model will be exposed through the shared DNS {region}-aiplatform.googleapis.com. dedicatedEndpointEnabled: Optional. Deprecated. Use dedicated_endpoint_disabled instead. If true, the endpoint will be exposed through a dedicated DNS [Endpoint.dedicated_endpoint_dns]. Your request to the dedicated DNS will be isolated from other users' traffic and will have better performance and reliability. Note: Once you enabled dedicated endpoint, you won't be able to send request to the shared DNS {region}-aiplatform.googleapis.com. The limitations will be removed soon. endpointDisplayName: Optional. The user-specified display name of the endpoint. If not set, a default name will be used. endpointUserId: Optional. Immutable. The ID to use for endpoint, which will become the final component of the endpoint resource name. If not provided, Vertex AI will generate a value for this ID. If the first character is a letter, this value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The last character must be a letter or number. If the first character is a number, this value may be up to 9 characters, and valid characters are `[0-9]` with no leading zeros. When using HTTP/JSON, this field is populated based on a query string argument, such as `?endpoint_id=12345`. This is the fallback for fields that are not included in either the URI or the body. labels: Optional. The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. privateServiceConnectConfig: Optional. Configuration for private service connect. If set, the endpoint will be exposed through private service connect. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) dedicatedEndpointDisabled = _messages.BooleanField(1) dedicatedEndpointEnabled = _messages.BooleanField(2) endpointDisplayName = _messages.StringField(3) endpointUserId = _messages.StringField(4) labels = _messages.MessageField('LabelsValue', 5) privateServiceConnectConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig', 6) class GoogleCloudAiplatformV1beta1DeployRequestModelConfig(_messages.Message): r"""The model config to use for the deployment. Fields: acceptEula: Optional. Whether the user accepts the End User License Agreement (EULA) for the model. containerSpec: Optional. The specification of the container that is to be used when deploying. If not set, the default container spec will be used. huggingFaceAccessToken: Optional. The Hugging Face read access token used to access the model artifacts of gated models. huggingFaceCacheEnabled: Optional. If true, the model will deploy with a cached version instead of directly downloading the model artifacts from Hugging Face. This is suitable for VPC-SC users with limited internet access. modelDisplayName: Optional. The user-specified display name of the uploaded model. If not set, a default name will be used. modelUserId: Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. When not provided, Vertex AI will generate a value for this ID. When Model Registry model is provided, this field will be ignored. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen. """ acceptEula = _messages.BooleanField(1) containerSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelContainerSpec', 2) huggingFaceAccessToken = _messages.StringField(3) huggingFaceCacheEnabled = _messages.BooleanField(4) modelDisplayName = _messages.StringField(5) modelUserId = _messages.StringField(6) class GoogleCloudAiplatformV1beta1DeploySolverOperationMetadata(_messages.Message): r"""Runtime operation information for SolverService.DeploySolver. Fields: genericMetadata: The generic operation information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1DeployedIndex(_messages.Message): r"""A deployment of an Index. IndexEndpoints contain one or more DeployedIndexes. Enums: DeploymentTierValueValuesEnum: Optional. The deployment tier that the index is deployed to. DEPLOYMENT_TIER_UNSPECIFIED will use a system- chosen default tier. Fields: automaticResources: Optional. A description of resources that the DeployedIndex uses, which to large degree are decided by Vertex AI, and optionally allows only a modest additional configuration. If min_replica_count is not set, the default value is 2 (we don't provide SLA when min_replica_count=1). If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000. createTime: Output only. Timestamp when the DeployedIndex was created. dedicatedResources: Optional. A description of resources that are dedicated to the DeployedIndex, and that need a higher degree of manual configuration. The field min_replica_count must be set to a value strictly greater than 0, or else validation will fail. We don't provide SLA when min_replica_count=1. If max_replica_count is not set, the default value is min_replica_count. The max allowed replica count is 1000. Available machine types for SMALL shard: e2-standard-2 and all machine types available for MEDIUM and LARGE shard. Available machine types for MEDIUM shard: e2-standard-16 and all machine types available for LARGE shard. Available machine types for LARGE shard: e2-highmem-16, n2d-standard-32. n1-standard-16 and n1-standard-32 are still available, but we recommend e2-standard-16 and e2-highmem-16 for cost efficiency. deployedIndexAuthConfig: Optional. If set, the authentication is enabled for the private endpoint. deploymentGroup: Optional. The deployment group can be no longer than 64 characters (eg: 'test', 'prod'). If not set, we will use the 'default' deployment group. Creating `deployment_groups` with `reserved_ip_ranges` is a recommended practice when the peered network has multiple peering ranges. This creates your deployments from predictable IP spaces for easier traffic administration. Also, one deployment_group (except 'default') can only be used with the same reserved_ip_ranges which means if the deployment_group has been used with reserved_ip_ranges: [a, b, c], using it with [a, b] or [d, e] is disallowed. Note: we only support up to 5 deployment groups(not including 'default'). deploymentTier: Optional. The deployment tier that the index is deployed to. DEPLOYMENT_TIER_UNSPECIFIED will use a system-chosen default tier. displayName: The display name of the DeployedIndex. If not provided upon creation, the Index's display_name is used. enableAccessLogging: Optional. If true, private endpoint's access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each MatchRequest. Note that logs may incur a cost, especially if the deployed index receives a high queries per second rate (QPS). Estimate your costs before enabling this option. enableDatapointUpsertLogging: Optional. If true, logs to Cloud Logging errors relating to datapoint upserts. Under normal operation conditions, these log entries should be very rare. However, if incompatible datapoint updates are being uploaded to an index, a high volume of log entries may be generated in a short period of time. Note that logs may incur a cost, especially if the deployed index receives a high volume of datapoint upserts. Estimate your costs before enabling this option. id: Required. The user specified ID of the DeployedIndex. The ID can be up to 128 characters long and must start with a letter and only contain letters, numbers, and underscores. The ID must be unique within the project it is created in. index: Required. The name of the Index this is the deployment of. We may refer to this Index as the DeployedIndex's "original" Index. indexSyncTime: Output only. The DeployedIndex may depend on various data on its original Index. Additionally when certain changes to the original Index are being done (e.g. when what the Index contains is being changed) the DeployedIndex may be asynchronously updated in the background to reflect these changes. If this timestamp's value is at least the Index.update_time of the original Index, it means that this DeployedIndex and the original Index are in sync. If this timestamp is older, then to see which updates this DeployedIndex already contains (and which it does not), one must list the operations that are running on the original Index. Only the successfully completed Operations with update_time equal or before this sync time are contained in this DeployedIndex. privateEndpoints: Output only. Provides paths for users to send requests directly to the deployed index services running on Cloud via private services access. This field is populated if network is configured. pscAutomationConfigs: Optional. If set for PSC deployed index, PSC connection will be automatically created after deployment is done and the endpoint information is populated in private_endpoints.psc_automated_endpoints. reservedIpRanges: Optional. A list of reserved ip ranges under the VPC network that can be used for this DeployedIndex. If set, we will deploy the index within the provided ip ranges. Otherwise, the index might be deployed to any ip ranges under the provided VPC network. The value should be the name of the address (https://cloud.google.com/compute/docs/reference/rest/v1/addresses) Example: ['vertex-ai-ip-range']. For more information about subnets and network IP ranges, please see https://cloud.google.com/vpc/docs/subnets# manually_created_subnet_ip_ranges. """ class DeploymentTierValueValuesEnum(_messages.Enum): r"""Optional. The deployment tier that the index is deployed to. DEPLOYMENT_TIER_UNSPECIFIED will use a system-chosen default tier. Values: DEPLOYMENT_TIER_UNSPECIFIED: Default deployment tier. STORAGE: Optimized for costs. """ DEPLOYMENT_TIER_UNSPECIFIED = 0 STORAGE = 1 automaticResources = _messages.MessageField('GoogleCloudAiplatformV1beta1AutomaticResources', 1) createTime = _messages.StringField(2) dedicatedResources = _messages.MessageField('GoogleCloudAiplatformV1beta1DedicatedResources', 3) deployedIndexAuthConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedIndexAuthConfig', 4) deploymentGroup = _messages.StringField(5) deploymentTier = _messages.EnumField('DeploymentTierValueValuesEnum', 6) displayName = _messages.StringField(7) enableAccessLogging = _messages.BooleanField(8) enableDatapointUpsertLogging = _messages.BooleanField(9) id = _messages.StringField(10) index = _messages.StringField(11) indexSyncTime = _messages.StringField(12) privateEndpoints = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexPrivateEndpoints', 13) pscAutomationConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1PSCAutomationConfig', 14, repeated=True) reservedIpRanges = _messages.StringField(15, repeated=True) class GoogleCloudAiplatformV1beta1DeployedIndexAuthConfig(_messages.Message): r"""Used to set up the auth on the DeployedIndex's private endpoint. Fields: authProvider: Defines the authentication provider that the DeployedIndex uses. """ authProvider = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedIndexAuthConfigAuthProvider', 1) class GoogleCloudAiplatformV1beta1DeployedIndexAuthConfigAuthProvider(_messages.Message): r"""Configuration for an authentication provider, including support for [JSON Web Token (JWT)](https://tools.ietf.org/html/draft-ietf-oauth-json- web-token-32). Fields: allowedIssuers: A list of allowed JWT issuers. Each entry must be a valid Google service account, in the following format: `service-account- name@project-id.iam.gserviceaccount.com` audiences: The list of JWT [audiences](https://tools.ietf.org/html/draft- ietf-oauth-json-web-token-32#section-4.1.3). that are allowed to access. A JWT containing any of these audiences will be accepted. """ allowedIssuers = _messages.StringField(1, repeated=True) audiences = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1DeployedIndexRef(_messages.Message): r"""Points to a DeployedIndex. Fields: deployedIndexId: Immutable. The ID of the DeployedIndex in the above IndexEndpoint. displayName: Output only. The display name of the DeployedIndex. indexEndpoint: Immutable. A resource name of the IndexEndpoint. """ deployedIndexId = _messages.StringField(1) displayName = _messages.StringField(2) indexEndpoint = _messages.StringField(3) class GoogleCloudAiplatformV1beta1DeployedModel(_messages.Message): r"""A deployment of a Model. Endpoints contain one or more DeployedModels. Messages: SystemLabelsValue: System labels to apply to Model Garden deployments. System labels are managed by Google for internal use only. Fields: automaticResources: A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. checkpointId: The checkpoint id of the model. createTime: Output only. Timestamp when the DeployedModel was created. dedicatedResources: A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration. disableContainerLogging: For custom-trained Models and AutoML Tabular Models, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true. disableExplanations: If true, deploy the model without explainable feature, regardless the existence of Model.explanation_spec or explanation_spec. displayName: The display name of the DeployedModel. If not provided upon creation, the Model's display_name is used. enableAccessLogging: If true, online prediction access logs are sent to Cloud Logging. These logs are like standard server access logs, containing information like timestamp and latency for each prediction request. Note that logs may incur a cost, especially if your project receives prediction requests at a high queries per second rate (QPS). Estimate your costs before enabling this option. enableContainerLogging: If true, the container of the DeployedModel instances will send `stderr` and `stdout` streams to Cloud Logging. Only supported for custom-trained Models and AutoML Tabular Models. explanationSpec: Explanation configuration for this DeployedModel. When deploying a Model using EndpointService.DeployModel, this value overrides the value of Model.explanation_spec. All fields of explanation_spec are optional in the request. If a field of explanation_spec is not populated, the value of the same field of Model.explanation_spec is inherited. If the corresponding Model.explanation_spec is not populated, all fields of the explanation_spec will be used for the explanation configuration. fasterDeploymentConfig: Configuration for faster model deployment. gdcConnectedModel: GDC pretrained / Gemini model name. The model name is a plain model name, e.g. gemini-1.5-flash-002. gdcGgsModel: Reserved for future use. id: Immutable. The ID of the DeployedModel. If not provided upon deployment, Vertex AI will generate a value for this ID. This value should be 1-10 characters, and valid characters are `/[0-9]/`. model: The resource name of the Model that this is the deployment of. Note that the Model may be in a different location than the DeployedModel's Endpoint. The resource name may contain version id or version alias to specify the version. Example: `projects/{project}/locations/{location}/models/{model}@2` or `projects/{project}/locations/{location}/models/{model}@golden` if no version is specified, the default version will be deployed. modelVersionId: Output only. The version ID of the model that is deployed. privateEndpoints: Output only. Provide paths for users to send predict/explain/health requests directly to the deployed model services running on Cloud via private services access. This field is populated if network is configured. rolloutOptions: Options for configuring rolling deployments. serviceAccount: The service account that the DeployedModel's container runs as. Specify the email address of the service account. If this service account is not specified, the container runs as a service account that doesn't have access to the resource project. Users deploying the Model must have the `iam.serviceAccounts.actAs` permission on this service account. sharedResources: The resource name of the shared DeploymentResourcePool to deploy on. Format: `projects/{project}/locations/{location}/deploymentRe sourcePools/{deployment_resource_pool}` speculativeDecodingSpec: Optional. Spec for configuring speculative decoding. status: Output only. Runtime status of the deployed model. systemLabels: System labels to apply to Model Garden deployments. System labels are managed by Google for internal use only. """ @encoding.MapUnrecognizedFields('additionalProperties') class SystemLabelsValue(_messages.Message): r"""System labels to apply to Model Garden deployments. System labels are managed by Google for internal use only. Messages: AdditionalProperty: An additional property for a SystemLabelsValue object. Fields: additionalProperties: Additional properties of type SystemLabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a SystemLabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) automaticResources = _messages.MessageField('GoogleCloudAiplatformV1beta1AutomaticResources', 1) checkpointId = _messages.StringField(2) createTime = _messages.StringField(3) dedicatedResources = _messages.MessageField('GoogleCloudAiplatformV1beta1DedicatedResources', 4) disableContainerLogging = _messages.BooleanField(5) disableExplanations = _messages.BooleanField(6) displayName = _messages.StringField(7) enableAccessLogging = _messages.BooleanField(8) enableContainerLogging = _messages.BooleanField(9) explanationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationSpec', 10) fasterDeploymentConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FasterDeploymentConfig', 11) gdcConnectedModel = _messages.StringField(12) gdcGgsModel = _messages.StringField(13) id = _messages.StringField(14) model = _messages.StringField(15) modelVersionId = _messages.StringField(16) privateEndpoints = _messages.MessageField('GoogleCloudAiplatformV1beta1PrivateEndpoints', 17) rolloutOptions = _messages.MessageField('GoogleCloudAiplatformV1beta1RolloutOptions', 18) serviceAccount = _messages.StringField(19) sharedResources = _messages.StringField(20) speculativeDecodingSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1SpeculativeDecodingSpec', 21) status = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedModelStatus', 22) systemLabels = _messages.MessageField('SystemLabelsValue', 23) class GoogleCloudAiplatformV1beta1DeployedModelRef(_messages.Message): r"""Points to a DeployedModel. Fields: checkpointId: Immutable. The ID of the Checkpoint deployed in the DeployedModel. deployedModelId: Immutable. An ID of a DeployedModel in the above Endpoint. endpoint: Immutable. A resource name of an Endpoint. """ checkpointId = _messages.StringField(1) deployedModelId = _messages.StringField(2) endpoint = _messages.StringField(3) class GoogleCloudAiplatformV1beta1DeployedModelStatus(_messages.Message): r"""Runtime status of the deployed model. Fields: availableReplicaCount: Output only. The number of available replicas of the deployed model. lastUpdateTime: Output only. The time at which the status was last updated. message: Output only. The latest deployed model's status message (if any). """ availableReplicaCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) lastUpdateTime = _messages.StringField(2) message = _messages.StringField(3) class GoogleCloudAiplatformV1beta1DeploymentResourcePool(_messages.Message): r"""A description of resources that can be shared by multiple DeployedModels, whose underlying specification consists of a DedicatedResources. Enums: ResourcePoolTypeValueValuesEnum: Immutable. The intended use case of the DeploymentResourcePool. Fields: clusterAffinityLabel: Optional. Immutable. The affinity label of the cluster that the DeploymentResourcePool is deployed to. createTime: Output only. Timestamp when this DeploymentResourcePool was created. dedicatedResources: Required. The underlying DedicatedResources that the DeploymentResourcePool uses. disableContainerLogging: If the DeploymentResourcePool is deployed with custom-trained Models or AutoML Tabular Models, the container(s) of the DeploymentResourcePool will send `stderr` and `stdout` streams to Cloud Logging by default. Please note that the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging/pricing). User can disable container logging by setting this flag to true. encryptionSpec: Customer-managed encryption key spec for a DeploymentResourcePool. If set, this DeploymentResourcePool will be secured by this key. Endpoints and the DeploymentResourcePool they deploy in need to have the same EncryptionSpec. name: Immutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deploy ment_resource_pool}` resourcePoolType: Immutable. The intended use case of the DeploymentResourcePool. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. serviceAccount: The service account that the DeploymentResourcePool's container(s) run as. Specify the email address of the service account. If this service account is not specified, the container(s) run as a service account that doesn't have access to the resource project. Users deploying the Models to this DeploymentResourcePool must have the `iam.serviceAccounts.actAs` permission on this service account. """ class ResourcePoolTypeValueValuesEnum(_messages.Enum): r"""Immutable. The intended use case of the DeploymentResourcePool. Values: RESOURCE_POOL_TYPE_UNSPECIFIED: The default value. This value is unused. RESOURCE_POOL_TYPE_MODEL_COHOSTING: The resource pool is used for [model cohosting] (https://cloud.google.com/vertex-ai/docs/model- cohosting/overview). RESOURCE_POOL_TYPE_RESERVED_CAPACITY: The resource pool is used for reserving capacity. """ RESOURCE_POOL_TYPE_UNSPECIFIED = 0 RESOURCE_POOL_TYPE_MODEL_COHOSTING = 1 RESOURCE_POOL_TYPE_RESERVED_CAPACITY = 2 clusterAffinityLabel = _messages.StringField(1) createTime = _messages.StringField(2) dedicatedResources = _messages.MessageField('GoogleCloudAiplatformV1beta1DedicatedResources', 3) disableContainerLogging = _messages.BooleanField(4) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 5) name = _messages.StringField(6) resourcePoolType = _messages.EnumField('ResourcePoolTypeValueValuesEnum', 7) satisfiesPzi = _messages.BooleanField(8) satisfiesPzs = _messages.BooleanField(9) serviceAccount = _messages.StringField(10) class GoogleCloudAiplatformV1beta1DestinationFeatureSetting(_messages.Message): r"""A GoogleCloudAiplatformV1beta1DestinationFeatureSetting object. Fields: destinationField: Specify the field name in the export destination. If not specified, Feature ID is used. featureId: Required. The ID of the Feature to apply the setting to. """ destinationField = _messages.StringField(1) featureId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1DirectPredictRequest(_messages.Message): r"""Request message for PredictionService.DirectPredict. Fields: inputs: The prediction input. parameters: The parameters that govern the prediction. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensor', 1, repeated=True) parameters = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensor', 2) class GoogleCloudAiplatformV1beta1DirectPredictResponse(_messages.Message): r"""Response message for PredictionService.DirectPredict. Fields: outputs: The prediction output. parameters: The parameters that govern the prediction. """ outputs = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensor', 1, repeated=True) parameters = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensor', 2) class GoogleCloudAiplatformV1beta1DirectRawPredictRequest(_messages.Message): r"""Request message for PredictionService.DirectRawPredict. Fields: input: The prediction input. methodName: Fully qualified name of the API method being invoked to perform predictions. Format: `/namespace.Service/Method/` Example: `/tensorflow.serving.PredictionService/Predict` """ input = _messages.BytesField(1) methodName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1DirectRawPredictResponse(_messages.Message): r"""Response message for PredictionService.DirectRawPredict. Fields: output: The prediction output. """ output = _messages.BytesField(1) class GoogleCloudAiplatformV1beta1DirectUploadSource(_messages.Message): r"""The input content is encapsulated and uploaded in the request.""" class GoogleCloudAiplatformV1beta1DiskSpec(_messages.Message): r"""Represents the spec of disk options. Fields: bootDiskSizeGb: Size in GB of the boot disk (default is 100GB). bootDiskType: Type of the boot disk. For non-A3U machines, the default value is "pd-ssd", for A3U machines, the default value is "hyperdisk- balanced". Valid values: "pd-ssd" (Persistent Disk Solid State Drive), "pd-standard" (Persistent Disk Hard Disk Drive) or "hyperdisk-balanced". """ bootDiskSizeGb = _messages.IntegerField(1, variant=_messages.Variant.INT32) bootDiskType = _messages.StringField(2) class GoogleCloudAiplatformV1beta1DistillationDataStats(_messages.Message): r"""Statistics computed for datasets used for distillation. Fields: trainingDatasetStats: Output only. Statistics computed for the training dataset. """ trainingDatasetStats = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetStats', 1) class GoogleCloudAiplatformV1beta1DistillationHyperParameters(_messages.Message): r"""Hyperparameters for Distillation. Enums: AdapterSizeValueValuesEnum: Optional. Adapter size for distillation. Fields: adapterSize: Optional. Adapter size for distillation. epochCount: Optional. Number of complete passes the model makes over the entire training dataset during training. learningRateMultiplier: Optional. Multiplier for adjusting the default learning rate. """ class AdapterSizeValueValuesEnum(_messages.Enum): r"""Optional. Adapter size for distillation. Values: ADAPTER_SIZE_UNSPECIFIED: Adapter size is unspecified. ADAPTER_SIZE_ONE: Adapter size 1. ADAPTER_SIZE_TWO: Adapter size 2. ADAPTER_SIZE_FOUR: Adapter size 4. ADAPTER_SIZE_EIGHT: Adapter size 8. ADAPTER_SIZE_SIXTEEN: Adapter size 16. ADAPTER_SIZE_THIRTY_TWO: Adapter size 32. """ ADAPTER_SIZE_UNSPECIFIED = 0 ADAPTER_SIZE_ONE = 1 ADAPTER_SIZE_TWO = 2 ADAPTER_SIZE_FOUR = 3 ADAPTER_SIZE_EIGHT = 4 ADAPTER_SIZE_SIXTEEN = 5 ADAPTER_SIZE_THIRTY_TWO = 6 adapterSize = _messages.EnumField('AdapterSizeValueValuesEnum', 1) epochCount = _messages.IntegerField(2) learningRateMultiplier = _messages.FloatField(3) class GoogleCloudAiplatformV1beta1DistillationSpec(_messages.Message): r"""Tuning Spec for Distillation. Fields: baseTeacherModel: The base teacher model that is being distilled. See [Supported models](https://cloud.google.com/vertex-ai/generative- ai/docs/model-reference/tuning#supported_models). hyperParameters: Optional. Hyperparameters for Distillation. pipelineRootDirectory: Deprecated. A path in a Cloud Storage bucket, which will be treated as the root output directory of the distillation pipeline. It is used by the system to generate the paths of output artifacts. studentModel: The student model that is being tuned, e.g., "google/gemma-2b-1.1-it". Deprecated. Use base_model instead. trainingDatasetUri: Deprecated. Cloud Storage path to file containing training dataset for tuning. The dataset must be formatted as a JSONL file. tunedTeacherModelSource: The resource name of the Tuned teacher model. Format: `projects/{project}/locations/{location}/models/{model}`. validationDatasetUri: Optional. Cloud Storage path to file containing validation dataset for tuning. The dataset must be formatted as a JSONL file. """ baseTeacherModel = _messages.StringField(1) hyperParameters = _messages.MessageField('GoogleCloudAiplatformV1beta1DistillationHyperParameters', 2) pipelineRootDirectory = _messages.StringField(3) studentModel = _messages.StringField(4) trainingDatasetUri = _messages.StringField(5) tunedTeacherModelSource = _messages.StringField(6) validationDatasetUri = _messages.StringField(7) class GoogleCloudAiplatformV1beta1DnsPeeringConfig(_messages.Message): r"""DNS peering configuration. These configurations are used to create DNS peering zones in the Vertex tenant project VPC, enabling resolution of records within the specified domain hosted in the target network's Cloud DNS. Fields: domain: Required. The DNS name suffix of the zone being peered to, e.g., "my-internal-domain.corp.". Must end with a dot. targetNetwork: Required. The VPC network name in the target_project where the DNS zone specified by 'domain' is visible. targetProject: Required. The project ID hosting the Cloud DNS managed zone that contains the 'domain'. The Vertex AI Service Agent requires the dns.peer role on this project. """ domain = _messages.StringField(1) targetNetwork = _messages.StringField(2) targetProject = _messages.StringField(3) class GoogleCloudAiplatformV1beta1DoubleArray(_messages.Message): r"""A list of double values. Fields: values: A list of double values. """ values = _messages.FloatField(1, repeated=True) class GoogleCloudAiplatformV1beta1DynamicRetrievalConfig(_messages.Message): r"""Describes the options to customize dynamic retrieval. Enums: ModeValueValuesEnum: The mode of the predictor to be used in dynamic retrieval. Fields: dynamicThreshold: Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used. mode: The mode of the predictor to be used in dynamic retrieval. """ class ModeValueValuesEnum(_messages.Enum): r"""The mode of the predictor to be used in dynamic retrieval. Values: MODE_UNSPECIFIED: Always trigger retrieval. MODE_DYNAMIC: Run retrieval only when system decides it is necessary. """ MODE_UNSPECIFIED = 0 MODE_DYNAMIC = 1 dynamicThreshold = _messages.FloatField(1, variant=_messages.Variant.FLOAT) mode = _messages.EnumField('ModeValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1EmbedContentRequest(_messages.Message): r"""Request message for PredictionService.EmbedContent. Enums: TaskTypeValueValuesEnum: Optional. The task type of the embedding. Fields: autoTruncate: Optional. Whether to silently truncate the input content if it's longer than the maximum sequence length. content: Required. Input content to be embedded. Required. outputDimensionality: Optional. Optional reduced dimension for the output embedding. If set, excessive values in the output embedding are truncated from the end. taskType: Optional. The task type of the embedding. title: Optional. An optional title for the text. """ class TaskTypeValueValuesEnum(_messages.Enum): r"""Optional. The task type of the embedding. Values: UNSPECIFIED: Unset value, which will default to one of the other enum values. RETRIEVAL_QUERY: Specifies the given text is a query in a search/retrieval setting. RETRIEVAL_DOCUMENT: Specifies the given text is a document from the corpus being searched. SEMANTIC_SIMILARITY: Specifies the given text will be used for STS. CLASSIFICATION: Specifies that the given text will be classified. CLUSTERING: Specifies that the embeddings will be used for clustering. QUESTION_ANSWERING: Specifies that the embeddings will be used for question answering. FACT_VERIFICATION: Specifies that the embeddings will be used for fact verification. CODE_RETRIEVAL_QUERY: Specifies that the embeddings will be used for code retrieval. """ UNSPECIFIED = 0 RETRIEVAL_QUERY = 1 RETRIEVAL_DOCUMENT = 2 SEMANTIC_SIMILARITY = 3 CLASSIFICATION = 4 CLUSTERING = 5 QUESTION_ANSWERING = 6 FACT_VERIFICATION = 7 CODE_RETRIEVAL_QUERY = 8 autoTruncate = _messages.BooleanField(1) content = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 2) outputDimensionality = _messages.IntegerField(3, variant=_messages.Variant.INT32) taskType = _messages.EnumField('TaskTypeValueValuesEnum', 4) title = _messages.StringField(5) class GoogleCloudAiplatformV1beta1EmbedContentResponse(_messages.Message): r"""Response message for PredictionService.EmbedContent. Fields: embedding: The embedding generated from the input content. truncated: Whether the input content was truncated before generating the embedding. usageMetadata: Metadata about the response(s). """ embedding = _messages.MessageField('GoogleCloudAiplatformV1beta1EmbedContentResponseEmbedding', 1) truncated = _messages.BooleanField(2) usageMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1UsageMetadata', 3) class GoogleCloudAiplatformV1beta1EmbedContentResponseEmbedding(_messages.Message): r"""A list of floats representing an embedding. Fields: values: Embedding vector values. """ values = _messages.FloatField(1, repeated=True, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1EnableModelRequest(_messages.Message): r"""Request message for ModelGardenService.EnableModel. Fields: service: Optional. The ID links the Marketplace listing to the underlying Vertex AI model endpoint. Format: `services/{service_id}` Format: `services/{service_id}` """ service = _messages.StringField(1) class GoogleCloudAiplatformV1beta1EnableModelResponse(_messages.Message): r"""Response message for ModelGardenService.EnableModel. Enums: EnablementStateValueValuesEnum: Output only. The result of the model enablement. Fields: enablementState: Output only. The result of the model enablement. publisherEndpoint: Output only. The publisher endpoint that the project is enabled for. Format: `projects/{project}/locations/{location}/publishers /{publisher}/models/{publisher_model}` """ class EnablementStateValueValuesEnum(_messages.Enum): r"""Output only. The result of the model enablement. Values: ENABLEMENT_STATE_UNSPECIFIED: The PublisherModel enable status is unclear. The API will default to this value. ENABLEMENT_STATE_SUCCEEDED: The PublisherModel is enabled successfully. ENABLEMENT_STATE_FAILED: The PublisherModel is failed to enable """ ENABLEMENT_STATE_UNSPECIFIED = 0 ENABLEMENT_STATE_SUCCEEDED = 1 ENABLEMENT_STATE_FAILED = 2 enablementState = _messages.EnumField('EnablementStateValueValuesEnum', 1) publisherEndpoint = _messages.StringField(2) class GoogleCloudAiplatformV1beta1EncryptionSpec(_messages.Message): r"""Represents a customer-managed encryption key spec that can be applied to a top-level resource. Fields: kmsKeyName: Required. The Cloud KMS resource identifier of the customer managed encryption key used to protect a resource. Has the form: `projects/my-project/locations/my-region/keyRings/my-kr/cryptoKeys/my- key`. The key needs to be in the same region as where the compute resource is created. """ kmsKeyName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1Endpoint(_messages.Message): r"""Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations. Messages: LabelsValue: The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. TrafficSplitValue: A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If a DeployedModel's ID is not listed in this map, then it receives no traffic. The traffic percentage values must add up to 100, or map must be empty if the Endpoint is to not accept any traffic at a moment. Fields: clientConnectionConfig: Configurations that are applied to the endpoint for online prediction. createTime: Output only. Timestamp when this Endpoint was created. dedicatedEndpointDns: Output only. DNS of the dedicated endpoint. Will only be populated if dedicated_endpoint_enabled is true. Depending on the features enabled, uid might be a random number or a string. For example, if fast_tryout is enabled, uid will be fasttryout. Format: `https://{endpoint_id}.{region}-{uid}.prediction.vertexai.goog`. dedicatedEndpointEnabled: If true, the endpoint will be exposed through a dedicated DNS [Endpoint.dedicated_endpoint_dns]. Your request to the dedicated DNS will be isolated from other users' traffic and will have better performance and reliability. Note: Once you enabled dedicated endpoint, you won't be able to send request to the shared DNS {region}-aiplatform.googleapis.com. The limitation will be removed soon. deployedModels: Output only. The models deployed in this Endpoint. To add or remove DeployedModels use EndpointService.DeployModel and EndpointService.UndeployModel respectively. description: The description of the Endpoint. displayName: Required. The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters. enablePrivateServiceConnect: Deprecated: If true, expose the Endpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set. encryptionSpec: Customer-managed encryption key spec for an Endpoint. If set, this Endpoint and all sub-resources of this Endpoint will be secured by this key. etag: Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. gdcConfig: Configures the Google Distributed Cloud (GDC) environment for online prediction. Only set this field when the Endpoint is to be deployed in a GDC environment. gdceConfig: Configures the Google Distributed Cloud Edge (GDCE) environment for online prediction. Only set this field when the Endpoint is to be deployed in a GDCE environment. genAiAdvancedFeaturesConfig: Optional. Configuration for GenAiAdvancedFeatures. If the endpoint is serving GenAI models, advanced features like native RAG integration can be configured. Currently, only Model Garden models are supported. labels: The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. modelDeploymentMonitoringJob: Output only. Resource name of the Model Monitoring job associated with this Endpoint if monitoring is enabled by JobService.CreateModelDeploymentMonitoringJob. Format: `projects/{projec t}/locations/{location}/modelDeploymentMonitoringJobs/{model_deployment_ monitoring_job}` name: Output only. The resource name of the Endpoint. network: Optional. The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and- firewalls#networks) to which the Endpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. Only one of the fields, network or enable_private_service_connect, can be set. [Form at](https://cloud.google.com/compute/docs/reference/rest/v1/networks/ins ert): `projects/{project}/global/networks/{network}`. Where `{project}` is a project number, as in `12345`, and `{network}` is network name. predictRequestResponseLoggingConfig: Configures the request-response logging for online prediction. privateServiceConnectConfig: Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. trafficSplit: A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If a DeployedModel's ID is not listed in this map, then it receives no traffic. The traffic percentage values must add up to 100, or map must be empty if the Endpoint is to not accept any traffic at a moment. updateTime: Output only. Timestamp when this Endpoint was last updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your Endpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class TrafficSplitValue(_messages.Message): r"""A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If a DeployedModel's ID is not listed in this map, then it receives no traffic. The traffic percentage values must add up to 100, or map must be empty if the Endpoint is to not accept any traffic at a moment. Messages: AdditionalProperty: An additional property for a TrafficSplitValue object. Fields: additionalProperties: Additional properties of type TrafficSplitValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a TrafficSplitValue object. Fields: key: Name of the additional property. value: A integer attribute. """ key = _messages.StringField(1) value = _messages.IntegerField(2, variant=_messages.Variant.INT32) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) clientConnectionConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ClientConnectionConfig', 1) createTime = _messages.StringField(2) dedicatedEndpointDns = _messages.StringField(3) dedicatedEndpointEnabled = _messages.BooleanField(4) deployedModels = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedModel', 5, repeated=True) description = _messages.StringField(6) displayName = _messages.StringField(7) enablePrivateServiceConnect = _messages.BooleanField(8) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 9) etag = _messages.StringField(10) gdcConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GdcConfig', 11) gdceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GdceConfig', 12) genAiAdvancedFeaturesConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GenAiAdvancedFeaturesConfig', 13) labels = _messages.MessageField('LabelsValue', 14) modelDeploymentMonitoringJob = _messages.StringField(15) name = _messages.StringField(16) network = _messages.StringField(17) predictRequestResponseLoggingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictRequestResponseLoggingConfig', 18) privateServiceConnectConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig', 19) satisfiesPzi = _messages.BooleanField(20) satisfiesPzs = _messages.BooleanField(21) trafficSplit = _messages.MessageField('TrafficSplitValue', 22) updateTime = _messages.StringField(23) class GoogleCloudAiplatformV1beta1EnterpriseWebSearch(_messages.Message): r"""Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. Enums: BlockingConfidenceValueValuesEnum: Optional. Sites with confidence level chosen & above this value will be blocked from the search results. Fields: blockingConfidence: Optional. Sites with confidence level chosen & above this value will be blocked from the search results. excludeDomains: Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. """ class BlockingConfidenceValueValuesEnum(_messages.Enum): r"""Optional. Sites with confidence level chosen & above this value will be blocked from the search results. Values: PHISH_BLOCK_THRESHOLD_UNSPECIFIED: Defaults to unspecified. BLOCK_LOW_AND_ABOVE: Blocks Low and above confidence URL that is risky. BLOCK_MEDIUM_AND_ABOVE: Blocks Medium and above confidence URL that is risky. BLOCK_HIGH_AND_ABOVE: Blocks High and above confidence URL that is risky. BLOCK_HIGHER_AND_ABOVE: Blocks Higher and above confidence URL that is risky. BLOCK_VERY_HIGH_AND_ABOVE: Blocks Very high and above confidence URL that is risky. BLOCK_ONLY_EXTREMELY_HIGH: Blocks Extremely high confidence URL that is risky. """ PHISH_BLOCK_THRESHOLD_UNSPECIFIED = 0 BLOCK_LOW_AND_ABOVE = 1 BLOCK_MEDIUM_AND_ABOVE = 2 BLOCK_HIGH_AND_ABOVE = 3 BLOCK_HIGHER_AND_ABOVE = 4 BLOCK_VERY_HIGH_AND_ABOVE = 5 BLOCK_ONLY_EXTREMELY_HIGH = 6 blockingConfidence = _messages.EnumField('BlockingConfidenceValueValuesEnum', 1) excludeDomains = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1EntityIdSelector(_messages.Message): r"""Selector for entityId. Getting ids from the given source. Fields: csvSource: Source of Csv entityIdField: Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id. """ csvSource = _messages.MessageField('GoogleCloudAiplatformV1beta1CsvSource', 1) entityIdField = _messages.StringField(2) class GoogleCloudAiplatformV1beta1EntityType(_messages.Message): r"""An entity type is a type of object in a system that needs to be modeled and have stored information about. For example, driver is an entity type, and driver0 is an instance of an entity type driver. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: createTime: Output only. Timestamp when this EntityType was created. description: Optional. Description of the EntityType. etag: Optional. Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. monitoringConfig: Optional. The default monitoring configuration for all Features with value type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 under this EntityType. If this is populated with [FeaturestoreMonitoringConfig.monitoring_interval] specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring is disabled. name: Immutable. Name of the EntityType. Format: `projects/{project}/locat ions/{location}/featurestores/{featurestore}/entityTypes/{entity_type}` The last part entity_type is assigned by the client. The entity_type can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z and underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given a featurestore. offlineStorageTtlDays: Optional. Config for data retention policy in offline storage. TTL in days for feature values that will be stored in offline storage. The Feature Store offline storage periodically removes obsolete feature values older than `offline_storage_ttl_days` since the feature generation time. If unset (or explicitly set to 0), default to 4000 days TTL. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. updateTime: Output only. Timestamp when this EntityType was most recently updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize your EntityTypes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one EntityType (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) description = _messages.StringField(2) etag = _messages.StringField(3) labels = _messages.MessageField('LabelsValue', 4) monitoringConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfig', 5) name = _messages.StringField(6) offlineStorageTtlDays = _messages.IntegerField(7, variant=_messages.Variant.INT32) satisfiesPzi = _messages.BooleanField(8) satisfiesPzs = _messages.BooleanField(9) updateTime = _messages.StringField(10) class GoogleCloudAiplatformV1beta1EnvVar(_messages.Message): r"""Represents an environment variable present in a Container or Python Module. Fields: name: Required. Name of the environment variable. Must be a valid C identifier. value: Required. Variables that reference a $(VAR_NAME) are expanded using the previous defined environment variables in the container and any service environment variables. If a variable cannot be resolved, the reference in the input string will be unchanged. The $(VAR_NAME) syntax can be escaped with a double $$, ie: $$(VAR_NAME). Escaped references will never be expanded, regardless of whether the variable exists or not. """ name = _messages.StringField(1) value = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotation(_messages.Message): r"""Model error analysis for each annotation. Enums: QueryTypeValueValuesEnum: The query type used for finding the attributed items. Fields: attributedItems: Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type. outlierScore: The outlier score of this annotated item. Usually defined as the min of all distances from attributed items. outlierThreshold: The threshold used to determine if this annotation is an outlier or not. queryType: The query type used for finding the attributed items. """ class QueryTypeValueValuesEnum(_messages.Enum): r"""The query type used for finding the attributed items. Values: QUERY_TYPE_UNSPECIFIED: Unspecified query type for model error analysis. ALL_SIMILAR: Query similar samples across all classes in the dataset. SAME_CLASS_SIMILAR: Query similar samples from the same class of the input sample. SAME_CLASS_DISSIMILAR: Query dissimilar samples from the same class of the input sample. """ QUERY_TYPE_UNSPECIFIED = 0 ALL_SIMILAR = 1 SAME_CLASS_SIMILAR = 2 SAME_CLASS_DISSIMILAR = 3 attributedItems = _messages.MessageField('GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotationAttributedItem', 1, repeated=True) outlierScore = _messages.FloatField(2) outlierThreshold = _messages.FloatField(3) queryType = _messages.EnumField('QueryTypeValueValuesEnum', 4) class GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotationAttributedItem(_messages.Message): r"""Attributed items for a given annotation, typically representing neighbors from the training sets constrained by the query type. Fields: annotationResourceName: The unique ID for each annotation. Used by FE to allocate the annotation in DB. distance: The distance of this item to the annotation. """ annotationResourceName = _messages.StringField(1) distance = _messages.FloatField(2) class GoogleCloudAiplatformV1beta1EvaluateDatasetRequest(_messages.Message): r"""Request message for EvaluationService.EvaluateDataset. Fields: autoraterConfig: Optional. Autorater config used for evaluation. Currently only publisher Gemini models are supported. Format: `projects/{PROJECT}/ locations/{LOCATION}/publishers/google/models/{MODEL}.` dataset: Required. The dataset used for evaluation. metrics: Required. The metrics used for evaluation. outputConfig: Required. Config for evaluation output. """ autoraterConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AutoraterConfig', 1) dataset = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationDataset', 2) metrics = _messages.MessageField('GoogleCloudAiplatformV1beta1Metric', 3, repeated=True) outputConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1OutputConfig', 4) class GoogleCloudAiplatformV1beta1EvaluateDatasetResponse(_messages.Message): r"""Response in LRO for EvaluationService.EvaluateDataset. Fields: aggregationOutput: Output only. Aggregation statistics derived from results of EvaluationService.EvaluateDataset. outputInfo: Output only. Output info for EvaluationService.EvaluateDataset. """ aggregationOutput = _messages.MessageField('GoogleCloudAiplatformV1beta1AggregationOutput', 1) outputInfo = _messages.MessageField('GoogleCloudAiplatformV1beta1OutputInfo', 2) class GoogleCloudAiplatformV1beta1EvaluateDatasetRun(_messages.Message): r"""Evaluate Dataset Run Result for Tuning Job. Fields: checkpointId: Output only. The checkpoint id used in the evaluation run. Only populated when evaluating checkpoints. error: Output only. The error of the evaluation run if any. evaluateDatasetResponse: Output only. Results for EvaluationService.EvaluateDataset. operationName: Output only. The operation ID of the evaluation run. Format: `projects/{project}/locations/{location}/operations/{operation_id}`. """ checkpointId = _messages.StringField(1) error = _messages.MessageField('GoogleRpcStatus', 2) evaluateDatasetResponse = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluateDatasetResponse', 3) operationName = _messages.StringField(4) class GoogleCloudAiplatformV1beta1EvaluateInstancesRequest(_messages.Message): r"""Request message for EvaluationService.EvaluateInstances. Fields: autoraterConfig: Optional. Autorater config used for evaluation. bleuInput: Instances and metric spec for bleu metric. coherenceInput: Input for coherence metric. cometInput: Translation metrics. Input for Comet metric. exactMatchInput: Auto metric instances. Instances and metric spec for exact match metric. fluencyInput: LLM-based metric instance. General text generation metrics, applicable to other categories. Input for fluency metric. fulfillmentInput: Input for fulfillment metric. groundednessInput: Input for groundedness metric. instance: The instance to be evaluated. metrics: The metrics used for evaluation. Currently, we only support evaluating a single metric. If multiple metrics are provided, only the first one will be evaluated. metricxInput: Input for Metricx metric. pairwiseMetricInput: Input for pairwise metric. pairwiseQuestionAnsweringQualityInput: Input for pairwise question answering quality metric. pairwiseSummarizationQualityInput: Input for pairwise summarization quality metric. pointwiseMetricInput: Input for pointwise metric. questionAnsweringCorrectnessInput: Input for question answering correctness metric. questionAnsweringHelpfulnessInput: Input for question answering helpfulness metric. questionAnsweringQualityInput: Input for question answering quality metric. questionAnsweringRelevanceInput: Input for question answering relevance metric. rougeInput: Instances and metric spec for rouge metric. rubricBasedInstructionFollowingInput: Rubric Based Instruction Following metric. safetyInput: Input for safety metric. summarizationHelpfulnessInput: Input for summarization helpfulness metric. summarizationQualityInput: Input for summarization quality metric. summarizationVerbosityInput: Input for summarization verbosity metric. toolCallValidInput: Tool call metric instances. Input for tool call valid metric. toolNameMatchInput: Input for tool name match metric. toolParameterKeyMatchInput: Input for tool parameter key match metric. toolParameterKvMatchInput: Input for tool parameter key value match metric. trajectoryAnyOrderMatchInput: Input for trajectory match any order metric. trajectoryExactMatchInput: Input for trajectory exact match metric. trajectoryInOrderMatchInput: Input for trajectory in order match metric. trajectoryPrecisionInput: Input for trajectory precision metric. trajectoryRecallInput: Input for trajectory recall metric. trajectorySingleToolUseInput: Input for trajectory single tool use metric. """ autoraterConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AutoraterConfig', 1) bleuInput = _messages.MessageField('GoogleCloudAiplatformV1beta1BleuInput', 2) coherenceInput = _messages.MessageField('GoogleCloudAiplatformV1beta1CoherenceInput', 3) cometInput = _messages.MessageField('GoogleCloudAiplatformV1beta1CometInput', 4) exactMatchInput = _messages.MessageField('GoogleCloudAiplatformV1beta1ExactMatchInput', 5) fluencyInput = _messages.MessageField('GoogleCloudAiplatformV1beta1FluencyInput', 6) fulfillmentInput = _messages.MessageField('GoogleCloudAiplatformV1beta1FulfillmentInput', 7) groundednessInput = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundednessInput', 8) instance = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstance', 9) metrics = _messages.MessageField('GoogleCloudAiplatformV1beta1Metric', 10, repeated=True) metricxInput = _messages.MessageField('GoogleCloudAiplatformV1beta1MetricxInput', 11) pairwiseMetricInput = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseMetricInput', 12) pairwiseQuestionAnsweringQualityInput = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInput', 13) pairwiseSummarizationQualityInput = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInput', 14) pointwiseMetricInput = _messages.MessageField('GoogleCloudAiplatformV1beta1PointwiseMetricInput', 15) questionAnsweringCorrectnessInput = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInput', 16) questionAnsweringHelpfulnessInput = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInput', 17) questionAnsweringQualityInput = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInput', 18) questionAnsweringRelevanceInput = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInput', 19) rougeInput = _messages.MessageField('GoogleCloudAiplatformV1beta1RougeInput', 20) rubricBasedInstructionFollowingInput = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingInput', 21) safetyInput = _messages.MessageField('GoogleCloudAiplatformV1beta1SafetyInput', 22) summarizationHelpfulnessInput = _messages.MessageField('GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInput', 23) summarizationQualityInput = _messages.MessageField('GoogleCloudAiplatformV1beta1SummarizationQualityInput', 24) summarizationVerbosityInput = _messages.MessageField('GoogleCloudAiplatformV1beta1SummarizationVerbosityInput', 25) toolCallValidInput = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolCallValidInput', 26) toolNameMatchInput = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolNameMatchInput', 27) toolParameterKeyMatchInput = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInput', 28) toolParameterKvMatchInput = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolParameterKVMatchInput', 29) trajectoryAnyOrderMatchInput = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchInput', 30) trajectoryExactMatchInput = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryExactMatchInput', 31) trajectoryInOrderMatchInput = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchInput', 32) trajectoryPrecisionInput = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryPrecisionInput', 33) trajectoryRecallInput = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryRecallInput', 34) trajectorySingleToolUseInput = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectorySingleToolUseInput', 35) class GoogleCloudAiplatformV1beta1EvaluateInstancesResponse(_messages.Message): r"""Response message for EvaluationService.EvaluateInstances. Fields: bleuResults: Results for bleu metric. coherenceResult: Result for coherence metric. cometResult: Translation metrics. Result for Comet metric. exactMatchResults: Auto metric evaluation results. Results for exact match metric. fluencyResult: LLM-based metric evaluation result. General text generation metrics, applicable to other categories. Result for fluency metric. fulfillmentResult: Result for fulfillment metric. groundednessResult: Result for groundedness metric. metricResults: Metric results for each instance. The order of the metric results is guaranteed to be the same as the order of the instances in the request. metricxResult: Result for Metricx metric. pairwiseMetricResult: Result for pairwise metric. pairwiseQuestionAnsweringQualityResult: Result for pairwise question answering quality metric. pairwiseSummarizationQualityResult: Result for pairwise summarization quality metric. pointwiseMetricResult: Generic metrics. Result for pointwise metric. questionAnsweringCorrectnessResult: Result for question answering correctness metric. questionAnsweringHelpfulnessResult: Result for question answering helpfulness metric. questionAnsweringQualityResult: Question answering only metrics. Result for question answering quality metric. questionAnsweringRelevanceResult: Result for question answering relevance metric. rougeResults: Results for rouge metric. rubricBasedInstructionFollowingResult: Result for rubric based instruction following metric. safetyResult: Result for safety metric. summarizationHelpfulnessResult: Result for summarization helpfulness metric. summarizationQualityResult: Summarization only metrics. Result for summarization quality metric. summarizationVerbosityResult: Result for summarization verbosity metric. toolCallValidResults: Tool call metrics. Results for tool call valid metric. toolNameMatchResults: Results for tool name match metric. toolParameterKeyMatchResults: Results for tool parameter key match metric. toolParameterKvMatchResults: Results for tool parameter key value match metric. trajectoryAnyOrderMatchResults: Result for trajectory any order match metric. trajectoryExactMatchResults: Result for trajectory exact match metric. trajectoryInOrderMatchResults: Result for trajectory in order match metric. trajectoryPrecisionResults: Result for trajectory precision metric. trajectoryRecallResults: Results for trajectory recall metric. trajectorySingleToolUseResults: Results for trajectory single tool use metric. """ bleuResults = _messages.MessageField('GoogleCloudAiplatformV1beta1BleuResults', 1) coherenceResult = _messages.MessageField('GoogleCloudAiplatformV1beta1CoherenceResult', 2) cometResult = _messages.MessageField('GoogleCloudAiplatformV1beta1CometResult', 3) exactMatchResults = _messages.MessageField('GoogleCloudAiplatformV1beta1ExactMatchResults', 4) fluencyResult = _messages.MessageField('GoogleCloudAiplatformV1beta1FluencyResult', 5) fulfillmentResult = _messages.MessageField('GoogleCloudAiplatformV1beta1FulfillmentResult', 6) groundednessResult = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundednessResult', 7) metricResults = _messages.MessageField('GoogleCloudAiplatformV1beta1MetricResult', 8, repeated=True) metricxResult = _messages.MessageField('GoogleCloudAiplatformV1beta1MetricxResult', 9) pairwiseMetricResult = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseMetricResult', 10) pairwiseQuestionAnsweringQualityResult = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityResult', 11) pairwiseSummarizationQualityResult = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityResult', 12) pointwiseMetricResult = _messages.MessageField('GoogleCloudAiplatformV1beta1PointwiseMetricResult', 13) questionAnsweringCorrectnessResult = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessResult', 14) questionAnsweringHelpfulnessResult = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessResult', 15) questionAnsweringQualityResult = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringQualityResult', 16) questionAnsweringRelevanceResult = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceResult', 17) rougeResults = _messages.MessageField('GoogleCloudAiplatformV1beta1RougeResults', 18) rubricBasedInstructionFollowingResult = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingResult', 19) safetyResult = _messages.MessageField('GoogleCloudAiplatformV1beta1SafetyResult', 20) summarizationHelpfulnessResult = _messages.MessageField('GoogleCloudAiplatformV1beta1SummarizationHelpfulnessResult', 21) summarizationQualityResult = _messages.MessageField('GoogleCloudAiplatformV1beta1SummarizationQualityResult', 22) summarizationVerbosityResult = _messages.MessageField('GoogleCloudAiplatformV1beta1SummarizationVerbosityResult', 23) toolCallValidResults = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolCallValidResults', 24) toolNameMatchResults = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolNameMatchResults', 25) toolParameterKeyMatchResults = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolParameterKeyMatchResults', 26) toolParameterKvMatchResults = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolParameterKVMatchResults', 27) trajectoryAnyOrderMatchResults = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchResults', 28) trajectoryExactMatchResults = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryExactMatchResults', 29) trajectoryInOrderMatchResults = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchResults', 30) trajectoryPrecisionResults = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryPrecisionResults', 31) trajectoryRecallResults = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryRecallResults', 32) trajectorySingleToolUseResults = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectorySingleToolUseResults', 33) class GoogleCloudAiplatformV1beta1EvaluatedAnnotation(_messages.Message): r"""True positive, false positive, or false negative. EvaluatedAnnotation is only available under ModelEvaluationSlice with slice of `annotationSpec` dimension. Enums: TypeValueValuesEnum: Output only. Type of the EvaluatedAnnotation. Fields: dataItemPayload: Output only. The data item payload that the Model predicted this EvaluatedAnnotation on. errorAnalysisAnnotations: Annotations of model error analysis results. evaluatedDataItemViewId: Output only. ID of the EvaluatedDataItemView under the same ancestor ModelEvaluation. The EvaluatedDataItemView consists of all ground truths and predictions on data_item_payload. explanations: Explanations of predictions. Each element of the explanations indicates the explanation for one explanation Method. The attributions list in the EvaluatedAnnotationExplanation.explanation object corresponds to the predictions list. For example, the second element in the attributions list explains the second element in the predictions list. groundTruths: Output only. The ground truth Annotations, i.e. the Annotations that exist in the test data the Model is evaluated on. For true positive, there is one and only one ground truth annotation, which matches the only prediction in predictions. For false positive, there are zero or more ground truth annotations that are similar to the only prediction in predictions, but not enough for a match. For false negative, there is one and only one ground truth annotation, which doesn't match any predictions created by the model. The schema of the ground truth is stored in ModelEvaluation.annotation_schema_uri predictions: Output only. The model predicted annotations. For true positive, there is one and only one prediction, which matches the only one ground truth annotation in ground_truths. For false positive, there is one and only one prediction, which doesn't match any ground truth annotation of the corresponding data_item_view_id. For false negative, there are zero or more predictions which are similar to the only ground truth annotation in ground_truths but not enough for a match. The schema of the prediction is stored in ModelEvaluation.annotation_schema_uri type: Output only. Type of the EvaluatedAnnotation. """ class TypeValueValuesEnum(_messages.Enum): r"""Output only. Type of the EvaluatedAnnotation. Values: EVALUATED_ANNOTATION_TYPE_UNSPECIFIED: Invalid value. TRUE_POSITIVE: The EvaluatedAnnotation is a true positive. It has a prediction created by the Model and a ground truth Annotation which the prediction matches. FALSE_POSITIVE: The EvaluatedAnnotation is false positive. It has a prediction created by the Model which does not match any ground truth annotation. FALSE_NEGATIVE: The EvaluatedAnnotation is false negative. It has a ground truth annotation which is not matched by any of the model created predictions. """ EVALUATED_ANNOTATION_TYPE_UNSPECIFIED = 0 TRUE_POSITIVE = 1 FALSE_POSITIVE = 2 FALSE_NEGATIVE = 3 dataItemPayload = _messages.MessageField('extra_types.JsonValue', 1) errorAnalysisAnnotations = _messages.MessageField('GoogleCloudAiplatformV1beta1ErrorAnalysisAnnotation', 2, repeated=True) evaluatedDataItemViewId = _messages.StringField(3) explanations = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluatedAnnotationExplanation', 4, repeated=True) groundTruths = _messages.MessageField('extra_types.JsonValue', 5, repeated=True) predictions = _messages.MessageField('extra_types.JsonValue', 6, repeated=True) type = _messages.EnumField('TypeValueValuesEnum', 7) class GoogleCloudAiplatformV1beta1EvaluatedAnnotationExplanation(_messages.Message): r"""Explanation result of the prediction produced by the Model. Fields: explanation: Explanation attribution response details. explanationType: Explanation type. For AutoML Image Classification models, possible values are: * `image-integrated-gradients` * `image-xrai` """ explanation = _messages.MessageField('GoogleCloudAiplatformV1beta1Explanation', 1) explanationType = _messages.StringField(2) class GoogleCloudAiplatformV1beta1EvaluationConfig(_messages.Message): r"""Evaluation Config for Tuning Job. Fields: autoraterConfig: Optional. Autorater config for evaluation. metrics: Required. The metrics used for evaluation. outputConfig: Required. Config for evaluation output. """ autoraterConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AutoraterConfig', 1) metrics = _messages.MessageField('GoogleCloudAiplatformV1beta1Metric', 2, repeated=True) outputConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1OutputConfig', 3) class GoogleCloudAiplatformV1beta1EvaluationDataset(_messages.Message): r"""The dataset used for evaluation. Fields: bigquerySource: BigQuery source holds the dataset. gcsSource: Cloud storage source holds the dataset. Currently only one Cloud Storage file path is supported. """ bigquerySource = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQuerySource', 1) gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsSource', 2) class GoogleCloudAiplatformV1beta1EvaluationInstance(_messages.Message): r"""A single instance to be evaluated. Instances are used to specify the input data for evaluation, from simple string comparisons to complex, multi- turn model evaluations Messages: RubricGroupsValue: Optional. Named groups of rubrics associated with the prompt. This is used for rubric-based evaluations where rubrics can be referenced by a key. The key could represent versions, associated metrics, etc. Fields: agentData: Optional. Data used for agent evaluation. otherData: Optional. Other data used to populate placeholders based on their key. prompt: Optional. Data used to populate placeholder `prompt` in a metric prompt template. reference: Optional. Data used to populate placeholder `reference` in a metric prompt template. response: Optional. Data used to populate placeholder `response` in a metric prompt template. rubricGroups: Optional. Named groups of rubrics associated with the prompt. This is used for rubric-based evaluations where rubrics can be referenced by a key. The key could represent versions, associated metrics, etc. """ @encoding.MapUnrecognizedFields('additionalProperties') class RubricGroupsValue(_messages.Message): r"""Optional. Named groups of rubrics associated with the prompt. This is used for rubric-based evaluations where rubrics can be referenced by a key. The key could represent versions, associated metrics, etc. Messages: AdditionalProperty: An additional property for a RubricGroupsValue object. Fields: additionalProperties: Additional properties of type RubricGroupsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a RubricGroupsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1RubricGroup attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricGroup', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) agentData = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceAgentData', 1) otherData = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceMapInstance', 2) prompt = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData', 3) reference = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData', 4) response = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData', 5) rubricGroups = _messages.MessageField('RubricGroupsValue', 6) class GoogleCloudAiplatformV1beta1EvaluationInstanceAgentConfig(_messages.Message): r"""Configuration for an Agent. Fields: developerInstruction: Optional. A field containing instructions from the developer for the agent. tools: List of tools. toolsText: A JSON string containing a list of tools available to an agent with info such as name, description, parameters and required parameters. """ developerInstruction = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData', 1) tools = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceAgentConfigTools', 2) toolsText = _messages.StringField(3) class GoogleCloudAiplatformV1beta1EvaluationInstanceAgentConfigTools(_messages.Message): r"""Represents a list of tools for an agent. Fields: tool: Optional. List of tools: each tool can have multiple function declarations. """ tool = _messages.MessageField('GoogleCloudAiplatformV1beta1Tool', 1, repeated=True) class GoogleCloudAiplatformV1beta1EvaluationInstanceAgentData(_messages.Message): r"""Contains data specific to agent evaluations. Fields: agentConfig: Optional. Agent configuration. developerInstruction: Optional. A field containing instructions from the developer for the agent. events: A list of events. tools: List of tools. toolsText: A JSON string containing a list of tools available to an agent with info such as name, description, parameters and required parameters. Example: [ { "name": "search_actors", "description": "Search for actors in a movie. Returns a list of actors, their roles, their birthdate, and their place of birth.", "parameters": [ { "name": "movie_name", "description": "The name of the movie." }, { "name": "character_name", "description": "The name of the character." } ], "required": ["movie_name", "character_name"] } ] """ agentConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceAgentConfig', 1) developerInstruction = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData', 2) events = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceAgentDataEvents', 3) tools = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceAgentDataTools', 4) toolsText = _messages.StringField(5) class GoogleCloudAiplatformV1beta1EvaluationInstanceAgentDataEvents(_messages.Message): r"""Represents a list of events for an agent. Fields: event: Optional. A list of events. """ event = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1, repeated=True) class GoogleCloudAiplatformV1beta1EvaluationInstanceAgentDataTools(_messages.Message): r"""Represents a list of tools for an agent. Fields: tool: Optional. List of tools: each tool can have multiple function declarations. """ tool = _messages.MessageField('GoogleCloudAiplatformV1beta1Tool', 1, repeated=True) class GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData(_messages.Message): r"""Instance data used to populate placeholders in a metric prompt template. Fields: contents: List of Gemini content data. text: Text data. """ contents = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceDataContents', 1) text = _messages.StringField(2) class GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceDataContents(_messages.Message): r"""List of standard Content messages from Gemini API. Fields: contents: Optional. Repeated contents. """ contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1, repeated=True) class GoogleCloudAiplatformV1beta1EvaluationInstanceMapInstance(_messages.Message): r"""Instance data specified as a map. Messages: MapInstanceValue: Optional. Map of instance data. Fields: mapInstance: Optional. Map of instance data. """ @encoding.MapUnrecognizedFields('additionalProperties') class MapInstanceValue(_messages.Message): r"""Optional. Map of instance data. Messages: AdditionalProperty: An additional property for a MapInstanceValue object. Fields: additionalProperties: Additional properties of type MapInstanceValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a MapInstanceValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceInstanceData', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) mapInstance = _messages.MessageField('MapInstanceValue', 1) class GoogleCloudAiplatformV1beta1EvaluationItem(_messages.Message): r"""EvaluationItem is a single evaluation request or result. The content of an EvaluationItem is immutable - it cannot be updated once created. EvaluationItems can be deleted when no longer needed. Enums: EvaluationItemTypeValueValuesEnum: Required. The type of the EvaluationItem. Messages: LabelsValue: Optional. Labels for the EvaluationItem. Fields: createTime: Output only. Timestamp when this item was created. displayName: Required. The display name of the EvaluationItem. error: Output only. Error for the evaluation item. evaluationItemType: Required. The type of the EvaluationItem. evaluationRequest: The request to evaluate. evaluationResponse: Output only. The response from evaluation. gcsUri: The Cloud Storage object where the request or response is stored. labels: Optional. Labels for the EvaluationItem. metadata: Optional. Metadata for the EvaluationItem. name: Identifier. The resource name of the EvaluationItem. Format: `projec ts/{project}/locations/{location}/evaluationItems/{evaluation_item}` """ class EvaluationItemTypeValueValuesEnum(_messages.Enum): r"""Required. The type of the EvaluationItem. Values: EVALUATION_ITEM_TYPE_UNSPECIFIED: The default value. This value is unused. REQUEST: The EvaluationItem is a request to evaluate. RESULT: The EvaluationItem is the result of evaluation. """ EVALUATION_ITEM_TYPE_UNSPECIFIED = 0 REQUEST = 1 RESULT = 2 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. Labels for the EvaluationItem. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) displayName = _messages.StringField(2) error = _messages.MessageField('GoogleRpcStatus', 3) evaluationItemType = _messages.EnumField('EvaluationItemTypeValueValuesEnum', 4) evaluationRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRequest', 5) evaluationResponse = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationResult', 6) gcsUri = _messages.StringField(7) labels = _messages.MessageField('LabelsValue', 8) metadata = _messages.MessageField('extra_types.JsonValue', 9) name = _messages.StringField(10) class GoogleCloudAiplatformV1beta1EvaluationPrompt(_messages.Message): r"""Prompt to be evaluated. Fields: promptTemplateData: Prompt template data. text: Text prompt. value: Fields and values that can be used to populate the prompt template. """ promptTemplateData = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationPromptPromptTemplateData', 1) text = _messages.StringField(2) value = _messages.MessageField('extra_types.JsonValue', 3) class GoogleCloudAiplatformV1beta1EvaluationPromptPromptTemplateData(_messages.Message): r"""Message to hold a prompt template and the values to populate the template. Messages: ValuesValue: The values for fields in the prompt template. Fields: values: The values for fields in the prompt template. """ @encoding.MapUnrecognizedFields('additionalProperties') class ValuesValue(_messages.Message): r"""The values for fields in the prompt template. Messages: AdditionalProperty: An additional property for a ValuesValue object. Fields: additionalProperties: Additional properties of type ValuesValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ValuesValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1Content attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) values = _messages.MessageField('ValuesValue', 1) class GoogleCloudAiplatformV1beta1EvaluationRequest(_messages.Message): r"""Single evaluation request. Messages: RubricsValue: Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group. Fields: candidateResponses: Optional. Responses from model under test and other baseline models for comparison. goldenResponse: Optional. The Ideal response or ground truth. prompt: Required. The request/prompt to evaluate. rubrics: Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group. """ @encoding.MapUnrecognizedFields('additionalProperties') class RubricsValue(_messages.Message): r"""Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group. Messages: AdditionalProperty: An additional property for a RubricsValue object. Fields: additionalProperties: Additional properties of type RubricsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a RubricsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1RubricGroup attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricGroup', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) candidateResponses = _messages.MessageField('GoogleCloudAiplatformV1beta1CandidateResponse', 1, repeated=True) goldenResponse = _messages.MessageField('GoogleCloudAiplatformV1beta1CandidateResponse', 2) prompt = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationPrompt', 3) rubrics = _messages.MessageField('RubricsValue', 4) class GoogleCloudAiplatformV1beta1EvaluationResult(_messages.Message): r"""Evaluation result. Fields: candidateResults: Optional. The results for the metric. evaluationRequest: Required. The request item that was evaluated. Format: projects/{project}/locations/{location}/evaluationItems/{evaluation_item } evaluationRun: Required. The evaluation run that was used to generate the result. Format: projects/{project}/locations/{location}/evaluationRuns/{evaluation_run} metadata: Optional. Metadata about the evaluation result. metric: Required. The metric that was evaluated. request: Required. The request that was evaluated. """ candidateResults = _messages.MessageField('GoogleCloudAiplatformV1beta1CandidateResult', 1, repeated=True) evaluationRequest = _messages.StringField(2) evaluationRun = _messages.StringField(3) metadata = _messages.MessageField('extra_types.JsonValue', 4) metric = _messages.StringField(5) request = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRequest', 6) class GoogleCloudAiplatformV1beta1EvaluationResults(_messages.Message): r"""The results of the evaluation run. Fields: evaluationSet: The evaluation set where item level results are stored. summaryMetrics: Optional. The summary metrics for the evaluation run. """ evaluationSet = _messages.StringField(1) summaryMetrics = _messages.MessageField('GoogleCloudAiplatformV1beta1SummaryMetrics', 2) class GoogleCloudAiplatformV1beta1EvaluationRubricConfig(_messages.Message): r"""Configuration for a rubric group to be generated/saved for evaluation. Fields: predefinedRubricGenerationSpec: Dynamically generate rubrics using a predefined spec. rubricGenerationSpec: Dynamically generate rubrics using this specification. rubricGroupKey: Required. The key used to save the generated rubrics. If a generation spec is provided, this key will be used for the name of the generated rubric group. Otherwise, this key will be used to look up the existing rubric group on the evaluation item. Note that if a rubric group key is specified on both a rubric config and an evaluation metric, the key from the metric will be used to select the rubrics for evaluation. """ predefinedRubricGenerationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunMetricPredefinedMetricSpec', 1) rubricGenerationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricGenerationSpec', 2) rubricGroupKey = _messages.StringField(3) class GoogleCloudAiplatformV1beta1EvaluationRun(_messages.Message): r"""EvaluationRun is a resource that represents a single evaluation run, which includes a set of prompts, model responses, evaluation configuration and the resulting metrics. Enums: StateValueValuesEnum: Output only. The state of the evaluation run. Messages: InferenceConfigsValue: Optional. The candidate to inference config map for the evaluation run. The candidate can be up to 128 characters long and can consist of any UTF-8 characters. LabelsValue: Optional. Labels for the evaluation run. Fields: completionTime: Output only. Time when the evaluation run was completed. createTime: Output only. Time when the evaluation run was created. dataSource: Required. The data source for the evaluation run. displayName: Required. The display name of the Evaluation Run. error: Output only. Only populated when the evaluation run's state is FAILED or CANCELLED. evaluationConfig: Required. The configuration used for the evaluation. evaluationResults: Output only. The results of the evaluation run. Only populated when the evaluation run's state is SUCCEEDED. evaluationSetSnapshot: Output only. The specific evaluation set of the evaluation run. For runs with an evaluation set input, this will be that same set. For runs with BigQuery input, it's the sampled BigQuery dataset. inferenceConfigs: Optional. The candidate to inference config map for the evaluation run. The candidate can be up to 128 characters long and can consist of any UTF-8 characters. labels: Optional. Labels for the evaluation run. metadata: Optional. Metadata about the evaluation run, can be used by the caller to store additional tracking information about the evaluation run. name: Identifier. The resource name of the EvaluationRun. This is a unique identifier. Format: `projects/{project}/locations/{location}/evaluationR uns/{evaluation_run}` state: Output only. The state of the evaluation run. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The state of the evaluation run. Values: STATE_UNSPECIFIED: Unspecified state. PENDING: The evaluation run is pending. RUNNING: The evaluation run is running. SUCCEEDED: The evaluation run has succeeded. FAILED: The evaluation run has failed. CANCELLED: The evaluation run has been cancelled. INFERENCE: The evaluation run is performing inference. GENERATING_RUBRICS: The evaluation run is performing rubric generation. """ STATE_UNSPECIFIED = 0 PENDING = 1 RUNNING = 2 SUCCEEDED = 3 FAILED = 4 CANCELLED = 5 INFERENCE = 6 GENERATING_RUBRICS = 7 @encoding.MapUnrecognizedFields('additionalProperties') class InferenceConfigsValue(_messages.Message): r"""Optional. The candidate to inference config map for the evaluation run. The candidate can be up to 128 characters long and can consist of any UTF-8 characters. Messages: AdditionalProperty: An additional property for a InferenceConfigsValue object. Fields: additionalProperties: Additional properties of type InferenceConfigsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a InferenceConfigsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfig attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfig', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. Labels for the evaluation run. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) completionTime = _messages.StringField(1) createTime = _messages.StringField(2) dataSource = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunDataSource', 3) displayName = _messages.StringField(4) error = _messages.MessageField('GoogleRpcStatus', 5) evaluationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfig', 6) evaluationResults = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationResults', 7) evaluationSetSnapshot = _messages.StringField(8) inferenceConfigs = _messages.MessageField('InferenceConfigsValue', 9) labels = _messages.MessageField('LabelsValue', 10) metadata = _messages.MessageField('extra_types.JsonValue', 11) name = _messages.StringField(12) state = _messages.EnumField('StateValueValuesEnum', 13) class GoogleCloudAiplatformV1beta1EvaluationRunDataSource(_messages.Message): r"""The data source for the evaluation run. Fields: bigqueryRequestSet: Evaluation data in bigquery. evaluationSet: The EvaluationSet resource name. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set} ` """ bigqueryRequestSet = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQueryRequestSet', 1) evaluationSet = _messages.StringField(2) class GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfig(_messages.Message): r"""The Evalution configuration used for the evaluation run. Fields: autoraterConfig: Optional. The autorater config for the evaluation run. metrics: Required. The metrics to be calculated in the evaluation run. outputConfig: Optional. The output config for the evaluation run. promptTemplate: The prompt template used for inference. The values for variables in the prompt template are defined in EvaluationItem.EvaluationPrompt.PromptTemplateData.values. rubricConfigs: Optional. The rubric configs for the evaluation run. They are used to generate rubrics which can be used by rubric-based metrics. Multiple rubric configs can be specified for rubric generation but only one rubric config can be used for a rubric-based metric. If more than one rubric config is provided, the evaluation metric must specify a rubric group key. Note that if a generation spec is specified on both a rubric config and an evaluation metric, the rubrics generated for the metric will be used for evaluation. """ autoraterConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigAutoraterConfig', 1) metrics = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunMetric', 2, repeated=True) outputConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigOutputConfig', 3) promptTemplate = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigPromptTemplate', 4) rubricConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRubricConfig', 5, repeated=True) class GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigAutoraterConfig(_messages.Message): r"""The autorater config used for the evaluation run. Fields: autoraterModel: Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` generationConfig: Optional. Configuration options for model generation and outputs. sampleCount: Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32. """ autoraterModel = _messages.StringField(1) generationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerationConfig', 2) sampleCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigOutputConfig(_messages.Message): r"""The output config for the evaluation run. Fields: bigqueryDestination: BigQuery destination for evaluation output. gcsDestination: Cloud Storage destination for evaluation output. """ bigqueryDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQueryDestination', 1) gcsDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 2) class GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigPromptTemplate(_messages.Message): r"""Prompt template used for inference. Fields: gcsUri: Prompt template stored in Cloud Storage. Format: "gs://my- bucket/file-name.txt". promptTemplate: Inline prompt template. Template variables should be in the format "{var_name}". Example: "Translate the following from {source_lang} to {target_lang}: {text}" """ gcsUri = _messages.StringField(1) promptTemplate = _messages.StringField(2) class GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfig(_messages.Message): r"""An inference config used for model inference during the evaluation run. Fields: agentConfig: Optional. Agent config used to generate responses. generationConfig: Optional. Generation config. model: Optional. The fully qualified name of the publisher model or endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` """ agentConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigAgentConfig', 1) generationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerationConfig', 2) model = _messages.StringField(3) class GoogleCloudAiplatformV1beta1EvaluationRunInferenceConfigAgentConfig(_messages.Message): r"""Configuration that describes an agent. Fields: developerInstruction: Optional. The developer instruction for the agent. tools: Optional. The tools available to the agent. """ developerInstruction = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1) tools = _messages.MessageField('GoogleCloudAiplatformV1beta1Tool', 2, repeated=True) class GoogleCloudAiplatformV1beta1EvaluationRunMetric(_messages.Message): r"""The metric used for evaluation runs. Fields: llmBasedMetricSpec: Spec for an LLM based metric. metric: Required. The name of the metric. metricConfig: The metric config. predefinedMetricSpec: Spec for a pre-defined metric. rubricBasedMetricSpec: Spec for rubric based metric. """ llmBasedMetricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunMetricLLMBasedMetricSpec', 1) metric = _messages.StringField(2) metricConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1Metric', 3) predefinedMetricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunMetricPredefinedMetricSpec', 4) rubricBasedMetricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricBasedMetricSpec', 5) class GoogleCloudAiplatformV1beta1EvaluationRunMetricLLMBasedMetricSpec(_messages.Message): r"""Specification for an LLM based metric. Messages: AdditionalConfigValue: Optional. Optional additional configuration for the metric. Fields: additionalConfig: Optional. Optional additional configuration for the metric. judgeAutoraterConfig: Optional. Optional configuration for the judge LLM (Autorater). metricPromptTemplate: Required. Template for the prompt sent to the judge model. predefinedRubricGenerationSpec: Dynamically generate rubrics using a predefined spec. rubricGenerationSpec: Dynamically generate rubrics using this specification. rubricGroupKey: Use a pre-defined group of rubrics associated with the input. Refers to a key in the rubric_groups map of EvaluationInstance. systemInstruction: Optional. System instructions for the judge model. """ @encoding.MapUnrecognizedFields('additionalProperties') class AdditionalConfigValue(_messages.Message): r"""Optional. Optional additional configuration for the metric. Messages: AdditionalProperty: An additional property for a AdditionalConfigValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a AdditionalConfigValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) additionalConfig = _messages.MessageField('AdditionalConfigValue', 1) judgeAutoraterConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigAutoraterConfig', 2) metricPromptTemplate = _messages.StringField(3) predefinedRubricGenerationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunMetricPredefinedMetricSpec', 4) rubricGenerationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricGenerationSpec', 5) rubricGroupKey = _messages.StringField(6) systemInstruction = _messages.StringField(7) class GoogleCloudAiplatformV1beta1EvaluationRunMetricPredefinedMetricSpec(_messages.Message): r"""Specification for a pre-defined metric. Messages: ParametersValue: Optional. The parameters needed to run the pre-defined metric. Fields: metricSpecName: Required. The name of a pre-defined metric, such as "instruction_following_v1" or "text_quality_v1". parameters: Optional. The parameters needed to run the pre-defined metric. """ @encoding.MapUnrecognizedFields('additionalProperties') class ParametersValue(_messages.Message): r"""Optional. The parameters needed to run the pre-defined metric. Messages: AdditionalProperty: An additional property for a ParametersValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a ParametersValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) metricSpecName = _messages.StringField(1) parameters = _messages.MessageField('ParametersValue', 2) class GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricBasedMetricSpec(_messages.Message): r"""Specification for a metric that is based on rubrics. Fields: inlineRubrics: Use rubrics provided directly in the spec. judgeAutoraterConfig: Optional. Optional configuration for the judge LLM (Autorater). The definition of AutoraterConfig needs to be provided. metricPromptTemplate: Optional. Template for the prompt used by the judge model to evaluate against rubrics. rubricGenerationSpec: Dynamically generate rubrics for evaluation using this specification. rubricGroupKey: Use a pre-defined group of rubrics associated with the input content. This refers to a key in the `rubric_groups` map of `RubricEnhancedContents`. """ inlineRubrics = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricBasedMetricSpecRepeatedRubrics', 1) judgeAutoraterConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigAutoraterConfig', 2) metricPromptTemplate = _messages.StringField(3) rubricGenerationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricGenerationSpec', 4) rubricGroupKey = _messages.StringField(5) class GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricBasedMetricSpecRepeatedRubrics(_messages.Message): r"""Defines a list of rubrics, used when providing rubrics inline. Fields: rubrics: The list of rubrics. """ rubrics = _messages.MessageField('GoogleCloudAiplatformV1beta1Rubric', 1, repeated=True) class GoogleCloudAiplatformV1beta1EvaluationRunMetricRubricGenerationSpec(_messages.Message): r"""Specification for how rubrics should be generated. Enums: RubricContentTypeValueValuesEnum: Optional. The type of rubric content to be generated. Fields: modelConfig: Optional. Configuration for the model used in rubric generation. Configs including sampling count and base model can be specified here. Flipping is not supported for rubric generation. promptTemplate: Optional. Template for the prompt used to generate rubrics. The details should be updated based on the most-recent recipe requirements. rubricContentType: Optional. The type of rubric content to be generated. rubricTypeOntology: Optional. An optional, pre-defined list of allowed types for generated rubrics. If this field is provided, it implies `include_rubric_type` should be true, and the generated rubric types should be chosen from this ontology. """ class RubricContentTypeValueValuesEnum(_messages.Enum): r"""Optional. The type of rubric content to be generated. Values: RUBRIC_CONTENT_TYPE_UNSPECIFIED: The content type to generate is not specified. PROPERTY: Generate rubrics based on properties. NL_QUESTION_ANSWER: Generate rubrics in an NL question answer format. PYTHON_CODE_ASSERTION: Generate rubrics in a unit test format. """ RUBRIC_CONTENT_TYPE_UNSPECIFIED = 0 PROPERTY = 1 NL_QUESTION_ANSWER = 2 PYTHON_CODE_ASSERTION = 3 modelConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRunEvaluationConfigAutoraterConfig', 1) promptTemplate = _messages.StringField(2) rubricContentType = _messages.EnumField('RubricContentTypeValueValuesEnum', 3) rubricTypeOntology = _messages.StringField(4, repeated=True) class GoogleCloudAiplatformV1beta1EvaluationSet(_messages.Message): r"""EvaluationSet is a collection of related EvaluationItems that are evaluated together. Fields: createTime: Output only. Timestamp when this item was created. displayName: Required. The display name of the EvaluationSet. evaluationItems: Required. The EvaluationItems that are part of this dataset. metadata: Optional. Metadata for the EvaluationSet. name: Identifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set} ` updateTime: Output only. Timestamp when this item was last updated. """ createTime = _messages.StringField(1) displayName = _messages.StringField(2) evaluationItems = _messages.StringField(3, repeated=True) metadata = _messages.MessageField('extra_types.JsonValue', 4) name = _messages.StringField(5) updateTime = _messages.StringField(6) class GoogleCloudAiplatformV1beta1Event(_messages.Message): r"""An edge describing the relationship between an Artifact and an Execution in a lineage graph. Enums: TypeValueValuesEnum: Required. The type of the Event. Messages: LabelsValue: The labels with user-defined metadata to annotate Events. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Event (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: artifact: Required. The relative resource name of the Artifact in the Event. eventTime: Output only. Time the Event occurred. execution: Output only. The relative resource name of the Execution in the Event. labels: The labels with user-defined metadata to annotate Events. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Event (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. type: Required. The type of the Event. """ class TypeValueValuesEnum(_messages.Enum): r"""Required. The type of the Event. Values: TYPE_UNSPECIFIED: Unspecified whether input or output of the Execution. INPUT: An input of the Execution. OUTPUT: An output of the Execution. """ TYPE_UNSPECIFIED = 0 INPUT = 1 OUTPUT = 2 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to annotate Events. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Event (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) artifact = _messages.StringField(1) eventTime = _messages.StringField(2) execution = _messages.StringField(3) labels = _messages.MessageField('LabelsValue', 4) type = _messages.EnumField('TypeValueValuesEnum', 5) class GoogleCloudAiplatformV1beta1EventActions(_messages.Message): r"""Actions are parts of events that are executed by the agent. Messages: ArtifactDeltaValue: Optional. Indicates that the event is updating an artifact. key is the filename, value is the version. RequestedAuthConfigsValue: Optional. Will only be set by a tool response indicating tool request euc. Struct key is the function call id since one function call response (from model) could correspond to multiple function calls. Struct value is the required auth config, which can be another struct. StateDeltaValue: Optional. Indicates that the event is updating the state with the given delta. Fields: artifactDelta: Optional. Indicates that the event is updating an artifact. key is the filename, value is the version. escalate: Optional. The agent is escalating to a higher level agent. requestedAuthConfigs: Optional. Will only be set by a tool response indicating tool request euc. Struct key is the function call id since one function call response (from model) could correspond to multiple function calls. Struct value is the required auth config, which can be another struct. skipSummarization: Optional. If true, it won't call model to summarize function response. Only used for function_response event. stateDelta: Optional. Indicates that the event is updating the state with the given delta. transferAgent: Optional. If set, the event transfers to the specified agent. """ @encoding.MapUnrecognizedFields('additionalProperties') class ArtifactDeltaValue(_messages.Message): r"""Optional. Indicates that the event is updating an artifact. key is the filename, value is the version. Messages: AdditionalProperty: An additional property for a ArtifactDeltaValue object. Fields: additionalProperties: Additional properties of type ArtifactDeltaValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ArtifactDeltaValue object. Fields: key: Name of the additional property. value: A integer attribute. """ key = _messages.StringField(1) value = _messages.IntegerField(2, variant=_messages.Variant.INT32) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class RequestedAuthConfigsValue(_messages.Message): r"""Optional. Will only be set by a tool response indicating tool request euc. Struct key is the function call id since one function call response (from model) could correspond to multiple function calls. Struct value is the required auth config, which can be another struct. Messages: AdditionalProperty: An additional property for a RequestedAuthConfigsValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a RequestedAuthConfigsValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class StateDeltaValue(_messages.Message): r"""Optional. Indicates that the event is updating the state with the given delta. Messages: AdditionalProperty: An additional property for a StateDeltaValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a StateDeltaValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) artifactDelta = _messages.MessageField('ArtifactDeltaValue', 1) escalate = _messages.BooleanField(2) requestedAuthConfigs = _messages.MessageField('RequestedAuthConfigsValue', 3) skipSummarization = _messages.BooleanField(4) stateDelta = _messages.MessageField('StateDeltaValue', 5) transferAgent = _messages.StringField(6) class GoogleCloudAiplatformV1beta1EventMetadata(_messages.Message): r"""Metadata relating to a LLM response event. Messages: CustomMetadataValue: The custom metadata of the LlmResponse. Fields: branch: Optional. The branch of the event. The format is like agent_1.agent_2.agent_3, where agent_1 is the parent of agent_2, and agent_2 is the parent of agent_3. Branch is used when multiple child agents shouldn't see their siblings' conversation history. customMetadata: The custom metadata of the LlmResponse. groundingMetadata: Optional. Metadata returned to client when grounding is enabled. interrupted: Optional. Flag indicating that LLM was interrupted when generating the content. Usually it's due to user interruption during a bidi streaming. longRunningToolIds: Optional. Set of ids of the long running function calls. Agent client will know from this field about which function call is long running. Only valid for function call event. partial: Optional. Indicates whether the text content is part of a unfinished text stream. Only used for streaming mode and when the content is plain text. turnComplete: Optional. Indicates whether the response from the model is complete. Only used for streaming mode. """ @encoding.MapUnrecognizedFields('additionalProperties') class CustomMetadataValue(_messages.Message): r"""The custom metadata of the LlmResponse. Messages: AdditionalProperty: An additional property for a CustomMetadataValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a CustomMetadataValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) branch = _messages.StringField(1) customMetadata = _messages.MessageField('CustomMetadataValue', 2) groundingMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundingMetadata', 3) interrupted = _messages.BooleanField(4) longRunningToolIds = _messages.StringField(5, repeated=True) partial = _messages.BooleanField(6) turnComplete = _messages.BooleanField(7) class GoogleCloudAiplatformV1beta1ExactMatchInput(_messages.Message): r"""Input for exact match metric. Fields: instances: Required. Repeated exact match instances. metricSpec: Required. Spec for exact match metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1ExactMatchInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ExactMatchSpec', 2) class GoogleCloudAiplatformV1beta1ExactMatchInstance(_messages.Message): r"""Spec for exact match instance. Fields: prediction: Required. Output of the evaluated model. reference: Required. Ground truth used to compare against the prediction. """ prediction = _messages.StringField(1) reference = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ExactMatchMetricValue(_messages.Message): r"""Exact match metric value for an instance. Fields: score: Output only. Exact match score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1ExactMatchResults(_messages.Message): r"""Results for exact match metric. Fields: exactMatchMetricValues: Output only. Exact match metric values. """ exactMatchMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1ExactMatchMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1ExactMatchSpec(_messages.Message): r"""Spec for exact match metric - returns 1 if prediction and reference exactly matches, otherwise 0. """ class GoogleCloudAiplatformV1beta1Example(_messages.Message): r"""A GoogleCloudAiplatformV1beta1Example object. Fields: createTime: Output only. Timestamp when this Example was created. displayName: Optional. The display name for Example. exampleId: Optional. Immutable. Unique identifier of an example. If not specified when upserting new examples, the example_id will be generated. storedContentsExample: An example of chat history and its expected outcome to be used with GenerateContent. """ createTime = _messages.StringField(1) displayName = _messages.StringField(2) exampleId = _messages.StringField(3) storedContentsExample = _messages.MessageField('GoogleCloudAiplatformV1beta1StoredContentsExample', 4) class GoogleCloudAiplatformV1beta1ExampleStore(_messages.Message): r"""Represents an executable service to manage and retrieve examples. Fields: createTime: Output only. Timestamp when this ExampleStore was created. description: Optional. Description of the ExampleStore. displayName: Required. Display name of the ExampleStore. exampleStoreConfig: Required. Example Store config. name: Identifier. The resource name of the ExampleStore. This is a unique identifier. Format: projects/{project}/locations/{location}/exampleStores/{example_store} updateTime: Output only. Timestamp when this ExampleStore was most recently updated. """ createTime = _messages.StringField(1) description = _messages.StringField(2) displayName = _messages.StringField(3) exampleStoreConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ExampleStoreConfig', 4) name = _messages.StringField(5) updateTime = _messages.StringField(6) class GoogleCloudAiplatformV1beta1ExampleStoreConfig(_messages.Message): r"""Configuration for the Example Store. Fields: vertexEmbeddingModel: Required. The embedding model to be used for vector embedding. Immutable. Supported models: * "text-embedding-005" * "text- multilingual-embedding-002" """ vertexEmbeddingModel = _messages.StringField(1) class GoogleCloudAiplatformV1beta1Examples(_messages.Message): r"""Example-based explainability that returns the nearest neighbors from the provided dataset. Fields: exampleGcsSource: The Cloud Storage input instances. gcsSource: The Cloud Storage locations that contain the instances to be indexed for approximate nearest neighbor search. nearestNeighborSearchConfig: The full configuration for the generated index, the semantics are the same as metadata and should match [NearestNeighborSearchConfig](https://cloud.google.com/vertex- ai/docs/explainable-ai/configuring-explanations-example-based#nearest- neighbor-search-config). neighborCount: The number of neighbors to return when querying for examples. presets: Simplified preset configuration, which automatically sets configuration values based on the desired query speed-precision trade- off and modality. """ exampleGcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1ExamplesExampleGcsSource', 1) gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsSource', 2) nearestNeighborSearchConfig = _messages.MessageField('extra_types.JsonValue', 3) neighborCount = _messages.IntegerField(4, variant=_messages.Variant.INT32) presets = _messages.MessageField('GoogleCloudAiplatformV1beta1Presets', 5) class GoogleCloudAiplatformV1beta1ExamplesArrayFilter(_messages.Message): r"""Filters for examples' array metadata fields. An array field is example metadata where multiple values are attributed to a single example. Enums: ArrayOperatorValueValuesEnum: Required. The operator logic to use for filtering. Fields: arrayOperator: Required. The operator logic to use for filtering. values: Required. The values by which to filter examples. """ class ArrayOperatorValueValuesEnum(_messages.Enum): r"""Required. The operator logic to use for filtering. Values: ARRAY_OPERATOR_UNSPECIFIED: Not specified. This value should not be used. CONTAINS_ANY: The metadata array field in the example must contain at least one of the values. CONTAINS_ALL: The metadata array field in the example must contain all of the values. """ ARRAY_OPERATOR_UNSPECIFIED = 0 CONTAINS_ANY = 1 CONTAINS_ALL = 2 arrayOperator = _messages.EnumField('ArrayOperatorValueValuesEnum', 1) values = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1ExamplesExampleGcsSource(_messages.Message): r"""The Cloud Storage input instances. Enums: DataFormatValueValuesEnum: The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported. Fields: dataFormat: The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported. gcsSource: The Cloud Storage location for the input instances. """ class DataFormatValueValuesEnum(_messages.Enum): r"""The format in which instances are given, if not specified, assume it's JSONL format. Currently only JSONL format is supported. Values: DATA_FORMAT_UNSPECIFIED: Format unspecified, used when unset. JSONL: Examples are stored in JSONL files. """ DATA_FORMAT_UNSPECIFIED = 0 JSONL = 1 dataFormat = _messages.EnumField('DataFormatValueValuesEnum', 1) gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsSource', 2) class GoogleCloudAiplatformV1beta1ExamplesOverride(_messages.Message): r"""Overrides for example-based explanations. Enums: DataFormatValueValuesEnum: The format of the data being provided with each call. Fields: crowdingCount: The number of neighbors to return that have the same crowding tag. dataFormat: The format of the data being provided with each call. neighborCount: The number of neighbors to return. restrictions: Restrict the resulting nearest neighbors to respect these constraints. returnEmbeddings: If true, return the embeddings instead of neighbors. """ class DataFormatValueValuesEnum(_messages.Enum): r"""The format of the data being provided with each call. Values: DATA_FORMAT_UNSPECIFIED: Unspecified format. Must not be used. INSTANCES: Provided data is a set of model inputs. EMBEDDINGS: Provided data is a set of embeddings. """ DATA_FORMAT_UNSPECIFIED = 0 INSTANCES = 1 EMBEDDINGS = 2 crowdingCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) dataFormat = _messages.EnumField('DataFormatValueValuesEnum', 2) neighborCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) restrictions = _messages.MessageField('GoogleCloudAiplatformV1beta1ExamplesRestrictionsNamespace', 4, repeated=True) returnEmbeddings = _messages.BooleanField(5) class GoogleCloudAiplatformV1beta1ExamplesRestrictionsNamespace(_messages.Message): r"""Restrictions namespace for example-based explanations overrides. Fields: allow: The list of allowed tags. deny: The list of deny tags. namespaceName: The namespace name. """ allow = _messages.StringField(1, repeated=True) deny = _messages.StringField(2, repeated=True) namespaceName = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ExecutableCode(_messages.Message): r"""Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the [CodeExecution] tool, in which the code will be automatically executed, and a corresponding [CodeExecutionResult] will also be generated. Enums: LanguageValueValuesEnum: Required. Programming language of the `code`. Fields: code: Required. The code to be executed. language: Required. Programming language of the `code`. """ class LanguageValueValuesEnum(_messages.Enum): r"""Required. Programming language of the `code`. Values: LANGUAGE_UNSPECIFIED: Unspecified language. This value should not be used. PYTHON: Python >= 3.10, with numpy and simpy available. """ LANGUAGE_UNSPECIFIED = 0 PYTHON = 1 code = _messages.StringField(1) language = _messages.EnumField('LanguageValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1ExecuteCodeRequest(_messages.Message): r"""Request message for SandboxEnvironmentExecutionService.ExecuteCode. Fields: inputs: Required. The inputs used for the stateless code execution. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1Chunk', 1, repeated=True) class GoogleCloudAiplatformV1beta1ExecuteCodeResponse(_messages.Message): r"""Response message for SandboxEnvironmentExecutionService.ExecuteCode. Fields: outputs: The outputs from the sandbox environment. """ outputs = _messages.MessageField('GoogleCloudAiplatformV1beta1Chunk', 1, repeated=True) class GoogleCloudAiplatformV1beta1ExecuteExtensionRequest(_messages.Message): r"""Request message for ExtensionExecutionService.ExecuteExtension. Messages: OperationParamsValue: Optional. Request parameters that will be used for executing this operation. The struct should be in a form of map with param name as the key and actual param value as the value. E.g. If this operation requires a param "name" to be set to "abc". you can set this to something like {"name": "abc"}. Fields: operationId: Required. The desired ID of the operation to be executed in this extension as defined in ExtensionOperation.operation_id. operationParams: Optional. Request parameters that will be used for executing this operation. The struct should be in a form of map with param name as the key and actual param value as the value. E.g. If this operation requires a param "name" to be set to "abc". you can set this to something like {"name": "abc"}. runtimeAuthConfig: Optional. Auth config provided at runtime to override the default value in Extension.manifest.auth_config. The AuthConfig.auth_type should match the value in Extension.manifest.auth_config. """ @encoding.MapUnrecognizedFields('additionalProperties') class OperationParamsValue(_messages.Message): r"""Optional. Request parameters that will be used for executing this operation. The struct should be in a form of map with param name as the key and actual param value as the value. E.g. If this operation requires a param "name" to be set to "abc". you can set this to something like {"name": "abc"}. Messages: AdditionalProperty: An additional property for a OperationParamsValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a OperationParamsValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) operationId = _messages.StringField(1) operationParams = _messages.MessageField('OperationParamsValue', 2) runtimeAuthConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AuthConfig', 3) class GoogleCloudAiplatformV1beta1ExecuteExtensionResponse(_messages.Message): r"""Response message for ExtensionExecutionService.ExecuteExtension. Fields: content: Response content from the extension. The content should be conformant to the response.content schema in the extension's manifest/OpenAPI spec. """ content = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentRequest(_messages.Message): r"""Request message for SandboxEnvironmentExecutionService.Execute. Fields: inputs: Required. The inputs to the sandbox environment. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1Chunk', 1, repeated=True) class GoogleCloudAiplatformV1beta1ExecuteSandboxEnvironmentResponse(_messages.Message): r"""Response message for SandboxEnvironmentExecutionService.Execute. Fields: outputs: The outputs from the sandbox environment. """ outputs = _messages.MessageField('GoogleCloudAiplatformV1beta1Chunk', 1, repeated=True) class GoogleCloudAiplatformV1beta1Execution(_messages.Message): r"""Instance of a general execution. Enums: StateValueValuesEnum: The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions. Messages: LabelsValue: The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded). MetadataValue: Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB. Fields: createTime: Output only. Timestamp when this Execution was created. description: Description of the Execution displayName: User provided display name of the Execution. May be up to 128 Unicode characters. etag: An eTag used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded). metadata: Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB. name: Output only. The resource name of the Execution. schemaTitle: The title of the schema describing the metadata. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store. schemaVersion: The version of the schema in `schema_title` to use. Schema title and version is expected to be registered in earlier Create Schema calls. And both are used together as unique identifiers to identify schemas within the local metadata store. state: The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions. updateTime: Output only. Timestamp when this Execution was last updated. """ class StateValueValuesEnum(_messages.Enum): r"""The state of this Execution. This is a property of the Execution, and does not imply or capture any ongoing process. This property is managed by clients (such as Vertex AI Pipelines) and the system does not prescribe or check the validity of state transitions. Values: STATE_UNSPECIFIED: Unspecified Execution state NEW: The Execution is new RUNNING: The Execution is running COMPLETE: The Execution has finished running FAILED: The Execution has failed CACHED: The Execution completed through Cache hit. CANCELLED: The Execution was cancelled. """ STATE_UNSPECIFIED = 0 NEW = 1 RUNNING = 2 COMPLETE = 3 FAILED = 4 CACHED = 5 CANCELLED = 6 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your Executions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Execution (System labels are excluded). Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class MetadataValue(_messages.Message): r"""Properties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB. Messages: AdditionalProperty: An additional property for a MetadataValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a MetadataValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) description = _messages.StringField(2) displayName = _messages.StringField(3) etag = _messages.StringField(4) labels = _messages.MessageField('LabelsValue', 5) metadata = _messages.MessageField('MetadataValue', 6) name = _messages.StringField(7) schemaTitle = _messages.StringField(8) schemaVersion = _messages.StringField(9) state = _messages.EnumField('StateValueValuesEnum', 10) updateTime = _messages.StringField(11) class GoogleCloudAiplatformV1beta1ExplainRequest(_messages.Message): r"""Request message for PredictionService.Explain. Messages: ConcurrentExplanationSpecOverrideValue: Optional. This field is the same as the one above, but supports multiple explanations to occur in parallel. The key can be any string. Each override will be run against the model, then its explanations will be grouped together. Note - these explanations are run **In Addition** to the default Explanation in the deployed model. Fields: concurrentExplanationSpecOverride: Optional. This field is the same as the one above, but supports multiple explanations to occur in parallel. The key can be any string. Each override will be run against the model, then its explanations will be grouped together. Note - these explanations are run **In Addition** to the default Explanation in the deployed model. deployedModelId: If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split. explanationSpecOverride: If specified, overrides the explanation_spec of the DeployedModel. Can be used for explaining prediction results with different configurations, such as: - Explaining top-5 predictions results as opposed to top-1; - Increasing path count or step count of the attribution methods to reduce approximate errors; - Using different baselines for explaining the prediction results. instances: Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri. parameters: The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri. """ @encoding.MapUnrecognizedFields('additionalProperties') class ConcurrentExplanationSpecOverrideValue(_messages.Message): r"""Optional. This field is the same as the one above, but supports multiple explanations to occur in parallel. The key can be any string. Each override will be run against the model, then its explanations will be grouped together. Note - these explanations are run **In Addition** to the default Explanation in the deployed model. Messages: AdditionalProperty: An additional property for a ConcurrentExplanationSpecOverrideValue object. Fields: additionalProperties: Additional properties of type ConcurrentExplanationSpecOverrideValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ConcurrentExplanationSpecOverrideValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ExplanationSpecOverride attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationSpecOverride', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) concurrentExplanationSpecOverride = _messages.MessageField('ConcurrentExplanationSpecOverrideValue', 1) deployedModelId = _messages.StringField(2) explanationSpecOverride = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationSpecOverride', 3) instances = _messages.MessageField('extra_types.JsonValue', 4, repeated=True) parameters = _messages.MessageField('extra_types.JsonValue', 5) class GoogleCloudAiplatformV1beta1ExplainResponse(_messages.Message): r"""Response message for PredictionService.Explain. Messages: ConcurrentExplanationsValue: This field stores the results of the explanations run in parallel with The default explanation strategy/method. Fields: concurrentExplanations: This field stores the results of the explanations run in parallel with The default explanation strategy/method. deployedModelId: ID of the Endpoint's DeployedModel that served this explanation. explanations: The explanations of the Model's PredictResponse.predictions. It has the same number of elements as instances to be explained. predictions: The predictions that are the output of the predictions call. Same as PredictResponse.predictions. """ @encoding.MapUnrecognizedFields('additionalProperties') class ConcurrentExplanationsValue(_messages.Message): r"""This field stores the results of the explanations run in parallel with The default explanation strategy/method. Messages: AdditionalProperty: An additional property for a ConcurrentExplanationsValue object. Fields: additionalProperties: Additional properties of type ConcurrentExplanationsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ConcurrentExplanationsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ExplainResponseConcurrentExplanation attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplainResponseConcurrentExplanation', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) concurrentExplanations = _messages.MessageField('ConcurrentExplanationsValue', 1) deployedModelId = _messages.StringField(2) explanations = _messages.MessageField('GoogleCloudAiplatformV1beta1Explanation', 3, repeated=True) predictions = _messages.MessageField('extra_types.JsonValue', 4, repeated=True) class GoogleCloudAiplatformV1beta1ExplainResponseConcurrentExplanation(_messages.Message): r"""This message is a wrapper grouping Concurrent Explanations. Fields: explanations: The explanations of the Model's PredictResponse.predictions. It has the same number of elements as instances to be explained. """ explanations = _messages.MessageField('GoogleCloudAiplatformV1beta1Explanation', 1, repeated=True) class GoogleCloudAiplatformV1beta1Explanation(_messages.Message): r"""Explanation of a prediction (provided in PredictResponse.predictions) produced by the Model on a given instance. Fields: attributions: Output only. Feature attributions grouped by predicted outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. Attribution.output_index can be used to identify which output this attribution is explaining. By default, we provide Shapley values for the predicted class. However, you can configure the explanation request to generate Shapley values for any other classes too. For example, if a model predicts a probability of `0.4` for approving a loan application, the model's decision is to reject the application since `p(reject) = 0.6 > p(approve) = 0.4`, and the default Shapley values would be computed for rejection decision and not approval, even though the latter might be the positive class. If users set ExplanationParameters.top_k, the attributions are sorted by instance_output_value in descending order. If ExplanationParameters.output_indices is specified, the attributions are stored by Attribution.output_index in the same order as they appear in the output_indices. neighbors: Output only. List of the nearest neighbors for example-based explanations. For models deployed with the examples explanations feature enabled, the attributions field is empty and instead the neighbors field is populated. """ attributions = _messages.MessageField('GoogleCloudAiplatformV1beta1Attribution', 1, repeated=True) neighbors = _messages.MessageField('GoogleCloudAiplatformV1beta1Neighbor', 2, repeated=True) class GoogleCloudAiplatformV1beta1ExplanationMetadata(_messages.Message): r"""Metadata describing the Model's input and output for explanation. Messages: InputsValue: Required. Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI- provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance. OutputsValue: Required. Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed. Fields: featureAttributionsSchemaUri: Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI- Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML tabular Models always have this field populated by Vertex AI. Note: The URI given on output may be different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access. inputs: Required. Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI- provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance. latentSpaceSource: Name of the source to generate embeddings for example based explanations. outputs: Required. Map from output names to output metadata. For Vertex AI-provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed. """ @encoding.MapUnrecognizedFields('additionalProperties') class InputsValue(_messages.Message): r"""Required. Map from feature names to feature input metadata. Keys are the name of the features. Values are the specification of the feature. An empty InputMetadata is valid. It describes a text feature which has the name specified as the key in ExplanationMetadata.inputs. The baseline of the empty feature is chosen by Vertex AI. For Vertex AI-provided Tensorflow images, the key can be any friendly name of the feature. Once specified, featureAttributions are keyed by this key (if not grouped with another feature). For custom images, the key must match with the key in instance. Messages: AdditionalProperty: An additional property for a InputsValue object. Fields: additionalProperties: Additional properties of type InputsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a InputsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadata attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadata', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class OutputsValue(_messages.Message): r"""Required. Map from output names to output metadata. For Vertex AI- provided Tensorflow images, keys can be any user defined string that consists of any UTF-8 characters. For custom images, keys are the name of the output field in the prediction to be explained. Currently only one key is allowed. Messages: AdditionalProperty: An additional property for a OutputsValue object. Fields: additionalProperties: Additional properties of type OutputsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a OutputsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ExplanationMetadataOutputMetadata attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationMetadataOutputMetadata', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) featureAttributionsSchemaUri = _messages.StringField(1) inputs = _messages.MessageField('InputsValue', 2) latentSpaceSource = _messages.StringField(3) outputs = _messages.MessageField('OutputsValue', 4) class GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadata(_messages.Message): r"""Metadata of the input of a feature. Fields other than InputMetadata.input_baselines are applicable only for Models that are using Vertex AI-provided images for Tensorflow. Enums: EncodingValueValuesEnum: Defines how the feature is encoded into the input tensor. Defaults to IDENTITY. Fields: denseShapeTensorName: Specifies the shape of the values of the input if the input is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor. encodedBaselines: A list of baselines for the encoded tensor. The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor. encodedTensorName: Encoded tensor is a transformation of the input tensor. Must be provided if choosing Integrated Gradients attribution or XRAI attribution and the input tensor is not differentiable. An encoded tensor is generated if the input tensor is encoded by a lookup table. encoding: Defines how the feature is encoded into the input tensor. Defaults to IDENTITY. featureValueDomain: The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized. groupName: Name of the group that the input belongs to. Features with the same group name will be treated as one feature when computing attributions. Features grouped together can have different shapes in value. If provided, there will be one single attribution generated in Attribution.feature_attributions, keyed by the group name. indexFeatureMapping: A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR. indicesTensorName: Specifies the index of the values of the input tensor. Required when the input tensor is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor. inputBaselines: Baseline inputs for this feature. If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions. For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor. For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri. inputTensorName: Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow. modality: Modality of the feature. Valid values are: numeric, image. Defaults to numeric. visualization: Visualization configurations for image explanation. """ class EncodingValueValuesEnum(_messages.Enum): r"""Defines how the feature is encoded into the input tensor. Defaults to IDENTITY. Values: ENCODING_UNSPECIFIED: Default value. This is the same as IDENTITY. IDENTITY: The tensor represents one feature. BAG_OF_FEATURES: The tensor represents a bag of features where each index maps to a feature. InputMetadata.index_feature_mapping must be provided for this encoding. For example: ``` input = [27, 6.0, 150] index_feature_mapping = ["age", "height", "weight"] ``` BAG_OF_FEATURES_SPARSE: The tensor represents a bag of features where each index maps to a feature. Zero values in the tensor indicates feature being non-existent. InputMetadata.index_feature_mapping must be provided for this encoding. For example: ``` input = [2, 0, 5, 0, 1] index_feature_mapping = ["a", "b", "c", "d", "e"] ``` INDICATOR: The tensor is a list of binaries representing whether a feature exists or not (1 indicates existence). InputMetadata.index_feature_mapping must be provided for this encoding. For example: ``` input = [1, 0, 1, 0, 1] index_feature_mapping = ["a", "b", "c", "d", "e"] ``` COMBINED_EMBEDDING: The tensor is encoded into a 1-dimensional array represented by an encoded tensor. InputMetadata.encoded_tensor_name must be provided for this encoding. For example: ``` input = ["This", "is", "a", "test", "."] encoded = [0.1, 0.2, 0.3, 0.4, 0.5] ``` CONCAT_EMBEDDING: Select this encoding when the input tensor is encoded into a 2-dimensional array represented by an encoded tensor. InputMetadata.encoded_tensor_name must be provided for this encoding. The first dimension of the encoded tensor's shape is the same as the input tensor's shape. For example: ``` input = ["This", "is", "a", "test", "."] encoded = [[0.1, 0.2, 0.3, 0.4, 0.5], [0.2, 0.1, 0.4, 0.3, 0.5], [0.5, 0.1, 0.3, 0.5, 0.4], [0.5, 0.3, 0.1, 0.2, 0.4], [0.4, 0.3, 0.2, 0.5, 0.1]] ``` """ ENCODING_UNSPECIFIED = 0 IDENTITY = 1 BAG_OF_FEATURES = 2 BAG_OF_FEATURES_SPARSE = 3 INDICATOR = 4 COMBINED_EMBEDDING = 5 CONCAT_EMBEDDING = 6 denseShapeTensorName = _messages.StringField(1) encodedBaselines = _messages.MessageField('extra_types.JsonValue', 2, repeated=True) encodedTensorName = _messages.StringField(3) encoding = _messages.EnumField('EncodingValueValuesEnum', 4) featureValueDomain = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataFeatureValueDomain', 5) groupName = _messages.StringField(6) indexFeatureMapping = _messages.StringField(7, repeated=True) indicesTensorName = _messages.StringField(8) inputBaselines = _messages.MessageField('extra_types.JsonValue', 9, repeated=True) inputTensorName = _messages.StringField(10) modality = _messages.StringField(11) visualization = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataVisualization', 12) class GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataFeatureValueDomain(_messages.Message): r"""Domain details of the input feature value. Provides numeric information about the feature, such as its range (min, max). If the feature has been pre-processed, for example with z-scoring, then it provides information about how to recover the original feature. For example, if the input feature is an image and it has been pre-processed to obtain 0-mean and stddev = 1 values, then original_mean, and original_stddev refer to the mean and stddev of the original feature (e.g. image tensor) from which input feature (with mean = 0 and stddev = 1) was obtained. Fields: maxValue: The maximum permissible value for this feature. minValue: The minimum permissible value for this feature. originalMean: If this input feature has been normalized to a mean value of 0, the original_mean specifies the mean value of the domain prior to normalization. originalStddev: If this input feature has been normalized to a standard deviation of 1.0, the original_stddev specifies the standard deviation of the domain prior to normalization. """ maxValue = _messages.FloatField(1, variant=_messages.Variant.FLOAT) minValue = _messages.FloatField(2, variant=_messages.Variant.FLOAT) originalMean = _messages.FloatField(3, variant=_messages.Variant.FLOAT) originalStddev = _messages.FloatField(4, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1ExplanationMetadataInputMetadataVisualization(_messages.Message): r"""Visualization configurations for image explanation. Enums: ColorMapValueValuesEnum: The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue. OverlayTypeValueValuesEnum: How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE. PolarityValueValuesEnum: Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE. TypeValueValuesEnum: Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES. Fields: clipPercentLowerbound: Excludes attributions below the specified percentile, from the highlighted areas. Defaults to 62. clipPercentUpperbound: Excludes attributions above the specified percentile from the highlighted areas. Using the clip_percent_upperbound and clip_percent_lowerbound together can be useful for filtering out noise and making it easier to see areas of strong attribution. Defaults to 99.9. colorMap: The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue. overlayType: How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE. polarity: Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE. type: Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES. """ class ColorMapValueValuesEnum(_messages.Enum): r"""The color scheme used for the highlighted areas. Defaults to PINK_GREEN for Integrated Gradients attribution, which shows positive attributions in green and negative in pink. Defaults to VIRIDIS for XRAI attribution, which highlights the most influential regions in yellow and the least influential in blue. Values: COLOR_MAP_UNSPECIFIED: Should not be used. PINK_GREEN: Positive: green. Negative: pink. VIRIDIS: Viridis color map: A perceptually uniform color mapping which is easier to see by those with colorblindness and progresses from yellow to green to blue. Positive: yellow. Negative: blue. RED: Positive: red. Negative: red. GREEN: Positive: green. Negative: green. RED_GREEN: Positive: green. Negative: red. PINK_WHITE_GREEN: PiYG palette. """ COLOR_MAP_UNSPECIFIED = 0 PINK_GREEN = 1 VIRIDIS = 2 RED = 3 GREEN = 4 RED_GREEN = 5 PINK_WHITE_GREEN = 6 class OverlayTypeValueValuesEnum(_messages.Enum): r"""How the original image is displayed in the visualization. Adjusting the overlay can help increase visual clarity if the original image makes it difficult to view the visualization. Defaults to NONE. Values: OVERLAY_TYPE_UNSPECIFIED: Default value. This is the same as NONE. NONE: No overlay. ORIGINAL: The attributions are shown on top of the original image. GRAYSCALE: The attributions are shown on top of grayscaled version of the original image. MASK_BLACK: The attributions are used as a mask to reveal predictive parts of the image and hide the un-predictive parts. """ OVERLAY_TYPE_UNSPECIFIED = 0 NONE = 1 ORIGINAL = 2 GRAYSCALE = 3 MASK_BLACK = 4 class PolarityValueValuesEnum(_messages.Enum): r"""Whether to only highlight pixels with positive contributions, negative or both. Defaults to POSITIVE. Values: POLARITY_UNSPECIFIED: Default value. This is the same as POSITIVE. POSITIVE: Highlights the pixels/outlines that were most influential to the model's prediction. NEGATIVE: Setting polarity to negative highlights areas that does not lead to the models's current prediction. BOTH: Shows both positive and negative attributions. """ POLARITY_UNSPECIFIED = 0 POSITIVE = 1 NEGATIVE = 2 BOTH = 3 class TypeValueValuesEnum(_messages.Enum): r"""Type of the image visualization. Only applicable to Integrated Gradients attribution. OUTLINES shows regions of attribution, while PIXELS shows per-pixel attribution. Defaults to OUTLINES. Values: TYPE_UNSPECIFIED: Should not be used. PIXELS: Shows which pixel contributed to the image prediction. OUTLINES: Shows which region contributed to the image prediction by outlining the region. """ TYPE_UNSPECIFIED = 0 PIXELS = 1 OUTLINES = 2 clipPercentLowerbound = _messages.FloatField(1, variant=_messages.Variant.FLOAT) clipPercentUpperbound = _messages.FloatField(2, variant=_messages.Variant.FLOAT) colorMap = _messages.EnumField('ColorMapValueValuesEnum', 3) overlayType = _messages.EnumField('OverlayTypeValueValuesEnum', 4) polarity = _messages.EnumField('PolarityValueValuesEnum', 5) type = _messages.EnumField('TypeValueValuesEnum', 6) class GoogleCloudAiplatformV1beta1ExplanationMetadataOutputMetadata(_messages.Message): r"""Metadata of the prediction output to be explained. Fields: displayNameMappingKey: Specify a field name in the prediction to look for the display name. Use this if the prediction contains the display names for the outputs. The display names in the prediction must have the same shape of the outputs, so that it can be located by Attribution.output_index for a specific output. indexDisplayNameMapping: Static mapping between the index and display name. Use this if the outputs are a deterministic n-dimensional array, e.g. a list of scores of all the classes in a pre-defined order for a multi-classification Model. It's not feasible if the outputs are non- deterministic, e.g. the Model produces top-k classes or sort the outputs by their values. The shape of the value must be an n-dimensional array of strings. The number of dimensions must match that of the outputs to be explained. The Attribution.output_display_name is populated by locating in the mapping with Attribution.output_index. outputTensorName: Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow. """ displayNameMappingKey = _messages.StringField(1) indexDisplayNameMapping = _messages.MessageField('extra_types.JsonValue', 2) outputTensorName = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ExplanationMetadataOverride(_messages.Message): r"""The ExplanationMetadata entries that can be overridden at online explanation time. Messages: InputsValue: Required. Overrides the input metadata of the features. The key is the name of the feature to be overridden. The keys specified here must exist in the input metadata to be overridden. If a feature is not specified here, the corresponding feature's input metadata is not overridden. Fields: inputs: Required. Overrides the input metadata of the features. The key is the name of the feature to be overridden. The keys specified here must exist in the input metadata to be overridden. If a feature is not specified here, the corresponding feature's input metadata is not overridden. """ @encoding.MapUnrecognizedFields('additionalProperties') class InputsValue(_messages.Message): r"""Required. Overrides the input metadata of the features. The key is the name of the feature to be overridden. The keys specified here must exist in the input metadata to be overridden. If a feature is not specified here, the corresponding feature's input metadata is not overridden. Messages: AdditionalProperty: An additional property for a InputsValue object. Fields: additionalProperties: Additional properties of type InputsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a InputsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ExplanationMetadataOverrideInputM etadataOverride attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationMetadataOverrideInputMetadataOverride', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) inputs = _messages.MessageField('InputsValue', 1) class GoogleCloudAiplatformV1beta1ExplanationMetadataOverrideInputMetadataOverride(_messages.Message): r"""The input metadata entries to be overridden. Fields: inputBaselines: Baseline inputs for this feature. This overrides the `input_baseline` field of the ExplanationMetadata.InputMetadata object of the corresponding feature's input metadata. If it's not specified, the original baselines are not overridden. """ inputBaselines = _messages.MessageField('extra_types.JsonValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1ExplanationParameters(_messages.Message): r"""Parameters to configure explaining for Model's predictions. Fields: examples: Example-based explanations that returns the nearest neighbors from the provided dataset. integratedGradientsAttribution: An attribution method that computes Aumann-Shapley values taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365 outputIndices: If populated, only returns attributions that have output_index contained in output_indices. It must be an ndarray of integers, with the same shape of the output it's explaining. If not populated, returns attributions for top_k indices of outputs. If neither top_k nor output_indices is populated, returns the argmax index of the outputs. Only applicable to Models that predict multiple outputs (e,g, multi-class Models that predict multiple classes). sampledShapleyAttribution: An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Refer to this paper for model details: https://arxiv.org/abs/1306.4265. topK: If populated, returns attributions for top K indices of outputs (defaults to 1). Only applies to Models that predicts more than one outputs (e,g, multi-class Models). When set to -1, returns explanations for all outputs. xraiAttribution: An attribution method that redistributes Integrated Gradients attribution to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 XRAI currently performs better on natural images, like a picture of a house or an animal. If the images are taken in artificial environments, like a lab or manufacturing line, or from diagnostic equipment, like x-rays or quality-control cameras, use Integrated Gradients instead. """ examples = _messages.MessageField('GoogleCloudAiplatformV1beta1Examples', 1) integratedGradientsAttribution = _messages.MessageField('GoogleCloudAiplatformV1beta1IntegratedGradientsAttribution', 2) outputIndices = _messages.MessageField('extra_types.JsonValue', 3, repeated=True) sampledShapleyAttribution = _messages.MessageField('GoogleCloudAiplatformV1beta1SampledShapleyAttribution', 4) topK = _messages.IntegerField(5, variant=_messages.Variant.INT32) xraiAttribution = _messages.MessageField('GoogleCloudAiplatformV1beta1XraiAttribution', 6) class GoogleCloudAiplatformV1beta1ExplanationSpec(_messages.Message): r"""Specification of Model explanation. Fields: metadata: Optional. Metadata describing the Model's input and output for explanation. parameters: Required. Parameters that configure explaining of the Model's predictions. """ metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationMetadata', 1) parameters = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationParameters', 2) class GoogleCloudAiplatformV1beta1ExplanationSpecOverride(_messages.Message): r"""The ExplanationSpec entries that can be overridden at online explanation time. Fields: examplesOverride: The example-based explanations parameter overrides. metadata: The metadata to be overridden. If not specified, no metadata is overridden. parameters: The parameters to be overridden. Note that the attribution method cannot be changed. If not specified, no parameter is overridden. """ examplesOverride = _messages.MessageField('GoogleCloudAiplatformV1beta1ExamplesOverride', 1) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationMetadataOverride', 2) parameters = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationParameters', 3) class GoogleCloudAiplatformV1beta1ExportDataConfig(_messages.Message): r"""Describes what part of the Dataset is to be exported, the destination of the export and how to export. Fields: annotationsFilter: An expression for filtering what part of the Dataset is to be exported. Only Annotations that match this filter will be exported. The filter syntax is the same as in ListAnnotations. fractionSplit: Split based on fractions defining the size of each set. gcsDestination: The Google Cloud Storage location where the output is to be written to. In the given directory a new directory will be created with name: `export-data--` where timestamp is in YYYY-MM- DDThh:mm:ss.sssZ ISO-8601 format. All export output will be written into that directory. Inside that directory, annotations with the same schema will be grouped into sub directories which are named with the corresponding annotations' schema title. Inside these sub directories, a schema.yaml will be created to describe the output format. """ annotationsFilter = _messages.StringField(1) fractionSplit = _messages.MessageField('GoogleCloudAiplatformV1beta1ExportFractionSplit', 2) gcsDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 3) class GoogleCloudAiplatformV1beta1ExportDataOperationMetadata(_messages.Message): r"""Runtime operation information for DatasetService.ExportData. Fields: gcsOutputDirectory: A Google Cloud Storage directory which path ends with '/'. The exported data is stored in the directory. genericMetadata: The common part of the operation metadata. """ gcsOutputDirectory = _messages.StringField(1) genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 2) class GoogleCloudAiplatformV1beta1ExportDataRequest(_messages.Message): r"""Request message for DatasetService.ExportData. Fields: exportConfig: Required. The desired output location. """ exportConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ExportDataConfig', 1) class GoogleCloudAiplatformV1beta1ExportDataResponse(_messages.Message): r"""Response message for DatasetService.ExportData. Fields: exportedFiles: All of the files that are exported in this export operation. For custom code training export, only three (training, validation and test) Cloud Storage paths in wildcard format are populated (for example, gs://.../training-*). """ exportedFiles = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1ExportFeatureValuesOperationMetadata(_messages.Message): r"""Details of operations that exports Features values. Fields: genericMetadata: Operation metadata for Featurestore export Feature values. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1ExportFeatureValuesRequest(_messages.Message): r"""Request message for FeaturestoreService.ExportFeatureValues. Fields: destination: Required. Specifies destination location and format. featureSelector: Required. Selects Features to export values of. fullExport: Exports all historical values of all entities of the EntityType within a time range settings: Per-Feature export settings. snapshotExport: Exports the latest Feature values of all entities of the EntityType within a time range. """ destination = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureValueDestination', 1) featureSelector = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureSelector', 2) fullExport = _messages.MessageField('GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestFullExport', 3) settings = _messages.MessageField('GoogleCloudAiplatformV1beta1DestinationFeatureSetting', 4, repeated=True) snapshotExport = _messages.MessageField('GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestSnapshotExport', 5) class GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestFullExport(_messages.Message): r"""Describes exporting all historical Feature values of all entities of the EntityType between [start_time, end_time]. Fields: endTime: Exports Feature values as of this timestamp. If not set, retrieve values as of now. Timestamp, if present, must not have higher than millisecond precision. startTime: Excludes Feature values with feature generation timestamp before this timestamp. If not set, retrieve oldest values kept in Feature Store. Timestamp, if present, must not have higher than millisecond precision. """ endTime = _messages.StringField(1) startTime = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ExportFeatureValuesRequestSnapshotExport(_messages.Message): r"""Describes exporting the latest Feature values of all entities of the EntityType between [start_time, snapshot_time]. Fields: snapshotTime: Exports Feature values as of this timestamp. If not set, retrieve values as of now. Timestamp, if present, must not have higher than millisecond precision. startTime: Excludes Feature values with feature generation timestamp before this timestamp. If not set, retrieve oldest values kept in Feature Store. Timestamp, if present, must not have higher than millisecond precision. """ snapshotTime = _messages.StringField(1) startTime = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ExportFeatureValuesResponse(_messages.Message): r"""Response message for FeaturestoreService.ExportFeatureValues.""" class GoogleCloudAiplatformV1beta1ExportFractionSplit(_messages.Message): r"""Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test. Fields: testFraction: The fraction of the input data that is to be used to evaluate the Model. trainingFraction: The fraction of the input data that is to be used to train the Model. validationFraction: The fraction of the input data that is to be used to validate the Model. """ testFraction = _messages.FloatField(1) trainingFraction = _messages.FloatField(2) validationFraction = _messages.FloatField(3) class GoogleCloudAiplatformV1beta1ExportModelOperationMetadata(_messages.Message): r"""Details of ModelService.ExportModel operation. Fields: genericMetadata: The common part of the operation metadata. outputInfo: Output only. Information further describing the output of this Model export. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) outputInfo = _messages.MessageField('GoogleCloudAiplatformV1beta1ExportModelOperationMetadataOutputInfo', 2) class GoogleCloudAiplatformV1beta1ExportModelOperationMetadataOutputInfo(_messages.Message): r"""Further describes the output of the ExportModel. Supplements ExportModelRequest.OutputConfig. Fields: artifactOutputUri: Output only. If the Model artifact is being exported to Google Cloud Storage this is the full path of the directory created, into which the Model files are being written to. imageOutputUri: Output only. If the Model image is being exported to Google Container Registry or Artifact Registry this is the full path of the image created. """ artifactOutputUri = _messages.StringField(1) imageOutputUri = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ExportModelRequest(_messages.Message): r"""Request message for ModelService.ExportModel. Fields: outputConfig: Required. The desired output location and configuration. """ outputConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ExportModelRequestOutputConfig', 1) class GoogleCloudAiplatformV1beta1ExportModelRequestOutputConfig(_messages.Message): r"""Output configuration for the Model export. Fields: artifactDestination: The Cloud Storage location where the Model artifact is to be written to. Under the directory given as the destination a new one with name "`model-export--`", where timestamp is in YYYY-MM- DDThh:mm:ss.sssZ ISO-8601 format, will be created. Inside, the Model and any of its supporting files will be written. This field should only be set when the `exportableContent` field of the [Model.supported_export_formats] object contains `ARTIFACT`. exportFormatId: The ID of the format in which the Model must be exported. Each Model lists the export formats it supports. If no value is provided here, then the first from the list of the Model's supported formats is used by default. imageDestination: The Google Container Registry or Artifact Registry uri where the Model container image will be copied to. This field should only be set when the `exportableContent` field of the [Model.supported_export_formats] object contains `IMAGE`. """ artifactDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 1) exportFormatId = _messages.StringField(2) imageDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1ContainerRegistryDestination', 3) class GoogleCloudAiplatformV1beta1ExportModelResponse(_messages.Message): r"""Response message of ModelService.ExportModel operation.""" class GoogleCloudAiplatformV1beta1ExportPublisherModelOperationMetadata(_messages.Message): r"""Runtime operation information for ModelGardenService.ExportPublisherModel. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1ExportPublisherModelRequest(_messages.Message): r"""Request message for ModelGardenService.ExportPublisherModel. Fields: destination: Required. The target where we are exporting the model weights to """ destination = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 1) class GoogleCloudAiplatformV1beta1ExportPublisherModelResponse(_messages.Message): r"""Response message for ModelGardenService.ExportPublisherModel. Fields: destinationUri: The destination uri of the model weights. publisherModel: The name of the PublisherModel resource. Format: `publishers/{publisher}/models/{publisher_model}@{version_id}` """ destinationUri = _messages.StringField(1) publisherModel = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataRequest(_messages.Message): r"""Request message for TensorboardService.ExportTensorboardTimeSeriesData. Fields: filter: Exports the TensorboardTimeSeries' data that match the filter expression. orderBy: Field to use to sort the TensorboardTimeSeries' data. By default, TensorboardTimeSeries' data is returned in a pseudo random order. pageSize: The maximum number of data points to return per page. The default page_size is 1000. Values must be between 1 and 10000. Values above 10000 are coerced to 10000. pageToken: A page token, received from a previous ExportTensorboardTimeSeriesData call. Provide this to retrieve the subsequent page. When paginating, all other parameters provided to ExportTensorboardTimeSeriesData must match the call that provided the page token. """ filter = _messages.StringField(1) orderBy = _messages.StringField(2) pageSize = _messages.IntegerField(3, variant=_messages.Variant.INT32) pageToken = _messages.StringField(4) class GoogleCloudAiplatformV1beta1ExportTensorboardTimeSeriesDataResponse(_messages.Message): r"""Response message for TensorboardService.ExportTensorboardTimeSeriesData. Fields: nextPageToken: A token, which can be sent as page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. timeSeriesDataPoints: The returned time series data points. """ nextPageToken = _messages.StringField(1) timeSeriesDataPoints = _messages.MessageField('GoogleCloudAiplatformV1beta1TimeSeriesDataPoint', 2, repeated=True) class GoogleCloudAiplatformV1beta1Extension(_messages.Message): r"""Extensions are tools for large language models to access external data, run computations, etc. Fields: createTime: Output only. Timestamp when this Extension was created. description: Optional. The description of the Extension. displayName: Required. The display name of the Extension. The name can be up to 128 characters long and can consist of any UTF-8 characters. etag: Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. extensionOperations: Output only. Supported operations. manifest: Required. Manifest of the Extension. name: Identifier. The resource name of the Extension. privateServiceConnectConfig: Optional. The PrivateServiceConnect config for the extension. If specified, the service endpoints associated with the Extension should be [registered with private network access in the provided Service Directory](https://cloud.google.com/service- directory/docs/configuring-private-network-access). If the service contains more than one endpoint with a network, the service will arbitrarilty choose one of the endpoints to use for extension execution. runtimeConfig: Optional. Runtime config controlling the runtime behavior of this Extension. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. toolUseExamples: Optional. Examples to illustrate the usage of the extension as a tool. updateTime: Output only. Timestamp when this Extension was most recently updated. """ createTime = _messages.StringField(1) description = _messages.StringField(2) displayName = _messages.StringField(3) etag = _messages.StringField(4) extensionOperations = _messages.MessageField('GoogleCloudAiplatformV1beta1ExtensionOperation', 5, repeated=True) manifest = _messages.MessageField('GoogleCloudAiplatformV1beta1ExtensionManifest', 6) name = _messages.StringField(7) privateServiceConnectConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ExtensionPrivateServiceConnectConfig', 8) runtimeConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RuntimeConfig', 9) satisfiesPzi = _messages.BooleanField(10) satisfiesPzs = _messages.BooleanField(11) toolUseExamples = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolUseExample', 12, repeated=True) updateTime = _messages.StringField(13) class GoogleCloudAiplatformV1beta1ExtensionManifest(_messages.Message): r"""Manifest spec of an Extension needed for runtime execution. Fields: apiSpec: Required. Immutable. The API specification shown to the LLM. authConfig: Required. Immutable. Type of auth supported by this extension. description: Required. The natural language description shown to the LLM. It should describe the usage of the extension, and is essential for the LLM to perform reasoning. e.g., if the extension is a data store, you can let the LLM know what data it contains. name: Required. Extension name shown to the LLM. The name can be up to 128 characters long. """ apiSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ExtensionManifestApiSpec', 1) authConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AuthConfig', 2) description = _messages.StringField(3) name = _messages.StringField(4) class GoogleCloudAiplatformV1beta1ExtensionManifestApiSpec(_messages.Message): r"""The API specification shown to the LLM. Fields: openApiGcsUri: Cloud Storage URI pointing to the OpenAPI spec. openApiYaml: The API spec in Open API standard and YAML format. """ openApiGcsUri = _messages.StringField(1) openApiYaml = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ExtensionOperation(_messages.Message): r"""Operation of an extension. Fields: functionDeclaration: Output only. Structured representation of a function declaration as defined by the OpenAPI Spec. operationId: Operation ID that uniquely identifies the operations among the extension. See: "Operation Object" in https://swagger.io/specification/. This field is parsed from the OpenAPI spec. For HTTP extensions, if it does not exist in the spec, we will generate one from the HTTP method and path. """ functionDeclaration = _messages.MessageField('GoogleCloudAiplatformV1beta1FunctionDeclaration', 1) operationId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ExtensionPrivateServiceConnectConfig(_messages.Message): r"""PrivateExtensionConfig configuration for the extension. Fields: serviceDirectory: Required. The Service Directory resource name in which the service endpoints associated to the extension are registered. Format: `projects/{project_id}/locations/{location_id}/namespaces/{names pace_id}/services/{service_id}` - The Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service- agents) should be granted `servicedirectory.viewer` and `servicedirectory.pscAuthorizedService` roles on the resource. """ serviceDirectory = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ExternalApi(_messages.Message): r"""Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. Enums: ApiSpecValueValuesEnum: The API spec that the external API implements. Fields: apiAuth: The authentication config to access the API. Deprecated. Please use auth_config instead. apiSpec: The API spec that the external API implements. authConfig: The authentication config to access the API. elasticSearchParams: Parameters for the elastic search API. endpoint: The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search simpleSearchParams: Parameters for the simple search API. """ class ApiSpecValueValuesEnum(_messages.Enum): r"""The API spec that the external API implements. Values: API_SPEC_UNSPECIFIED: Unspecified API spec. This value should not be used. SIMPLE_SEARCH: Simple search API spec. ELASTIC_SEARCH: Elastic search API spec. """ API_SPEC_UNSPECIFIED = 0 SIMPLE_SEARCH = 1 ELASTIC_SEARCH = 2 apiAuth = _messages.MessageField('GoogleCloudAiplatformV1beta1ApiAuth', 1) apiSpec = _messages.EnumField('ApiSpecValueValuesEnum', 2) authConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AuthConfig', 3) elasticSearchParams = _messages.MessageField('GoogleCloudAiplatformV1beta1ExternalApiElasticSearchParams', 4) endpoint = _messages.StringField(5) simpleSearchParams = _messages.MessageField('GoogleCloudAiplatformV1beta1ExternalApiSimpleSearchParams', 6) class GoogleCloudAiplatformV1beta1ExternalApiElasticSearchParams(_messages.Message): r"""The search parameters to use for the ELASTIC_SEARCH spec. Fields: index: The ElasticSearch index to use. numHits: Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param. searchTemplate: The ElasticSearch search template to use. """ index = _messages.StringField(1) numHits = _messages.IntegerField(2, variant=_messages.Variant.INT32) searchTemplate = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ExternalApiSimpleSearchParams(_messages.Message): r"""The search parameters to use for SIMPLE_SEARCH spec.""" class GoogleCloudAiplatformV1beta1Fact(_messages.Message): r"""The fact used in grounding. Fields: chunk: If present, chunk properties. query: Query that is used to retrieve this fact. score: If present, according to the underlying Vector DB and the selected metric type, the score can be either the distance or the similarity between the query and the fact and its range depends on the metric type. For example, if the metric type is COSINE_DISTANCE, it represents the distance between the query and the fact. The larger the distance, the less relevant the fact is to the query. The range is [0, 2], while 0 means the most relevant and 2 means the least relevant. summary: If present, the summary/snippet of the fact. title: If present, it refers to the title of this fact. uri: If present, this uri links to the source of the fact. vectorDistance: If present, the distance between the query vector and this fact vector. """ chunk = _messages.MessageField('GoogleCloudAiplatformV1beta1RagChunk', 1) query = _messages.StringField(2) score = _messages.FloatField(3) summary = _messages.StringField(4) title = _messages.StringField(5) uri = _messages.StringField(6) vectorDistance = _messages.FloatField(7) class GoogleCloudAiplatformV1beta1FasterDeploymentConfig(_messages.Message): r"""Configuration for faster model deployment. Fields: fastTryoutEnabled: If true, enable fast tryout feature for this deployed model. """ fastTryoutEnabled = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1Feature(_messages.Message): r"""Feature Metadata information. For example, color is a feature that describes an apple. Enums: ValueTypeValueValuesEnum: Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: createTime: Output only. Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was created. description: Description of the Feature. disableMonitoring: Optional. Only applicable for Vertex AI Feature Store (Legacy). If not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If set to true, all types of data monitoring are disabled despite the config on EntityType. etag: Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens. featureStatsAndAnomaly: Output only. Only applicable for Vertex AI Feature Store. The list of historical stats and anomalies. labels: Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. monitoringConfig: Optional. Only applicable for Vertex AI Feature Store (Legacy). Deprecated: The custom monitoring configuration for this Feature, if not set, use the monitoring_config defined for the EntityType this Feature belongs to. Only Features with type (Feature.ValueType) BOOL, STRING, DOUBLE or INT64 can enable monitoring. If this is populated with FeaturestoreMonitoringConfig.disabled = true, snapshot analysis monitoring is disabled; if FeaturestoreMonitoringConfig.monitoring_interval specified, snapshot analysis monitoring is enabled. Otherwise, snapshot analysis monitoring config is same as the EntityType's this Feature belongs to. monitoringStats: Output only. Only applicable for Vertex AI Feature Store (Legacy). A list of historical SnapshotAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending. monitoringStatsAnomalies: Output only. Only applicable for Vertex AI Feature Store (Legacy). The list of historical stats and anomalies with specified objectives. name: Immutable. Name of the Feature. Format: `projects/{project}/location s/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/feat ures/{feature}` `projects/{project}/locations/{location}/featureGroups/{ feature_group}/features/{feature}` The last part feature is assigned by the client. The feature can be up to 64 characters long and can consist only of ASCII Latin letters A-Z and a-z, underscore(_), and ASCII digits 0-9 starting with a letter. The value will be unique given an entity type. pointOfContact: Entity responsible for maintaining this feature. Can be comma separated list of email addresses or URIs. updateTime: Output only. Only applicable for Vertex AI Feature Store (Legacy). Timestamp when this EntityType was most recently updated. valueType: Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value. versionColumnName: Only applicable for Vertex AI Feature Store. The name of the BigQuery Table/View column hosting data for this version. If no value is provided, will use feature_id. """ class ValueTypeValueValuesEnum(_messages.Enum): r"""Immutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value. Values: VALUE_TYPE_UNSPECIFIED: The value type is unspecified. BOOL: Used for Feature that is a boolean. BOOL_ARRAY: Used for Feature that is a list of boolean. DOUBLE: Used for Feature that is double. DOUBLE_ARRAY: Used for Feature that is a list of double. INT64: Used for Feature that is INT64. INT64_ARRAY: Used for Feature that is a list of INT64. STRING: Used for Feature that is string. STRING_ARRAY: Used for Feature that is a list of String. BYTES: Used for Feature that is bytes. STRUCT: Used for Feature that is struct. """ VALUE_TYPE_UNSPECIFIED = 0 BOOL = 1 BOOL_ARRAY = 2 DOUBLE = 3 DOUBLE_ARRAY = 4 INT64 = 5 INT64_ARRAY = 6 STRING = 7 STRING_ARRAY = 8 BYTES = 9 STRUCT = 10 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize your Features. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Feature (System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) description = _messages.StringField(2) disableMonitoring = _messages.BooleanField(3) etag = _messages.StringField(4) featureStatsAndAnomaly = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureStatsAndAnomaly', 5, repeated=True) labels = _messages.MessageField('LabelsValue', 6) monitoringConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfig', 7) monitoringStats = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureStatsAnomaly', 8, repeated=True) monitoringStatsAnomalies = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureMonitoringStatsAnomaly', 9, repeated=True) name = _messages.StringField(10) pointOfContact = _messages.StringField(11) updateTime = _messages.StringField(12) valueType = _messages.EnumField('ValueTypeValueValuesEnum', 13) versionColumnName = _messages.StringField(14) class GoogleCloudAiplatformV1beta1FeatureGroup(_messages.Message): r"""Vertex AI Feature Group. Enums: ServiceAgentTypeValueValuesEnum: Optional. Service agent type used during jobs under a FeatureGroup. By default, the Vertex AI Service Agent is used. When using an IAM Policy to isolate this FeatureGroup within a project, a separate service account should be provisioned by setting this field to `SERVICE_AGENT_TYPE_FEATURE_GROUP`. This will generate a separate service account to access the BigQuery source table. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize your FeatureGroup. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: bigQuery: Indicates that features for this group come from BigQuery Table/View. By default treats the source as a sparse time series source. The BigQuery source table or view must have at least one entity ID column and a column named `feature_timestamp`. createTime: Output only. Timestamp when this FeatureGroup was created. description: Optional. Description of the FeatureGroup. etag: Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: Optional. The labels with user-defined metadata to organize your FeatureGroup. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. name: Identifier. Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}` serviceAccountEmail: Output only. A Service Account unique to this FeatureGroup. The role bigquery.dataViewer should be granted to this service account to allow Vertex AI Feature Store to access source data while running jobs under this FeatureGroup. serviceAgentType: Optional. Service agent type used during jobs under a FeatureGroup. By default, the Vertex AI Service Agent is used. When using an IAM Policy to isolate this FeatureGroup within a project, a separate service account should be provisioned by setting this field to `SERVICE_AGENT_TYPE_FEATURE_GROUP`. This will generate a separate service account to access the BigQuery source table. updateTime: Output only. Timestamp when this FeatureGroup was last updated. """ class ServiceAgentTypeValueValuesEnum(_messages.Enum): r"""Optional. Service agent type used during jobs under a FeatureGroup. By default, the Vertex AI Service Agent is used. When using an IAM Policy to isolate this FeatureGroup within a project, a separate service account should be provisioned by setting this field to `SERVICE_AGENT_TYPE_FEATURE_GROUP`. This will generate a separate service account to access the BigQuery source table. Values: SERVICE_AGENT_TYPE_UNSPECIFIED: By default, the project-level Vertex AI Service Agent is enabled. SERVICE_AGENT_TYPE_PROJECT: Specifies the project-level Vertex AI Service Agent (https://cloud.google.com/vertex-ai/docs/general/access- control#service-agents). SERVICE_AGENT_TYPE_FEATURE_GROUP: Enable a FeatureGroup service account to be created by Vertex AI and output in the field `service_account_email`. This service account will be used to read from the source BigQuery table during jobs under a FeatureGroup. """ SERVICE_AGENT_TYPE_UNSPECIFIED = 0 SERVICE_AGENT_TYPE_PROJECT = 1 SERVICE_AGENT_TYPE_FEATURE_GROUP = 2 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize your FeatureGroup. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureGroup(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) bigQuery = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureGroupBigQuery', 1) createTime = _messages.StringField(2) description = _messages.StringField(3) etag = _messages.StringField(4) labels = _messages.MessageField('LabelsValue', 5) name = _messages.StringField(6) serviceAccountEmail = _messages.StringField(7) serviceAgentType = _messages.EnumField('ServiceAgentTypeValueValuesEnum', 8) updateTime = _messages.StringField(9) class GoogleCloudAiplatformV1beta1FeatureGroupBigQuery(_messages.Message): r"""Input source type for BigQuery Tables and Views. Fields: bigQuerySource: Required. Immutable. The BigQuery source URI that points to either a BigQuery Table or View. dense: Optional. If set, all feature values will be fetched from a single row per unique entityId including nulls. If not set, will collapse all rows for each unique entityId into a singe row with any non-null values if present, if no non-null values are present will sync null. ex: If source has schema `(entity_id, feature_timestamp, f0, f1)` and the following rows: `(e1, 2020-01-01T10:00:00.123Z, 10, 15)` `(e1, 2020-02-01T10:00:00.123Z, 20, null)` If dense is set, `(e1, 20, null)` is synced to online stores. If dense is not set, `(e1, 20, 15)` is synced to online stores. entityIdColumns: Optional. Columns to construct entity_id / row keys. If not provided defaults to `entity_id`. staticDataSource: Optional. Set if the data source is not a time-series. timeSeries: Optional. If the source is a time-series source, this can be set to control how downstream sources (ex: FeatureView ) will treat time-series sources. If not set, will treat the source as a time-series source with `feature_timestamp` as timestamp column and no scan boundary. """ bigQuerySource = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQuerySource', 1) dense = _messages.BooleanField(2) entityIdColumns = _messages.StringField(3, repeated=True) staticDataSource = _messages.BooleanField(4) timeSeries = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureGroupBigQueryTimeSeries', 5) class GoogleCloudAiplatformV1beta1FeatureGroupBigQueryTimeSeries(_messages.Message): r"""A GoogleCloudAiplatformV1beta1FeatureGroupBigQueryTimeSeries object. Fields: timestampColumn: Optional. Column hosting timestamp values for a time- series source. Will be used to determine the latest `feature_values` for each entity. Optional. If not provided, column named `feature_timestamp` of type `TIMESTAMP` will be used. """ timestampColumn = _messages.StringField(1) class GoogleCloudAiplatformV1beta1FeatureMonitor(_messages.Message): r"""Vertex AI Feature Monitor. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize your FeatureMonitor. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureMonitor(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: createTime: Output only. Timestamp when this FeatureMonitor was created. description: Optional. Description of the FeatureMonitor. etag: Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. featureSelectionConfig: Required. Feature selection config for the FeatureMonitor. labels: Optional. The labels with user-defined metadata to organize your FeatureMonitor. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureMonitor(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. name: Identifier. Name of the FeatureMonitor. Format: `projects/{project}/ locations/{location}/featureGroups/{featureGroup}/featureMonitors/{featu reMonitor}` scheduleConfig: Required. Schedule config for the FeatureMonitor. updateTime: Output only. Timestamp when this FeatureMonitor was last updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize your FeatureMonitor. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureMonitor(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) description = _messages.StringField(2) etag = _messages.StringField(3) featureSelectionConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureSelectionConfig', 4) labels = _messages.MessageField('LabelsValue', 5) name = _messages.StringField(6) scheduleConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ScheduleConfig', 7) updateTime = _messages.StringField(8) class GoogleCloudAiplatformV1beta1FeatureMonitorJob(_messages.Message): r"""Vertex AI Feature Monitor Job. Enums: TriggerTypeValueValuesEnum: Output only. Trigger type of the Feature Monitor Job. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize your FeatureMonitorJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureMonitor(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: createTime: Output only. Timestamp when this FeatureMonitorJob was created. Creation of a FeatureMonitorJob means that the job is pending / waiting for sufficient resources but may not have started running yet. description: Optional. Description of the FeatureMonitor. driftBaseFeatureMonitorJobId: Output only. FeatureMonitorJob ID comparing to which the drift is calculated. driftBaseSnapshotTime: Output only. Data snapshot time comparing to which the drift is calculated. featureSelectionConfig: Output only. Feature selection config used when creating FeatureMonitorJob. finalStatus: Output only. Final status of the FeatureMonitorJob. jobSummary: Output only. Summary from the FeatureMonitorJob. labels: Optional. The labels with user-defined metadata to organize your FeatureMonitorJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureMonitor(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. name: Identifier. Name of the FeatureMonitorJob. Format: `projects/{projec t}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{f eature_monitor}/featureMonitorJobs/{feature_monitor_job}`. triggerType: Output only. Trigger type of the Feature Monitor Job. """ class TriggerTypeValueValuesEnum(_messages.Enum): r"""Output only. Trigger type of the Feature Monitor Job. Values: FEATURE_MONITOR_JOB_TRIGGER_UNSPECIFIED: Trigger type unspecified. FEATURE_MONITOR_JOB_TRIGGER_PERIODIC: Triggered by periodic schedule. FEATURE_MONITOR_JOB_TRIGGER_ON_DEMAND: Triggered on demand by CreateFeatureMonitorJob request. """ FEATURE_MONITOR_JOB_TRIGGER_UNSPECIFIED = 0 FEATURE_MONITOR_JOB_TRIGGER_PERIODIC = 1 FEATURE_MONITOR_JOB_TRIGGER_ON_DEMAND = 2 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize your FeatureMonitorJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureMonitor(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) description = _messages.StringField(2) driftBaseFeatureMonitorJobId = _messages.IntegerField(3) driftBaseSnapshotTime = _messages.StringField(4) featureSelectionConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureSelectionConfig', 5) finalStatus = _messages.MessageField('GoogleRpcStatus', 6) jobSummary = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureMonitorJobJobSummary', 7) labels = _messages.MessageField('LabelsValue', 8) name = _messages.StringField(9) triggerType = _messages.EnumField('TriggerTypeValueValuesEnum', 10) class GoogleCloudAiplatformV1beta1FeatureMonitorJobJobSummary(_messages.Message): r"""Summary from the FeatureMonitorJob. Fields: featureStatsAndAnomalies: Output only. Features and their stats and anomalies totalSlotMs: Output only. BigQuery slot milliseconds consumed. """ featureStatsAndAnomalies = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureStatsAndAnomaly', 1, repeated=True) totalSlotMs = _messages.IntegerField(2) class GoogleCloudAiplatformV1beta1FeatureMonitoringStatsAnomaly(_messages.Message): r"""A list of historical SnapshotAnalysis or ImportFeaturesAnalysis stats requested by user, sorted by FeatureStatsAnomaly.start_time descending. Enums: ObjectiveValueValuesEnum: Output only. The objective for each stats. Fields: featureStatsAnomaly: Output only. The stats and anomalies generated at specific timestamp. objective: Output only. The objective for each stats. """ class ObjectiveValueValuesEnum(_messages.Enum): r"""Output only. The objective for each stats. Values: OBJECTIVE_UNSPECIFIED: If it's OBJECTIVE_UNSPECIFIED, monitoring_stats will be empty. IMPORT_FEATURE_ANALYSIS: Stats are generated by Import Feature Analysis. SNAPSHOT_ANALYSIS: Stats are generated by Snapshot Analysis. """ OBJECTIVE_UNSPECIFIED = 0 IMPORT_FEATURE_ANALYSIS = 1 SNAPSHOT_ANALYSIS = 2 featureStatsAnomaly = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureStatsAnomaly', 1) objective = _messages.EnumField('ObjectiveValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1FeatureNoiseSigma(_messages.Message): r"""Noise sigma by features. Noise sigma represents the standard deviation of the gaussian kernel that will be used to add noise to interpolated inputs prior to computing gradients. Fields: noiseSigma: Noise sigma per feature. No noise is added to features that are not set. """ noiseSigma = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureNoiseSigmaNoiseSigmaForFeature', 1, repeated=True) class GoogleCloudAiplatformV1beta1FeatureNoiseSigmaNoiseSigmaForFeature(_messages.Message): r"""Noise sigma for a single feature. Fields: name: The name of the input feature for which noise sigma is provided. The features are defined in explanation metadata inputs. sigma: This represents the standard deviation of the Gaussian kernel that will be used to add noise to the feature prior to computing gradients. Similar to noise_sigma but represents the noise added to the current feature. Defaults to 0.1. """ name = _messages.StringField(1) sigma = _messages.FloatField(2, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1FeatureOnlineStore(_messages.Message): r"""Vertex AI Feature Online Store provides a centralized repository for serving ML features and embedding indexes at low latency. The Feature Online Store is a top-level container. Enums: StateValueValuesEnum: Output only. State of the featureOnlineStore. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize your FeatureOnlineStore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: bigtable: Contains settings for the Cloud Bigtable instance that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. createTime: Output only. Timestamp when this FeatureOnlineStore was created. dedicatedServingEndpoint: Optional. The dedicated serving endpoint for this FeatureOnlineStore, which is different from common Vertex service endpoint. embeddingManagement: Optional. Deprecated: This field is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type. encryptionSpec: Optional. Customer-managed encryption key spec for data storage. If set, online store will be secured by this key. etag: Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: Optional. The labels with user-defined metadata to organize your FeatureOnlineStore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. name: Identifier. Name of the FeatureOnlineStore. Format: `projects/{proje ct}/locations/{location}/featureOnlineStores/{featureOnlineStore}` optimized: Contains settings for the Optimized store that will be created to serve featureValues for all FeatureViews under this FeatureOnlineStore. When choose Optimized storage type, need to set PrivateServiceConnectConfig.enable_private_service_connect to use private endpoint. Otherwise will use public endpoint by default. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. state: Output only. State of the featureOnlineStore. updateTime: Output only. Timestamp when this FeatureOnlineStore was last updated. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. State of the featureOnlineStore. Values: STATE_UNSPECIFIED: Default value. This value is unused. STABLE: State when the featureOnlineStore configuration is not being updated and the fields reflect the current configuration of the featureOnlineStore. The featureOnlineStore is usable in this state. UPDATING: The state of the featureOnlineStore configuration when it is being updated. During an update, the fields reflect either the original configuration or the updated configuration of the featureOnlineStore. The featureOnlineStore is still usable in this state. """ STATE_UNSPECIFIED = 0 STABLE = 1 UPDATING = 2 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize your FeatureOnlineStore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) bigtable = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtable', 1) createTime = _messages.StringField(2) dedicatedServingEndpoint = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureOnlineStoreDedicatedServingEndpoint', 3) embeddingManagement = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureOnlineStoreEmbeddingManagement', 4) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 5) etag = _messages.StringField(6) labels = _messages.MessageField('LabelsValue', 7) name = _messages.StringField(8) optimized = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized', 9) satisfiesPzi = _messages.BooleanField(10) satisfiesPzs = _messages.BooleanField(11) state = _messages.EnumField('StateValueValuesEnum', 12) updateTime = _messages.StringField(13) class GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtable(_messages.Message): r"""A GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtable object. Fields: autoScaling: Required. Autoscaling config applied to Bigtable Instance. bigtableMetadata: Output only. Metadata of the Bigtable instance. Output only. enableDirectBigtableAccess: Optional. It true, enable direct access to the Bigtable instance. """ autoScaling = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableAutoScaling', 1) bigtableMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableBigtableMetadata', 2) enableDirectBigtableAccess = _messages.BooleanField(3) class GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableAutoScaling(_messages.Message): r"""A GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableAutoScaling object. Fields: cpuUtilizationTarget: Optional. A percentage of the cluster's CPU capacity. Can be from 10% to 80%. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set will default to 50%. maxNodeCount: Required. The maximum number of nodes to scale up to. Must be greater than or equal to min_node_count, and less than or equal to 10 times of 'min_node_count'. minNodeCount: Required. The minimum number of nodes to scale down to. Must be greater than or equal to 1. """ cpuUtilizationTarget = _messages.IntegerField(1, variant=_messages.Variant.INT32) maxNodeCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) minNodeCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1FeatureOnlineStoreBigtableBigtableMetadata(_messages.Message): r"""Metadata of the Bigtable instance. This is used by direct read access to the Bigtable in tenant project. Fields: instanceId: The Cloud Bigtable instance id. tableId: The Cloud Bigtable table id. tenantProjectId: Tenant project ID. """ instanceId = _messages.StringField(1) tableId = _messages.StringField(2) tenantProjectId = _messages.StringField(3) class GoogleCloudAiplatformV1beta1FeatureOnlineStoreDedicatedServingEndpoint(_messages.Message): r"""The dedicated serving endpoint for this FeatureOnlineStore. Only need to set when you choose Optimized storage type. Public endpoint is provisioned by default. Fields: privateServiceConnectConfig: Optional. Private service connect config. The private service connection is available only for Optimized storage type, not for embedding management now. If PrivateServiceConnectConfig.enable_private_service_connect set to true, customers will use private service connection to send request. Otherwise, the connection will set to public endpoint. publicEndpointDomainName: Output only. This field will be populated with the domain name to use for this FeatureOnlineStore serviceAttachment: Output only. The name of the service attachment resource. Populated if private service connect is enabled and after FeatureViewSync is created. """ privateServiceConnectConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig', 1) publicEndpointDomainName = _messages.StringField(2) serviceAttachment = _messages.StringField(3) class GoogleCloudAiplatformV1beta1FeatureOnlineStoreEmbeddingManagement(_messages.Message): r"""Deprecated: This sub message is no longer needed anymore and embedding management is automatically enabled when specifying Optimized storage type. Contains settings for embedding management. Fields: enabled: Optional. Immutable. Whether to enable embedding management in this FeatureOnlineStore. It's immutable after creation to ensure the FeatureOnlineStore availability. """ enabled = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1FeatureOnlineStoreOptimized(_messages.Message): r"""Optimized storage type""" class GoogleCloudAiplatformV1beta1FeatureSelectionConfig(_messages.Message): r"""Feature selection configuration for the FeatureMonitor. Fields: featureConfigs: Optional. A list of features to be monitored and each feature's drift threshold. """ featureConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureSelectionConfigFeatureConfig', 1, repeated=True) class GoogleCloudAiplatformV1beta1FeatureSelectionConfigFeatureConfig(_messages.Message): r"""Feature configuration. Fields: driftThreshold: Optional. Drift threshold. If calculated difference with baseline data larger than threshold, it will be considered as the feature has drift. If not present, the threshold will be default to 0.3. Must be in range [0, 1). featureId: Required. The ID of the feature resource. Final component of the Feature's resource name. """ driftThreshold = _messages.FloatField(1) featureId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1FeatureSelector(_messages.Message): r"""Selector for Features of an EntityType. Fields: idMatcher: Required. Matches Features based on ID. """ idMatcher = _messages.MessageField('GoogleCloudAiplatformV1beta1IdMatcher', 1) class GoogleCloudAiplatformV1beta1FeatureStatsAndAnomaly(_messages.Message): r"""Stats and Anomaly generated by FeatureMonitorJobs. Anomaly only includes Drift. Fields: distributionDeviation: Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen\u2013Shannon divergence. driftDetected: If set to true, indicates current stats is detected as and comparing with baseline stats. driftDetectionThreshold: This is the threshold used when detecting drifts, which is set in FeatureMonitor.FeatureSelectionConfig.FeatureConfig.drift_threshold featureId: Feature Id. featureMonitorId: The ID of the FeatureMonitor that this FeatureStatsAndAnomaly generated according to. featureMonitorJobId: The ID of the FeatureMonitorJob that generated this FeatureStatsAndAnomaly. featureStats: Feature stats. e.g. histogram buckets. In the format of tensorflow.metadata.v0.DatasetFeatureStatistics. statsTime: The timestamp we take snapshot for feature values to generate stats. """ distributionDeviation = _messages.FloatField(1) driftDetected = _messages.BooleanField(2) driftDetectionThreshold = _messages.FloatField(3) featureId = _messages.StringField(4) featureMonitorId = _messages.StringField(5) featureMonitorJobId = _messages.IntegerField(6) featureStats = _messages.MessageField('extra_types.JsonValue', 7) statsTime = _messages.StringField(8) class GoogleCloudAiplatformV1beta1FeatureStatsAnomaly(_messages.Message): r"""Stats and Anomaly generated at specific timestamp for specific Feature. The start_time and end_time are used to define the time range of the dataset that current stats belongs to, e.g. prediction traffic is bucketed into prediction datasets by time window. If the Dataset is not defined by time window, start_time = end_time. Timestamp of the stats and anomalies always refers to end_time. Raw stats and anomalies are stored in stats_uri or anomaly_uri in the tensorflow defined protos. Field data_stats contains almost identical information with the raw stats in Vertex AI defined proto, for UI to display. Fields: anomalyDetectionThreshold: This is the threshold used when detecting anomalies. The threshold can be changed by user, so this one might be different from ThresholdConfig.value. anomalyUri: Path of the anomaly file for current feature values in Cloud Storage bucket. Format: gs:////anomalies. Example: gs://monitoring_bucket/feature_name/anomalies. Stats are stored as binary format with Protobuf message Anoamlies are stored as binary format with Protobuf message [tensorflow.metadata.v0.AnomalyInfo] (https ://github.com/tensorflow/metadata/blob/master/tensorflow_metadata/proto/ v0/anomalies.proto). distributionDeviation: Deviation from the current stats to baseline stats. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen\u2013Shannon divergence. endTime: The end timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), end_time indicates the timestamp of the data used to generate stats (e.g. timestamp we take snapshots for feature values). score: Feature importance score, only populated when cross-feature monitoring is enabled. For now only used to represent feature attribution score within range [0, 1] for ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_SKEW and ModelDeploymentMonitoringObjectiveType.FEATURE_ATTRIBUTION_DRIFT. startTime: The start timestamp of window where stats were generated. For objectives where time window doesn't make sense (e.g. Featurestore Snapshot Monitoring), start_time is only used to indicate the monitoring intervals, so it always equals to (end_time - monitoring_interval). statsUri: Path of the stats file for current feature values in Cloud Storage bucket. Format: gs:////stats. Example: gs://monitoring_bucket/feature_name/stats. Stats are stored as binary format with Protobuf message [tensorflow.metadata.v0.FeatureNameStatisti cs](https://github.com/tensorflow/metadata/blob/master/tensorflow_metada ta/proto/v0/statistics.proto). """ anomalyDetectionThreshold = _messages.FloatField(1) anomalyUri = _messages.StringField(2) distributionDeviation = _messages.FloatField(3) endTime = _messages.StringField(4) score = _messages.FloatField(5) startTime = _messages.StringField(6) statsUri = _messages.StringField(7) class GoogleCloudAiplatformV1beta1FeatureValue(_messages.Message): r"""Value for a feature. Fields: boolArrayValue: A list of bool type feature value. boolValue: Bool type feature value. bytesValue: Bytes feature value. doubleArrayValue: A list of double type feature value. doubleValue: Double type feature value. int64ArrayValue: A list of int64 type feature value. int64Value: Int64 feature value. metadata: Metadata of feature value. stringArrayValue: A list of string type feature value. stringValue: String feature value. structValue: A struct type feature value. """ boolArrayValue = _messages.MessageField('GoogleCloudAiplatformV1beta1BoolArray', 1) boolValue = _messages.BooleanField(2) bytesValue = _messages.BytesField(3) doubleArrayValue = _messages.MessageField('GoogleCloudAiplatformV1beta1DoubleArray', 4) doubleValue = _messages.FloatField(5) int64ArrayValue = _messages.MessageField('GoogleCloudAiplatformV1beta1Int64Array', 6) int64Value = _messages.IntegerField(7) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureValueMetadata', 8) stringArrayValue = _messages.MessageField('GoogleCloudAiplatformV1beta1StringArray', 9) stringValue = _messages.StringField(10) structValue = _messages.MessageField('GoogleCloudAiplatformV1beta1StructValue', 11) class GoogleCloudAiplatformV1beta1FeatureValueDestination(_messages.Message): r"""A destination location for Feature values and format. Fields: bigqueryDestination: Output in BigQuery format. BigQueryDestination.output_uri in FeatureValueDestination.bigquery_destination must refer to a table. csvDestination: Output in CSV format. Array Feature value types are not allowed in CSV format. tfrecordDestination: Output in TFRecord format. Below are the mapping from Feature value type in Featurestore to Feature value type in TFRecord: Value type in Featurestore | Value type in TFRecord DOUBLE, DOUBLE_ARRAY | FLOAT_LIST INT64, INT64_ARRAY | INT64_LIST STRING, STRING_ARRAY, BYTES | BYTES_LIST true -> byte_string("true"), false -> byte_string("false") BOOL, BOOL_ARRAY (true, false) | BYTES_LIST """ bigqueryDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQueryDestination', 1) csvDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1CsvDestination', 2) tfrecordDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1TFRecordDestination', 3) class GoogleCloudAiplatformV1beta1FeatureValueList(_messages.Message): r"""Container for list of values. Fields: values: A list of feature values. All of them should be the same data type. """ values = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1FeatureValueMetadata(_messages.Message): r"""Metadata of feature value. Fields: generateTime: Feature generation timestamp. Typically, it is provided by user at feature ingestion time. If not, feature store will use the system timestamp when the data is ingested into feature store. Legacy Feature Store: For streaming ingestion, the time, aligned by days, must be no older than five years (1825 days) and no later than one year (366 days) in the future. """ generateTime = _messages.StringField(1) class GoogleCloudAiplatformV1beta1FeatureView(_messages.Message): r"""FeatureView is representation of values that the FeatureOnlineStore will serve based on its syncConfig. Enums: ServiceAgentTypeValueValuesEnum: Optional. Service agent type used during data sync. By default, the Vertex AI Service Agent is used. When using an IAM Policy to isolate this FeatureView within a project, a separate service account should be provisioned by setting this field to `SERVICE_AGENT_TYPE_FEATURE_VIEW`. This will generate a separate service account to access the BigQuery source table. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: bigQuerySource: Optional. Configures how data is supposed to be extracted from a BigQuery source to be loaded onto the FeatureOnlineStore. bigtableMetadata: Output only. Metadata containing information about the Cloud Bigtable. createTime: Output only. Timestamp when this FeatureView was created. etag: Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. featureRegistrySource: Optional. Configures the features from a Feature Registry source that need to be loaded onto the FeatureOnlineStore. indexConfig: Optional. Configuration for index preparation for vector search. It contains the required configurations to create an index from source data, so that approximate nearest neighbor (a.k.a ANN) algorithms search can be performed during online serving. labels: Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. name: Identifier. Name of the FeatureView. Format: `projects/{project}/loc ations/{location}/featureOnlineStores/{feature_online_store}/featureView s/{feature_view}` optimizedConfig: Optional. Configuration for FeatureView created under Optimized FeatureOnlineStore. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. serviceAccountEmail: Output only. A Service Account unique to this FeatureView. The role bigquery.dataViewer should be granted to this service account to allow Vertex AI Feature Store to sync data to the online store. serviceAgentType: Optional. Service agent type used during data sync. By default, the Vertex AI Service Agent is used. When using an IAM Policy to isolate this FeatureView within a project, a separate service account should be provisioned by setting this field to `SERVICE_AGENT_TYPE_FEATURE_VIEW`. This will generate a separate service account to access the BigQuery source table. syncConfig: Configures when data is to be synced/updated for this FeatureView. At the end of the sync the latest featureValues for each entityId of this FeatureView are made ready for online serving. updateTime: Output only. Timestamp when this FeatureView was last updated. vectorSearchConfig: Optional. Deprecated: please use FeatureView.index_config instead. vertexRagSource: Optional. The Vertex RAG Source that the FeatureView is linked to. """ class ServiceAgentTypeValueValuesEnum(_messages.Enum): r"""Optional. Service agent type used during data sync. By default, the Vertex AI Service Agent is used. When using an IAM Policy to isolate this FeatureView within a project, a separate service account should be provisioned by setting this field to `SERVICE_AGENT_TYPE_FEATURE_VIEW`. This will generate a separate service account to access the BigQuery source table. Values: SERVICE_AGENT_TYPE_UNSPECIFIED: By default, the project-level Vertex AI Service Agent is enabled. SERVICE_AGENT_TYPE_PROJECT: Indicates the project-level Vertex AI Service Agent (https://cloud.google.com/vertex-ai/docs/general/access- control#service-agents) will be used during sync jobs. SERVICE_AGENT_TYPE_FEATURE_VIEW: Enable a FeatureView service account to be created by Vertex AI and output in the field `service_account_email`. This service account will be used to read from the source BigQuery table during sync. """ SERVICE_AGENT_TYPE_UNSPECIFIED = 0 SERVICE_AGENT_TYPE_PROJECT = 1 SERVICE_AGENT_TYPE_FEATURE_VIEW = 2 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize your FeatureViews. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one FeatureOnlineStore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) bigQuerySource = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewBigQuerySource', 1) bigtableMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewBigtableMetadata', 2) createTime = _messages.StringField(3) etag = _messages.StringField(4) featureRegistrySource = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySource', 5) indexConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewIndexConfig', 6) labels = _messages.MessageField('LabelsValue', 7) name = _messages.StringField(8) optimizedConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewOptimizedConfig', 9) satisfiesPzi = _messages.BooleanField(10) satisfiesPzs = _messages.BooleanField(11) serviceAccountEmail = _messages.StringField(12) serviceAgentType = _messages.EnumField('ServiceAgentTypeValueValuesEnum', 13) syncConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewSyncConfig', 14) updateTime = _messages.StringField(15) vectorSearchConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfig', 16) vertexRagSource = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewVertexRagSource', 17) class GoogleCloudAiplatformV1beta1FeatureViewBigQuerySource(_messages.Message): r"""A GoogleCloudAiplatformV1beta1FeatureViewBigQuerySource object. Fields: entityIdColumns: Required. Columns to construct entity_id / row keys. uri: Required. The BigQuery view URI that will be materialized on each sync trigger based on FeatureView.SyncConfig. """ entityIdColumns = _messages.StringField(1, repeated=True) uri = _messages.StringField(2) class GoogleCloudAiplatformV1beta1FeatureViewBigtableMetadata(_messages.Message): r"""Metadata for the Cloud Bigtable that supports directly interacting Bigtable instances. Fields: readAppProfile: Output only. The Bigtable App Profile to use for reading from Bigtable. """ readAppProfile = _messages.StringField(1) class GoogleCloudAiplatformV1beta1FeatureViewDataKey(_messages.Message): r"""Lookup key for a feature view. Fields: compositeKey: The actual Entity ID will be composed from this struct. This should match with the way ID is defined in the FeatureView spec. key: String key to use for lookup. """ compositeKey = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewDataKeyCompositeKey', 1) key = _messages.StringField(2) class GoogleCloudAiplatformV1beta1FeatureViewDataKeyCompositeKey(_messages.Message): r"""ID that is comprised from several parts (columns). Fields: parts: Parts to construct Entity ID. Should match with the same ID columns as defined in FeatureView in the same order. """ parts = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequest(_messages.Message): r"""Request message for FeatureOnlineStoreService.FeatureViewDirectWrite. Fields: dataKeyAndFeatureValues: Required. The data keys and associated feature values. """ dataKeyAndFeatureValues = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValues', 1, repeated=True) class GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValues(_messages.Message): r"""A data key and associated feature values to write to the feature view. Fields: dataKey: The data key. features: List of features to write. """ dataKey = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewDataKey', 1) features = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeature', 2, repeated=True) class GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeature(_messages.Message): r"""Feature name & value pair. Fields: name: Feature short name. value: Feature value. A user provided timestamp may be set in the `FeatureValue.metadata.generate_time` field. valueAndTimestamp: Feature value and timestamp. """ name = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureValue', 2) valueAndTimestamp = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeatureFeatureValueAndTimestamp', 3) class GoogleCloudAiplatformV1beta1FeatureViewDirectWriteRequestDataKeyAndFeatureValuesFeatureFeatureValueAndTimestamp(_messages.Message): r"""Feature value and timestamp. Fields: timestamp: The feature timestamp to store with this value. If not set, then the Feature Store server will generate a timestamp when it receives the write request. value: The feature value. """ timestamp = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureValue', 2) class GoogleCloudAiplatformV1beta1FeatureViewDirectWriteResponse(_messages.Message): r"""Response message for FeatureOnlineStoreService.FeatureViewDirectWrite. Fields: status: Response status for the keys listed in FeatureViewDirectWriteResponse.write_responses. The error only applies to the listed data keys - the stream will remain open for further FeatureOnlineStoreService.FeatureViewDirectWriteRequest requests. Partial failures (e.g. if the first 10 keys of a request fail, but the rest succeed) from a single request may result in multiple responses - there will be one response for the successful request keys and one response for the failing request keys. writeResponses: Details about write for each key. If status is not OK, WriteResponse.data_key will have the key with error, but WriteResponse.online_store_write_time will not be present. """ status = _messages.MessageField('GoogleRpcStatus', 1) writeResponses = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewDirectWriteResponseWriteResponse', 2, repeated=True) class GoogleCloudAiplatformV1beta1FeatureViewDirectWriteResponseWriteResponse(_messages.Message): r"""Details about the write for each key. Fields: dataKey: What key is this write response associated with. onlineStoreWriteTime: When the feature values were written to the online store. If FeatureViewDirectWriteResponse.status is not OK, this field is not populated. """ dataKey = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewDataKey', 1) onlineStoreWriteTime = _messages.StringField(2) class GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySource(_messages.Message): r"""A Feature Registry source for features that need to be synced to Online Store. Fields: featureGroups: Required. List of features that need to be synced to Online Store. projectNumber: Optional. The project number of the parent project of the Feature Groups. """ featureGroups = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySourceFeatureGroup', 1, repeated=True) projectNumber = _messages.IntegerField(2) class GoogleCloudAiplatformV1beta1FeatureViewFeatureRegistrySourceFeatureGroup(_messages.Message): r"""Features belonging to a single feature group that will be synced to Online Store. Fields: featureGroupId: Required. Identifier of the feature group. featureIds: Required. Identifiers of features under the feature group. """ featureGroupId = _messages.StringField(1) featureIds = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1FeatureViewIndexConfig(_messages.Message): r"""Configuration for vector indexing. Enums: DistanceMeasureTypeValueValuesEnum: Optional. The distance measure used in nearest neighbor search. Fields: bruteForceConfig: Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search. crowdingColumn: Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response. distanceMeasureType: Optional. The distance measure used in nearest neighbor search. embeddingColumn: Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search. embeddingDimension: Optional. The number of dimensions of the input embedding. filterColumns: Optional. Columns of features that're used to filter vector search results. treeAhConfig: Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396 """ class DistanceMeasureTypeValueValuesEnum(_messages.Enum): r"""Optional. The distance measure used in nearest neighbor search. Values: DISTANCE_MEASURE_TYPE_UNSPECIFIED: Should not be set. SQUARED_L2_DISTANCE: Euclidean (L_2) Distance. COSINE_DISTANCE: Cosine Distance. Defined as 1 - cosine similarity. We strongly suggest using DOT_PRODUCT_DISTANCE + UNIT_L2_NORM instead of COSINE distance. Our algorithms have been more optimized for DOT_PRODUCT distance which, when combined with UNIT_L2_NORM, is mathematically equivalent to COSINE distance and results in the same ranking. DOT_PRODUCT_DISTANCE: Dot Product Distance. Defined as a negative of the dot product. """ DISTANCE_MEASURE_TYPE_UNSPECIFIED = 0 SQUARED_L2_DISTANCE = 1 COSINE_DISTANCE = 2 DOT_PRODUCT_DISTANCE = 3 bruteForceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewIndexConfigBruteForceConfig', 1) crowdingColumn = _messages.StringField(2) distanceMeasureType = _messages.EnumField('DistanceMeasureTypeValueValuesEnum', 3) embeddingColumn = _messages.StringField(4) embeddingDimension = _messages.IntegerField(5, variant=_messages.Variant.INT32) filterColumns = _messages.StringField(6, repeated=True) treeAhConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewIndexConfigTreeAHConfig', 7) class GoogleCloudAiplatformV1beta1FeatureViewIndexConfigBruteForceConfig(_messages.Message): r"""Configuration options for using brute force search.""" class GoogleCloudAiplatformV1beta1FeatureViewIndexConfigTreeAHConfig(_messages.Message): r"""Configuration options for the tree-AH algorithm. Fields: leafNodeEmbeddingCount: Optional. Number of embeddings on each leaf node. The default value is 1000 if not set. """ leafNodeEmbeddingCount = _messages.IntegerField(1) class GoogleCloudAiplatformV1beta1FeatureViewOptimizedConfig(_messages.Message): r"""Configuration for FeatureViews created in Optimized FeatureOnlineStore. Fields: automaticResources: Optional. A description of resources that the FeatureView uses, which to large degree are decided by Vertex AI, and optionally allows only a modest additional configuration. If min_replica_count is not set, the default value is 2. If max_replica_count is not set, the default value is 6. The max allowed replica count is 1000. """ automaticResources = _messages.MessageField('GoogleCloudAiplatformV1beta1AutomaticResources', 1) class GoogleCloudAiplatformV1beta1FeatureViewSync(_messages.Message): r"""FeatureViewSync is a representation of sync operation which copies data from data source to Feature View in Online Store. Fields: createTime: Output only. Time when this FeatureViewSync is created. Creation of a FeatureViewSync means that the job is pending / waiting for sufficient resources but may not have started the actual data transfer yet. finalStatus: Output only. Final status of the FeatureViewSync. name: Identifier. Name of the FeatureViewSync. Format: `projects/{project} /locations/{location}/featureOnlineStores/{feature_online_store}/feature Views/{feature_view}/featureViewSyncs/{feature_view_sync}` runTime: Output only. Time when this FeatureViewSync is finished. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. syncSummary: Output only. Summary of the sync job. """ createTime = _messages.StringField(1) finalStatus = _messages.MessageField('GoogleRpcStatus', 2) name = _messages.StringField(3) runTime = _messages.MessageField('GoogleTypeInterval', 4) satisfiesPzi = _messages.BooleanField(5) satisfiesPzs = _messages.BooleanField(6) syncSummary = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewSyncSyncSummary', 7) class GoogleCloudAiplatformV1beta1FeatureViewSyncConfig(_messages.Message): r"""Configuration for Sync. Only one option is set. Fields: continuous: Optional. If true, syncs the FeatureView in a continuous manner to Online Store. cron: Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *". """ continuous = _messages.BooleanField(1) cron = _messages.StringField(2) class GoogleCloudAiplatformV1beta1FeatureViewSyncSyncSummary(_messages.Message): r"""Summary from the Sync job. For continuous syncs, the summary is updated periodically. For batch syncs, it gets updated on completion of the sync. Fields: rowSynced: Output only. Total number of rows synced. systemWatermarkTime: Lower bound of the system time watermark for the sync job. This is only set for continuously syncing feature views. totalSlot: Output only. BigQuery slot milliseconds consumed for the sync job. """ rowSynced = _messages.IntegerField(1) systemWatermarkTime = _messages.StringField(2) totalSlot = _messages.IntegerField(3) class GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfig(_messages.Message): r"""Deprecated. Use IndexConfig instead. Enums: DistanceMeasureTypeValueValuesEnum: Optional. The distance measure used in nearest neighbor search. Fields: bruteForceConfig: Optional. Configuration options for using brute force search, which simply implements the standard linear search in the database for each query. It is primarily meant for benchmarking and to generate the ground truth for approximate search. crowdingColumn: Optional. Column of crowding. This column contains crowding attribute which is a constraint on a neighbor list produced by FeatureOnlineStoreService.SearchNearestEntities to diversify search results. If NearestNeighborQuery.per_crowding_attribute_neighbor_count is set to K in SearchNearestEntitiesRequest, it's guaranteed that no more than K entities of the same crowding attribute are returned in the response. distanceMeasureType: Optional. The distance measure used in nearest neighbor search. embeddingColumn: Optional. Column of embedding. This column contains the source data to create index for vector search. embedding_column must be set when using vector search. embeddingDimension: Optional. The number of dimensions of the input embedding. filterColumns: Optional. Columns of features that're used to filter vector search results. treeAhConfig: Optional. Configuration options for the tree-AH algorithm (Shallow tree + Asymmetric Hashing). Please refer to this paper for more details: https://arxiv.org/abs/1908.10396 """ class DistanceMeasureTypeValueValuesEnum(_messages.Enum): r"""Optional. The distance measure used in nearest neighbor search. Values: DISTANCE_MEASURE_TYPE_UNSPECIFIED: Should not be set. SQUARED_L2_DISTANCE: Euclidean (L_2) Distance. COSINE_DISTANCE: Cosine Distance. Defined as 1 - cosine similarity. We strongly suggest using DOT_PRODUCT_DISTANCE + UNIT_L2_NORM instead of COSINE distance. Our algorithms have been more optimized for DOT_PRODUCT distance which, when combined with UNIT_L2_NORM, is mathematically equivalent to COSINE distance and results in the same ranking. DOT_PRODUCT_DISTANCE: Dot Product Distance. Defined as a negative of the dot product. """ DISTANCE_MEASURE_TYPE_UNSPECIFIED = 0 SQUARED_L2_DISTANCE = 1 COSINE_DISTANCE = 2 DOT_PRODUCT_DISTANCE = 3 bruteForceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigBruteForceConfig', 1) crowdingColumn = _messages.StringField(2) distanceMeasureType = _messages.EnumField('DistanceMeasureTypeValueValuesEnum', 3) embeddingColumn = _messages.StringField(4) embeddingDimension = _messages.IntegerField(5, variant=_messages.Variant.INT32) filterColumns = _messages.StringField(6, repeated=True) treeAhConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigTreeAHConfig', 7) class GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigBruteForceConfig(_messages.Message): r"""A GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigBruteForceConfig object. """ class GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigTreeAHConfig(_messages.Message): r"""A GoogleCloudAiplatformV1beta1FeatureViewVectorSearchConfigTreeAHConfig object. Fields: leafNodeEmbeddingCount: Optional. Number of embeddings on each leaf node. The default value is 1000 if not set. """ leafNodeEmbeddingCount = _messages.IntegerField(1) class GoogleCloudAiplatformV1beta1FeatureViewVertexRagSource(_messages.Message): r"""A Vertex Rag source for features that need to be synced to Online Store. Fields: ragCorpusId: Optional. The RAG corpus id corresponding to this FeatureView. uri: Required. The BigQuery view/table URI that will be materialized on each manual sync trigger. The table/view is expected to have the following columns and types at least: - `corpus_id` (STRING, NULLABLE/REQUIRED) - `file_id` (STRING, NULLABLE/REQUIRED) - `chunk_id` (STRING, NULLABLE/REQUIRED) - `chunk_data_type` (STRING, NULLABLE/REQUIRED) - `chunk_data` (STRING, NULLABLE/REQUIRED) - `embeddings` (FLOAT, REPEATED) - `file_original_uri` (STRING, NULLABLE/REQUIRED) """ ragCorpusId = _messages.IntegerField(1) uri = _messages.StringField(2) class GoogleCloudAiplatformV1beta1Featurestore(_messages.Message): r"""Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top- level container for your features and their values. Enums: StateValueValuesEnum: Output only. State of the featurestore. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize your Featurestore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Featurestore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: createTime: Output only. Timestamp when this Featurestore was created. encryptionSpec: Optional. Customer-managed encryption key spec for data storage. If set, both of the online and offline data storage will be secured by this key. etag: Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: Optional. The labels with user-defined metadata to organize your Featurestore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Featurestore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. name: Output only. Name of the Featurestore. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}` onlineServingConfig: Optional. Config for online storage resources. The field should not co-exist with the field of `OnlineStoreReplicationConfig`. If both of it and OnlineStoreReplicationConfig are unset, the feature store will not have an online store and cannot be used for online serving. onlineStorageTtlDays: Optional. TTL in days for feature values that will be stored in online serving storage. The Feature Store online storage periodically removes obsolete feature values older than `online_storage_ttl_days` since the feature generation time. Note that `online_storage_ttl_days` should be less than or equal to `offline_storage_ttl_days` for each EntityType under a featurestore. If not set, default to 4000 days satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. state: Output only. State of the featurestore. updateTime: Output only. Timestamp when this Featurestore was last updated. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. State of the featurestore. Values: STATE_UNSPECIFIED: Default value. This value is unused. STABLE: State when the featurestore configuration is not being updated and the fields reflect the current configuration of the featurestore. The featurestore is usable in this state. UPDATING: The state of the featurestore configuration when it is being updated. During an update, the fields reflect either the original configuration or the updated configuration of the featurestore. For example, `online_serving_config.fixed_node_count` can take minutes to update. While the update is in progress, the featurestore is in the UPDATING state, and the value of `fixed_node_count` can be the original value or the updated value, depending on the progress of the operation. Until the update completes, the actual number of nodes can still be the original value of `fixed_node_count`. The featurestore is still usable in this state. """ STATE_UNSPECIFIED = 0 STABLE = 1 UPDATING = 2 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize your Featurestore. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information on and examples of labels. No more than 64 user labels can be associated with one Featurestore(System labels are excluded)." System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 2) etag = _messages.StringField(3) labels = _messages.MessageField('LabelsValue', 4) name = _messages.StringField(5) onlineServingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfig', 6) onlineStorageTtlDays = _messages.IntegerField(7, variant=_messages.Variant.INT32) satisfiesPzi = _messages.BooleanField(8) satisfiesPzs = _messages.BooleanField(9) state = _messages.EnumField('StateValueValuesEnum', 10) updateTime = _messages.StringField(11) class GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfig(_messages.Message): r"""Configuration of how features in Featurestore are monitored. Fields: categoricalThresholdConfig: Threshold for categorical features of anomaly detection. This is shared by all types of Featurestore Monitoring for categorical features (i.e. Features with type (Feature.ValueType) BOOL or STRING). importFeaturesAnalysis: The config for ImportFeatures Analysis Based Feature Monitoring. numericalThresholdConfig: Threshold for numerical features of anomaly detection. This is shared by all objectives of Featurestore Monitoring for numerical features (i.e. Features with type (Feature.ValueType) DOUBLE or INT64). snapshotAnalysis: The config for Snapshot Analysis Based Feature Monitoring. """ categoricalThresholdConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigThresholdConfig', 1) importFeaturesAnalysis = _messages.MessageField('GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigImportFeaturesAnalysis', 2) numericalThresholdConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigThresholdConfig', 3) snapshotAnalysis = _messages.MessageField('GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigSnapshotAnalysis', 4) class GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigImportFeaturesAnalysis(_messages.Message): r"""Configuration of the Featurestore's ImportFeature Analysis Based Monitoring. This type of analysis generates statistics for values of each Feature imported by every ImportFeatureValues operation. Enums: AnomalyDetectionBaselineValueValuesEnum: The baseline used to do anomaly detection for the statistics generated by import features analysis. StateValueValuesEnum: Whether to enable / disable / inherite default hebavior for import features analysis. Fields: anomalyDetectionBaseline: The baseline used to do anomaly detection for the statistics generated by import features analysis. state: Whether to enable / disable / inherite default hebavior for import features analysis. """ class AnomalyDetectionBaselineValueValuesEnum(_messages.Enum): r"""The baseline used to do anomaly detection for the statistics generated by import features analysis. Values: BASELINE_UNSPECIFIED: Should not be used. LATEST_STATS: Choose the later one statistics generated by either most recent snapshot analysis or previous import features analysis. If non of them exists, skip anomaly detection and only generate a statistics. MOST_RECENT_SNAPSHOT_STATS: Use the statistics generated by the most recent snapshot analysis if exists. PREVIOUS_IMPORT_FEATURES_STATS: Use the statistics generated by the previous import features analysis if exists. """ BASELINE_UNSPECIFIED = 0 LATEST_STATS = 1 MOST_RECENT_SNAPSHOT_STATS = 2 PREVIOUS_IMPORT_FEATURES_STATS = 3 class StateValueValuesEnum(_messages.Enum): r"""Whether to enable / disable / inherite default hebavior for import features analysis. Values: STATE_UNSPECIFIED: Should not be used. DEFAULT: The default behavior of whether to enable the monitoring. EntityType-level config: disabled. Feature-level config: inherited from the configuration of EntityType this Feature belongs to. ENABLED: Explicitly enables import features analysis. EntityType-level config: by default enables import features analysis for all Features under it. Feature-level config: enables import features analysis regardless of the EntityType-level config. DISABLED: Explicitly disables import features analysis. EntityType-level config: by default disables import features analysis for all Features under it. Feature-level config: disables import features analysis regardless of the EntityType-level config. """ STATE_UNSPECIFIED = 0 DEFAULT = 1 ENABLED = 2 DISABLED = 3 anomalyDetectionBaseline = _messages.EnumField('AnomalyDetectionBaselineValueValuesEnum', 1) state = _messages.EnumField('StateValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigSnapshotAnalysis(_messages.Message): r"""Configuration of the Featurestore's Snapshot Analysis Based Monitoring. This type of analysis generates statistics for each Feature based on a snapshot of the latest feature value of each entities every monitoring_interval. Fields: disabled: The monitoring schedule for snapshot analysis. For EntityType- level config: unset / disabled = true indicates disabled by default for Features under it; otherwise by default enable snapshot analysis monitoring with monitoring_interval for Features under it. Feature-level config: disabled = true indicates disabled regardless of the EntityType- level config; unset monitoring_interval indicates going with EntityType- level config; otherwise run snapshot analysis monitoring with monitoring_interval regardless of the EntityType-level config. Explicitly Disable the snapshot analysis based monitoring. monitoringInterval: Configuration of the snapshot analysis based monitoring pipeline running interval. The value is rolled up to full day. If both monitoring_interval_days and the deprecated `monitoring_interval` field are set when creating/updating EntityTypes/Features, monitoring_interval_days will be used. monitoringIntervalDays: Configuration of the snapshot analysis based monitoring pipeline running interval. The value indicates number of days. stalenessDays: Customized export features time window for snapshot analysis. Unit is one day. Default value is 3 weeks. Minimum value is 1 day. Maximum value is 4000 days. """ disabled = _messages.BooleanField(1) monitoringInterval = _messages.StringField(2) monitoringIntervalDays = _messages.IntegerField(3, variant=_messages.Variant.INT32) stalenessDays = _messages.IntegerField(4, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1FeaturestoreMonitoringConfigThresholdConfig(_messages.Message): r"""The config for Featurestore Monitoring threshold. Fields: value: Specify a threshold value that can trigger the alert. 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen\u2013Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature. """ value = _messages.FloatField(1) class GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfig(_messages.Message): r"""OnlineServingConfig specifies the details for provisioning online serving resources. Fields: fixedNodeCount: The number of nodes for the online store. The number of nodes doesn't scale automatically, but you can manually update the number of nodes. If set to 0, the featurestore will not have an online store and cannot be used for online serving. scaling: Online serving scaling configuration. Only one of `fixed_node_count` and `scaling` can be set. Setting one will reset the other. """ fixedNodeCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) scaling = _messages.MessageField('GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfigScaling', 2) class GoogleCloudAiplatformV1beta1FeaturestoreOnlineServingConfigScaling(_messages.Message): r"""Online serving scaling configuration. If min_node_count and max_node_count are set to the same value, the cluster will be configured with the fixed number of node (no auto-scaling). Fields: cpuUtilizationTarget: Optional. The cpu utilization that the Autoscaler should be trying to achieve. This number is on a scale from 0 (no utilization) to 100 (total utilization), and is limited between 10 and 80. When a cluster's CPU utilization exceeds the target that you have set, Bigtable immediately adds nodes to the cluster. When CPU utilization is substantially lower than the target, Bigtable removes nodes. If not set or set to 0, default to 50. maxNodeCount: The maximum number of nodes to scale up to. Must be greater than min_node_count, and less than or equal to 10 times of 'min_node_count'. minNodeCount: Required. The minimum number of nodes to scale down to. Must be greater than or equal to 1. """ cpuUtilizationTarget = _messages.IntegerField(1, variant=_messages.Variant.INT32) maxNodeCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) minNodeCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1FetchExamplesRequest(_messages.Message): r"""Request message for ExampleStoreService.FetchExamples. Fields: exampleIds: Optional. Example IDs to fetch. If both metadata filters and Example IDs are specified, then both ID and metadata filtering will be applied. pageSize: Optional. The maximum number of examples to return. The service may return fewer than this value. If unspecified, at most 100 examples will be returned. pageToken: Optional. The next_page_token value returned from a previous list ExampleStoreService.FetchExamplesResponse call. storedContentsExampleFilter: The metadata filters for StoredContentsExamples. """ exampleIds = _messages.StringField(1, repeated=True) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) storedContentsExampleFilter = _messages.MessageField('GoogleCloudAiplatformV1beta1StoredContentsExampleFilter', 4) class GoogleCloudAiplatformV1beta1FetchExamplesResponse(_messages.Message): r"""Response message for ExampleStoreService.FetchExamples. Fields: examples: The examples in the Example Store that satisfy the metadata filters. nextPageToken: A token, which can be sent as FetchExamplesRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages. """ examples = _messages.MessageField('GoogleCloudAiplatformV1beta1Example', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1FetchFeatureValuesRequest(_messages.Message): r"""Request message for FeatureOnlineStoreService.FetchFeatureValues. All the features under the requested feature view will be returned. Enums: DataFormatValueValuesEnum: Optional. Response data format. If not set, FeatureViewDataFormat.KEY_VALUE will be used. FormatValueValuesEnum: Specify response data format. If not set, KeyValue format will be used. Deprecated. Use FetchFeatureValuesRequest.data_format. Fields: dataFormat: Optional. Response data format. If not set, FeatureViewDataFormat.KEY_VALUE will be used. dataKey: Optional. The request key to fetch feature values for. format: Specify response data format. If not set, KeyValue format will be used. Deprecated. Use FetchFeatureValuesRequest.data_format. id: Simple ID. The whole string will be used as is to identify Entity to fetch feature values for. """ class DataFormatValueValuesEnum(_messages.Enum): r"""Optional. Response data format. If not set, FeatureViewDataFormat.KEY_VALUE will be used. Values: FEATURE_VIEW_DATA_FORMAT_UNSPECIFIED: Not set. Will be treated as the KeyValue format. KEY_VALUE: Return response data in key-value format. PROTO_STRUCT: Return response data in proto Struct format. """ FEATURE_VIEW_DATA_FORMAT_UNSPECIFIED = 0 KEY_VALUE = 1 PROTO_STRUCT = 2 class FormatValueValuesEnum(_messages.Enum): r"""Specify response data format. If not set, KeyValue format will be used. Deprecated. Use FetchFeatureValuesRequest.data_format. Values: FORMAT_UNSPECIFIED: Not set. Will be treated as the KeyValue format. KEY_VALUE: Return response data in key-value format. PROTO_STRUCT: Return response data in proto Struct format. """ FORMAT_UNSPECIFIED = 0 KEY_VALUE = 1 PROTO_STRUCT = 2 dataFormat = _messages.EnumField('DataFormatValueValuesEnum', 1) dataKey = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewDataKey', 2) format = _messages.EnumField('FormatValueValuesEnum', 3) id = _messages.StringField(4) class GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse(_messages.Message): r"""Response message for FeatureOnlineStoreService.FetchFeatureValues Messages: ProtoStructValue: Feature values in proto Struct format. Fields: dataKey: The data key associated with this response. Will only be populated for FeatureOnlineStoreService.StreamingFetchFeatureValues RPCs. keyValues: Feature values in KeyValue format. protoStruct: Feature values in proto Struct format. """ @encoding.MapUnrecognizedFields('additionalProperties') class ProtoStructValue(_messages.Message): r"""Feature values in proto Struct format. Messages: AdditionalProperty: An additional property for a ProtoStructValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a ProtoStructValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) dataKey = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewDataKey', 1) keyValues = _messages.MessageField('GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairList', 2) protoStruct = _messages.MessageField('ProtoStructValue', 3) class GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairList(_messages.Message): r"""Response structure in the format of key (feature name) and (feature) value pair. Fields: features: List of feature names and values. """ features = _messages.MessageField('GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair', 1, repeated=True) class GoogleCloudAiplatformV1beta1FetchFeatureValuesResponseFeatureNameValuePairListFeatureNameValuePair(_messages.Message): r"""Feature name & value pair. Fields: name: Feature short name. value: Feature value. """ name = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureValue', 2) class GoogleCloudAiplatformV1beta1FetchPredictOperationRequest(_messages.Message): r"""Request message for PredictionService.FetchPredictOperation. Fields: operationName: Required. The server-assigned name for the operation. """ operationName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1FileData(_messages.Message): r"""URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. Fields: displayName: Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled. fileUri: Required. The URI of the file in Google Cloud Storage. mimeType: Required. The IANA standard MIME type of the source data. """ displayName = _messages.StringField(1) fileUri = _messages.StringField(2) mimeType = _messages.StringField(3) class GoogleCloudAiplatformV1beta1FileStatus(_messages.Message): r"""RagFile status. Enums: StateValueValuesEnum: Output only. RagFile state. Fields: errorStatus: Output only. Only when the `state` field is ERROR. state: Output only. RagFile state. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. RagFile state. Values: STATE_UNSPECIFIED: RagFile state is unspecified. ACTIVE: RagFile resource has been created and indexed successfully. ERROR: RagFile resource is in a problematic state. See `error_message` field for details. """ STATE_UNSPECIFIED = 0 ACTIVE = 1 ERROR = 2 errorStatus = _messages.StringField(1) state = _messages.EnumField('StateValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1FilterSplit(_messages.Message): r"""Assigns input data to training, validation, and test sets based on the given filters, data pieces not matched by any filter are ignored. Currently only supported for Datasets containing DataItems. If any of the filters in this message are to match nothing, then they can be set as '-' (the minus sign). Supported only for unstructured Datasets. Fields: testFilter: Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to test the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order. trainingFilter: Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to train the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order. validationFilter: Required. A filter on DataItems of the Dataset. DataItems that match this filter are used to validate the Model. A filter with same syntax as the one used in DatasetService.ListDataItems may be used. If a single DataItem is matched by more than one of the FilterSplit filters, then it is assigned to the first set that applies to it in the training, validation, test order. """ testFilter = _messages.StringField(1) trainingFilter = _messages.StringField(2) validationFilter = _messages.StringField(3) class GoogleCloudAiplatformV1beta1FindNeighborsRequest(_messages.Message): r"""The request message for MatchService.FindNeighbors. Fields: deployedIndexId: The ID of the DeployedIndex that will serve the request. This request is sent to a specific IndexEndpoint, as per the IndexEndpoint.network. That IndexEndpoint also has IndexEndpoint.deployed_indexes, and each such index has a DeployedIndex.id field. The value of the field below must equal one of the DeployedIndex.id fields of the IndexEndpoint that is being called for this request. queries: The list of queries. returnFullDatapoint: If set to true, the full datapoints (including all vector values and restricts) of the nearest neighbors are returned. Note that returning full datapoint will significantly increase the latency and cost of the query. """ deployedIndexId = _messages.StringField(1) queries = _messages.MessageField('GoogleCloudAiplatformV1beta1FindNeighborsRequestQuery', 2, repeated=True) returnFullDatapoint = _messages.BooleanField(3) class GoogleCloudAiplatformV1beta1FindNeighborsRequestQuery(_messages.Message): r"""A query to find a number of the nearest neighbors (most similar vectors) of a vector. Fields: approximateNeighborCount: The number of neighbors to find via approximate search before exact reordering is performed. If not set, the default value from scam config is used; if set, this value must be > 0. datapoint: Required. The datapoint/vector whose nearest neighbors should be searched for. fractionLeafNodesToSearchOverride: The fraction of the number of leaves to search, set at query time allows user to tune search performance. This value increase result in both search accuracy and latency increase. The value should be between 0.0 and 1.0. If not set or set to 0.0, query uses the default value specified in NearestNeighborSearchConfig.TreeAHConfig.fraction_leaf_nodes_to_search. neighborCount: The number of nearest neighbors to be retrieved from database for each query. If not set, will use the default from the service configuration (https://cloud.google.com/vertex-ai/docs/matching- engine/configuring-indexes#nearest-neighbor-search-config). perCrowdingAttributeNeighborCount: Crowding is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute. It's used for improving result diversity. This field is the maximum number of matches with the same crowding tag. rrf: Optional. Represents RRF algorithm that combines search results. """ approximateNeighborCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) datapoint = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexDatapoint', 2) fractionLeafNodesToSearchOverride = _messages.FloatField(3) neighborCount = _messages.IntegerField(4, variant=_messages.Variant.INT32) perCrowdingAttributeNeighborCount = _messages.IntegerField(5, variant=_messages.Variant.INT32) rrf = _messages.MessageField('GoogleCloudAiplatformV1beta1FindNeighborsRequestQueryRRF', 6) class GoogleCloudAiplatformV1beta1FindNeighborsRequestQueryRRF(_messages.Message): r"""Parameters for RRF algorithm that combines search results. Fields: alpha: Required. Users can provide an alpha value to give more weight to dense vs sparse results. For example, if the alpha is 0, we only return sparse and if the alpha is 1, we only return dense. """ alpha = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1FindNeighborsResponse(_messages.Message): r"""The response message for MatchService.FindNeighbors. Fields: nearestNeighbors: The nearest neighbors of the query datapoints. """ nearestNeighbors = _messages.MessageField('GoogleCloudAiplatformV1beta1FindNeighborsResponseNearestNeighbors', 1, repeated=True) class GoogleCloudAiplatformV1beta1FindNeighborsResponseNearestNeighbors(_messages.Message): r"""Nearest neighbors for one query. Fields: id: The ID of the query datapoint. neighbors: All its neighbors. """ id = _messages.StringField(1) neighbors = _messages.MessageField('GoogleCloudAiplatformV1beta1FindNeighborsResponseNeighbor', 2, repeated=True) class GoogleCloudAiplatformV1beta1FindNeighborsResponseNeighbor(_messages.Message): r"""A neighbor of the query vector. Fields: datapoint: The datapoint of the neighbor. Note that full datapoints are returned only when "return_full_datapoint" is set to true. Otherwise, only the "datapoint_id" and "crowding_tag" fields are populated. distance: The distance between the neighbor and the dense embedding query. sparseDistance: The distance between the neighbor and the query sparse_embedding. """ datapoint = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexDatapoint', 1) distance = _messages.FloatField(2) sparseDistance = _messages.FloatField(3) class GoogleCloudAiplatformV1beta1FlexStart(_messages.Message): r"""FlexStart is used to schedule the deployment workload on DWS resource. It contains the max duration of the deployment. Fields: maxRuntimeDuration: The max duration of the deployment is max_runtime_duration. The deployment will be terminated after the duration. The max_runtime_duration can be set up to 7 days. """ maxRuntimeDuration = _messages.StringField(1) class GoogleCloudAiplatformV1beta1FluencyInput(_messages.Message): r"""Input for fluency metric. Fields: instance: Required. Fluency instance. metricSpec: Required. Spec for fluency score metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1FluencyInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1FluencySpec', 2) class GoogleCloudAiplatformV1beta1FluencyInstance(_messages.Message): r"""Spec for fluency instance. Fields: prediction: Required. Output of the evaluated model. """ prediction = _messages.StringField(1) class GoogleCloudAiplatformV1beta1FluencyResult(_messages.Message): r"""Spec for fluency result. Fields: confidence: Output only. Confidence for fluency score. explanation: Output only. Explanation for fluency score. score: Output only. Fluency score. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1FluencySpec(_messages.Message): r"""Spec for fluency score metric. Fields: version: Optional. Which version to use for evaluation. """ version = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1FractionSplit(_messages.Message): r"""Assigns the input data to training, validation, and test sets as per the given fractions. Any of `training_fraction`, `validation_fraction` and `test_fraction` may optionally be provided, they must sum to up to 1. If the provided ones sum to less than 1, the remainder is assigned to sets as decided by Vertex AI. If none of the fractions are set, by default roughly 80% of data is used for training, 10% for validation, and 10% for test. Fields: testFraction: The fraction of the input data that is to be used to evaluate the Model. trainingFraction: The fraction of the input data that is to be used to train the Model. validationFraction: The fraction of the input data that is to be used to validate the Model. """ testFraction = _messages.FloatField(1) trainingFraction = _messages.FloatField(2) validationFraction = _messages.FloatField(3) class GoogleCloudAiplatformV1beta1FulfillmentInput(_messages.Message): r"""Input for fulfillment metric. Fields: instance: Required. Fulfillment instance. metricSpec: Required. Spec for fulfillment score metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1FulfillmentInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1FulfillmentSpec', 2) class GoogleCloudAiplatformV1beta1FulfillmentInstance(_messages.Message): r"""Spec for fulfillment instance. Fields: instruction: Required. Inference instruction prompt to compare prediction with. prediction: Required. Output of the evaluated model. """ instruction = _messages.StringField(1) prediction = _messages.StringField(2) class GoogleCloudAiplatformV1beta1FulfillmentResult(_messages.Message): r"""Spec for fulfillment result. Fields: confidence: Output only. Confidence for fulfillment score. explanation: Output only. Explanation for fulfillment score. score: Output only. Fulfillment score. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1FulfillmentSpec(_messages.Message): r"""Spec for fulfillment metric. Fields: version: Optional. Which version to use for evaluation. """ version = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1FullFineTuningSpec(_messages.Message): r"""Tuning Spec for Full Fine Tuning. Fields: hyperParameters: Optional. Hyperparameters for Full Fine Tuning. trainingDatasetUri: Required. Training dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset. validationDatasetUri: Optional. Validation dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset. """ hyperParameters = _messages.MessageField('GoogleCloudAiplatformV1beta1SupervisedHyperParameters', 1) trainingDatasetUri = _messages.StringField(2) validationDatasetUri = _messages.StringField(3) class GoogleCloudAiplatformV1beta1FunctionCall(_messages.Message): r"""A predicted [FunctionCall] returned from the model that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing the parameters and their values. Messages: ArgsValue: Optional. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details. Fields: args: Optional. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details. id: Optional. The unique id of the function call. If populated, the client to execute the `function_call` and return the response with the matching `id`. name: Optional. The name of the function to call. Matches [FunctionDeclaration.name]. """ @encoding.MapUnrecognizedFields('additionalProperties') class ArgsValue(_messages.Message): r"""Optional. The function parameters and values in JSON object format. See [FunctionDeclaration.parameters] for parameter details. Messages: AdditionalProperty: An additional property for a ArgsValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a ArgsValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) args = _messages.MessageField('ArgsValue', 1) id = _messages.StringField(2) name = _messages.StringField(3) class GoogleCloudAiplatformV1beta1FunctionCallingConfig(_messages.Message): r"""Function calling config. Enums: ModeValueValuesEnum: Optional. Function calling mode. Fields: allowedFunctionNames: Optional. Function names to call. Only set when the Mode is ANY. Function names should match [FunctionDeclaration.name]. With mode set to ANY, model will predict a function call from the set of function names provided. mode: Optional. Function calling mode. """ class ModeValueValuesEnum(_messages.Enum): r"""Optional. Function calling mode. Values: MODE_UNSPECIFIED: Unspecified function calling mode. This value should not be used. AUTO: Default model behavior, model decides to predict either function calls or natural language response. ANY: Model is constrained to always predicting function calls only. If "allowed_function_names" are set, the predicted function calls will be limited to any one of "allowed_function_names", else the predicted function calls will be any one of the provided "function_declarations". NONE: Model will not predict any function calls. Model behavior is same as when not passing any function declarations. VALIDATED: Model is constrained to predict either function calls or natural language response. If "allowed_function_names" are set, the predicted function calls will be limited to any one of "allowed_function_names", else the predicted function calls will be any one of the provided "function_declarations". """ MODE_UNSPECIFIED = 0 AUTO = 1 ANY = 2 NONE = 3 VALIDATED = 4 allowedFunctionNames = _messages.StringField(1, repeated=True) mode = _messages.EnumField('ModeValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1FunctionDeclaration(_messages.Message): r"""Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client. Fields: description: Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function. name: Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots and dashes, with a maximum length of 64. parameters: Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1 parametersJsonSchema: Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`. response: Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function. responseJsonSchema: Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`. """ description = _messages.StringField(1) name = _messages.StringField(2) parameters = _messages.MessageField('GoogleCloudAiplatformV1beta1Schema', 3) parametersJsonSchema = _messages.MessageField('extra_types.JsonValue', 4) response = _messages.MessageField('GoogleCloudAiplatformV1beta1Schema', 5) responseJsonSchema = _messages.MessageField('extra_types.JsonValue', 6) class GoogleCloudAiplatformV1beta1FunctionResponse(_messages.Message): r"""The result output from a [FunctionCall] that contains a string representing the [FunctionDeclaration.name] and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a [FunctionCall] made based on model prediction. Messages: ResponseValue: Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output. Fields: id: Optional. The id of the function call this response is for. Populated by the client to match the corresponding function call `id`. name: Required. The name of the function to call. Matches [FunctionDeclaration.name] and [FunctionCall.name]. parts: Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types. response: Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output. """ @encoding.MapUnrecognizedFields('additionalProperties') class ResponseValue(_messages.Message): r"""Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output. Messages: AdditionalProperty: An additional property for a ResponseValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a ResponseValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) id = _messages.StringField(1) name = _messages.StringField(2) parts = _messages.MessageField('GoogleCloudAiplatformV1beta1FunctionResponsePart', 3, repeated=True) response = _messages.MessageField('ResponseValue', 4) class GoogleCloudAiplatformV1beta1FunctionResponseBlob(_messages.Message): r"""Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. Fields: data: Required. Raw bytes. displayName: Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled. mimeType: Required. The IANA standard MIME type of the source data. """ data = _messages.BytesField(1) displayName = _messages.StringField(2) mimeType = _messages.StringField(3) class GoogleCloudAiplatformV1beta1FunctionResponseFileData(_messages.Message): r"""URI based data for function response. Fields: displayName: Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled. fileUri: Required. URI. mimeType: Required. The IANA standard MIME type of the source data. """ displayName = _messages.StringField(1) fileUri = _messages.StringField(2) mimeType = _messages.StringField(3) class GoogleCloudAiplatformV1beta1FunctionResponsePart(_messages.Message): r"""A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes. Fields: fileData: URI based data. inlineData: Inline media bytes. """ fileData = _messages.MessageField('GoogleCloudAiplatformV1beta1FunctionResponseFileData', 1) inlineData = _messages.MessageField('GoogleCloudAiplatformV1beta1FunctionResponseBlob', 2) class GoogleCloudAiplatformV1beta1GcsDestination(_messages.Message): r"""The Google Cloud Storage location where the output is to be written to. Fields: outputUriPrefix: Required. Google Cloud Storage URI to output directory. If the uri doesn't end with '/', a '/' will be automatically appended. The directory is created if it doesn't exist. """ outputUriPrefix = _messages.StringField(1) class GoogleCloudAiplatformV1beta1GcsSource(_messages.Message): r"""The Google Cloud Storage location for the input content. Fields: uris: Required. Google Cloud Storage URI(-s) to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/wildcards. """ uris = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1GdcConfig(_messages.Message): r"""Google Distributed Cloud (GDC) config. Fields: zone: GDC zone. A cluster will be designated for the Vertex AI workload in this zone. """ zone = _messages.StringField(1) class GoogleCloudAiplatformV1beta1GdceConfig(_messages.Message): r"""Google Distributed Cloud Edge (GDCE) config. Fields: zone: GDCE zone. A cluster will be designated for the Vertex AI workload in this zone. Format: `-edge-[-]#`. Example: us-central1-edge-att-dfw1. """ zone = _messages.StringField(1) class GoogleCloudAiplatformV1beta1GeminiExample(_messages.Message): r"""Format for Gemini examples used for Vertex Multimodal datasets. Messages: LabelsValue: Optional. The labels with user-defined metadata for the request. It is used for billing and reporting only. Label keys and values can be no longer than 63 characters (Unicode codepoints) and can only contain lowercase letters, numeric characters, underscores, and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter. Fields: cachedContent: Optional. The name of the cached content used as context to serve the prediction. Note: only used in explicit caching, where users can have control over caching (e.g. what content to cache) and enjoy guaranteed cost savings. Format: `projects/{project}/locations/{location}/cachedContents/{cachedContent}` contents: Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi- turn queries, this is a repeated field that contains conversation history + latest request. generationConfig: Optional. Generation config. labels: Optional. The labels with user-defined metadata for the request. It is used for billing and reporting only. Label keys and values can be no longer than 63 characters (Unicode codepoints) and can only contain lowercase letters, numeric characters, underscores, and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter. model: Optional. The fully qualified name of the publisher model or tuned model endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}` safetySettings: Optional. Per request settings for blocking unsafe content. Enforced on GenerateContentResponse.candidates. systemInstruction: Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph. toolConfig: Optional. Tool config. This config is shared for all tools provided in the request. tools: Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata for the request. It is used for billing and reporting only. Label keys and values can be no longer than 63 characters (Unicode codepoints) and can only contain lowercase letters, numeric characters, underscores, and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) cachedContent = _messages.StringField(1) contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 2, repeated=True) generationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerationConfig', 3) labels = _messages.MessageField('LabelsValue', 4) model = _messages.StringField(5) safetySettings = _messages.MessageField('GoogleCloudAiplatformV1beta1SafetySetting', 6, repeated=True) systemInstruction = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 7) toolConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolConfig', 8) tools = _messages.MessageField('GoogleCloudAiplatformV1beta1Tool', 9, repeated=True) class GoogleCloudAiplatformV1beta1GeminiPreferenceExample(_messages.Message): r"""Input example for preference optimization. Fields: completions: List of completions for a given prompt. contents: Multi-turn contents that represents the Prompt. """ completions = _messages.MessageField('GoogleCloudAiplatformV1beta1GeminiPreferenceExampleCompletion', 1, repeated=True) contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 2, repeated=True) class GoogleCloudAiplatformV1beta1GeminiPreferenceExampleCompletion(_messages.Message): r"""Completion and its preference score. Fields: completion: Single turn completion for the given prompt. score: The score for the given completion. """ completion = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1) score = _messages.FloatField(2, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1GeminiRequestReadConfig(_messages.Message): r"""Configuration for how to read Gemini requests from a multimodal dataset. Fields: assembledRequestColumnName: Optional. Column name in the dataset table that contains already fully assembled Gemini requests. templateConfig: Gemini request template with placeholders. """ assembledRequestColumnName = _messages.StringField(1) templateConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GeminiTemplateConfig', 2) class GoogleCloudAiplatformV1beta1GeminiTemplateConfig(_messages.Message): r"""Template configuration to create Gemini examples from a multimodal dataset. Messages: FieldMappingValue: Required. Map of template parameters to the columns in the dataset table. Fields: fieldMapping: Required. Map of template parameters to the columns in the dataset table. geminiExample: Required. The template that will be used for assembling the request to use for downstream applications. """ @encoding.MapUnrecognizedFields('additionalProperties') class FieldMappingValue(_messages.Message): r"""Required. Map of template parameters to the columns in the dataset table. Messages: AdditionalProperty: An additional property for a FieldMappingValue object. Fields: additionalProperties: Additional properties of type FieldMappingValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a FieldMappingValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) fieldMapping = _messages.MessageField('FieldMappingValue', 1) geminiExample = _messages.MessageField('GoogleCloudAiplatformV1beta1GeminiExample', 2) class GoogleCloudAiplatformV1beta1GenAiAdvancedFeaturesConfig(_messages.Message): r"""Configuration for GenAiAdvancedFeatures. Fields: ragConfig: Configuration for Retrieval Augmented Generation feature. """ ragConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GenAiAdvancedFeaturesConfigRagConfig', 1) class GoogleCloudAiplatformV1beta1GenAiAdvancedFeaturesConfigRagConfig(_messages.Message): r"""Configuration for Retrieval Augmented Generation feature. Fields: enableRag: If true, enable Retrieval Augmented Generation in ChatCompletion request. Once enabled, the endpoint will be identified as GenAI endpoint and Arthedain router will be used. """ enableRag = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1GenerateAccessTokenRequest(_messages.Message): r"""Request message for NotebookInternalService.GenerateAccessToken. Fields: vmToken: Required. The VM identity token (a JWT) for authenticating the VM. https://cloud.google.com/compute/docs/instances/verifying-instance- identity """ vmToken = _messages.StringField(1) class GoogleCloudAiplatformV1beta1GenerateAccessTokenResponse(_messages.Message): r"""Response message for NotebookInternalService.GenerateToken. Fields: accessToken: Short-lived access token string which may be used to access Google APIs. expiresIn: The time in seconds when the access token expires. Typically that's 3600. scope: Space-separated list of scopes contained in the returned token. https://cloud.google.com/docs/authentication/token-types#access-contents tokenType: Type of the returned access token (e.g. "Bearer"). It specifies how the token must be used. Bearer tokens may be used by any entity without proof of identity. """ accessToken = _messages.StringField(1) expiresIn = _messages.IntegerField(2, variant=_messages.Variant.INT32) scope = _messages.StringField(3) tokenType = _messages.StringField(4) class GoogleCloudAiplatformV1beta1GenerateContentRequest(_messages.Message): r"""Request message for [PredictionService.GenerateContent]. Messages: LabelsValue: Optional. The labels with user-defined metadata for the request. It is used for billing and reporting only. Label keys and values can be no longer than 63 characters (Unicode codepoints) and can only contain lowercase letters, numeric characters, underscores, and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter. Fields: cachedContent: Optional. The name of the cached content used as context to serve the prediction. Note: only used in explicit caching, where users can have control over caching (e.g. what content to cache) and enjoy guaranteed cost savings. Format: `projects/{project}/locations/{location}/cachedContents/{cachedContent}` contents: Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi- turn queries, this is a repeated field that contains conversation history + latest request. generationConfig: Optional. Generation config. labels: Optional. The labels with user-defined metadata for the request. It is used for billing and reporting only. Label keys and values can be no longer than 63 characters (Unicode codepoints) and can only contain lowercase letters, numeric characters, underscores, and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter. modelArmorConfig: Optional. Settings for prompt and response sanitization using the Model Armor service. If supplied, safety_settings must not be supplied. safetySettings: Optional. Per request settings for blocking unsafe content. Enforced on GenerateContentResponse.candidates. systemInstruction: Optional. The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph. toolConfig: Optional. Tool config. This config is shared for all tools provided in the request. tools: Optional. A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata for the request. It is used for billing and reporting only. Label keys and values can be no longer than 63 characters (Unicode codepoints) and can only contain lowercase letters, numeric characters, underscores, and dashes. International characters are allowed. Label values are optional. Label keys must start with a letter. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) cachedContent = _messages.StringField(1) contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 2, repeated=True) generationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerationConfig', 3) labels = _messages.MessageField('LabelsValue', 4) modelArmorConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelArmorConfig', 5) safetySettings = _messages.MessageField('GoogleCloudAiplatformV1beta1SafetySetting', 6, repeated=True) systemInstruction = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 7) toolConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolConfig', 8) tools = _messages.MessageField('GoogleCloudAiplatformV1beta1Tool', 9, repeated=True) class GoogleCloudAiplatformV1beta1GenerateContentResponse(_messages.Message): r"""Response message for [PredictionService.GenerateContent]. Fields: candidates: Output only. Generated candidates. createTime: Output only. Timestamp when the request is made to the server. modelVersion: Output only. The model version used to generate the response. promptFeedback: Output only. Content filter results for a prompt sent in the request. Note: Sent only in the first stream chunk. Only happens when no candidates were generated due to content violations. responseId: Output only. response_id is used to identify each response. It is the encoding of the event_id. usageMetadata: Usage metadata about the response(s). """ candidates = _messages.MessageField('GoogleCloudAiplatformV1beta1Candidate', 1, repeated=True) createTime = _messages.StringField(2) modelVersion = _messages.StringField(3) promptFeedback = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback', 4) responseId = _messages.StringField(5) usageMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata', 6) class GoogleCloudAiplatformV1beta1GenerateContentResponsePromptFeedback(_messages.Message): r"""Content filter results for a prompt sent in the request. Note: This is sent only in the first stream chunk and only if no candidates were generated due to content violations. Enums: BlockReasonValueValuesEnum: Output only. The reason why the prompt was blocked. Fields: blockReason: Output only. The reason why the prompt was blocked. blockReasonMessage: Output only. A readable message that explains the reason why the prompt was blocked. safetyRatings: Output only. A list of safety ratings for the prompt. There is one rating per category. """ class BlockReasonValueValuesEnum(_messages.Enum): r"""Output only. The reason why the prompt was blocked. Values: BLOCKED_REASON_UNSPECIFIED: The blocked reason is unspecified. SAFETY: The prompt was blocked for safety reasons. OTHER: The prompt was blocked for other reasons. For example, it may be due to the prompt's language, or because it contains other harmful content. BLOCKLIST: The prompt was blocked because it contains a term from the terminology blocklist. PROHIBITED_CONTENT: The prompt was blocked because it contains prohibited content. MODEL_ARMOR: The prompt was blocked by Model Armor. IMAGE_SAFETY: The prompt was blocked because it contains content that is unsafe for image generation. JAILBREAK: The prompt was blocked as a jailbreak attempt. """ BLOCKED_REASON_UNSPECIFIED = 0 SAFETY = 1 OTHER = 2 BLOCKLIST = 3 PROHIBITED_CONTENT = 4 MODEL_ARMOR = 5 IMAGE_SAFETY = 6 JAILBREAK = 7 blockReason = _messages.EnumField('BlockReasonValueValuesEnum', 1) blockReasonMessage = _messages.StringField(2) safetyRatings = _messages.MessageField('GoogleCloudAiplatformV1beta1SafetyRating', 3, repeated=True) class GoogleCloudAiplatformV1beta1GenerateContentResponseUsageMetadata(_messages.Message): r"""Usage metadata about the content generation request and response. This message provides a detailed breakdown of token usage and other relevant metrics. Enums: TrafficTypeValueValuesEnum: Output only. The traffic type for this request. Fields: cacheTokensDetails: Output only. A detailed breakdown of the token count for each modality in the cached content. cachedContentTokenCount: Output only. The number of tokens in the cached content that was used for this request. candidatesTokenCount: The total number of tokens in the generated candidates. candidatesTokensDetails: Output only. A detailed breakdown of the token count for each modality in the generated candidates. promptTokenCount: The total number of tokens in the prompt. This includes any text, images, or other media provided in the request. When `cached_content` is set, this also includes the number of tokens in the cached content. promptTokensDetails: Output only. A detailed breakdown of the token count for each modality in the prompt. thoughtsTokenCount: Output only. The number of tokens that were part of the model's generated "thoughts" output, if applicable. toolUsePromptTokenCount: Output only. The number of tokens in the results from tool executions, which are provided back to the model as input, if applicable. toolUsePromptTokensDetails: Output only. A detailed breakdown by modality of the token counts from the results of tool executions, which are provided back to the model as input. totalTokenCount: The total number of tokens for the entire request. This is the sum of `prompt_token_count`, `candidates_token_count`, `tool_use_prompt_token_count`, and `thoughts_token_count`. trafficType: Output only. The traffic type for this request. """ class TrafficTypeValueValuesEnum(_messages.Enum): r"""Output only. The traffic type for this request. Values: TRAFFIC_TYPE_UNSPECIFIED: Unspecified request traffic type. ON_DEMAND: The request was processed using Pay-As-You-Go quota. PROVISIONED_THROUGHPUT: Type for Provisioned Throughput traffic. """ TRAFFIC_TYPE_UNSPECIFIED = 0 ON_DEMAND = 1 PROVISIONED_THROUGHPUT = 2 cacheTokensDetails = _messages.MessageField('GoogleCloudAiplatformV1beta1ModalityTokenCount', 1, repeated=True) cachedContentTokenCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) candidatesTokenCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) candidatesTokensDetails = _messages.MessageField('GoogleCloudAiplatformV1beta1ModalityTokenCount', 4, repeated=True) promptTokenCount = _messages.IntegerField(5, variant=_messages.Variant.INT32) promptTokensDetails = _messages.MessageField('GoogleCloudAiplatformV1beta1ModalityTokenCount', 6, repeated=True) thoughtsTokenCount = _messages.IntegerField(7, variant=_messages.Variant.INT32) toolUsePromptTokenCount = _messages.IntegerField(8, variant=_messages.Variant.INT32) toolUsePromptTokensDetails = _messages.MessageField('GoogleCloudAiplatformV1beta1ModalityTokenCount', 9, repeated=True) totalTokenCount = _messages.IntegerField(10, variant=_messages.Variant.INT32) trafficType = _messages.EnumField('TrafficTypeValueValuesEnum', 11) class GoogleCloudAiplatformV1beta1GenerateFetchAccessTokenRequest(_messages.Message): r"""Request message for FeatureOnlineStoreService.GenerateFetchAccessToken. """ class GoogleCloudAiplatformV1beta1GenerateFetchAccessTokenResponse(_messages.Message): r"""Response message for FeatureOnlineStoreService.GenerateFetchAccessToken. Fields: accessToken: The OAuth 2.0 access token. expireTime: Token expiration time. This is always set """ accessToken = _messages.StringField(1) expireTime = _messages.StringField(2) class GoogleCloudAiplatformV1beta1GenerateInstanceRubricsRequest(_messages.Message): r"""Request message for EvaluationService.GenerateInstanceRubrics. Fields: agentConfig: Optional. Agent configuration, required for agent-based rubric generation. contents: Required. The prompt to generate rubrics from. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request. predefinedRubricGenerationSpec: Optional. Specification for using the rubric generation configs of a pre-defined metric, e.g. "generic_quality_v1" and "instruction_following_v1". Some of the configs may be only used in rubric generation and not supporting evaluation, e.g. "fully_customized_generic_quality_v1". If this field is set, the `rubric_generation_spec` field will be ignored. rubricGenerationSpec: Optional. Specification for how the rubrics should be generated. """ agentConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationInstanceAgentConfig', 1) contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 2, repeated=True) predefinedRubricGenerationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PredefinedMetricSpec', 3) rubricGenerationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricGenerationSpec', 4) class GoogleCloudAiplatformV1beta1GenerateInstanceRubricsResponse(_messages.Message): r"""Response message for EvaluationService.GenerateInstanceRubrics. Fields: generatedRubrics: Output only. A list of generated rubrics. """ generatedRubrics = _messages.MessageField('GoogleCloudAiplatformV1beta1Rubric', 1, repeated=True) class GoogleCloudAiplatformV1beta1GenerateMemoriesRequest(_messages.Message): r"""Request message for MemoryBankService.GenerateMemories. Maximum size is 8 MB. Messages: RevisionLabelsValue: Optional. Labels to be applied to the generated memory revisions. For example, you can use this to label a revision with its data source. ScopeValue: Optional. The scope of the memories that should be generated. Memories will be consolidated across memories with the same scope. Must be provided unless the scope is defined in the source content. If `scope` is provided, it will override the scope defined in the source content. Scope values cannot contain the wildcard character '*'. Fields: directContentsSource: Defines a direct source of content as the source content from which to generate memories. directMemoriesSource: Defines a direct source of memories that should be uploaded to Memory Bank. This is similar to `CreateMemory`, but it allows for consolidation between these new memories and existing memories for the same scope. disableConsolidation: Optional. If true, generated memories will not be consolidated with existing memories; all generated memories will be added as new memories regardless of whether they are duplicates of or contradictory to existing memories. By default, memory consolidation is enabled. disableMemoryRevisions: Optional. If true, no revisions will be created for this request. revisionExpireTime: Optional. Timestamp of when the revision is considered expired. If not set, the memory revision will be kept until manually deleted. revisionLabels: Optional. Labels to be applied to the generated memory revisions. For example, you can use this to label a revision with its data source. revisionTtl: Optional. The TTL for the revision. The expiration time is computed: now + TTL. scope: Optional. The scope of the memories that should be generated. Memories will be consolidated across memories with the same scope. Must be provided unless the scope is defined in the source content. If `scope` is provided, it will override the scope defined in the source content. Scope values cannot contain the wildcard character '*'. vertexSessionSource: Defines a Vertex Session as the source content from which to generate memories. """ @encoding.MapUnrecognizedFields('additionalProperties') class RevisionLabelsValue(_messages.Message): r"""Optional. Labels to be applied to the generated memory revisions. For example, you can use this to label a revision with its data source. Messages: AdditionalProperty: An additional property for a RevisionLabelsValue object. Fields: additionalProperties: Additional properties of type RevisionLabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a RevisionLabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class ScopeValue(_messages.Message): r"""Optional. The scope of the memories that should be generated. Memories will be consolidated across memories with the same scope. Must be provided unless the scope is defined in the source content. If `scope` is provided, it will override the scope defined in the source content. Scope values cannot contain the wildcard character '*'. Messages: AdditionalProperty: An additional property for a ScopeValue object. Fields: additionalProperties: Additional properties of type ScopeValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ScopeValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) directContentsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectContentsSource', 1) directMemoriesSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectMemoriesSource', 2) disableConsolidation = _messages.BooleanField(3) disableMemoryRevisions = _messages.BooleanField(4) revisionExpireTime = _messages.StringField(5) revisionLabels = _messages.MessageField('RevisionLabelsValue', 6) revisionTtl = _messages.StringField(7) scope = _messages.MessageField('ScopeValue', 8) vertexSessionSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateMemoriesRequestVertexSessionSource', 9) class GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectContentsSource(_messages.Message): r"""Defines a direct source of content from which to generate the memories. Fields: events: Required. The source content (i.e. chat history) to generate memories from. """ events = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectContentsSourceEvent', 1, repeated=True) class GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectContentsSourceEvent(_messages.Message): r"""A single piece of conversation from which to generate memories. Fields: content: Required. A single piece of content from which to generate memories. """ content = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1) class GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectMemoriesSource(_messages.Message): r"""Defines a direct source of memories that should be uploaded to Memory Bank with consolidation. Fields: directMemories: Required. The direct memories to upload to Memory Bank. At most 5 direct memories are allowed per request. """ directMemories = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectMemoriesSourceDirectMemory', 1, repeated=True) class GoogleCloudAiplatformV1beta1GenerateMemoriesRequestDirectMemoriesSourceDirectMemory(_messages.Message): r"""A direct memory to upload to Memory Bank. Fields: fact: Required. The fact to consolidate with existing memories. topics: Optional. The topics that the consolidated memories should be associated with. """ fact = _messages.StringField(1) topics = _messages.MessageField('GoogleCloudAiplatformV1beta1MemoryTopicId', 2, repeated=True) class GoogleCloudAiplatformV1beta1GenerateMemoriesRequestVertexSessionSource(_messages.Message): r"""Defines an Agent Engine Session from which to generate the memories. If `scope` is not provided, the scope will be extracted from the Session (i.e. {"user_id": sesison.user_id}). Fields: endTime: Optional. End time (exclusive) of the time range. If not set, the end time is unbounded. session: Required. The resource name of the Session to generate memories for. Format: `projects/{project}/locations/{location}/reasoningEngines/{ reasoning_engine}/sessions/{session}` startTime: Optional. Time range to define which session events should be used to generate memories. Start time (inclusive) of the time range. If not set, the start time is unbounded. """ endTime = _messages.StringField(1) session = _messages.StringField(2) startTime = _messages.StringField(3) class GoogleCloudAiplatformV1beta1GenerateSyntheticDataRequest(_messages.Message): r"""Request message for DataFoundryService.GenerateSyntheticData. Fields: count: Required. The number of synthetic examples to generate. For this stateless API, the count is limited to a small number. examples: Optional. A list of few-shot examples to guide the model's output style and format. outputFieldSpecs: Required. The schema of the desired output, defined by a list of fields. taskDescription: Generate data from a high-level task description. """ count = _messages.IntegerField(1, variant=_messages.Variant.INT32) examples = _messages.MessageField('GoogleCloudAiplatformV1beta1SyntheticExample', 2, repeated=True) outputFieldSpecs = _messages.MessageField('GoogleCloudAiplatformV1beta1OutputFieldSpec', 3, repeated=True) taskDescription = _messages.MessageField('GoogleCloudAiplatformV1beta1TaskDescriptionStrategy', 4) class GoogleCloudAiplatformV1beta1GenerateSyntheticDataResponse(_messages.Message): r"""The response containing the generated data. Fields: syntheticExamples: A list of generated synthetic examples. """ syntheticExamples = _messages.MessageField('GoogleCloudAiplatformV1beta1SyntheticExample', 1, repeated=True) class GoogleCloudAiplatformV1beta1GenerateVideoResponse(_messages.Message): r"""Generate video response. Fields: generatedSamples: The cloud storage uris of the generated videos. raiMediaFilteredCount: Returns if any videos were filtered due to RAI policies. raiMediaFilteredReasons: Returns rai failure reasons if any. videos: List of video bytes or Cloud Storage URIs of the generated videos. """ generatedSamples = _messages.StringField(1, repeated=True) raiMediaFilteredCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) raiMediaFilteredReasons = _messages.StringField(3, repeated=True) videos = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateVideoResponseVideo', 4, repeated=True) class GoogleCloudAiplatformV1beta1GenerateVideoResponseVideo(_messages.Message): r"""A generated video. Fields: bytesBase64Encoded: Base64 encoded bytes string representing the video. gcsUri: Cloud Storage URI where the generated video is written. mimeType: The MIME type of the content of the video. - video/mp4 """ bytesBase64Encoded = _messages.StringField(1) gcsUri = _messages.StringField(2) mimeType = _messages.StringField(3) class GoogleCloudAiplatformV1beta1GenerationConfig(_messages.Message): r"""Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. Enums: MediaResolutionValueValuesEnum: Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model. ResponseModalitiesValueListEntryValuesEnum: Fields: audioTimestamp: Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response. candidateCount: Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one. enableAffectiveDialog: Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response. frequencyPenalty: Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0]. imageConfig: Optional. Config for image generation features. logprobs: Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response. maxOutputTokens: Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses. mediaResolution: Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model. modelConfig: Optional. Config for model selection. presencePenalty: Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0]. responseJsonSchema: Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`. responseLogprobs: Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging. responseMimeType: Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. This is a preview feature. responseModalities: Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image. responseSchema: Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`. routingConfig: Optional. Routing configuration. seed: Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the "random" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results. speechConfig: Optional. The speech generation config. stopSequences: Optional. A list of character sequences that will stop the model from generating further tokens. If a stop sequence is generated, the output will end at that point. This is useful for controlling the length and structure of the output. For example, you can use ["\n", "###"] to stop generation at a new line or a specific marker. temperature: Optional. Controls the randomness of the output. A higher temperature results in more creative and diverse responses, while a lower temperature makes the output more predictable and focused. The valid range is (0.0, 2.0]. thinkingConfig: Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking. topK: Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words. topP: Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust either temperature or `top_p`, but not both. """ class MediaResolutionValueValuesEnum(_messages.Enum): r"""Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model. Values: MEDIA_RESOLUTION_UNSPECIFIED: Media resolution has not been set. MEDIA_RESOLUTION_LOW: Media resolution set to low (64 tokens). MEDIA_RESOLUTION_MEDIUM: Media resolution set to medium (256 tokens). MEDIA_RESOLUTION_HIGH: Media resolution set to high (zoomed reframing with 256 tokens). """ MEDIA_RESOLUTION_UNSPECIFIED = 0 MEDIA_RESOLUTION_LOW = 1 MEDIA_RESOLUTION_MEDIUM = 2 MEDIA_RESOLUTION_HIGH = 3 class ResponseModalitiesValueListEntryValuesEnum(_messages.Enum): r"""ResponseModalitiesValueListEntryValuesEnum enum type. Values: MODALITY_UNSPECIFIED: Unspecified modality. Will be processed as text. TEXT: Text modality. IMAGE: Image modality. AUDIO: Audio modality. """ MODALITY_UNSPECIFIED = 0 TEXT = 1 IMAGE = 2 AUDIO = 3 audioTimestamp = _messages.BooleanField(1) candidateCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) enableAffectiveDialog = _messages.BooleanField(3) frequencyPenalty = _messages.FloatField(4, variant=_messages.Variant.FLOAT) imageConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ImageConfig', 5) logprobs = _messages.IntegerField(6, variant=_messages.Variant.INT32) maxOutputTokens = _messages.IntegerField(7, variant=_messages.Variant.INT32) mediaResolution = _messages.EnumField('MediaResolutionValueValuesEnum', 8) modelConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerationConfigModelConfig', 9) presencePenalty = _messages.FloatField(10, variant=_messages.Variant.FLOAT) responseJsonSchema = _messages.MessageField('extra_types.JsonValue', 11) responseLogprobs = _messages.BooleanField(12) responseMimeType = _messages.StringField(13) responseModalities = _messages.EnumField('ResponseModalitiesValueListEntryValuesEnum', 14, repeated=True) responseSchema = _messages.MessageField('GoogleCloudAiplatformV1beta1Schema', 15) routingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfig', 16) seed = _messages.IntegerField(17, variant=_messages.Variant.INT32) speechConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SpeechConfig', 18) stopSequences = _messages.StringField(19, repeated=True) temperature = _messages.FloatField(20, variant=_messages.Variant.FLOAT) thinkingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerationConfigThinkingConfig', 21) topK = _messages.FloatField(22, variant=_messages.Variant.FLOAT) topP = _messages.FloatField(23, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1GenerationConfigModelConfig(_messages.Message): r"""Config for model selection. Enums: FeatureSelectionPreferenceValueValuesEnum: Required. Feature selection preference. Fields: featureSelectionPreference: Required. Feature selection preference. """ class FeatureSelectionPreferenceValueValuesEnum(_messages.Enum): r"""Required. Feature selection preference. Values: FEATURE_SELECTION_PREFERENCE_UNSPECIFIED: Unspecified feature selection preference. PRIORITIZE_QUALITY: Prefer higher quality over lower cost. BALANCED: Balanced feature selection preference. PRIORITIZE_COST: Prefer lower cost over higher quality. """ FEATURE_SELECTION_PREFERENCE_UNSPECIFIED = 0 PRIORITIZE_QUALITY = 1 BALANCED = 2 PRIORITIZE_COST = 3 featureSelectionPreference = _messages.EnumField('FeatureSelectionPreferenceValueValuesEnum', 1) class GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfig(_messages.Message): r"""The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name. Fields: autoMode: In this mode, the model is selected automatically based on the content of the request. manualMode: In this mode, the model is specified manually. """ autoMode = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigAutoRoutingMode', 1) manualMode = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigManualRoutingMode', 2) class GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigAutoRoutingMode(_messages.Message): r"""The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. Enums: ModelRoutingPreferenceValueValuesEnum: The model routing preference. Fields: modelRoutingPreference: The model routing preference. """ class ModelRoutingPreferenceValueValuesEnum(_messages.Enum): r"""The model routing preference. Values: UNKNOWN: Unspecified model routing preference. PRIORITIZE_QUALITY: The model will be selected to prioritize the quality of the response. BALANCED: The model will be selected to balance quality and cost. PRIORITIZE_COST: The model will be selected to prioritize the cost of the request. """ UNKNOWN = 0 PRIORITIZE_QUALITY = 1 BALANCED = 2 PRIORITIZE_COST = 3 modelRoutingPreference = _messages.EnumField('ModelRoutingPreferenceValueValuesEnum', 1) class GoogleCloudAiplatformV1beta1GenerationConfigRoutingConfigManualRoutingMode(_messages.Message): r"""The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided. Fields: modelName: The name of the model to use. Only public LLM models are accepted. """ modelName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1GenerationConfigThinkingConfig(_messages.Message): r"""Configuration for the model's thinking features. "Thinking" is a process where the model breaks down a complex task into smaller, manageable steps. This allows the model to reason about the task, plan its approach, and execute the plan to generate a high-quality response. Fields: includeThoughts: Optional. If true, the model will include its thoughts in the response. "Thoughts" are the intermediate steps the model takes to arrive at the final response. They can provide insights into the model's reasoning process and help with debugging. If this is true, thoughts are returned only when available. thinkingBudget: Optional. The token budget for the model's thinking process. The model will make a best effort to stay within this budget. This can be used to control the trade-off between response quality and latency. """ includeThoughts = _messages.BooleanField(1) thinkingBudget = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1GenericOperationMetadata(_messages.Message): r"""Generic Metadata shared by all operations. Fields: createTime: Output only. Time when the operation was created. partialFailures: Output only. Partial failures encountered. E.g. single files that couldn't be read. This field should never exceed 20 entries. Status details field will contain standard Google Cloud error details. updateTime: Output only. Time when the operation was updated for the last time. If the operation has finished (successfully or not), this is the finish time. """ createTime = _messages.StringField(1) partialFailures = _messages.MessageField('GoogleRpcStatus', 2, repeated=True) updateTime = _messages.StringField(3) class GoogleCloudAiplatformV1beta1GenieSource(_messages.Message): r"""Contains information about the source of the models generated from Generative AI Studio. Fields: baseModelUri: Required. The public base model URI. """ baseModelUri = _messages.StringField(1) class GoogleCloudAiplatformV1beta1GoogleDriveSource(_messages.Message): r"""The Google Drive location for the input content. Fields: resourceIds: Required. Google Drive resource IDs. """ resourceIds = _messages.MessageField('GoogleCloudAiplatformV1beta1GoogleDriveSourceResourceId', 1, repeated=True) class GoogleCloudAiplatformV1beta1GoogleDriveSourceResourceId(_messages.Message): r"""The type and ID of the Google Drive resource. Enums: ResourceTypeValueValuesEnum: Required. The type of the Google Drive resource. Fields: resourceId: Required. The ID of the Google Drive resource. resourceType: Required. The type of the Google Drive resource. """ class ResourceTypeValueValuesEnum(_messages.Enum): r"""Required. The type of the Google Drive resource. Values: RESOURCE_TYPE_UNSPECIFIED: Unspecified resource type. RESOURCE_TYPE_FILE: File resource type. RESOURCE_TYPE_FOLDER: Folder resource type. """ RESOURCE_TYPE_UNSPECIFIED = 0 RESOURCE_TYPE_FILE = 1 RESOURCE_TYPE_FOLDER = 2 resourceId = _messages.StringField(1) resourceType = _messages.EnumField('ResourceTypeValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1GoogleMaps(_messages.Message): r"""Tool to retrieve public maps data for grounding, powered by Google. Fields: enableWidget: Optional. If true, include the widget context token in the response. """ enableWidget = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1GoogleSearchRetrieval(_messages.Message): r"""Tool to retrieve public web data for grounding, powered by Google. Fields: dynamicRetrievalConfig: Specifies the dynamic retrieval configuration for the given source. """ dynamicRetrievalConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1DynamicRetrievalConfig', 1) class GoogleCloudAiplatformV1beta1GroundednessInput(_messages.Message): r"""Input for groundedness metric. Fields: instance: Required. Groundedness instance. metricSpec: Required. Spec for groundedness metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundednessInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundednessSpec', 2) class GoogleCloudAiplatformV1beta1GroundednessInstance(_messages.Message): r"""Spec for groundedness instance. Fields: context: Required. Background information provided in context used to compare against the prediction. prediction: Required. Output of the evaluated model. """ context = _messages.StringField(1) prediction = _messages.StringField(2) class GoogleCloudAiplatformV1beta1GroundednessResult(_messages.Message): r"""Spec for groundedness result. Fields: confidence: Output only. Confidence for groundedness score. explanation: Output only. Explanation for groundedness score. score: Output only. Groundedness score. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1GroundednessSpec(_messages.Message): r"""Spec for groundedness metric. Fields: version: Optional. Which version to use for evaluation. """ version = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1GroundingChunk(_messages.Message): r"""A piece of evidence that supports a claim made by the model. This is used to show a citation for a claim made by the model. When grounding is enabled, the model returns a `GroundingChunk` that contains a reference to the source of the information. Fields: maps: A grounding chunk from Google Maps. See the `Maps` message for details. retrievedContext: A grounding chunk from a data source retrieved by a retrieval tool, such as Vertex AI Search. See the `RetrievedContext` message for details web: A grounding chunk from a web page, typically from Google Search. See the `Web` message for details. """ maps = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundingChunkMaps', 1) retrievedContext = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext', 2) web = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundingChunkWeb', 3) class GoogleCloudAiplatformV1beta1GroundingChunkMaps(_messages.Message): r"""A `Maps` chunk is a piece of evidence that comes from Google Maps. It contains information about a place, such as its name, address, and reviews. This is used to provide the user with rich, location-based information. Fields: placeAnswerSources: The sources that were used to generate the place answer. This includes review snippets and photos that were used to generate the answer, as well as URIs to flag content. placeId: This Place's resource name, in `places/{place_id}` format. This can be used to look up the place in the Google Maps API. text: The text of the place answer. title: The title of the place. uri: The URI of the place. """ placeAnswerSources = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSources', 1) placeId = _messages.StringField(2) text = _messages.StringField(3) title = _messages.StringField(4) uri = _messages.StringField(5) class GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSources(_messages.Message): r"""The sources that were used to generate the place answer. This includes review snippets and photos that were used to generate the answer, as well as URIs to flag content. Fields: reviewSnippets: Snippets of reviews that were used to generate the answer. """ reviewSnippets = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet', 1, repeated=True) class GoogleCloudAiplatformV1beta1GroundingChunkMapsPlaceAnswerSourcesReviewSnippet(_messages.Message): r"""A review snippet that is used to generate the answer. Fields: googleMapsUri: A link to show the review on Google Maps. reviewId: The ID of the review that is being referenced. title: The title of the review. """ googleMapsUri = _messages.StringField(1) reviewId = _messages.StringField(2) title = _messages.StringField(3) class GoogleCloudAiplatformV1beta1GroundingChunkRetrievedContext(_messages.Message): r"""Context retrieved from a data source to ground the model's response. This is used when a retrieval tool fetches information from a user-provided corpus or a public dataset. Fields: documentName: Output only. The full resource name of the referenced Vertex AI Search document. This is used to identify the specific document that was retrieved. The format is `projects/{project}/locations/{location}/co llections/{collection}/dataStores/{data_store}/branches/{branch}/documen ts/{document}`. ragChunk: Additional context for a Retrieval-Augmented Generation (RAG) retrieval result. This is populated only when the RAG retrieval tool is used. text: The content of the retrieved data source. title: The title of the retrieved data source. uri: The URI of the retrieved data source. """ documentName = _messages.StringField(1) ragChunk = _messages.MessageField('GoogleCloudAiplatformV1beta1RagChunk', 2) text = _messages.StringField(3) title = _messages.StringField(4) uri = _messages.StringField(5) class GoogleCloudAiplatformV1beta1GroundingChunkWeb(_messages.Message): r"""A `Web` chunk is a piece of evidence that comes from a web page. It contains the URI of the web page, the title of the page, and the domain of the page. This is used to provide the user with a link to the source of the information. Fields: domain: The domain of the web page that contains the evidence. This can be used to filter out low-quality sources. title: The title of the web page that contains the evidence. uri: The URI of the web page that contains the evidence. """ domain = _messages.StringField(1) title = _messages.StringField(2) uri = _messages.StringField(3) class GoogleCloudAiplatformV1beta1GroundingMetadata(_messages.Message): r"""Information about the sources that support the content of a response. When grounding is enabled, the model returns citations for claims in the response. This object contains the retrieved sources. Fields: googleMapsWidgetContextToken: Optional. Output only. A token that can be used to render a Google Maps widget with the contextual data. This field is populated only when the grounding source is Google Maps. groundingChunks: A list of supporting references retrieved from the grounding source. This field is populated when the grounding source is Google Search, Vertex AI Search, or Google Maps. groundingSupports: Optional. A list of grounding supports that connect the generated content to the grounding chunks. This field is populated when the grounding source is Google Search or Vertex AI Search. retrievalMetadata: Optional. Output only. Metadata related to the retrieval grounding source. retrievalQueries: Optional. The queries that were executed by the retrieval tools. This field is populated only when the grounding source is a retrieval tool, such as Vertex AI Search. searchEntryPoint: Optional. A web search entry point that can be used to display search results. This field is populated only when the grounding source is Google Search. sourceFlaggingUris: Optional. Output only. A list of URIs that can be used to flag a place or review for inappropriate content. This field is populated only when the grounding source is Google Maps. webSearchQueries: Optional. The web search queries that were used to generate the content. This field is populated only when the grounding source is Google Search. """ googleMapsWidgetContextToken = _messages.StringField(1) groundingChunks = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundingChunk', 2, repeated=True) groundingSupports = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundingSupport', 3, repeated=True) retrievalMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1RetrievalMetadata', 4) retrievalQueries = _messages.StringField(5, repeated=True) searchEntryPoint = _messages.MessageField('GoogleCloudAiplatformV1beta1SearchEntryPoint', 6) sourceFlaggingUris = _messages.MessageField('GoogleCloudAiplatformV1beta1GroundingMetadataSourceFlaggingUri', 7, repeated=True) webSearchQueries = _messages.StringField(8, repeated=True) class GoogleCloudAiplatformV1beta1GroundingMetadataSourceFlaggingUri(_messages.Message): r"""A URI that can be used to flag a place or review for inappropriate content. This is populated only when the grounding source is Google Maps. Fields: flagContentUri: The URI that can be used to flag the content. sourceId: The ID of the place or review. """ flagContentUri = _messages.StringField(1) sourceId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1GroundingSupport(_messages.Message): r"""A collection of supporting references for a segment of the model's response. Fields: confidenceScores: The confidence scores for the support references. This list is parallel to the `grounding_chunk_indices` list. A score is a value between 0.0 and 1.0, with a higher score indicating a higher confidence that the reference supports the claim. For Gemini 2.0 and before, this list has the same size as `grounding_chunk_indices`. For Gemini 2.5 and later, this list is empty and should be ignored. groundingChunkIndices: A list of indices into the `grounding_chunks` field of the `GroundingMetadata` message. These indices specify which grounding chunks support the claim made in the content segment. For example, if this field has the values `[1, 3]`, it means that `grounding_chunks[1]` and `grounding_chunks[3]` are the sources for the claim in the content segment. segment: The content segment that this support message applies to. """ confidenceScores = _messages.FloatField(1, repeated=True, variant=_messages.Variant.FLOAT) groundingChunkIndices = _messages.IntegerField(2, repeated=True, variant=_messages.Variant.INT32) segment = _messages.MessageField('GoogleCloudAiplatformV1beta1Segment', 3) class GoogleCloudAiplatformV1beta1HyperparameterTuningJob(_messages.Message): r"""Represents a HyperparameterTuningJob. A HyperparameterTuningJob has a Study specification and multiple CustomJobs with identical CustomJob specification. Enums: StateValueValuesEnum: Output only. The detailed state of the job. Messages: LabelsValue: The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: createTime: Output only. Time when the HyperparameterTuningJob was created. displayName: Required. The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. encryptionSpec: Customer-managed encryption key options for a HyperparameterTuningJob. If this is set, then all resources created by the HyperparameterTuningJob will be encrypted with the provided encryption key. endTime: Output only. Time when the HyperparameterTuningJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`. error: Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED. labels: The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. maxFailedTrialCount: The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails. maxTrialCount: Required. The desired total number of Trials. name: Output only. Resource name of the HyperparameterTuningJob. parallelTrialCount: Required. The desired number of Trials to run in parallel. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. startTime: Output only. Time when the HyperparameterTuningJob for the first time entered the `JOB_STATE_RUNNING` state. state: Output only. The detailed state of the job. studySpec: Required. Study configuration of the HyperparameterTuningJob. trialJobSpec: Required. The spec of a trial job. The same spec applies to the CustomJobs created in all the trials. trials: Output only. Trials of the HyperparameterTuningJob. updateTime: Output only. Time when the HyperparameterTuningJob was most recently updated. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of the job. Values: JOB_STATE_UNSPECIFIED: The job state is unspecified. JOB_STATE_QUEUED: The job has been just created or resumed and processing has not yet begun. JOB_STATE_PENDING: The service is preparing to run the job. JOB_STATE_RUNNING: The job is in progress. JOB_STATE_SUCCEEDED: The job completed successfully. JOB_STATE_FAILED: The job failed. JOB_STATE_CANCELLING: The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. JOB_STATE_CANCELLED: The job has been cancelled. JOB_STATE_PAUSED: The job has been stopped, and can be resumed. JOB_STATE_EXPIRED: The job has expired. JOB_STATE_UPDATING: The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state. JOB_STATE_PARTIALLY_SUCCEEDED: The job is partially succeeded, some results may be missing due to errors. """ JOB_STATE_UNSPECIFIED = 0 JOB_STATE_QUEUED = 1 JOB_STATE_PENDING = 2 JOB_STATE_RUNNING = 3 JOB_STATE_SUCCEEDED = 4 JOB_STATE_FAILED = 5 JOB_STATE_CANCELLING = 6 JOB_STATE_CANCELLED = 7 JOB_STATE_PAUSED = 8 JOB_STATE_EXPIRED = 9 JOB_STATE_UPDATING = 10 JOB_STATE_PARTIALLY_SUCCEEDED = 11 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize HyperparameterTuningJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) displayName = _messages.StringField(2) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 3) endTime = _messages.StringField(4) error = _messages.MessageField('GoogleRpcStatus', 5) labels = _messages.MessageField('LabelsValue', 6) maxFailedTrialCount = _messages.IntegerField(7, variant=_messages.Variant.INT32) maxTrialCount = _messages.IntegerField(8, variant=_messages.Variant.INT32) name = _messages.StringField(9) parallelTrialCount = _messages.IntegerField(10, variant=_messages.Variant.INT32) satisfiesPzi = _messages.BooleanField(11) satisfiesPzs = _messages.BooleanField(12) startTime = _messages.StringField(13) state = _messages.EnumField('StateValueValuesEnum', 14) studySpec = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpec', 15) trialJobSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomJobSpec', 16) trials = _messages.MessageField('GoogleCloudAiplatformV1beta1Trial', 17, repeated=True) updateTime = _messages.StringField(18) class GoogleCloudAiplatformV1beta1IdMatcher(_messages.Message): r"""Matcher for Features of an EntityType by Feature ID. Fields: ids: Required. The following are accepted as `ids`: * A single-element list containing only `*`, which selects all Features in the target EntityType, or * A list containing only Feature IDs, which selects only Features with those IDs in the target EntityType. """ ids = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1ImageConfig(_messages.Message): r"""Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people. Enums: PersonGenerationValueValuesEnum: Optional. Controls whether the model can generate people. Fields: aspectRatio: Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: "1:1" "2:3", "3:2" "3:4", "4:3" "4:5", "5:4" "9:16", "16:9" "21:9" imageOutputOptions: Optional. The image output format for generated images. personGeneration: Optional. Controls whether the model can generate people. """ class PersonGenerationValueValuesEnum(_messages.Enum): r"""Optional. Controls whether the model can generate people. Values: PERSON_GENERATION_UNSPECIFIED: The default behavior is unspecified. The model will decide whether to generate images of people. ALLOW_ALL: Allows the model to generate images of people, including adults and children. ALLOW_ADULT: Allows the model to generate images of adults, but not children. ALLOW_NONE: Prevents the model from generating images of people. """ PERSON_GENERATION_UNSPECIFIED = 0 ALLOW_ALL = 1 ALLOW_ADULT = 2 ALLOW_NONE = 3 aspectRatio = _messages.StringField(1) imageOutputOptions = _messages.MessageField('GoogleCloudAiplatformV1beta1ImageConfigImageOutputOptions', 2) personGeneration = _messages.EnumField('PersonGenerationValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1ImageConfigImageOutputOptions(_messages.Message): r"""The image output format for generated images. Fields: compressionQuality: Optional. The compression quality of the output image. mimeType: Optional. The image format that the output should be saved as. """ compressionQuality = _messages.IntegerField(1, variant=_messages.Variant.INT32) mimeType = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ImportDataConfig(_messages.Message): r"""Describes the location from where we import data into a Dataset, together with the labels that will be applied to the DataItems and the Annotations. Messages: AnnotationLabelsValue: Labels that will be applied to newly imported Annotations. If two Annotations are identical, one of them will be deduped. Two Annotations are considered identical if their payload, payload_schema_uri and all of their labels are the same. These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file. DataItemLabelsValue: Labels that will be applied to newly imported DataItems. If an identical DataItem as one being imported already exists in the Dataset, then these labels will be appended to these of the already existing one, and if labels with identical key is imported before, the old label value will be overwritten. If two DataItems are identical in the same import data operation, the labels will be combined and if key collision happens in this case, one of the values will be picked randomly. Two DataItems are considered identical if their content bytes are identical (e.g. image bytes or pdf bytes). These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file. Fields: annotationLabels: Labels that will be applied to newly imported Annotations. If two Annotations are identical, one of them will be deduped. Two Annotations are considered identical if their payload, payload_schema_uri and all of their labels are the same. These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file. dataItemLabels: Labels that will be applied to newly imported DataItems. If an identical DataItem as one being imported already exists in the Dataset, then these labels will be appended to these of the already existing one, and if labels with identical key is imported before, the old label value will be overwritten. If two DataItems are identical in the same import data operation, the labels will be combined and if key collision happens in this case, one of the values will be picked randomly. Two DataItems are considered identical if their content bytes are identical (e.g. image bytes or pdf bytes). These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file. gcsSource: The Google Cloud Storage location for the input content. importSchemaUri: Required. Points to a YAML file stored on Google Cloud Storage describing the import format. Validation will be done against the schema. The schema is defined as an [OpenAPI 3.0.2 Schema Object](https://github.com/OAI/OpenAPI- Specification/blob/main/versions/3.0.2.md#schemaObject). """ @encoding.MapUnrecognizedFields('additionalProperties') class AnnotationLabelsValue(_messages.Message): r"""Labels that will be applied to newly imported Annotations. If two Annotations are identical, one of them will be deduped. Two Annotations are considered identical if their payload, payload_schema_uri and all of their labels are the same. These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file. Messages: AdditionalProperty: An additional property for a AnnotationLabelsValue object. Fields: additionalProperties: Additional properties of type AnnotationLabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a AnnotationLabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class DataItemLabelsValue(_messages.Message): r"""Labels that will be applied to newly imported DataItems. If an identical DataItem as one being imported already exists in the Dataset, then these labels will be appended to these of the already existing one, and if labels with identical key is imported before, the old label value will be overwritten. If two DataItems are identical in the same import data operation, the labels will be combined and if key collision happens in this case, one of the values will be picked randomly. Two DataItems are considered identical if their content bytes are identical (e.g. image bytes or pdf bytes). These labels will be overridden by Annotation labels specified inside index file referenced by import_schema_uri, e.g. jsonl file. Messages: AdditionalProperty: An additional property for a DataItemLabelsValue object. Fields: additionalProperties: Additional properties of type DataItemLabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a DataItemLabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) annotationLabels = _messages.MessageField('AnnotationLabelsValue', 1) dataItemLabels = _messages.MessageField('DataItemLabelsValue', 2) gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsSource', 3) importSchemaUri = _messages.StringField(4) class GoogleCloudAiplatformV1beta1ImportDataOperationMetadata(_messages.Message): r"""Runtime operation information for DatasetService.ImportData. Fields: genericMetadata: The common part of the operation metadata. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1ImportDataRequest(_messages.Message): r"""Request message for DatasetService.ImportData. Fields: importConfigs: Required. The desired input locations. The contents of all input locations will be imported in one batch. """ importConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportDataConfig', 1, repeated=True) class GoogleCloudAiplatformV1beta1ImportDataResponse(_messages.Message): r"""Response message for DatasetService.ImportData.""" class GoogleCloudAiplatformV1beta1ImportExtensionOperationMetadata(_messages.Message): r"""Details of ExtensionRegistryService.ImportExtension operation. Fields: genericMetadata: The common part of the operation metadata. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1ImportFeatureValuesOperationMetadata(_messages.Message): r"""Details of operations that perform import Feature values. Fields: blockingOperationIds: List of ImportFeatureValues operations running under a single EntityType that are blocking this operation. genericMetadata: Operation metadata for Featurestore import Feature values. importedEntityCount: Number of entities that have been imported by the operation. importedFeatureValueCount: Number of Feature values that have been imported by the operation. invalidRowCount: The number of rows in input source that weren't imported due to either * Not having any featureValues. * Having a null entityId. * Having a null timestamp. * Not being parsable (applicable for CSV sources). sourceUris: The source URI from where Feature values are imported. timestampOutsideRetentionRowsCount: The number rows that weren't ingested due to having timestamps outside the retention boundary. """ blockingOperationIds = _messages.IntegerField(1, repeated=True) genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 2) importedEntityCount = _messages.IntegerField(3) importedFeatureValueCount = _messages.IntegerField(4) invalidRowCount = _messages.IntegerField(5) sourceUris = _messages.StringField(6, repeated=True) timestampOutsideRetentionRowsCount = _messages.IntegerField(7) class GoogleCloudAiplatformV1beta1ImportFeatureValuesRequest(_messages.Message): r"""Request message for FeaturestoreService.ImportFeatureValues. Fields: avroSource: A GoogleCloudAiplatformV1beta1AvroSource attribute. bigquerySource: A GoogleCloudAiplatformV1beta1BigQuerySource attribute. csvSource: A GoogleCloudAiplatformV1beta1CsvSource attribute. disableIngestionAnalysis: If true, API doesn't start ingestion analysis pipeline. disableOnlineServing: If set, data will not be imported for online serving. This is typically used for backfilling, where Feature generation timestamps are not in the timestamp range needed for online serving. entityIdField: Source column that holds entity IDs. If not provided, entity IDs are extracted from the column named entity_id. featureSpecs: Required. Specifications defining which Feature values to import from the entity. The request fails if no feature_specs are provided, and having multiple feature_specs for one Feature is not allowed. featureTime: Single Feature timestamp for all entities being imported. The timestamp must not have higher than millisecond precision. featureTimeField: Source column that holds the Feature timestamp for all Feature values in each entity. workerCount: Specifies the number of workers that are used to write data to the Featurestore. Consider the online serving capacity that you require to achieve the desired import throughput without interfering with online serving. The value must be positive, and less than or equal to 100. If not set, defaults to using 1 worker. The low count ensures minimal impact on online serving performance. """ avroSource = _messages.MessageField('GoogleCloudAiplatformV1beta1AvroSource', 1) bigquerySource = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQuerySource', 2) csvSource = _messages.MessageField('GoogleCloudAiplatformV1beta1CsvSource', 3) disableIngestionAnalysis = _messages.BooleanField(4) disableOnlineServing = _messages.BooleanField(5) entityIdField = _messages.StringField(6) featureSpecs = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportFeatureValuesRequestFeatureSpec', 7, repeated=True) featureTime = _messages.StringField(8) featureTimeField = _messages.StringField(9) workerCount = _messages.IntegerField(10, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1ImportFeatureValuesRequestFeatureSpec(_messages.Message): r"""Defines the Feature value(s) to import. Fields: id: Required. ID of the Feature to import values of. This Feature must exist in the target EntityType, or the request will fail. sourceField: Source column to get the Feature values from. If not set, uses the column with the same name as the Feature ID. """ id = _messages.StringField(1) sourceField = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ImportFeatureValuesResponse(_messages.Message): r"""Response message for FeaturestoreService.ImportFeatureValues. Fields: importedEntityCount: Number of entities that have been imported by the operation. importedFeatureValueCount: Number of Feature values that have been imported by the operation. invalidRowCount: The number of rows in input source that weren't imported due to either * Not having any featureValues. * Having a null entityId. * Having a null timestamp. * Not being parsable (applicable for CSV sources). timestampOutsideRetentionRowsCount: The number rows that weren't ingested due to having feature timestamps outside the retention boundary. """ importedEntityCount = _messages.IntegerField(1) importedFeatureValueCount = _messages.IntegerField(2) invalidRowCount = _messages.IntegerField(3) timestampOutsideRetentionRowsCount = _messages.IntegerField(4) class GoogleCloudAiplatformV1beta1ImportIndexRequest(_messages.Message): r"""Request message for IndexService.ImportIndex. Fields: config: Required. Configuration for importing data from an external source. isCompleteOverwrite: Optional. If true, completely replace existing index data. Must be true for streaming update indexes. """ config = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfig', 1) isCompleteOverwrite = _messages.BooleanField(2) class GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfig(_messages.Message): r"""Configuration for importing data from an external source. Fields: bigQuerySourceConfig: Configuration for importing data from a BigQuery table. """ bigQuerySourceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigBigQuerySourceConfig', 1) class GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigBigQuerySourceConfig(_messages.Message): r"""Configuration for importing data from a BigQuery table. Fields: datapointFieldMapping: Required. Mapping of datapoint fields to BigQuery column names. tablePath: Required. The path to the BigQuery table containing the index data, in the format of `bq://..`. """ datapointFieldMapping = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMapping', 1) tablePath = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMapping(_messages.Message): r"""Mapping of datapoint fields to column names for columnar data sources. Fields: embeddingColumn: Required. The column with the vector embeddings for each data point. idColumn: Required. The column with unique identifiers for each data point. metadataColumns: Optional. List of columns containing metadata to be included in the index. numericRestricts: Optional. List of restricts for numeric values. restricts: Optional. List of restricts for string values. """ embeddingColumn = _messages.StringField(1) idColumn = _messages.StringField(2) metadataColumns = _messages.StringField(3, repeated=True) numericRestricts = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMappingNumericRestrict', 4, repeated=True) restricts = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMappingRestrict', 5, repeated=True) class GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMappingNumericRestrict(_messages.Message): r"""Restrictions on numeric values. Enums: ValueTypeValueValuesEnum: Required. Numeric type of the restrict. Must be consistent for all datapoints within the namespace. Fields: namespace: Required. The namespace of the restrict. valueColumn: Optional. The column containing the numeric value. valueType: Required. Numeric type of the restrict. Must be consistent for all datapoints within the namespace. """ class ValueTypeValueValuesEnum(_messages.Enum): r"""Required. Numeric type of the restrict. Must be consistent for all datapoints within the namespace. Values: VALUE_TYPE_UNSPECIFIED: Should not be used. INT: Represents 64 bit integer. FLOAT: Represents 32 bit float. DOUBLE: Represents 64 bit float. """ VALUE_TYPE_UNSPECIFIED = 0 INT = 1 FLOAT = 2 DOUBLE = 3 namespace = _messages.StringField(1) valueColumn = _messages.StringField(2) valueType = _messages.EnumField('ValueTypeValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1ImportIndexRequestConnectorConfigDatapointFieldMappingRestrict(_messages.Message): r"""Restrictions on string values. Fields: allowColumn: Optional. The columns containing the allow values. denyColumn: Optional. The columns containing the deny values. namespace: Required. The namespace of the restrict in the index. """ allowColumn = _messages.StringField(1, repeated=True) denyColumn = _messages.StringField(2, repeated=True) namespace = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ImportModelEvaluationRequest(_messages.Message): r"""Request message for ModelService.ImportModelEvaluation Fields: modelEvaluation: Required. Model evaluation resource to be imported. """ modelEvaluation = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelEvaluation', 1) class GoogleCloudAiplatformV1beta1ImportRagFilesConfig(_messages.Message): r"""Config for importing RagFiles. Fields: gcsSource: Google Cloud Storage location. Supports importing individual files as well as entire Google Cloud Storage directories. Sample formats: - `gs://bucket_name/my_directory/object_name/my_file.txt` - `gs://bucket_name/my_directory` globalMaxEmbeddingRequestsPerMin: Optional. The max number of queries per minute that the indexing pipeline job is allowed to make to the embedding model specified in the project. Please follow the quota usage guideline of the embedding model you use to set the value properly.If this value is not specified, max_embedding_requests_per_min will be used by indexing pipeline job as the global limit. googleDriveSource: Google Drive location. Supports importing individual files as well as Google Drive folders. importResultBigquerySink: The BigQuery destination to write import result to. It should be a bigquery table resource name (e.g. "bq://projectId.bqDatasetId.bqTableId"). The dataset must exist. If the table does not exist, it will be created with the expected schema. If the table exists, the schema will be validated and data will be added to this existing table. importResultGcsSink: The Cloud Storage path to write import result to. jiraSource: Jira queries with their corresponding authentication. maxEmbeddingRequestsPerMin: Optional. The max number of queries per minute that this job is allowed to make to the embedding model specified on the corpus. This value is specific to this job and not shared across other import jobs. Consult the Quotas page on the project to set an appropriate value here. If unspecified, a default value of 1,000 QPM would be used. partialFailureBigquerySink: The BigQuery destination to write partial failures to. It should be a bigquery table resource name (e.g. "bq://projectId.bqDatasetId.bqTableId"). The dataset must exist. If the table does not exist, it will be created with the expected schema. If the table exists, the schema will be validated and data will be added to this existing table. Deprecated. Prefer to use `import_result_bq_sink`. partialFailureGcsSink: The Cloud Storage path to write partial failures to. Deprecated. Prefer to use `import_result_gcs_sink`. ragFileChunkingConfig: Specifies the size and overlap of chunks after importing RagFiles. ragFileMetadataConfig: Specifies the metadata config for RagFiles. Including paths for metadata schema and metadata. ragFileParsingConfig: Optional. Specifies the parsing config for RagFiles. RAG will use the default parser if this field is not set. ragFileTransformationConfig: Specifies the transformation config for RagFiles. rebuildAnnIndex: Rebuilds the ANN index to optimize for recall on the imported data. Only applicable for RagCorpora running on RagManagedDb with `retrieval_strategy` set to `ANN`. The rebuild will be performed using the existing ANN config set on the RagCorpus. To change the ANN config, please use the UpdateRagCorpus API. Default is false, i.e., index is not rebuilt. sharePointSources: SharePoint sources. slackSource: Slack channels with their corresponding access tokens. """ gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsSource', 1) globalMaxEmbeddingRequestsPerMin = _messages.IntegerField(2, variant=_messages.Variant.INT32) googleDriveSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GoogleDriveSource', 3) importResultBigquerySink = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQueryDestination', 4) importResultGcsSink = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 5) jiraSource = _messages.MessageField('GoogleCloudAiplatformV1beta1JiraSource', 6) maxEmbeddingRequestsPerMin = _messages.IntegerField(7, variant=_messages.Variant.INT32) partialFailureBigquerySink = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQueryDestination', 8) partialFailureGcsSink = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 9) ragFileChunkingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileChunkingConfig', 10) ragFileMetadataConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileMetadataConfig', 11) ragFileParsingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileParsingConfig', 12) ragFileTransformationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileTransformationConfig', 13) rebuildAnnIndex = _messages.BooleanField(14) sharePointSources = _messages.MessageField('GoogleCloudAiplatformV1beta1SharePointSources', 15) slackSource = _messages.MessageField('GoogleCloudAiplatformV1beta1SlackSource', 16) class GoogleCloudAiplatformV1beta1ImportRagFilesRequest(_messages.Message): r"""Request message for VertexRagDataService.ImportRagFiles. Fields: importRagFilesConfig: Required. The config for the RagFiles to be synced and imported into the RagCorpus. VertexRagDataService.ImportRagFiles. """ importRagFilesConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ImportRagFilesConfig', 1) class GoogleCloudAiplatformV1beta1Index(_messages.Message): r"""A representation of a collection of database items organized in a way that allows for approximate nearest neighbor (a.k.a ANN) algorithms search. Enums: IndexUpdateMethodValueValuesEnum: Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default. Messages: LabelsValue: The labels with user-defined metadata to organize your Indexes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: createTime: Output only. Timestamp when this Index was created. deployedIndexes: Output only. The pointers to DeployedIndexes created from this Index. An Index can be only deleted if all its DeployedIndexes had been undeployed first. description: The description of the Index. displayName: Required. The display name of the Index. The name can be up to 128 characters long and can consist of any UTF-8 characters. encryptionSpec: Immutable. Customer-managed encryption key spec for an Index. If set, this Index and all sub-resources of this Index will be secured by this key. etag: Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. indexStats: Output only. Stats of the index resource. indexUpdateMethod: Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default. labels: The labels with user-defined metadata to organize your Indexes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. metadata: An additional information about the Index; the schema of the metadata can be found in metadata_schema. metadataSchemaUri: Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Index, that is specific to it. Unset if the Index does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI- Specification/blob/main/versions/3.0.2.md#schemaObject). Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access. name: Output only. The resource name of the Index. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. updateTime: Output only. Timestamp when this Index was most recently updated. This also includes any update to the contents of the Index. Note that Operations working on this Index may have their Operations.metadata.generic_metadata.update_time a little after the value of this timestamp, yet that does not mean their results are not already reflected in the Index. Result of any successfully completed Operation on the Index is reflected in it. """ class IndexUpdateMethodValueValuesEnum(_messages.Enum): r"""Immutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default. Values: INDEX_UPDATE_METHOD_UNSPECIFIED: Should not be used. BATCH_UPDATE: BatchUpdate: user can call UpdateIndex with files on Cloud Storage of Datapoints to update. STREAM_UPDATE: StreamUpdate: user can call UpsertDatapoints/DeleteDatapoints to update the Index and the updates will be applied in corresponding DeployedIndexes in nearly real-time. """ INDEX_UPDATE_METHOD_UNSPECIFIED = 0 BATCH_UPDATE = 1 STREAM_UPDATE = 2 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your Indexes. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) deployedIndexes = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedIndexRef', 2, repeated=True) description = _messages.StringField(3) displayName = _messages.StringField(4) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 5) etag = _messages.StringField(6) indexStats = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexStats', 7) indexUpdateMethod = _messages.EnumField('IndexUpdateMethodValueValuesEnum', 8) labels = _messages.MessageField('LabelsValue', 9) metadata = _messages.MessageField('extra_types.JsonValue', 10) metadataSchemaUri = _messages.StringField(11) name = _messages.StringField(12) satisfiesPzi = _messages.BooleanField(13) satisfiesPzs = _messages.BooleanField(14) updateTime = _messages.StringField(15) class GoogleCloudAiplatformV1beta1IndexDatapoint(_messages.Message): r"""A datapoint of Index. Messages: EmbeddingMetadataValue: Optional. The key-value map of additional metadata for the datapoint. Fields: crowdingTag: Optional. CrowdingTag of the datapoint, the number of neighbors to return in each crowding can be configured during query. datapointId: Required. Unique identifier of the datapoint. embeddingMetadata: Optional. The key-value map of additional metadata for the datapoint. featureVector: Required. Feature embedding vector for dense index. An array of numbers with the length of [NearestNeighborSearchConfig.dimensions]. numericRestricts: Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses numeric comparisons. restricts: Optional. List of Restrict of the datapoint, used to perform "restricted searches" where boolean rule are used to filter the subset of the database eligible for matching. This uses categorical tokens. See: https://cloud.google.com/vertex-ai/docs/matching-engine/filtering sparseEmbedding: Optional. Feature embedding vector for sparse index. """ @encoding.MapUnrecognizedFields('additionalProperties') class EmbeddingMetadataValue(_messages.Message): r"""Optional. The key-value map of additional metadata for the datapoint. Messages: AdditionalProperty: An additional property for a EmbeddingMetadataValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a EmbeddingMetadataValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) crowdingTag = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexDatapointCrowdingTag', 1) datapointId = _messages.StringField(2) embeddingMetadata = _messages.MessageField('EmbeddingMetadataValue', 3) featureVector = _messages.FloatField(4, repeated=True, variant=_messages.Variant.FLOAT) numericRestricts = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexDatapointNumericRestriction', 5, repeated=True) restricts = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexDatapointRestriction', 6, repeated=True) sparseEmbedding = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexDatapointSparseEmbedding', 7) class GoogleCloudAiplatformV1beta1IndexDatapointCrowdingTag(_messages.Message): r"""Crowding tag is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than some value k' of the k neighbors returned have the same value of crowding_attribute. Fields: crowdingAttribute: The attribute value used for crowding. The maximum number of neighbors to return per crowding attribute value (per_crowding_attribute_num_neighbors) is configured per-query. This field is ignored if per_crowding_attribute_num_neighbors is larger than the total number of neighbors to return for a given query. """ crowdingAttribute = _messages.StringField(1) class GoogleCloudAiplatformV1beta1IndexDatapointNumericRestriction(_messages.Message): r"""This field allows restricts to be based on numeric comparisons rather than categorical tokens. Enums: OpValueValuesEnum: This MUST be specified for queries and must NOT be specified for datapoints. Fields: namespace: The namespace of this restriction. e.g.: cost. op: This MUST be specified for queries and must NOT be specified for datapoints. valueDouble: Represents 64 bit float. valueFloat: Represents 32 bit float. valueInt: Represents 64 bit integer. """ class OpValueValuesEnum(_messages.Enum): r"""This MUST be specified for queries and must NOT be specified for datapoints. Values: OPERATOR_UNSPECIFIED: Default value of the enum. LESS: Datapoints are eligible iff their value is < the query's. LESS_EQUAL: Datapoints are eligible iff their value is <= the query's. EQUAL: Datapoints are eligible iff their value is == the query's. GREATER_EQUAL: Datapoints are eligible iff their value is >= the query's. GREATER: Datapoints are eligible iff their value is > the query's. NOT_EQUAL: Datapoints are eligible iff their value is != the query's. """ OPERATOR_UNSPECIFIED = 0 LESS = 1 LESS_EQUAL = 2 EQUAL = 3 GREATER_EQUAL = 4 GREATER = 5 NOT_EQUAL = 6 namespace = _messages.StringField(1) op = _messages.EnumField('OpValueValuesEnum', 2) valueDouble = _messages.FloatField(3) valueFloat = _messages.FloatField(4, variant=_messages.Variant.FLOAT) valueInt = _messages.IntegerField(5) class GoogleCloudAiplatformV1beta1IndexDatapointRestriction(_messages.Message): r"""Restriction of a datapoint which describe its attributes(tokens) from each of several attribute categories(namespaces). Fields: allowList: The attributes to allow in this namespace. e.g.: 'red' denyList: The attributes to deny in this namespace. e.g.: 'blue' namespace: The namespace of this restriction. e.g.: color. """ allowList = _messages.StringField(1, repeated=True) denyList = _messages.StringField(2, repeated=True) namespace = _messages.StringField(3) class GoogleCloudAiplatformV1beta1IndexDatapointSparseEmbedding(_messages.Message): r"""Feature embedding vector for sparse index. An array of numbers whose values are located in the specified dimensions. Fields: dimensions: Required. The list of indexes for the embedding values of the sparse vector. values: Required. The list of embedding values of the sparse vector. """ dimensions = _messages.IntegerField(1, repeated=True) values = _messages.FloatField(2, repeated=True, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1IndexEndpoint(_messages.Message): r"""Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes. Messages: LabelsValue: The labels with user-defined metadata to organize your IndexEndpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: createTime: Output only. Timestamp when this IndexEndpoint was created. deployedIndexes: Output only. The indexes deployed in this endpoint. description: The description of the IndexEndpoint. displayName: Required. The display name of the IndexEndpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters. enablePrivateServiceConnect: Optional. Deprecated: If true, expose the IndexEndpoint via private service connect. Only one of the fields, network or enable_private_service_connect, can be set. encryptionSpec: Immutable. Customer-managed encryption key spec for an IndexEndpoint. If set, this IndexEndpoint and all sub-resources of this IndexEndpoint will be secured by this key. etag: Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: The labels with user-defined metadata to organize your IndexEndpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. name: Output only. The resource name of the IndexEndpoint. network: Optional. The full name of the Google Compute Engine [network](https://cloud.google.com/compute/docs/networks-and- firewalls#networks) to which the IndexEndpoint should be peered. Private services access must already be configured for the network. If left unspecified, the Endpoint is not peered with any network. network and private_service_connect_config are mutually exclusive. [Format](https:// cloud.google.com/compute/docs/reference/rest/v1/networks/insert): `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in '12345', and {network} is network name. privateServiceConnectConfig: Optional. Configuration for private service connect. network and private_service_connect_config are mutually exclusive. publicEndpointDomainName: Output only. If public_endpoint_enabled is true, this field will be populated with the domain name to use for this index endpoint. publicEndpointEnabled: Optional. If true, the deployed index will be accessible through public endpoint. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. updateTime: Output only. Timestamp when this IndexEndpoint was last updated. This timestamp is not updated when the endpoint's DeployedIndexes are updated, e.g. due to updates of the original Indexes they are the deployments of. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your IndexEndpoints. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) deployedIndexes = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedIndex', 2, repeated=True) description = _messages.StringField(3) displayName = _messages.StringField(4) enablePrivateServiceConnect = _messages.BooleanField(5) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 6) etag = _messages.StringField(7) labels = _messages.MessageField('LabelsValue', 8) name = _messages.StringField(9) network = _messages.StringField(10) privateServiceConnectConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig', 11) publicEndpointDomainName = _messages.StringField(12) publicEndpointEnabled = _messages.BooleanField(13) satisfiesPzi = _messages.BooleanField(14) satisfiesPzs = _messages.BooleanField(15) updateTime = _messages.StringField(16) class GoogleCloudAiplatformV1beta1IndexPrivateEndpoints(_messages.Message): r"""IndexPrivateEndpoints proto is used to provide paths for users to send requests via private endpoints (e.g. private service access, private service connect). To send request via private service access, use match_grpc_address. To send request via private service connect, use service_attachment. Fields: matchGrpcAddress: Output only. The ip address used to send match gRPC requests. pscAutomatedEndpoints: Output only. PscAutomatedEndpoints is populated if private service connect is enabled if PscAutomatedConfig is set. serviceAttachment: Output only. The name of the service attachment resource. Populated if private service connect is enabled. """ matchGrpcAddress = _messages.StringField(1) pscAutomatedEndpoints = _messages.MessageField('GoogleCloudAiplatformV1beta1PscAutomatedEndpoints', 2, repeated=True) serviceAttachment = _messages.StringField(3) class GoogleCloudAiplatformV1beta1IndexStats(_messages.Message): r"""Stats of the Index. Fields: shardsCount: Output only. The number of shards in the Index. sparseVectorsCount: Output only. The number of sparse vectors in the Index. vectorsCount: Output only. The number of dense vectors in the Index. """ shardsCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) sparseVectorsCount = _messages.IntegerField(2) vectorsCount = _messages.IntegerField(3) class GoogleCloudAiplatformV1beta1InputDataConfig(_messages.Message): r"""Specifies Vertex AI owned input data to be used for training, and possibly evaluating, the Model. Fields: annotationSchemaUri: Applicable only to custom training with Datasets that have DataItems and Annotations. Cloud Storage URI that points to a YAML file describing the annotation schema. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI- Specification/blob/main/versions/3.0.2.md#schemaObject). The schema files that can be used here are found in gs://google-cloud- aiplatform/schema/dataset/annotation/ , note that the chosen schema must be consistent with metadata of the Dataset specified by dataset_id. Only Annotations that both match this schema and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both annotations_filter and annotation_schema_uri. annotationsFilter: Applicable only to Datasets that have DataItems and Annotations. A filter on Annotations of the Dataset. Only Annotations that both match this filter and belong to DataItems not ignored by the split method are used in respectively training, validation or test role, depending on the role of the DataItem they are on (for the auto-assigned that role is decided by Vertex AI). A filter with same syntax as the one used in ListAnnotations may be used, but note here it filters across all Annotations of the Dataset, and not just within a single DataItem. bigqueryDestination: Only applicable to custom training with tabular Dataset with BigQuery source. The BigQuery project location where the training data is to be written to. In the given project a new dataset is created with name `dataset___` where timestamp is in YYYY_MM_DDThh_mm_ss_sssZ format. All training input data is written into that dataset. In the dataset three tables are created, `training`, `validation` and `test`. * AIP_DATA_FORMAT = "bigquery". * AIP_TRAINING_DATA_URI = "bigquery_destination.dataset___.training" * AIP_VALIDATION_DATA_URI = "bigquery_destination.dataset___.validation" * AIP_TEST_DATA_URI = "bigquery_destination.dataset___.test" datasetId: Required. The ID of the Dataset in the same Project and Location which data will be used to train the Model. The Dataset must use schema compatible with Model being trained, and what is compatible should be described in the used TrainingPipeline's training_task_definition. For tabular Datasets, all their data is exported to training, to pick and choose from. filterSplit: Split based on the provided filters for each set. fractionSplit: Split based on fractions defining the size of each set. gcsDestination: The Cloud Storage location where the training data is to be written to. In the given directory a new directory is created with name: `dataset---` where timestamp is in YYYY-MM-DDThh:mm:ss.sssZ ISO-8601 format. All training input data is written into that directory. The Vertex AI environment variables representing Cloud Storage data URIs are represented in the Cloud Storage wildcard format to support sharded data. e.g.: "gs://.../training-*.jsonl" * AIP_DATA_FORMAT = "jsonl" for non-tabular data, "csv" for tabular data * AIP_TRAINING_DATA_URI = "gcs_destination/dataset---/training-*.${AIP_DATA_FORMAT}" * AIP_VALIDATION_DATA_URI = "gcs_destination/dataset---/validation-*.${AIP_DATA_FORMAT}" * AIP_TEST_DATA_URI = "gcs_destination/dataset---/test-*.${AIP_DATA_FORMAT}" persistMlUseAssignment: Whether to persist the ML use assignment to data item system labels. predefinedSplit: Supported only for tabular Datasets. Split based on a predefined key. savedQueryId: Only applicable to Datasets that have SavedQueries. The ID of a SavedQuery (annotation set) under the Dataset specified by dataset_id used for filtering Annotations for training. Only Annotations that are associated with this SavedQuery are used in respectively training. When used in conjunction with annotations_filter, the Annotations used for training are filtered by both saved_query_id and annotations_filter. Only one of saved_query_id and annotation_schema_uri should be specified as both of them represent the same thing: problem type. stratifiedSplit: Supported only for tabular Datasets. Split based on the distribution of the specified column. timestampSplit: Supported only for tabular Datasets. Split based on the timestamp of the input data pieces. """ annotationSchemaUri = _messages.StringField(1) annotationsFilter = _messages.StringField(2) bigqueryDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQueryDestination', 3) datasetId = _messages.StringField(4) filterSplit = _messages.MessageField('GoogleCloudAiplatformV1beta1FilterSplit', 5) fractionSplit = _messages.MessageField('GoogleCloudAiplatformV1beta1FractionSplit', 6) gcsDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 7) persistMlUseAssignment = _messages.BooleanField(8) predefinedSplit = _messages.MessageField('GoogleCloudAiplatformV1beta1PredefinedSplit', 9) savedQueryId = _messages.StringField(10) stratifiedSplit = _messages.MessageField('GoogleCloudAiplatformV1beta1StratifiedSplit', 11) timestampSplit = _messages.MessageField('GoogleCloudAiplatformV1beta1TimestampSplit', 12) class GoogleCloudAiplatformV1beta1Int64Array(_messages.Message): r"""A list of int64 values. Fields: values: A list of int64 values. """ values = _messages.IntegerField(1, repeated=True) class GoogleCloudAiplatformV1beta1IntegratedGradientsAttribution(_messages.Message): r"""An attribution method that computes the Aumann-Shapley value taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1703.01365 Fields: blurBaselineConfig: Config for IG with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383 smoothGradConfig: Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf stepCount: Required. The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is within the desired error range. Valid range of its value is [1, 100], inclusively. """ blurBaselineConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1BlurBaselineConfig', 1) smoothGradConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SmoothGradConfig', 2) stepCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1IntermediateExtractedMemory(_messages.Message): r"""An extracted memory that is the intermediate result before consolidation. Fields: fact: Output only. The fact of the extracted memory. """ fact = _messages.StringField(1) class GoogleCloudAiplatformV1beta1InternalOsServiceStateInstance(_messages.Message): r"""Request message for [InternalOsServiceStateInstance]. Enums: ServiceNameValueValuesEnum: Required. internal service name. ServiceStateValueValuesEnum: Required. internal service state. Fields: serviceName: Required. internal service name. serviceState: Required. internal service state. """ class ServiceNameValueValuesEnum(_messages.Enum): r"""Required. internal service name. Values: INTERNAL_OS_SERVICE_ENUM_UNSPECIFIED: Service name unknown. DOCKER_SERVICE_STATE: Represents the internal os docker client. CONTROL_PLANE_API_DNS_STATE: Represents resolving DNS for the control plane api endpoint. PROXY_REGISTRATION_DNS_STATE: Represents resolving DNS for the proxy registration endpoint. JUPYTER_STATE: Represents the jupyter endpoint. JUPYTER_API_STATE: Represents the jupyter/api endpoint. EUC_METADATA_API_STATE: Represents the EUC metadata server API endpoint. EUC_AGENT_API_STATE: Represents the EUC agent server API endpoint. IDLE_SHUTDOWN_AGENT_STATE: Represents the idle shutdown agent sidecar container. PROXY_AGENT_STATE: Represents the proxy agent sidecar container. GCR_DNS_STATE: Represents resolving DNS for the gcr.io endpoint. GUEST_ATTRIBUTE_STATE: Represents if the guest attribute service is enabled. """ INTERNAL_OS_SERVICE_ENUM_UNSPECIFIED = 0 DOCKER_SERVICE_STATE = 1 CONTROL_PLANE_API_DNS_STATE = 2 PROXY_REGISTRATION_DNS_STATE = 3 JUPYTER_STATE = 4 JUPYTER_API_STATE = 5 EUC_METADATA_API_STATE = 6 EUC_AGENT_API_STATE = 7 IDLE_SHUTDOWN_AGENT_STATE = 8 PROXY_AGENT_STATE = 9 GCR_DNS_STATE = 10 GUEST_ATTRIBUTE_STATE = 11 class ServiceStateValueValuesEnum(_messages.Enum): r"""Required. internal service state. Values: UNKNOWN: Health status is unknown: not initialized or failed to retrieve. HEALTHY: The resource is healthy. UNHEALTHY: The resource is unhealthy. """ UNKNOWN = 0 HEALTHY = 1 UNHEALTHY = 2 serviceName = _messages.EnumField('ServiceNameValueValuesEnum', 1) serviceState = _messages.EnumField('ServiceStateValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1InvokeRequest(_messages.Message): r"""Request message for PredictionService.Invoke. Fields: deployedModelId: ID of the DeployedModel that serves the invoke request. httpBody: The invoke method input. Supports HTTP headers and arbitrary data payload. """ deployedModelId = _messages.StringField(1) httpBody = _messages.MessageField('GoogleApiHttpBody', 2) class GoogleCloudAiplatformV1beta1JiraSource(_messages.Message): r"""The Jira source for the ImportRagFilesRequest. Fields: jiraQueries: Required. The Jira queries. """ jiraQueries = _messages.MessageField('GoogleCloudAiplatformV1beta1JiraSourceJiraQueries', 1, repeated=True) class GoogleCloudAiplatformV1beta1JiraSourceJiraQueries(_messages.Message): r"""JiraQueries contains the Jira queries and corresponding authentication. Fields: apiKeyConfig: Required. The SecretManager secret version resource name (e.g. projects/{project}/secrets/{secret}/versions/{version}) storing the Jira API key. See [Manage API tokens for your Atlassian account](https://support.atlassian.com/atlassian-account/docs/manage- api-tokens-for-your-atlassian-account/). customQueries: A list of custom Jira queries to import. For information about JQL (Jira Query Language), see https://support.atlassian.com/jira- service-management-cloud/docs/use-advanced-search-with-jira-query- language-jql/ email: Required. The Jira email address. projects: A list of Jira projects to import in their entirety. serverUri: Required. The Jira server URI. """ apiKeyConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig', 1) customQueries = _messages.StringField(2, repeated=True) email = _messages.StringField(3) projects = _messages.StringField(4, repeated=True) serverUri = _messages.StringField(5) class GoogleCloudAiplatformV1beta1LLMBasedMetricSpec(_messages.Message): r"""Specification for an LLM based metric. Messages: AdditionalConfigValue: Optional. Optional additional configuration for the metric. Fields: additionalConfig: Optional. Optional additional configuration for the metric. judgeAutoraterConfig: Optional. Optional configuration for the judge LLM (Autorater). metricPromptTemplate: Required. Template for the prompt sent to the judge model. predefinedRubricGenerationSpec: Dynamically generate rubrics using a predefined spec. rubricGenerationSpec: Dynamically generate rubrics using this specification. rubricGroupKey: Use a pre-defined group of rubrics associated with the input. Refers to a key in the rubric_groups map of EvaluationInstance. systemInstruction: Optional. System instructions for the judge model. """ @encoding.MapUnrecognizedFields('additionalProperties') class AdditionalConfigValue(_messages.Message): r"""Optional. Optional additional configuration for the metric. Messages: AdditionalProperty: An additional property for a AdditionalConfigValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a AdditionalConfigValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) additionalConfig = _messages.MessageField('AdditionalConfigValue', 1) judgeAutoraterConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AutoraterConfig', 2) metricPromptTemplate = _messages.StringField(3) predefinedRubricGenerationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PredefinedMetricSpec', 4) rubricGenerationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricGenerationSpec', 5) rubricGroupKey = _messages.StringField(6) systemInstruction = _messages.StringField(7) class GoogleCloudAiplatformV1beta1LargeModelReference(_messages.Message): r"""Contains information about the Large Model. Fields: name: Required. The unique name of the large Foundation or pre-built model. Like "chat-bison", "text-bison". Or model name with version ID, like "chat-bison@001", "text-bison@005", etc. """ name = _messages.StringField(1) class GoogleCloudAiplatformV1beta1LineageSubgraph(_messages.Message): r"""A subgraph of the overall lineage graph. Event edges connect Artifact and Execution nodes. Fields: artifacts: The Artifact nodes in the subgraph. events: The Event edges between Artifacts and Executions in the subgraph. executions: The Execution nodes in the subgraph. """ artifacts = _messages.MessageField('GoogleCloudAiplatformV1beta1Artifact', 1, repeated=True) events = _messages.MessageField('GoogleCloudAiplatformV1beta1Event', 2, repeated=True) executions = _messages.MessageField('GoogleCloudAiplatformV1beta1Execution', 3, repeated=True) class GoogleCloudAiplatformV1beta1ListAnnotationsResponse(_messages.Message): r"""Response message for DatasetService.ListAnnotations. Fields: annotations: A list of Annotations that matches the specified filter in the request. nextPageToken: The standard List next-page token. """ annotations = _messages.MessageField('GoogleCloudAiplatformV1beta1Annotation', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListArtifactsResponse(_messages.Message): r"""Response message for MetadataService.ListArtifacts. Fields: artifacts: The Artifacts retrieved from the MetadataStore. nextPageToken: A token, which can be sent as ListArtifactsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages. """ artifacts = _messages.MessageField('GoogleCloudAiplatformV1beta1Artifact', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListBatchPredictionJobsResponse(_messages.Message): r"""Response message for JobService.ListBatchPredictionJobs Fields: batchPredictionJobs: List of BatchPredictionJobs in the requested page. nextPageToken: A token to retrieve the next page of results. Pass to ListBatchPredictionJobsRequest.page_token to obtain that page. """ batchPredictionJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchPredictionJob', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListCachedContentsResponse(_messages.Message): r"""Response with a list of CachedContents. Fields: cachedContents: List of cached contents. nextPageToken: A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages. """ cachedContents = _messages.MessageField('GoogleCloudAiplatformV1beta1CachedContent', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListContextsResponse(_messages.Message): r"""Response message for MetadataService.ListContexts. Fields: contexts: The Contexts retrieved from the MetadataStore. nextPageToken: A token, which can be sent as ListContextsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages. """ contexts = _messages.MessageField('GoogleCloudAiplatformV1beta1Context', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListCustomJobsResponse(_messages.Message): r"""Response message for JobService.ListCustomJobs Fields: customJobs: List of CustomJobs in the requested page. nextPageToken: A token to retrieve the next page of results. Pass to ListCustomJobsRequest.page_token to obtain that page. """ customJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomJob', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListDataItemsResponse(_messages.Message): r"""Response message for DatasetService.ListDataItems. Fields: dataItems: A list of DataItems that matches the specified filter in the request. nextPageToken: The standard List next-page token. """ dataItems = _messages.MessageField('GoogleCloudAiplatformV1beta1DataItem', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListDataLabelingJobsResponse(_messages.Message): r"""Response message for JobService.ListDataLabelingJobs. Fields: dataLabelingJobs: A list of DataLabelingJobs that matches the specified filter in the request. nextPageToken: The standard List next-page token. """ dataLabelingJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1DataLabelingJob', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListDatasetVersionsResponse(_messages.Message): r"""Response message for DatasetService.ListDatasetVersions. Fields: datasetVersions: A list of DatasetVersions that matches the specified filter in the request. nextPageToken: The standard List next-page token. """ datasetVersions = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetVersion', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListDatasetsResponse(_messages.Message): r"""Response message for DatasetService.ListDatasets. Fields: datasets: A list of Datasets that matches the specified filter in the request. nextPageToken: The standard List next-page token. """ datasets = _messages.MessageField('GoogleCloudAiplatformV1beta1Dataset', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListDeploymentResourcePoolsResponse(_messages.Message): r"""Response message for ListDeploymentResourcePools method. Fields: deploymentResourcePools: The DeploymentResourcePools from the specified location. nextPageToken: A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages. """ deploymentResourcePools = _messages.MessageField('GoogleCloudAiplatformV1beta1DeploymentResourcePool', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListEndpointsResponse(_messages.Message): r"""Response message for EndpointService.ListEndpoints. Fields: endpoints: List of Endpoints in the requested page. nextPageToken: A token to retrieve the next page of results. Pass to ListEndpointsRequest.page_token to obtain that page. """ endpoints = _messages.MessageField('GoogleCloudAiplatformV1beta1Endpoint', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListEntityTypesResponse(_messages.Message): r"""Response message for FeaturestoreService.ListEntityTypes. Fields: entityTypes: The EntityTypes matching the request. nextPageToken: A token, which can be sent as ListEntityTypesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. """ entityTypes = _messages.MessageField('GoogleCloudAiplatformV1beta1EntityType', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListEvaluationItemsResponse(_messages.Message): r"""Response message for EvaluationManagementService.ListEvaluationItems. Fields: evaluationItems: List of EvaluationItems in the requested page. nextPageToken: A token to retrieve the next page of results. """ evaluationItems = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationItem', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListEvaluationRunsResponse(_messages.Message): r"""Response message for EvaluationManagementService.ListEvaluationRuns. Fields: evaluationRuns: List of EvaluationRuns in the requested page. nextPageToken: A token to retrieve the next page of results. """ evaluationRuns = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationRun', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListEvaluationSetsResponse(_messages.Message): r"""Response message for EvaluationManagementService.ListEvaluationSets. Fields: evaluationSets: List of EvaluationSets in the requested page. nextPageToken: A token to retrieve the next page of results. """ evaluationSets = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationSet', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListEventsResponse(_messages.Message): r"""Response message for SessionService.ListEvents. Fields: nextPageToken: A token, which can be sent as ListEventsRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages. sessionEvents: A list of events matching the request. Ordered by timestamp in ascending order. """ nextPageToken = _messages.StringField(1) sessionEvents = _messages.MessageField('GoogleCloudAiplatformV1beta1SessionEvent', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListExampleStoresResponse(_messages.Message): r"""Response message for ExampleStoreService.ListExampleStores. Fields: exampleStores: List of ExampleStore in the requested page. nextPageToken: A token to retrieve the next page of results. Pass to ListExampleStoresRequest.page_token to obtain that page. """ exampleStores = _messages.MessageField('GoogleCloudAiplatformV1beta1ExampleStore', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListExecutionsResponse(_messages.Message): r"""Response message for MetadataService.ListExecutions. Fields: executions: The Executions retrieved from the MetadataStore. nextPageToken: A token, which can be sent as ListExecutionsRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages. """ executions = _messages.MessageField('GoogleCloudAiplatformV1beta1Execution', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListExtensionsResponse(_messages.Message): r"""Response message for ExtensionRegistryService.ListExtensions Fields: extensions: List of Extension in the requested page. nextPageToken: A token to retrieve the next page of results. Pass to ListExtensionsRequest.page_token to obtain that page. """ extensions = _messages.MessageField('GoogleCloudAiplatformV1beta1Extension', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListFeatureGroupsResponse(_messages.Message): r"""Response message for FeatureRegistryService.ListFeatureGroups. Fields: featureGroups: The FeatureGroups matching the request. nextPageToken: A token, which can be sent as ListFeatureGroupsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. """ featureGroups = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureGroup', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListFeatureMonitorJobsResponse(_messages.Message): r"""Response message for FeatureRegistryService.ListFeatureMonitorJobs. Fields: featureMonitorJobs: The FeatureMonitorJobs matching the request. nextPageToken: A token, which can be sent as ListFeatureMonitorJobsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. """ featureMonitorJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureMonitorJob', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListFeatureMonitorsResponse(_messages.Message): r"""Response message for FeatureRegistryService.ListFeatureMonitors. Fields: featureMonitors: The FeatureMonitors matching the request. nextPageToken: A token, which can be sent as ListFeatureMonitorsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. """ featureMonitors = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureMonitor', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListFeatureOnlineStoresResponse(_messages.Message): r"""Response message for FeatureOnlineStoreAdminService.ListFeatureOnlineStores. Fields: featureOnlineStores: The FeatureOnlineStores matching the request. nextPageToken: A token, which can be sent as ListFeatureOnlineStoresRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. """ featureOnlineStores = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureOnlineStore', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListFeatureViewSyncsResponse(_messages.Message): r"""Response message for FeatureOnlineStoreAdminService.ListFeatureViewSyncs. Fields: featureViewSyncs: The FeatureViewSyncs matching the request. nextPageToken: A token, which can be sent as ListFeatureViewSyncsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. """ featureViewSyncs = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewSync', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListFeatureViewsResponse(_messages.Message): r"""Response message for FeatureOnlineStoreAdminService.ListFeatureViews. Fields: featureViews: The FeatureViews matching the request. nextPageToken: A token, which can be sent as ListFeatureViewsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. """ featureViews = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureView', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListFeaturesResponse(_messages.Message): r"""Response message for FeaturestoreService.ListFeatures. Response message for FeatureRegistryService.ListFeatures. Fields: features: The Features matching the request. nextPageToken: A token, which can be sent as ListFeaturesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. """ features = _messages.MessageField('GoogleCloudAiplatformV1beta1Feature', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListFeaturestoresResponse(_messages.Message): r"""Response message for FeaturestoreService.ListFeaturestores. Fields: featurestores: The Featurestores matching the request. nextPageToken: A token, which can be sent as ListFeaturestoresRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. """ featurestores = _messages.MessageField('GoogleCloudAiplatformV1beta1Featurestore', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListHyperparameterTuningJobsResponse(_messages.Message): r"""Response message for JobService.ListHyperparameterTuningJobs Fields: hyperparameterTuningJobs: List of HyperparameterTuningJobs in the requested page. HyperparameterTuningJob.trials of the jobs will be not be returned. nextPageToken: A token to retrieve the next page of results. Pass to ListHyperparameterTuningJobsRequest.page_token to obtain that page. """ hyperparameterTuningJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1HyperparameterTuningJob', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListIndexEndpointsResponse(_messages.Message): r"""Response message for IndexEndpointService.ListIndexEndpoints. Fields: indexEndpoints: List of IndexEndpoints in the requested page. nextPageToken: A token to retrieve next page of results. Pass to ListIndexEndpointsRequest.page_token to obtain that page. """ indexEndpoints = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexEndpoint', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListIndexesResponse(_messages.Message): r"""Response message for IndexService.ListIndexes. Fields: indexes: List of indexes in the requested page. nextPageToken: A token to retrieve next page of results. Pass to ListIndexesRequest.page_token to obtain that page. """ indexes = _messages.MessageField('GoogleCloudAiplatformV1beta1Index', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListMemoriesResponse(_messages.Message): r"""Response message for MemoryBankService.ListMemories. Fields: memories: List of Memories in the requested page. nextPageToken: A token to retrieve the next page of results. Pass to ListMemoriesRequest.page_token to obtain that page. """ memories = _messages.MessageField('GoogleCloudAiplatformV1beta1Memory', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListMemoryRevisionsResponse(_messages.Message): r"""Response message for MemoryBankService.ListMemoryRevisions. Fields: memoryRevisions: The list of Memory Revisions in the request page. nextPageToken: A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages. """ memoryRevisions = _messages.MessageField('GoogleCloudAiplatformV1beta1MemoryRevision', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListMetadataSchemasResponse(_messages.Message): r"""Response message for MetadataService.ListMetadataSchemas. Fields: metadataSchemas: The MetadataSchemas found for the MetadataStore. nextPageToken: A token, which can be sent as ListMetadataSchemasRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages. """ metadataSchemas = _messages.MessageField('GoogleCloudAiplatformV1beta1MetadataSchema', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListMetadataStoresResponse(_messages.Message): r"""Response message for MetadataService.ListMetadataStores. Fields: metadataStores: The MetadataStores found for the Location. nextPageToken: A token, which can be sent as ListMetadataStoresRequest.page_token to retrieve the next page. If this field is not populated, there are no subsequent pages. """ metadataStores = _messages.MessageField('GoogleCloudAiplatformV1beta1MetadataStore', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListModelDeploymentMonitoringJobsResponse(_messages.Message): r"""Response message for JobService.ListModelDeploymentMonitoringJobs. Fields: modelDeploymentMonitoringJobs: A list of ModelDeploymentMonitoringJobs that matches the specified filter in the request. nextPageToken: The standard List next-page token. """ modelDeploymentMonitoringJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListModelEvaluationSlicesResponse(_messages.Message): r"""Response message for ModelService.ListModelEvaluationSlices. Fields: modelEvaluationSlices: List of ModelEvaluations in the requested page. nextPageToken: A token to retrieve next page of results. Pass to ListModelEvaluationSlicesRequest.page_token to obtain that page. """ modelEvaluationSlices = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelEvaluationSlice', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListModelEvaluationsResponse(_messages.Message): r"""Response message for ModelService.ListModelEvaluations. Fields: modelEvaluations: List of ModelEvaluations in the requested page. nextPageToken: A token to retrieve next page of results. Pass to ListModelEvaluationsRequest.page_token to obtain that page. """ modelEvaluations = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelEvaluation', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListModelMonitoringJobsResponse(_messages.Message): r"""Response message for ModelMonitoringService.ListModelMonitoringJobs. Fields: modelMonitoringJobs: A list of ModelMonitoringJobs that matches the specified filter in the request. nextPageToken: The standard List next-page token. """ modelMonitoringJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringJob', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListModelMonitorsResponse(_messages.Message): r"""Response message for ModelMonitoringService.ListModelMonitors Fields: modelMonitors: List of ModelMonitor in the requested page. nextPageToken: A token to retrieve the next page of results. Pass to ListModelMonitorsRequest.page_token to obtain that page. """ modelMonitors = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitor', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListModelVersionCheckpointsResponse(_messages.Message): r"""Response message for ModelService.ListModelVersionCheckpoints Fields: checkpoints: List of Model Version checkpoints. nextPageToken: A token to retrieve the next page of results. Pass to ListModelVersionCheckpointsRequest.page_token to obtain that page. """ checkpoints = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelVersionCheckpoint', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListModelVersionsResponse(_messages.Message): r"""Response message for ModelService.ListModelVersions Fields: models: List of Model versions in the requested page. In the returned Model name field, version ID instead of regvision tag will be included. nextPageToken: A token to retrieve the next page of results. Pass to ListModelVersionsRequest.page_token to obtain that page. """ models = _messages.MessageField('GoogleCloudAiplatformV1beta1Model', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListModelsResponse(_messages.Message): r"""Response message for ModelService.ListModels Fields: models: List of Models in the requested page. nextPageToken: A token to retrieve next page of results. Pass to ListModelsRequest.page_token to obtain that page. """ models = _messages.MessageField('GoogleCloudAiplatformV1beta1Model', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListNasJobsResponse(_messages.Message): r"""Response message for JobService.ListNasJobs Fields: nasJobs: List of NasJobs in the requested page. NasJob.nas_job_output of the jobs will not be returned. nextPageToken: A token to retrieve the next page of results. Pass to ListNasJobsRequest.page_token to obtain that page. """ nasJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1NasJob', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListNasTrialDetailsResponse(_messages.Message): r"""Response message for JobService.ListNasTrialDetails Fields: nasTrialDetails: List of top NasTrials in the requested page. nextPageToken: A token to retrieve the next page of results. Pass to ListNasTrialDetailsRequest.page_token to obtain that page. """ nasTrialDetails = _messages.MessageField('GoogleCloudAiplatformV1beta1NasTrialDetail', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ListNotebookExecutionJobsResponse(_messages.Message): r"""Response message for [NotebookService.CreateNotebookExecutionJob] Fields: nextPageToken: A token to retrieve next page of results. Pass to ListNotebookExecutionJobsRequest.page_token to obtain that page. notebookExecutionJobs: List of NotebookExecutionJobs in the requested page. """ nextPageToken = _messages.StringField(1) notebookExecutionJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookExecutionJob', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListNotebookRuntimeTemplatesResponse(_messages.Message): r"""Response message for NotebookService.ListNotebookRuntimeTemplates. Fields: nextPageToken: A token to retrieve next page of results. Pass to ListNotebookRuntimeTemplatesRequest.page_token to obtain that page. notebookRuntimeTemplates: List of NotebookRuntimeTemplates in the requested page. """ nextPageToken = _messages.StringField(1) notebookRuntimeTemplates = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListNotebookRuntimesResponse(_messages.Message): r"""Response message for NotebookService.ListNotebookRuntimes. Fields: nextPageToken: A token to retrieve next page of results. Pass to ListNotebookRuntimesRequest.page_token to obtain that page. notebookRuntimes: List of NotebookRuntimes in the requested page. """ nextPageToken = _messages.StringField(1) notebookRuntimes = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookRuntime', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListOptimalTrialsRequest(_messages.Message): r"""Request message for VizierService.ListOptimalTrials.""" class GoogleCloudAiplatformV1beta1ListOptimalTrialsResponse(_messages.Message): r"""Response message for VizierService.ListOptimalTrials. Fields: optimalTrials: The pareto-optimal Trials for multiple objective Study or the optimal trial for single objective Study. The definition of pareto- optimal can be checked in wiki page. https://en.wikipedia.org/wiki/Pareto_efficiency """ optimalTrials = _messages.MessageField('GoogleCloudAiplatformV1beta1Trial', 1, repeated=True) class GoogleCloudAiplatformV1beta1ListPersistentResourcesResponse(_messages.Message): r"""Response message for PersistentResourceService.ListPersistentResources Fields: nextPageToken: A token to retrieve next page of results. Pass to ListPersistentResourcesRequest.page_token to obtain that page. persistentResources: A GoogleCloudAiplatformV1beta1PersistentResource attribute. """ nextPageToken = _messages.StringField(1) persistentResources = _messages.MessageField('GoogleCloudAiplatformV1beta1PersistentResource', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListPipelineJobsResponse(_messages.Message): r"""Response message for PipelineService.ListPipelineJobs Fields: nextPageToken: A token to retrieve the next page of results. Pass to ListPipelineJobsRequest.page_token to obtain that page. pipelineJobs: List of PipelineJobs in the requested page. """ nextPageToken = _messages.StringField(1) pipelineJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineJob', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListPublisherModelsResponse(_messages.Message): r"""Response message for ModelGardenService.ListPublisherModels. Fields: nextPageToken: A token to retrieve next page of results. Pass to ListPublisherModels.page_token to obtain that page. publisherModels: List of PublisherModels in the requested page. """ nextPageToken = _messages.StringField(1) publisherModels = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModel', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListRagCorporaResponse(_messages.Message): r"""Response message for VertexRagDataService.ListRagCorpora. Fields: nextPageToken: A token to retrieve the next page of results. Pass to ListRagCorporaRequest.page_token to obtain that page. ragCorpora: List of RagCorpora in the requested page. """ nextPageToken = _messages.StringField(1) ragCorpora = _messages.MessageField('GoogleCloudAiplatformV1beta1RagCorpus', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListRagFilesResponse(_messages.Message): r"""Response message for VertexRagDataService.ListRagFiles. Fields: nextPageToken: A token to retrieve the next page of results. Pass to ListRagFilesRequest.page_token to obtain that page. ragFiles: List of RagFiles in the requested page. """ nextPageToken = _messages.StringField(1) ragFiles = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFile', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListReasoningEnginesResponse(_messages.Message): r"""Response message for ReasoningEngineService.ListReasoningEngines Fields: nextPageToken: A token to retrieve the next page of results. Pass to ListReasoningEnginesRequest.page_token to obtain that page. reasoningEngines: List of ReasoningEngines in the requested page. """ nextPageToken = _messages.StringField(1) reasoningEngines = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngine', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListSandboxEnvironmentsResponse(_messages.Message): r"""Response message for SandboxEnvironmentService.ListSandboxEnvironments. Fields: nextPageToken: A token, which can be sent as ListSandboxEnvironmentsRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages. sandboxEnvironments: The SandboxEnvironments matching the request. """ nextPageToken = _messages.StringField(1) sandboxEnvironments = _messages.MessageField('GoogleCloudAiplatformV1beta1SandboxEnvironment', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListSavedQueriesResponse(_messages.Message): r"""Response message for DatasetService.ListSavedQueries. Fields: nextPageToken: The standard List next-page token. savedQueries: A list of SavedQueries that match the specified filter in the request. """ nextPageToken = _messages.StringField(1) savedQueries = _messages.MessageField('GoogleCloudAiplatformV1beta1SavedQuery', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListSchedulesResponse(_messages.Message): r"""Response message for ScheduleService.ListSchedules Fields: nextPageToken: A token to retrieve the next page of results. Pass to ListSchedulesRequest.page_token to obtain that page. schedules: List of Schedules in the requested page. """ nextPageToken = _messages.StringField(1) schedules = _messages.MessageField('GoogleCloudAiplatformV1beta1Schedule', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListServerlessRayJobsResponse(_messages.Message): r"""Response message for JobService.ListServerlessRayJobs Fields: nextPageToken: A token to retrieve the next page of results. Pass to ListCustomJobsRequest.page_token to obtain that page. serverlessRayJobs: List of ServerlessRayJobs in the requested page. """ nextPageToken = _messages.StringField(1) serverlessRayJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1ServerlessRayJob', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListSessionsResponse(_messages.Message): r"""Response message for SessionService.ListSessions. Fields: nextPageToken: A token, which can be sent as ListSessionsRequest.page_token to retrieve the next page. Absence of this field indicates there are no subsequent pages. sessions: A list of sessions matching the request. """ nextPageToken = _messages.StringField(1) sessions = _messages.MessageField('GoogleCloudAiplatformV1beta1Session', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListSpecialistPoolsResponse(_messages.Message): r"""Response message for SpecialistPoolService.ListSpecialistPools. Fields: nextPageToken: The standard List next-page token. specialistPools: A list of SpecialistPools that matches the specified filter in the request. """ nextPageToken = _messages.StringField(1) specialistPools = _messages.MessageField('GoogleCloudAiplatformV1beta1SpecialistPool', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListStudiesResponse(_messages.Message): r"""Response message for VizierService.ListStudies. Fields: nextPageToken: Passes this token as the `page_token` field of the request for a subsequent call. If this field is omitted, there are no subsequent pages. studies: The studies associated with the project. """ nextPageToken = _messages.StringField(1) studies = _messages.MessageField('GoogleCloudAiplatformV1beta1Study', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListTensorboardExperimentsResponse(_messages.Message): r"""Response message for TensorboardService.ListTensorboardExperiments. Fields: nextPageToken: A token, which can be sent as ListTensorboardExperimentsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. tensorboardExperiments: The TensorboardExperiments mathching the request. """ nextPageToken = _messages.StringField(1) tensorboardExperiments = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardExperiment', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListTensorboardRunsResponse(_messages.Message): r"""Response message for TensorboardService.ListTensorboardRuns. Fields: nextPageToken: A token, which can be sent as ListTensorboardRunsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. tensorboardRuns: The TensorboardRuns mathching the request. """ nextPageToken = _messages.StringField(1) tensorboardRuns = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardRun', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListTensorboardTimeSeriesResponse(_messages.Message): r"""Response message for TensorboardService.ListTensorboardTimeSeries. Fields: nextPageToken: A token, which can be sent as ListTensorboardTimeSeriesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. tensorboardTimeSeries: The TensorboardTimeSeries mathching the request. """ nextPageToken = _messages.StringField(1) tensorboardTimeSeries = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardTimeSeries', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListTensorboardsResponse(_messages.Message): r"""Response message for TensorboardService.ListTensorboards. Fields: nextPageToken: A token, which can be sent as ListTensorboardsRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. tensorboards: The Tensorboards mathching the request. """ nextPageToken = _messages.StringField(1) tensorboards = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensorboard', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListTrainingPipelinesResponse(_messages.Message): r"""Response message for PipelineService.ListTrainingPipelines Fields: nextPageToken: A token to retrieve the next page of results. Pass to ListTrainingPipelinesRequest.page_token to obtain that page. trainingPipelines: List of TrainingPipelines in the requested page. """ nextPageToken = _messages.StringField(1) trainingPipelines = _messages.MessageField('GoogleCloudAiplatformV1beta1TrainingPipeline', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListTrialsResponse(_messages.Message): r"""Response message for VizierService.ListTrials. Fields: nextPageToken: Pass this token as the `page_token` field of the request for a subsequent call. If this field is omitted, there are no subsequent pages. trials: The Trials associated with the Study. """ nextPageToken = _messages.StringField(1) trials = _messages.MessageField('GoogleCloudAiplatformV1beta1Trial', 2, repeated=True) class GoogleCloudAiplatformV1beta1ListTuningJobsResponse(_messages.Message): r"""Response message for GenAiTuningService.ListTuningJobs Fields: nextPageToken: A token to retrieve the next page of results. Pass to ListTuningJobsRequest.page_token to obtain that page. tuningJobs: List of TuningJobs in the requested page. """ nextPageToken = _messages.StringField(1) tuningJobs = _messages.MessageField('GoogleCloudAiplatformV1beta1TuningJob', 2, repeated=True) class GoogleCloudAiplatformV1beta1LogprobsResult(_messages.Message): r"""The log probabilities of the tokens generated by the model. This is useful for understanding the model's confidence in its predictions and for debugging. For example, you can use log probabilities to identify when the model is making a less confident prediction or to explore alternative responses that the model considered. A low log probability can also indicate that the model is "hallucinating" or generating factually incorrect information. Fields: chosenCandidates: A list of the chosen candidate tokens at each decoding step. The length of this list is equal to the total number of decoding steps. Note that the chosen candidate might not be in `top_candidates`. topCandidates: A list of the top candidate tokens at each decoding step. The length of this list is equal to the total number of decoding steps. """ chosenCandidates = _messages.MessageField('GoogleCloudAiplatformV1beta1LogprobsResultCandidate', 1, repeated=True) topCandidates = _messages.MessageField('GoogleCloudAiplatformV1beta1LogprobsResultTopCandidates', 2, repeated=True) class GoogleCloudAiplatformV1beta1LogprobsResultCandidate(_messages.Message): r"""A single token and its associated log probability. Fields: logProbability: The log probability of this token. A higher value indicates that the model was more confident in this token. The log probability can be used to assess the relative likelihood of different tokens and to identify when the model is uncertain. token: The token's string representation. tokenId: The token's numerical ID. While the `token` field provides the string representation of the token, the `token_id` is the numerical representation that the model uses internally. This can be useful for developers who want to build custom logic based on the model's vocabulary. """ logProbability = _messages.FloatField(1, variant=_messages.Variant.FLOAT) token = _messages.StringField(2) tokenId = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1LogprobsResultTopCandidates(_messages.Message): r"""A list of the top candidate tokens and their log probabilities at each decoding step. This can be used to see what other tokens the model considered. Fields: candidates: The list of candidate tokens, sorted by log probability in descending order. """ candidates = _messages.MessageField('GoogleCloudAiplatformV1beta1LogprobsResultCandidate', 1, repeated=True) class GoogleCloudAiplatformV1beta1LookupStudyRequest(_messages.Message): r"""Request message for VizierService.LookupStudy. Fields: displayName: Required. The user-defined display name of the Study """ displayName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1LustreMount(_messages.Message): r"""Represents a mount configuration for Lustre file system. Fields: filesystem: Required. The name of the Lustre filesystem. instanceIp: Required. IP address of the Lustre instance. mountPoint: Required. Destination mount path. The Lustre file system will be mounted for the user under /mnt/lustre/ volumeHandle: Required. The unique identifier of the Lustre volume. """ filesystem = _messages.StringField(1) instanceIp = _messages.StringField(2) mountPoint = _messages.StringField(3) volumeHandle = _messages.StringField(4) class GoogleCloudAiplatformV1beta1MachineSpec(_messages.Message): r"""Specification of a single machine. Enums: AcceleratorTypeValueValuesEnum: Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count. Fields: acceleratorCount: The number of accelerators to attach to the machine. acceleratorType: Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count. gpuPartitionSize: Optional. Immutable. The Nvidia GPU partition size. When specified, the requested accelerators will be partitioned into smaller GPU partitions. For example, if the request is for 8 units of NVIDIA A100 GPUs, and gpu_partition_size="1g.10gb", the service will create 8 * 7 = 56 partitioned MIG instances. The partition size must be a value supported by the requested accelerator. Refer to [Nvidia GPU Partitioning](https://cloud.google.com/kubernetes-engine/docs/how- to/gpus-multi#multi-instance_gpu_partitions) for the available partition sizes. If set, the accelerator_count should be set to 1. machineType: Immutable. The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex- ai/docs/predictions/configure-compute#machine-types) See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure- compute#machine-types). For DeployedModel this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required. multihostGpuNodeCount: Optional. Immutable. The number of nodes per replica for multihost GPU deployments. reservationAffinity: Optional. Immutable. Configuration controlling how this resource pool consumes reservation. tpuTopology: Immutable. The topology of the TPUs. Corresponds to the TPU topologies available from GKE. (Example: tpu_topology: "2x2x1"). """ class AcceleratorTypeValueValuesEnum(_messages.Enum): r"""Immutable. The type of accelerator(s) that may be attached to the machine as per accelerator_count. Values: ACCELERATOR_TYPE_UNSPECIFIED: Unspecified accelerator type, which means no accelerator. NVIDIA_TESLA_K80: Deprecated: Nvidia Tesla K80 GPU has reached end of support, see https://cloud.google.com/compute/docs/eol/k80-eol. NVIDIA_TESLA_P100: Nvidia Tesla P100 GPU. NVIDIA_TESLA_V100: Nvidia Tesla V100 GPU. NVIDIA_TESLA_P4: Nvidia Tesla P4 GPU. NVIDIA_TESLA_T4: Nvidia Tesla T4 GPU. NVIDIA_TESLA_A100: Nvidia Tesla A100 GPU. NVIDIA_A100_80GB: Nvidia A100 80GB GPU. NVIDIA_L4: Nvidia L4 GPU. NVIDIA_H100_80GB: Nvidia H100 80Gb GPU. NVIDIA_H100_MEGA_80GB: Nvidia H100 Mega 80Gb GPU. NVIDIA_H200_141GB: Nvidia H200 141Gb GPU. NVIDIA_B200: Nvidia B200 GPU. NVIDIA_GB200: Nvidia GB200 GPU. NVIDIA_RTX_PRO_6000: Nvidia RTX Pro 6000 GPU. TPU_V2: TPU v2. TPU_V3: TPU v3. TPU_V4_POD: TPU v4. TPU_V5_LITEPOD: TPU v5. """ ACCELERATOR_TYPE_UNSPECIFIED = 0 NVIDIA_TESLA_K80 = 1 NVIDIA_TESLA_P100 = 2 NVIDIA_TESLA_V100 = 3 NVIDIA_TESLA_P4 = 4 NVIDIA_TESLA_T4 = 5 NVIDIA_TESLA_A100 = 6 NVIDIA_A100_80GB = 7 NVIDIA_L4 = 8 NVIDIA_H100_80GB = 9 NVIDIA_H100_MEGA_80GB = 10 NVIDIA_H200_141GB = 11 NVIDIA_B200 = 12 NVIDIA_GB200 = 13 NVIDIA_RTX_PRO_6000 = 14 TPU_V2 = 15 TPU_V3 = 16 TPU_V4_POD = 17 TPU_V5_LITEPOD = 18 acceleratorCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) acceleratorType = _messages.EnumField('AcceleratorTypeValueValuesEnum', 2) gpuPartitionSize = _messages.StringField(3) machineType = _messages.StringField(4) multihostGpuNodeCount = _messages.IntegerField(5, variant=_messages.Variant.INT32) reservationAffinity = _messages.MessageField('GoogleCloudAiplatformV1beta1ReservationAffinity', 6) tpuTopology = _messages.StringField(7) class GoogleCloudAiplatformV1beta1ManualBatchTuningParameters(_messages.Message): r"""Manual batch tuning parameters. Fields: batchSize: Immutable. The number of the records (e.g. instances) of the operation given in each batch to a machine replica. Machine type, and size of a single record should be considered when setting this parameter, higher value speeds up the batch operation's execution, but too high value will result in a whole batch not fitting in a machine's memory, and the whole operation will fail. The default value is 64. """ batchSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1Measurement(_messages.Message): r"""A message representing a Measurement of a Trial. A Measurement contains the Metrics got by executing a Trial using suggested hyperparameter values. Fields: elapsedDuration: Output only. Time that the Trial has been running at the point of this Measurement. metrics: Output only. A list of metrics got by evaluating the objective functions using suggested Parameter values. stepCount: Output only. The number of steps the machine learning model has been trained for. Must be non-negative. """ elapsedDuration = _messages.StringField(1) metrics = _messages.MessageField('GoogleCloudAiplatformV1beta1MeasurementMetric', 2, repeated=True) stepCount = _messages.IntegerField(3) class GoogleCloudAiplatformV1beta1MeasurementMetric(_messages.Message): r"""A message representing a metric in the measurement. Fields: metricId: Output only. The ID of the Metric. The Metric should be defined in StudySpec's Metrics. value: Output only. The value for this metric. """ metricId = _messages.StringField(1) value = _messages.FloatField(2) class GoogleCloudAiplatformV1beta1Memory(_messages.Message): r"""A memory. Messages: RevisionLabelsValue: Optional. Input only. The labels to apply to the Memory Revision created as a result of this request. ScopeValue: Required. Immutable. The scope of the Memory. Memories are isolated within their scope. The scope is defined when creating or generating memories. Scope values cannot contain the wildcard character '*'. Fields: createTime: Output only. Timestamp when this Memory was created. description: Optional. Description of the Memory. disableMemoryRevisions: Optional. Input only. If true, no revision will be created for this request. displayName: Optional. Display name of the Memory. expireTime: Optional. Timestamp of when this resource is considered expired. This is *always* provided on output when `expiration` is set on input, regardless of whether `expire_time` or `ttl` was provided. fact: Required. Semantic knowledge extracted from the source content. name: Identifier. The resource name of the Memory. Format: `projects/{proj ect}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{ memory}` revisionExpireTime: Optional. Input only. Timestamp of when the revision is considered expired. If not set, the memory revision will be kept until manually deleted. revisionLabels: Optional. Input only. The labels to apply to the Memory Revision created as a result of this request. revisionTtl: Optional. Input only. The TTL for the revision. The expiration time is computed: now + TTL. scope: Required. Immutable. The scope of the Memory. Memories are isolated within their scope. The scope is defined when creating or generating memories. Scope values cannot contain the wildcard character '*'. topics: Optional. The Topics of the Memory. ttl: Optional. Input only. The TTL for this resource. The expiration time is computed: now + TTL. updateTime: Output only. Timestamp when this Memory was most recently updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class RevisionLabelsValue(_messages.Message): r"""Optional. Input only. The labels to apply to the Memory Revision created as a result of this request. Messages: AdditionalProperty: An additional property for a RevisionLabelsValue object. Fields: additionalProperties: Additional properties of type RevisionLabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a RevisionLabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class ScopeValue(_messages.Message): r"""Required. Immutable. The scope of the Memory. Memories are isolated within their scope. The scope is defined when creating or generating memories. Scope values cannot contain the wildcard character '*'. Messages: AdditionalProperty: An additional property for a ScopeValue object. Fields: additionalProperties: Additional properties of type ScopeValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ScopeValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) description = _messages.StringField(2) disableMemoryRevisions = _messages.BooleanField(3) displayName = _messages.StringField(4) expireTime = _messages.StringField(5) fact = _messages.StringField(6) name = _messages.StringField(7) revisionExpireTime = _messages.StringField(8) revisionLabels = _messages.MessageField('RevisionLabelsValue', 9) revisionTtl = _messages.StringField(10) scope = _messages.MessageField('ScopeValue', 11) topics = _messages.MessageField('GoogleCloudAiplatformV1beta1MemoryTopicId', 12, repeated=True) ttl = _messages.StringField(13) updateTime = _messages.StringField(14) class GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfig(_messages.Message): r"""Configuration for organizing memories for a particular scope. Fields: generateMemoriesExamples: Optional. Examples of how to generate memories for a particular scope. memoryTopics: Optional. Topics of information that should be extracted from conversations and stored as memories. If not set, then Memory Bank's default topics will be used. scopeKeys: Optional. The scope keys (i.e. 'user_id') for which to use this config. A request's scope must include all of the provided keys for the config to be used (order does not matter). If empty, then the config will be used for all requests that do not have a more specific config. Only one default config is allowed per Memory Bank. """ generateMemoriesExamples = _messages.MessageField('GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExample', 1, repeated=True) memoryTopics = _messages.MessageField('GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopic', 2, repeated=True) scopeKeys = _messages.StringField(3, repeated=True) class GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExample(_messages.Message): r"""An example of how to generate memories for a particular scope. Fields: conversationSource: A conversation source for the example. generatedMemories: Optional. The memories that are expected to be generated from the input conversation. An empty list indicates that no memories are expected to be generated for the input conversation. """ conversationSource = _messages.MessageField('GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSource', 1) generatedMemories = _messages.MessageField('GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleGeneratedMemory', 2, repeated=True) class GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSource(_messages.Message): r"""A conversation source for the example. This is similar to `DirectContentsSource`. Fields: events: Optional. The input conversation events for the example. """ events = _messages.MessageField('GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSourceEvent', 1, repeated=True) class GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleConversationSourceEvent(_messages.Message): r"""A single conversation event. Fields: content: Required. The content of the event. """ content = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1) class GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigGenerateMemoriesExampleGeneratedMemory(_messages.Message): r"""A memory generated by the operation. Fields: fact: Required. The fact to generate a memory from. topics: Optional. The list of topics that the memory should be associated with. For example, use `custom_memory_topic_label = "jargon"` if the extracted memory is an example of memory extraction for the custom topic `jargon`. """ fact = _messages.StringField(1) topics = _messages.MessageField('GoogleCloudAiplatformV1beta1MemoryTopicId', 2, repeated=True) class GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopic(_messages.Message): r"""A topic of information that should be extracted from conversations and stored as memories. Fields: customMemoryTopic: A custom memory topic defined by the developer. managedMemoryTopic: A managed memory topic defined by Memory Bank. """ customMemoryTopic = _messages.MessageField('GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopicCustomMemoryTopic', 1) managedMemoryTopic = _messages.MessageField('GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopicManagedMemoryTopic', 2) class GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopicCustomMemoryTopic(_messages.Message): r"""A custom memory topic defined by the developer. Fields: description: Required. Description of the memory topic. This should explain what information should be extracted for this topic. label: Required. The label of the topic. """ description = _messages.StringField(1) label = _messages.StringField(2) class GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfigMemoryTopicManagedMemoryTopic(_messages.Message): r"""A managed memory topic defined by the system. Enums: ManagedTopicEnumValueValuesEnum: Required. The managed topic. Fields: managedTopicEnum: Required. The managed topic. """ class ManagedTopicEnumValueValuesEnum(_messages.Enum): r"""Required. The managed topic. Values: MANAGED_TOPIC_ENUM_UNSPECIFIED: Unspecified topic. This value should not be used. USER_PERSONAL_INFO: Significant personal information about the User like first names, relationships, hobbies, important dates. USER_PREFERENCES: Stated or implied likes, dislikes, preferred styles, or patterns. KEY_CONVERSATION_DETAILS: Important milestones or conclusions within the dialogue. EXPLICIT_INSTRUCTIONS: Information that the user explicitly requested to remember or forget. """ MANAGED_TOPIC_ENUM_UNSPECIFIED = 0 USER_PERSONAL_INFO = 1 USER_PREFERENCES = 2 KEY_CONVERSATION_DETAILS = 3 EXPLICIT_INSTRUCTIONS = 4 managedTopicEnum = _messages.EnumField('ManagedTopicEnumValueValuesEnum', 1) class GoogleCloudAiplatformV1beta1MemoryRevision(_messages.Message): r"""A revision of a Memory. Messages: LabelsValue: Output only. The labels of the Memory Revision. These labels are applied to the MemoryRevision when it is created based on `GenerateMemoriesRequest.revision_labels`. Fields: createTime: Output only. Timestamp when this Memory Revision was created. expireTime: Output only. Timestamp of when this resource is considered expired. extractedMemories: Output only. The extracted memories from the source content before consolidation when the memory was updated via GenerateMemories. This information was used to modify an existing Memory via Consolidation. fact: Output only. The fact of the Memory Revision. This corresponds to the `fact` field of the parent Memory at the time of revision creation. labels: Output only. The labels of the Memory Revision. These labels are applied to the MemoryRevision when it is created based on `GenerateMemoriesRequest.revision_labels`. name: Identifier. The resource name of the Memory Revision. Format: `proje cts/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/m emories/{memory}/revisions/{memory_revision}` """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Output only. The labels of the Memory Revision. These labels are applied to the MemoryRevision when it is created based on `GenerateMemoriesRequest.revision_labels`. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) expireTime = _messages.StringField(2) extractedMemories = _messages.MessageField('GoogleCloudAiplatformV1beta1IntermediateExtractedMemory', 3, repeated=True) fact = _messages.StringField(4) labels = _messages.MessageField('LabelsValue', 5) name = _messages.StringField(6) class GoogleCloudAiplatformV1beta1MemoryTopicId(_messages.Message): r"""A memory topic identifier. This will be used to label a Memory and to restrict which topics are eligible for generation or retrieval. Enums: ManagedMemoryTopicValueValuesEnum: Optional. The managed memory topic. Fields: customMemoryTopicLabel: Optional. The custom memory topic label. managedMemoryTopic: Optional. The managed memory topic. """ class ManagedMemoryTopicValueValuesEnum(_messages.Enum): r"""Optional. The managed memory topic. Values: MANAGED_TOPIC_ENUM_UNSPECIFIED: Unspecified topic. This value should not be used. USER_PERSONAL_INFO: Significant personal information about the User like first names, relationships, hobbies, important dates. USER_PREFERENCES: Stated or implied likes, dislikes, preferred styles, or patterns. KEY_CONVERSATION_DETAILS: Important milestones or conclusions within the dialogue. EXPLICIT_INSTRUCTIONS: Information that the user explicitly requested to remember or forget. """ MANAGED_TOPIC_ENUM_UNSPECIFIED = 0 USER_PERSONAL_INFO = 1 USER_PREFERENCES = 2 KEY_CONVERSATION_DETAILS = 3 EXPLICIT_INSTRUCTIONS = 4 customMemoryTopicLabel = _messages.StringField(1) managedMemoryTopic = _messages.EnumField('ManagedMemoryTopicValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1MergeVersionAliasesRequest(_messages.Message): r"""Request message for ModelService.MergeVersionAliases. Fields: versionAliases: Required. The set of version aliases to merge. The alias should be at most 128 characters, and match `a-z{0,126}[a-z-0-9]`. Add the `-` prefix to an alias means removing that alias from the version. `-` is NOT counted in the 128 characters. Example: `-golden` means removing the `golden` alias from the version. There is NO ordering in aliases, which means 1) The aliases returned from GetModel API might not have the exactly same order from this MergeVersionAliases API. 2) Adding and deleting the same alias in the request is not recommended, and the 2 operations will be cancelled out. """ versionAliases = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1Metadata(_messages.Message): r"""Metadata for a chunk. Messages: AttributesValue: Optional. Attributes attached to the data. The keys have semantic conventions and the consumers of the attributes should know how to deserialize the value bytes based on the keys. Fields: attributes: Optional. Attributes attached to the data. The keys have semantic conventions and the consumers of the attributes should know how to deserialize the value bytes based on the keys. """ @encoding.MapUnrecognizedFields('additionalProperties') class AttributesValue(_messages.Message): r"""Optional. Attributes attached to the data. The keys have semantic conventions and the consumers of the attributes should know how to deserialize the value bytes based on the keys. Messages: AdditionalProperty: An additional property for a AttributesValue object. Fields: additionalProperties: Additional properties of type AttributesValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a AttributesValue object. Fields: key: Name of the additional property. value: A byte attribute. """ key = _messages.StringField(1) value = _messages.BytesField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) attributes = _messages.MessageField('AttributesValue', 1) class GoogleCloudAiplatformV1beta1MetadataSchema(_messages.Message): r"""Instance of a general MetadataSchema. Enums: SchemaTypeValueValuesEnum: The type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema. Fields: createTime: Output only. Timestamp when this MetadataSchema was created. description: Description of the Metadata Schema name: Output only. The resource name of the MetadataSchema. schema: Required. The raw YAML string representation of the MetadataSchema. The combination of [MetadataSchema.version] and the schema name given by `title` in [MetadataSchema.schema] must be unique within a MetadataStore. The schema is defined as an OpenAPI 3.0.2 [MetadataSchema Object](https://github.com/OAI/OpenAPI- Specification/blob/master/versions/3.0.2.md#schemaObject) schemaType: The type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema. schemaVersion: The version of the MetadataSchema. The version's format must match the following regular expression: `^[0-9]+.+.+$`, which would allow to order/compare different versions. Example: 1.0.0, 1.0.1, etc. """ class SchemaTypeValueValuesEnum(_messages.Enum): r"""The type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema. Values: METADATA_SCHEMA_TYPE_UNSPECIFIED: Unspecified type for the MetadataSchema. ARTIFACT_TYPE: A type indicating that the MetadataSchema will be used by Artifacts. EXECUTION_TYPE: A typee indicating that the MetadataSchema will be used by Executions. CONTEXT_TYPE: A state indicating that the MetadataSchema will be used by Contexts. """ METADATA_SCHEMA_TYPE_UNSPECIFIED = 0 ARTIFACT_TYPE = 1 EXECUTION_TYPE = 2 CONTEXT_TYPE = 3 createTime = _messages.StringField(1) description = _messages.StringField(2) name = _messages.StringField(3) schema = _messages.StringField(4) schemaType = _messages.EnumField('SchemaTypeValueValuesEnum', 5) schemaVersion = _messages.StringField(6) class GoogleCloudAiplatformV1beta1MetadataStore(_messages.Message): r"""Instance of a metadata store. Contains a set of metadata that can be queried. Fields: createTime: Output only. Timestamp when this MetadataStore was created. dataplexConfig: Optional. Dataplex integration settings. description: Description of the MetadataStore. encryptionSpec: Customer-managed encryption key spec for a Metadata Store. If set, this Metadata Store and all sub-resources of this Metadata Store are secured using this key. name: Output only. The resource name of the MetadataStore instance. state: Output only. State information of the MetadataStore. updateTime: Output only. Timestamp when this MetadataStore was last updated. """ createTime = _messages.StringField(1) dataplexConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1MetadataStoreDataplexConfig', 2) description = _messages.StringField(3) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 4) name = _messages.StringField(5) state = _messages.MessageField('GoogleCloudAiplatformV1beta1MetadataStoreMetadataStoreState', 6) updateTime = _messages.StringField(7) class GoogleCloudAiplatformV1beta1MetadataStoreDataplexConfig(_messages.Message): r"""Represents Dataplex integration settings. Fields: enabledPipelinesLineage: Optional. Whether or not Data Lineage synchronization is enabled for Vertex Pipelines. """ enabledPipelinesLineage = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1MetadataStoreMetadataStoreState(_messages.Message): r"""Represents state information for a MetadataStore. Fields: diskUtilizationBytes: The disk utilization of the MetadataStore in bytes. """ diskUtilizationBytes = _messages.IntegerField(1) class GoogleCloudAiplatformV1beta1Metric(_messages.Message): r"""The metric used for running evaluations. Enums: AggregationMetricsValueListEntryValuesEnum: Fields: aggregationMetrics: Optional. The aggregation metrics to use. bleuSpec: Spec for bleu metric. customCodeExecutionSpec: Spec for Custom Code Execution metric. exactMatchSpec: Spec for exact match metric. llmBasedMetricSpec: Spec for an LLM based metric. pairwiseMetricSpec: Spec for pairwise metric. pointwiseMetricSpec: Spec for pointwise metric. predefinedMetricSpec: The spec for a pre-defined metric. rougeSpec: Spec for rouge metric. """ class AggregationMetricsValueListEntryValuesEnum(_messages.Enum): r"""AggregationMetricsValueListEntryValuesEnum enum type. Values: AGGREGATION_METRIC_UNSPECIFIED: Unspecified aggregation metric. AVERAGE: Average aggregation metric. Not supported for Pairwise metric. MODE: Mode aggregation metric. STANDARD_DEVIATION: Standard deviation aggregation metric. Not supported for pairwise metric. VARIANCE: Variance aggregation metric. Not supported for pairwise metric. MINIMUM: Minimum aggregation metric. Not supported for pairwise metric. MAXIMUM: Maximum aggregation metric. Not supported for pairwise metric. MEDIAN: Median aggregation metric. Not supported for pairwise metric. PERCENTILE_P90: 90th percentile aggregation metric. Not supported for pairwise metric. PERCENTILE_P95: 95th percentile aggregation metric. Not supported for pairwise metric. PERCENTILE_P99: 99th percentile aggregation metric. Not supported for pairwise metric. """ AGGREGATION_METRIC_UNSPECIFIED = 0 AVERAGE = 1 MODE = 2 STANDARD_DEVIATION = 3 VARIANCE = 4 MINIMUM = 5 MAXIMUM = 6 MEDIAN = 7 PERCENTILE_P90 = 8 PERCENTILE_P95 = 9 PERCENTILE_P99 = 10 aggregationMetrics = _messages.EnumField('AggregationMetricsValueListEntryValuesEnum', 1, repeated=True) bleuSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1BleuSpec', 2) customCodeExecutionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomCodeExecutionSpec', 3) exactMatchSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ExactMatchSpec', 4) llmBasedMetricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1LLMBasedMetricSpec', 5) pairwiseMetricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseMetricSpec', 6) pointwiseMetricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PointwiseMetricSpec', 7) predefinedMetricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PredefinedMetricSpec', 8) rougeSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1RougeSpec', 9) class GoogleCloudAiplatformV1beta1MetricResult(_messages.Message): r"""Result for a single metric on a single instance. Fields: error: Output only. The error status for the metric result. explanation: Output only. The explanation for the metric result. rubricVerdicts: Output only. For rubric-based metrics, the verdicts for each rubric. score: Output only. The score for the metric. Please refer to each metric's documentation for the meaning of the score. """ error = _messages.MessageField('GoogleRpcStatus', 1) explanation = _messages.StringField(2) rubricVerdicts = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricVerdict', 3, repeated=True) score = _messages.FloatField(4, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1MetricxInput(_messages.Message): r"""Input for MetricX metric. Fields: instance: Required. Metricx instance. metricSpec: Required. Spec for Metricx metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1MetricxInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1MetricxSpec', 2) class GoogleCloudAiplatformV1beta1MetricxInstance(_messages.Message): r"""Spec for MetricX instance - The fields used for evaluation are dependent on the MetricX version. Fields: prediction: Required. Output of the evaluated model. reference: Optional. Ground truth used to compare against the prediction. source: Optional. Source text in original language. """ prediction = _messages.StringField(1) reference = _messages.StringField(2) source = _messages.StringField(3) class GoogleCloudAiplatformV1beta1MetricxResult(_messages.Message): r"""Spec for MetricX result - calculates the MetricX score for the given instance using the version specified in the spec. Fields: score: Output only. MetricX score. Range depends on version. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1MetricxSpec(_messages.Message): r"""Spec for MetricX metric. Enums: VersionValueValuesEnum: Required. Which version to use for evaluation. Fields: sourceLanguage: Optional. Source language in BCP-47 format. targetLanguage: Optional. Target language in BCP-47 format. Covers both prediction and reference. version: Required. Which version to use for evaluation. """ class VersionValueValuesEnum(_messages.Enum): r"""Required. Which version to use for evaluation. Values: METRICX_VERSION_UNSPECIFIED: MetricX version unspecified. METRICX_24_REF: MetricX 2024 (2.6) for translation + reference (reference-based). METRICX_24_SRC: MetricX 2024 (2.6) for translation + source (QE). METRICX_24_SRC_REF: MetricX 2024 (2.6) for translation + source + reference (source-reference-combined). """ METRICX_VERSION_UNSPECIFIED = 0 METRICX_24_REF = 1 METRICX_24_SRC = 2 METRICX_24_SRC_REF = 3 sourceLanguage = _messages.StringField(1) targetLanguage = _messages.StringField(2) version = _messages.EnumField('VersionValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1MigratableResource(_messages.Message): r"""Represents one resource that exists in automl.googleapis.com, datalabeling.googleapis.com or ml.googleapis.com. Fields: automlDataset: Output only. Represents one Dataset in automl.googleapis.com. automlModel: Output only. Represents one Model in automl.googleapis.com. dataLabelingDataset: Output only. Represents one Dataset in datalabeling.googleapis.com. lastMigrateTime: Output only. Timestamp when the last migration attempt on this MigratableResource started. Will not be set if there's no migration attempt on this MigratableResource. lastUpdateTime: Output only. Timestamp when this MigratableResource was last updated. mlEngineModelVersion: Output only. Represents one Version in ml.googleapis.com. """ automlDataset = _messages.MessageField('GoogleCloudAiplatformV1beta1MigratableResourceAutomlDataset', 1) automlModel = _messages.MessageField('GoogleCloudAiplatformV1beta1MigratableResourceAutomlModel', 2) dataLabelingDataset = _messages.MessageField('GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDataset', 3) lastMigrateTime = _messages.StringField(4) lastUpdateTime = _messages.StringField(5) mlEngineModelVersion = _messages.MessageField('GoogleCloudAiplatformV1beta1MigratableResourceMlEngineModelVersion', 6) class GoogleCloudAiplatformV1beta1MigratableResourceAutomlDataset(_messages.Message): r"""Represents one Dataset in automl.googleapis.com. Fields: dataset: Full resource name of automl Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`. datasetDisplayName: The Dataset's display name in automl.googleapis.com. """ dataset = _messages.StringField(1) datasetDisplayName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1MigratableResourceAutomlModel(_messages.Message): r"""Represents one Model in automl.googleapis.com. Fields: model: Full resource name of automl Model. Format: `projects/{project}/locations/{location}/models/{model}`. modelDisplayName: The Model's display name in automl.googleapis.com. """ model = _messages.StringField(1) modelDisplayName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDataset(_messages.Message): r"""Represents one Dataset in datalabeling.googleapis.com. Fields: dataLabelingAnnotatedDatasets: The migratable AnnotatedDataset in datalabeling.googleapis.com belongs to the data labeling Dataset. dataset: Full resource name of data labeling Dataset. Format: `projects/{project}/datasets/{dataset}`. datasetDisplayName: The Dataset's display name in datalabeling.googleapis.com. """ dataLabelingAnnotatedDatasets = _messages.MessageField('GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset', 1, repeated=True) dataset = _messages.StringField(2) datasetDisplayName = _messages.StringField(3) class GoogleCloudAiplatformV1beta1MigratableResourceDataLabelingDatasetDataLabelingAnnotatedDataset(_messages.Message): r"""Represents one AnnotatedDataset in datalabeling.googleapis.com. Fields: annotatedDataset: Full resource name of data labeling AnnotatedDataset. Format: `projects/{project}/datasets/{dataset}/annotatedDatasets/{annota ted_dataset}`. annotatedDatasetDisplayName: The AnnotatedDataset's display name in datalabeling.googleapis.com. """ annotatedDataset = _messages.StringField(1) annotatedDatasetDisplayName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1MigratableResourceMlEngineModelVersion(_messages.Message): r"""Represents one model Version in ml.googleapis.com. Fields: endpoint: The ml.googleapis.com endpoint that this model Version currently lives in. Example values: * ml.googleapis.com * us-centrall- ml.googleapis.com * europe-west4-ml.googleapis.com * asia- east1-ml.googleapis.com version: Full resource name of ml engine model Version. Format: `projects/{project}/models/{model}/versions/{version}`. """ endpoint = _messages.StringField(1) version = _messages.StringField(2) class GoogleCloudAiplatformV1beta1MigrateResourceRequest(_messages.Message): r"""Config of migrating one resource from automl.googleapis.com, datalabeling.googleapis.com and ml.googleapis.com to Vertex AI. Fields: migrateAutomlDatasetConfig: Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset. migrateAutomlModelConfig: Config for migrating Model in automl.googleapis.com to Vertex AI's Model. migrateDataLabelingDatasetConfig: Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset. migrateMlEngineModelVersionConfig: Config for migrating Version in ml.googleapis.com to Vertex AI's Model. """ migrateAutomlDatasetConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlDatasetConfig', 1) migrateAutomlModelConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlModelConfig', 2) migrateDataLabelingDatasetConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfig', 3) migrateMlEngineModelVersionConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateMlEngineModelVersionConfig', 4) class GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlDatasetConfig(_messages.Message): r"""Config for migrating Dataset in automl.googleapis.com to Vertex AI's Dataset. Fields: dataset: Required. Full resource name of automl Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`. datasetDisplayName: Required. Display name of the Dataset in Vertex AI. System will pick a display name if unspecified. """ dataset = _messages.StringField(1) datasetDisplayName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateAutomlModelConfig(_messages.Message): r"""Config for migrating Model in automl.googleapis.com to Vertex AI's Model. Fields: model: Required. Full resource name of automl Model. Format: `projects/{project}/locations/{location}/models/{model}`. modelDisplayName: Optional. Display name of the model in Vertex AI. System will pick a display name if unspecified. """ model = _messages.StringField(1) modelDisplayName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfig(_messages.Message): r"""Config for migrating Dataset in datalabeling.googleapis.com to Vertex AI's Dataset. Fields: dataset: Required. Full resource name of data labeling Dataset. Format: `projects/{project}/datasets/{dataset}`. datasetDisplayName: Optional. Display name of the Dataset in Vertex AI. System will pick a display name if unspecified. migrateDataLabelingAnnotatedDatasetConfigs: Optional. Configs for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery. The specified AnnotatedDatasets have to belong to the datalabeling Dataset. """ dataset = _messages.StringField(1) datasetDisplayName = _messages.StringField(2) migrateDataLabelingAnnotatedDatasetConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig', 3, repeated=True) class GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateDataLabelingDatasetConfigMigrateDataLabelingAnnotatedDatasetConfig(_messages.Message): r"""Config for migrating AnnotatedDataset in datalabeling.googleapis.com to Vertex AI's SavedQuery. Fields: annotatedDataset: Required. Full resource name of data labeling AnnotatedDataset. Format: `projects/{project}/datasets/{dataset}/annotat edDatasets/{annotated_dataset}`. """ annotatedDataset = _messages.StringField(1) class GoogleCloudAiplatformV1beta1MigrateResourceRequestMigrateMlEngineModelVersionConfig(_messages.Message): r"""Config for migrating version in ml.googleapis.com to Vertex AI's Model. Fields: endpoint: Required. The ml.googleapis.com endpoint that this model version should be migrated from. Example values: * ml.googleapis.com * us- centrall-ml.googleapis.com * europe-west4-ml.googleapis.com * asia- east1-ml.googleapis.com modelDisplayName: Required. Display name of the model in Vertex AI. System will pick a display name if unspecified. modelVersion: Required. Full resource name of ml engine model version. Format: `projects/{project}/models/{model}/versions/{version}`. """ endpoint = _messages.StringField(1) modelDisplayName = _messages.StringField(2) modelVersion = _messages.StringField(3) class GoogleCloudAiplatformV1beta1MigrateResourceResponse(_messages.Message): r"""Describes a successfully migrated resource. Fields: dataset: Migrated Dataset's resource name. migratableResource: Before migration, the identifier in ml.googleapis.com, automl.googleapis.com or datalabeling.googleapis.com. model: Migrated Model's resource name. """ dataset = _messages.StringField(1) migratableResource = _messages.MessageField('GoogleCloudAiplatformV1beta1MigratableResource', 2) model = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ModalityTokenCount(_messages.Message): r"""Represents a breakdown of token usage by modality. This message is used in CountTokensResponse and GenerateContentResponse.UsageMetadata to provide a detailed view of how many tokens are used by each modality (e.g., text, image, video) in a request. This is particularly useful for multimodal models, allowing you to track and manage token consumption for billing and quota purposes. Enums: ModalityValueValuesEnum: The modality that this token count applies to. Fields: modality: The modality that this token count applies to. tokenCount: The number of tokens counted for this modality. """ class ModalityValueValuesEnum(_messages.Enum): r"""The modality that this token count applies to. Values: MODALITY_UNSPECIFIED: When a modality is not specified, it is treated as `TEXT`. TEXT: The `Part` contains plain text. IMAGE: The `Part` contains an image. VIDEO: The `Part` contains a video. AUDIO: The `Part` contains audio. DOCUMENT: The `Part` contains a document, such as a PDF. """ MODALITY_UNSPECIFIED = 0 TEXT = 1 IMAGE = 2 VIDEO = 3 AUDIO = 4 DOCUMENT = 5 modality = _messages.EnumField('ModalityValueValuesEnum', 1) tokenCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1Model(_messages.Message): r"""A trained machine learning Model. Enums: SupportedDeploymentResourcesTypesValueListEntryValuesEnum: Messages: LabelsValue: The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: artifactUri: Immutable. The path to the directory containing the Model artifact and any of its supporting files. Not required for AutoML Models. baseModelSource: Optional. User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models. checkpoints: Optional. Output only. The checkpoints of the model. containerSpec: Input only. The specification of the container that is to be used when deploying this Model. The specification is ingested upon ModelService.UploadModel, and all binaries it contains are copied and stored internally by Vertex AI. Not required for AutoML Models. createTime: Output only. Timestamp when this Model was uploaded into Vertex AI. defaultCheckpointId: The default checkpoint id of a model version. deployedModels: Output only. The pointers to DeployedModels created from this Model. Note that Model could have been deployed to Endpoints in different Locations. description: The description of the Model. displayName: Required. The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters. encryptionSpec: Customer-managed encryption key spec for a Model. If set, this Model and all sub-resources of this Model will be secured by this key. etag: Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. explanationSpec: The default explanation specification for this Model. The Model can be used for requesting explanation after being deployed if it is populated. The Model can be used for batch explanation if it is populated. All fields of the explanation_spec can be overridden by explanation_spec of DeployModelRequest.deployed_model, or explanation_spec of BatchPredictionJob. If the default explanation specification is not set for this Model, this Model can still be used for requesting explanation by setting explanation_spec of DeployModelRequest.deployed_model and for batch explanation by setting explanation_spec of BatchPredictionJob. labels: The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. metadata: Immutable. An additional information about the Model; the schema of the metadata can be found in metadata_schema. Unset if the Model does not have any additional information. metadataArtifact: Output only. The resource name of the Artifact that was created in MetadataStore when creating the Model. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/ {metadata_store}/artifacts/{artifact}`. metadataSchemaUri: Immutable. Points to a YAML file stored on Google Cloud Storage describing additional information about the Model, that is specific to it. Unset if the Model does not have any additional information. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI- Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no additional metadata is needed, this field is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access. modelSourceInfo: Output only. Source of a model. It can either be automl training pipeline, custom training pipeline, BigQuery ML, or saved and tuned from Genie or Model Garden. name: The resource name of the Model. originalModelInfo: Output only. If this Model is a copy of another Model, this contains info about the original. predictSchemata: The schemata that describe formats of the Model's predictions and explanations as given and returned via PredictionService.Predict and PredictionService.Explain. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. supportedDeploymentResourcesTypes: Output only. When this Model is deployed, its prediction resources are described by the `prediction_resources` field of the Endpoint.deployed_models object. Because not all Models support all resource configuration types, the configuration types this Model supports are listed here. If no configuration types are listed, the Model cannot be deployed to an Endpoint and does not support online predictions (PredictionService.Predict or PredictionService.Explain). Such a Model can serve predictions by using a BatchPredictionJob, if it has at least one entry each in supported_input_storage_formats and supported_output_storage_formats. supportedExportFormats: Output only. The formats in which this Model may be exported. If empty, this Model is not available for export. supportedInputStorageFormats: Output only. The formats this Model supports in BatchPredictionJob.input_config. If PredictSchemata.instance_schema_uri exists, the instances should be given as per that schema. The possible formats are: * `jsonl` The JSON Lines format, where each instance is a single line. Uses GcsSource. * `csv` The CSV format, where each instance is a single comma-separated line. The first line in the file is the header, containing comma- separated field names. Uses GcsSource. * `tf-record` The TFRecord format, where each instance is a single record in tfrecord syntax. Uses GcsSource. * `tf-record-gzip` Similar to `tf-record`, but the file is gzipped. Uses GcsSource. * `bigquery` Each instance is a single row in BigQuery. Uses BigQuerySource. * `file-list` Each line of the file is the location of an instance to process, uses `gcs_source` field of the InputConfig object. If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain. supportedOutputStorageFormats: Output only. The formats this Model supports in BatchPredictionJob.output_config. If both PredictSchemata.instance_schema_uri and PredictSchemata.prediction_schema_uri exist, the predictions are returned together with their instances. In other words, the prediction has the original instance data first, followed by the actual prediction content (as per the schema). The possible formats are: * `jsonl` The JSON Lines format, where each prediction is a single line. Uses GcsDestination. * `csv` The CSV format, where each prediction is a single comma-separated line. The first line in the file is the header, containing comma-separated field names. Uses GcsDestination. * `bigquery` Each prediction is a single row in a BigQuery table, uses BigQueryDestination . If this Model doesn't support any of these formats it means it cannot be used with a BatchPredictionJob. However, if it has supported_deployment_resources_types, it could serve online predictions by using PredictionService.Predict or PredictionService.Explain. trainingPipeline: Output only. The resource name of the TrainingPipeline that uploaded this Model, if any. updateTime: Output only. Timestamp when this Model was most recently updated. versionAliases: User provided version aliases so that a model version can be referenced via alias (i.e. `projects/{project}/locations/{location}/m odels/{model_id}@{version_alias}` instead of auto-generated version id (i.e. `projects/{project}/locations/{location}/models/{model_id}@{versio n_id})`. The format is a-z{0,126}[a-z0-9] to distinguish from version_id. A default version alias will be created for the first version of the model, and there must be exactly one default version alias for a model. versionCreateTime: Output only. Timestamp when this version was created. versionDescription: The description of this version. versionId: Output only. Immutable. The version ID of the model. A new version is committed when a new model version is uploaded or trained under an existing model id. It is an auto-incrementing decimal number in string representation. versionUpdateTime: Output only. Timestamp when this version was most recently updated. """ class SupportedDeploymentResourcesTypesValueListEntryValuesEnum(_messages.Enum): r"""SupportedDeploymentResourcesTypesValueListEntryValuesEnum enum type. Values: DEPLOYMENT_RESOURCES_TYPE_UNSPECIFIED: Should not be used. DEDICATED_RESOURCES: Resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration. AUTOMATIC_RESOURCES: Resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. SHARED_RESOURCES: Resources that can be shared by multiple DeployedModels. A pre-configured DeploymentResourcePool is required. """ DEPLOYMENT_RESOURCES_TYPE_UNSPECIFIED = 0 DEDICATED_RESOURCES = 1 AUTOMATIC_RESOURCES = 2 SHARED_RESOURCES = 3 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your Models. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) artifactUri = _messages.StringField(1) baseModelSource = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelBaseModelSource', 2) checkpoints = _messages.MessageField('GoogleCloudAiplatformV1beta1Checkpoint', 3, repeated=True) containerSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelContainerSpec', 4) createTime = _messages.StringField(5) defaultCheckpointId = _messages.StringField(6) deployedModels = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedModelRef', 7, repeated=True) description = _messages.StringField(8) displayName = _messages.StringField(9) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 10) etag = _messages.StringField(11) explanationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationSpec', 12) labels = _messages.MessageField('LabelsValue', 13) metadata = _messages.MessageField('extra_types.JsonValue', 14) metadataArtifact = _messages.StringField(15) metadataSchemaUri = _messages.StringField(16) modelSourceInfo = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelSourceInfo', 17) name = _messages.StringField(18) originalModelInfo = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelOriginalModelInfo', 19) predictSchemata = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictSchemata', 20) satisfiesPzi = _messages.BooleanField(21) satisfiesPzs = _messages.BooleanField(22) supportedDeploymentResourcesTypes = _messages.EnumField('SupportedDeploymentResourcesTypesValueListEntryValuesEnum', 23, repeated=True) supportedExportFormats = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelExportFormat', 24, repeated=True) supportedInputStorageFormats = _messages.StringField(25, repeated=True) supportedOutputStorageFormats = _messages.StringField(26, repeated=True) trainingPipeline = _messages.StringField(27) updateTime = _messages.StringField(28) versionAliases = _messages.StringField(29, repeated=True) versionCreateTime = _messages.StringField(30) versionDescription = _messages.StringField(31) versionId = _messages.StringField(32) versionUpdateTime = _messages.StringField(33) class GoogleCloudAiplatformV1beta1ModelArmorConfig(_messages.Message): r"""Configuration for Model Armor. Model Armor is a Google Cloud service that provides safety and security filtering for prompts and responses. It helps protect your AI applications from risks such as harmful content, sensitive data leakage, and prompt injection attacks. Fields: promptTemplateName: Optional. The resource name of the Model Armor template to use for prompt screening. A Model Armor template is a set of customized filters and thresholds that define how Model Armor screens content. If specified, Model Armor will use this template to check the user's prompt for safety and security risks before it is sent to the model. The name must be in the format `projects/{project}/locations/{location}/templates/{template}`. responseTemplateName: Optional. The resource name of the Model Armor template to use for response screening. A Model Armor template is a set of customized filters and thresholds that define how Model Armor screens content. If specified, Model Armor will use this template to check the model's response for safety and security risks before it is returned to the user. The name must be in the format `projects/{project}/locations/{location}/templates/{template}`. """ promptTemplateName = _messages.StringField(1) responseTemplateName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ModelBaseModelSource(_messages.Message): r"""User input field to specify the base model source. Currently it only supports specifing the Model Garden models and Genie models. Fields: genieSource: Information about the base model of Genie models. modelGardenSource: Source information of Model Garden models. """ genieSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GenieSource', 1) modelGardenSource = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelGardenSource', 2) class GoogleCloudAiplatformV1beta1ModelContainerSpec(_messages.Message): r"""Specification of a container for serving predictions. Some fields in this message correspond to fields in the [Kubernetes Container v1 core specification](https://kubernetes.io/docs/reference/generated/kubernetes- api/v1.23/#container-v1-core). Fields: args: Immutable. Specifies arguments for the command that runs when the container starts. This overrides the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd). Specify this field as an array of executable and arguments, similar to a Docker `CMD`'s "default parameters" form. If you don't specify this field but do specify the command field, then the command from the `command` field runs without any additional arguments. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data- application/define-command-argument-container/#notes). If you don't specify this field and don't specify the `command` field, then the container's [`ENTRYPOINT`](https://docs.docker.com/engine/reference/builder/#cmd) and `CMD` determine what runs based on their default behavior. See the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand- how-cmd-and-entrypoint-interact). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom- container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `args` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes- api/v1.23/#container-v1-core). command: Immutable. Specifies the command that runs when the container starts. This overrides the container's [ENTRYPOINT](https://docs.docker. com/engine/reference/builder/#entrypoint). Specify this field as an array of executable and arguments, similar to a Docker `ENTRYPOINT`'s "exec" form, not its "shell" form. If you do not specify this field, then the container's `ENTRYPOINT` runs, in conjunction with the args field or the container's [`CMD`](https://docs.docker.com/engine/reference/builder/#cmd), if either exists. If this field is not specified and the container does not have an `ENTRYPOINT`, then refer to the Docker documentation about [how `CMD` and `ENTRYPOINT` interact](https://docs.docker.com/engine/reference/builder/#understand- how-cmd-and-entrypoint-interact). If you specify this field, then you can also specify the `args` field to provide additional arguments for this command. However, if you specify this field, then the container's `CMD` is ignored. See the [Kubernetes documentation about how the `command` and `args` fields interact with a container's `ENTRYPOINT` and `CMD`](https://kubernetes.io/docs/tasks/inject-data-application/define- command-argument-container/#notes). In this field, you can reference [environment variables set by Vertex AI](https://cloud.google.com/vertex-ai/docs/predictions/custom- container-requirements#aip-variables) and environment variables set in the env field. You cannot reference environment variables set in the Docker image. In order for environment variables to be expanded, reference them by using the following syntax: $( VARIABLE_NAME) Note that this differs from Bash variable expansion, which does not use parentheses. If a variable cannot be resolved, the reference in the input string is used unchanged. To avoid variable expansion, you can escape this syntax with `$$`; for example: $$(VARIABLE_NAME) This field corresponds to the `command` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes- api/v1.23/#container-v1-core). deploymentTimeout: Immutable. Deployment timeout. Limit for deployment timeout is 2 hours. env: Immutable. List of environment variables to set in the container. After the container starts running, code running in the container can read these environment variables. Additionally, the command and args fields can reference these variables. Later entries in this list can also reference earlier entries. For example, the following example sets the variable `VAR_2` to have the value `foo bar`: ```json [ { "name": "VAR_1", "value": "foo" }, { "name": "VAR_2", "value": "$(VAR_1) bar" } ] ``` If you switch the order of the variables in the example, then the expansion does not occur. This field corresponds to the `env` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes- api/v1.23/#container-v1-core). grpcPorts: Immutable. List of ports to expose from the container. Vertex AI sends gRPC prediction requests that it receives to the first port on this list. Vertex AI also sends liveness and health checks to this port. If you do not specify this field, gRPC requests to the container will be disabled. Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers v1 core API. healthProbe: Immutable. Specification for Kubernetes readiness probe. healthRoute: Immutable. HTTP path on the container to send health checks to. Vertex AI intermittently sends GET requests to this path on the container's IP address and port to check that the container is healthy. Read more about [health checks](https://cloud.google.com/vertex- ai/docs/predictions/custom-container-requirements#health). For example, if you set this field to `/bar`, then Vertex AI intermittently sends a GET request to the `/bar` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/ DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom- container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex- ai/docs/predictions/custom-container-requirements#aip-variables).) imageUri: Required. Immutable. URI of the Docker image to be used as the custom container for serving predictions. This URI must identify an image in Artifact Registry or Container Registry. Learn more about the [container publishing requirements](https://cloud.google.com/vertex- ai/docs/predictions/custom-container-requirements#publishing), including permissions requirements for the Vertex AI Service Agent. The container image is ingested upon ModelService.UploadModel, stored internally, and this original path is afterwards not used. To learn about the requirements for the Docker image itself, see [Custom container requirements](https://cloud.google.com/vertex- ai/docs/predictions/custom-container-requirements#). You can use the URI to one of Vertex AI's [pre-built container images for prediction](https://cloud.google.com/vertex-ai/docs/predictions/pre- built-containers) in this field. invokeRoutePrefix: Immutable. Invoke route prefix for the custom container. "/*" is the only supported value right now. By setting this field, any non-root route on this model will be accessible with invoke http call eg: "/invoke/foo/bar", however the [PredictionService.Invoke] RPC is not supported yet. Only one of `predict_route` or `invoke_route_prefix` can be set, and we default to using `predict_route` if this field is not set. If this field is set, the Model can only be deployed to dedicated endpoint. livenessProbe: Immutable. Specification for Kubernetes liveness probe. ports: Immutable. List of ports to expose from the container. Vertex AI sends any prediction requests that it receives to the first port on this list. Vertex AI also sends [liveness and health checks](https://cloud.google.com/vertex-ai/docs/predictions/custom- container-requirements#liveness) to this port. If you do not specify this field, it defaults to following value: ```json [ { "containerPort": 8080 } ] ``` Vertex AI does not use ports other than the first one listed. This field corresponds to the `ports` field of the Kubernetes Containers [v1 core API](https://kubernetes.io/docs/reference/generated/kubernetes- api/v1.23/#container-v1-core). predictRoute: Immutable. HTTP path on the container to send prediction requests to. Vertex AI forwards requests sent using projects.locations.endpoints.predict to this path on the container's IP address and port. Vertex AI then returns the container's response in the API response. For example, if you set this field to `/foo`, then when Vertex AI receives a prediction request, it forwards the request body in a POST request to the `/foo` path on the port of your container specified by the first value of this `ModelContainerSpec`'s ports field. If you don't specify this field, it defaults to the following value when you deploy this Model to an Endpoint: /v1/endpoints/ENDPOINT/deployedModels/DEPLOYED_MODEL:predict The placeholders in this value are replaced as follows: * ENDPOINT: The last segment (following `endpoints/`)of the Endpoint.name][] field of the Endpoint where this Model has been deployed. (Vertex AI makes this value available to your container code as the [`AIP_ENDPOINT_ID` environment variable](https://cloud.google.com/vertex-ai/docs/predictions/custom- container-requirements#aip-variables).) * DEPLOYED_MODEL: DeployedModel.id of the `DeployedModel`. (Vertex AI makes this value available to your container code as the [`AIP_DEPLOYED_MODEL_ID` environment variable](https://cloud.google.com/vertex- ai/docs/predictions/custom-container-requirements#aip-variables).) sharedMemorySizeMb: Immutable. The amount of the VM memory to reserve as the shared memory for the model in megabytes. startupProbe: Immutable. Specification for Kubernetes startup probe. """ args = _messages.StringField(1, repeated=True) command = _messages.StringField(2, repeated=True) deploymentTimeout = _messages.StringField(3) env = _messages.MessageField('GoogleCloudAiplatformV1beta1EnvVar', 4, repeated=True) grpcPorts = _messages.MessageField('GoogleCloudAiplatformV1beta1Port', 5, repeated=True) healthProbe = _messages.MessageField('GoogleCloudAiplatformV1beta1Probe', 6) healthRoute = _messages.StringField(7) imageUri = _messages.StringField(8) invokeRoutePrefix = _messages.StringField(9) livenessProbe = _messages.MessageField('GoogleCloudAiplatformV1beta1Probe', 10) ports = _messages.MessageField('GoogleCloudAiplatformV1beta1Port', 11, repeated=True) predictRoute = _messages.StringField(12) sharedMemorySizeMb = _messages.IntegerField(13) startupProbe = _messages.MessageField('GoogleCloudAiplatformV1beta1Probe', 14) class GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringBigQueryTable(_messages.Message): r"""ModelDeploymentMonitoringBigQueryTable specifies the BigQuery table name as well as some information of the logs stored in this table. Enums: LogSourceValueValuesEnum: The source of log. LogTypeValueValuesEnum: The type of log. Fields: bigqueryTablePath: The created BigQuery table to store logs. Customer could do their own query & analysis. Format: `bq://.model_deployment_monitoring_._` logSource: The source of log. logType: The type of log. requestResponseLoggingSchemaVersion: Output only. The schema version of the request/response logging BigQuery table. Default to v1 if unset. """ class LogSourceValueValuesEnum(_messages.Enum): r"""The source of log. Values: LOG_SOURCE_UNSPECIFIED: Unspecified source. TRAINING: Logs coming from Training dataset. SERVING: Logs coming from Serving traffic. """ LOG_SOURCE_UNSPECIFIED = 0 TRAINING = 1 SERVING = 2 class LogTypeValueValuesEnum(_messages.Enum): r"""The type of log. Values: LOG_TYPE_UNSPECIFIED: Unspecified type. PREDICT: Predict logs. EXPLAIN: Explain logs. """ LOG_TYPE_UNSPECIFIED = 0 PREDICT = 1 EXPLAIN = 2 bigqueryTablePath = _messages.StringField(1) logSource = _messages.EnumField('LogSourceValueValuesEnum', 2) logType = _messages.EnumField('LogTypeValueValuesEnum', 3) requestResponseLoggingSchemaVersion = _messages.StringField(4) class GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob(_messages.Message): r"""Represents a job that runs periodically to monitor the deployed models in an endpoint. It will analyze the logged training & prediction data to detect any abnormal behaviors. Enums: ScheduleStateValueValuesEnum: Output only. Schedule state when the monitoring job is in Running state. StateValueValuesEnum: Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'. Messages: LabelsValue: The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: analysisInstanceSchemaUri: YAML schema file uri describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If this field is empty, all the feature data types are inferred from predict_instance_schema_uri, meaning that TFDV will use the data in the exact format(data type) as prediction request/response. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string. bigqueryTables: Output only. The created bigquery tables for the job under customer project. Customer could do their own query & analysis. There could be 4 log tables in maximum: 1. Training data logging predict request/response 2. Serving data logging predict request/response createTime: Output only. Timestamp when this ModelDeploymentMonitoringJob was created. displayName: Required. The user-defined name of the ModelDeploymentMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. Display name of a ModelDeploymentMonitoringJob. enableMonitoringPipelineLogs: If true, the scheduled monitoring pipeline logs are sent to Google Cloud Logging, including pipeline status and anomalies detected. Please note the logs incur cost, which are subject to [Cloud Logging pricing](https://cloud.google.com/logging#pricing). encryptionSpec: Customer-managed encryption key spec for a ModelDeploymentMonitoringJob. If set, this ModelDeploymentMonitoringJob and all sub-resources of this ModelDeploymentMonitoringJob will be secured by this key. endpoint: Required. Endpoint resource name. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` error: Output only. Only populated when the job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. labels: The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. latestMonitoringPipelineMetadata: Output only. Latest triggered monitoring pipeline metadata. logTtl: The TTL of BigQuery tables in user projects which stores logs. A day is the basic unit of the TTL and we take the ceil of TTL/86400(a day). e.g. { second: 3600} indicates ttl = 1 day. loggingSamplingStrategy: Required. Sample Strategy for logging. modelDeploymentMonitoringObjectiveConfigs: Required. The config for monitoring objectives. This is a per DeployedModel config. Each DeployedModel needs to be configured separately. modelDeploymentMonitoringScheduleConfig: Required. Schedule config for running the monitoring job. modelMonitoringAlertConfig: Alert config for model monitoring. name: Output only. Resource name of a ModelDeploymentMonitoringJob. nextScheduleTime: Output only. Timestamp when this monitoring pipeline will be scheduled to run for the next round. predictInstanceSchemaUri: YAML schema file uri describing the format of a single instance, which are given to format this Endpoint's prediction (and explanation). If not set, we will generate predict schema from collected predict requests. samplePredictInstance: Sample Predict instance, same format as PredictRequest.instances, this can be set as a replacement of ModelDeploymentMonitoringJob.predict_instance_schema_uri. If not set, we will generate predict schema from collected predict requests. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. scheduleState: Output only. Schedule state when the monitoring job is in Running state. state: Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'. statsAnomaliesBaseDirectory: Stats anomalies base folder path. updateTime: Output only. Timestamp when this ModelDeploymentMonitoringJob was updated most recently. """ class ScheduleStateValueValuesEnum(_messages.Enum): r"""Output only. Schedule state when the monitoring job is in Running state. Values: MONITORING_SCHEDULE_STATE_UNSPECIFIED: Unspecified state. PENDING: The pipeline is picked up and wait to run. OFFLINE: The pipeline is offline and will be scheduled for next run. RUNNING: The pipeline is running. """ MONITORING_SCHEDULE_STATE_UNSPECIFIED = 0 PENDING = 1 OFFLINE = 2 RUNNING = 3 class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of the monitoring job. When the job is still creating, the state will be 'PENDING'. Once the job is successfully created, the state will be 'RUNNING'. Pause the job, the state will be 'PAUSED'. Resume the job, the state will return to 'RUNNING'. Values: JOB_STATE_UNSPECIFIED: The job state is unspecified. JOB_STATE_QUEUED: The job has been just created or resumed and processing has not yet begun. JOB_STATE_PENDING: The service is preparing to run the job. JOB_STATE_RUNNING: The job is in progress. JOB_STATE_SUCCEEDED: The job completed successfully. JOB_STATE_FAILED: The job failed. JOB_STATE_CANCELLING: The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. JOB_STATE_CANCELLED: The job has been cancelled. JOB_STATE_PAUSED: The job has been stopped, and can be resumed. JOB_STATE_EXPIRED: The job has expired. JOB_STATE_UPDATING: The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state. JOB_STATE_PARTIALLY_SUCCEEDED: The job is partially succeeded, some results may be missing due to errors. """ JOB_STATE_UNSPECIFIED = 0 JOB_STATE_QUEUED = 1 JOB_STATE_PENDING = 2 JOB_STATE_RUNNING = 3 JOB_STATE_SUCCEEDED = 4 JOB_STATE_FAILED = 5 JOB_STATE_CANCELLING = 6 JOB_STATE_CANCELLED = 7 JOB_STATE_PAUSED = 8 JOB_STATE_EXPIRED = 9 JOB_STATE_UPDATING = 10 JOB_STATE_PARTIALLY_SUCCEEDED = 11 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your ModelDeploymentMonitoringJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) analysisInstanceSchemaUri = _messages.StringField(1) bigqueryTables = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringBigQueryTable', 2, repeated=True) createTime = _messages.StringField(3) displayName = _messages.StringField(4) enableMonitoringPipelineLogs = _messages.BooleanField(5) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 6) endpoint = _messages.StringField(7) error = _messages.MessageField('GoogleRpcStatus', 8) labels = _messages.MessageField('LabelsValue', 9) latestMonitoringPipelineMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata', 10) logTtl = _messages.StringField(11) loggingSamplingStrategy = _messages.MessageField('GoogleCloudAiplatformV1beta1SamplingStrategy', 12) modelDeploymentMonitoringObjectiveConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringObjectiveConfig', 13, repeated=True) modelDeploymentMonitoringScheduleConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringScheduleConfig', 14) modelMonitoringAlertConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig', 15) name = _messages.StringField(16) nextScheduleTime = _messages.StringField(17) predictInstanceSchemaUri = _messages.StringField(18) samplePredictInstance = _messages.MessageField('extra_types.JsonValue', 19) satisfiesPzi = _messages.BooleanField(20) satisfiesPzs = _messages.BooleanField(21) scheduleState = _messages.EnumField('ScheduleStateValueValuesEnum', 22) state = _messages.EnumField('StateValueValuesEnum', 23) statsAnomaliesBaseDirectory = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 24) updateTime = _messages.StringField(25) class GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJobLatestMonitoringPipelineMetadata(_messages.Message): r"""All metadata of most recent monitoring pipelines. Fields: runTime: The time that most recent monitoring pipelines that is related to this run. status: The status of the most recent monitoring pipeline. """ runTime = _messages.StringField(1) status = _messages.MessageField('GoogleRpcStatus', 2) class GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringObjectiveConfig(_messages.Message): r"""ModelDeploymentMonitoringObjectiveConfig contains the pair of deployed_model_id to ModelMonitoringObjectiveConfig. Fields: deployedModelId: The DeployedModel ID of the objective config. objectiveConfig: The objective config of for the modelmonitoring job of this deployed model. """ deployedModelId = _messages.StringField(1) objectiveConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfig', 2) class GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringScheduleConfig(_messages.Message): r"""The config for scheduling monitoring job. Fields: monitorInterval: Required. The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered. monitorWindow: The time window of the prediction data being included in each prediction dataset. This window specifies how long the data should be collected from historical model results for each run. If not set, ModelDeploymentMonitoringScheduleConfig.monitor_interval will be used. e.g. If currently the cutoff time is 2022-01-08 14:30:00 and the monitor_window is set to be 3600, then data from 2022-01-08 13:30:00 to 2022-01-08 14:30:00 will be retrieved and aggregated to calculate the monitoring statistics. """ monitorInterval = _messages.StringField(1) monitorWindow = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ModelEvaluation(_messages.Message): r"""A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data. Fields: biasConfigs: Specify the configuration for bias detection. createTime: Output only. Timestamp when this ModelEvaluation was created. displayName: The display name of the ModelEvaluation. explanationSpecs: Describes the values of ExplanationSpec that are used for explaining the predicted values on the evaluated data. metadata: The metadata of the ModelEvaluation. For the ModelEvaluation uploaded from Managed Pipeline, metadata contains a structured value with keys of "pipeline_job_id", "evaluation_dataset_type", "evaluation_dataset_path", "row_based_metrics_path". metrics: Evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri metricsSchemaUri: Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluation. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI- Specification/blob/main/versions/3.0.2.md#schemaObject). modelExplanation: Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for AutoML tabular Models. name: Output only. The resource name of the ModelEvaluation. sliceDimensions: All possible dimensions of ModelEvaluationSlices. The dimensions can be used as the filter of the ModelService.ListModelEvaluationSlices request, in the form of `slice.dimension = `. """ biasConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelEvaluationBiasConfig', 1) createTime = _messages.StringField(2) displayName = _messages.StringField(3) explanationSpecs = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelEvaluationModelEvaluationExplanationSpec', 4, repeated=True) metadata = _messages.MessageField('extra_types.JsonValue', 5) metrics = _messages.MessageField('extra_types.JsonValue', 6) metricsSchemaUri = _messages.StringField(7) modelExplanation = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelExplanation', 8) name = _messages.StringField(9) sliceDimensions = _messages.StringField(10, repeated=True) class GoogleCloudAiplatformV1beta1ModelEvaluationBiasConfig(_messages.Message): r"""Configuration for bias detection. Fields: biasSlices: Specification for how the data should be sliced for bias. It contains a list of slices, with limitation of two slices. The first slice of data will be the slice_a. The second slice in the list (slice_b) will be compared against the first slice. If only a single slice is provided, then slice_a will be compared against "not slice_a". Below are examples with feature "education" with value "low", "medium", "high" in the dataset: Example 1: bias_slices = [{'education': 'low'}] A single slice provided. In this case, slice_a is the collection of data with 'education' equals 'low', and slice_b is the collection of data with 'education' equals 'medium' or 'high'. Example 2: bias_slices = [{'education': 'low'}, {'education': 'high'}] Two slices provided. In this case, slice_a is the collection of data with 'education' equals 'low', and slice_b is the collection of data with 'education' equals 'high'. labels: Positive labels selection on the target field. """ biasSlices = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpec', 1) labels = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1ModelEvaluationModelEvaluationExplanationSpec(_messages.Message): r"""A GoogleCloudAiplatformV1beta1ModelEvaluationModelEvaluationExplanationSpec object. Fields: explanationSpec: Explanation spec details. explanationType: Explanation type. For AutoML Image Classification models, possible values are: * `image-integrated-gradients` * `image-xrai` """ explanationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationSpec', 1) explanationType = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ModelEvaluationSlice(_messages.Message): r"""A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations. Fields: createTime: Output only. Timestamp when this ModelEvaluationSlice was created. metrics: Output only. Sliced evaluation metrics of the Model. The schema of the metrics is stored in metrics_schema_uri metricsSchemaUri: Output only. Points to a YAML file stored on Google Cloud Storage describing the metrics of this ModelEvaluationSlice. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI- Specification/blob/main/versions/3.0.2.md#schemaObject). modelExplanation: Output only. Aggregated explanation metrics for the Model's prediction output over the data this ModelEvaluation uses. This field is populated only if the Model is evaluated with explanations, and only for tabular Models. name: Output only. The resource name of the ModelEvaluationSlice. slice: Output only. The slice of the test data that is used to evaluate the Model. """ createTime = _messages.StringField(1) metrics = _messages.MessageField('extra_types.JsonValue', 2) metricsSchemaUri = _messages.StringField(3) modelExplanation = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelExplanation', 4) name = _messages.StringField(5) slice = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelEvaluationSliceSlice', 6) class GoogleCloudAiplatformV1beta1ModelEvaluationSliceSlice(_messages.Message): r"""Definition of a slice. Fields: dimension: Output only. The dimension of the slice. Well-known dimensions are: * `annotationSpec`: This slice is on the test data that has either ground truth or prediction with AnnotationSpec.display_name equals to value. * `slice`: This slice is a user customized slice defined by its SliceSpec. sliceSpec: Output only. Specification for how the data was sliced. value: Output only. The value of the dimension in this slice. """ dimension = _messages.StringField(1) sliceSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpec', 2) value = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpec(_messages.Message): r"""Specification for how the data should be sliced. Messages: ConfigsValue: Mapping configuration for this SliceSpec. The key is the name of the feature. By default, the key will be prefixed by "instance" as a dictionary prefix for Vertex Batch Predictions output format. Fields: configs: Mapping configuration for this SliceSpec. The key is the name of the feature. By default, the key will be prefixed by "instance" as a dictionary prefix for Vertex Batch Predictions output format. """ @encoding.MapUnrecognizedFields('additionalProperties') class ConfigsValue(_messages.Message): r"""Mapping configuration for this SliceSpec. The key is the name of the feature. By default, the key will be prefixed by "instance" as a dictionary prefix for Vertex Batch Predictions output format. Messages: AdditionalProperty: An additional property for a ConfigsValue object. Fields: additionalProperties: Additional properties of type ConfigsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ConfigsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpe cSliceConfig attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecSliceConfig', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) configs = _messages.MessageField('ConfigsValue', 1) class GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecRange(_messages.Message): r"""A range of values for slice(s). `low` is inclusive, `high` is exclusive. Fields: high: Exclusive high value for the range. low: Inclusive low value for the range. """ high = _messages.FloatField(1, variant=_messages.Variant.FLOAT) low = _messages.FloatField(2, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecSliceConfig(_messages.Message): r"""Specification message containing the config for this SliceSpec. When `kind` is selected as `value` and/or `range`, only a single slice will be computed. When `all_values` is present, a separate slice will be computed for each possible label/value for the corresponding key in `config`. Examples, with feature zip_code with values 12345, 23334, 88888 and feature country with values "US", "Canada", "Mexico" in the dataset: Example 1: { "zip_code": { "value": { "float_value": 12345.0 } } } A single slice for any data with zip_code 12345 in the dataset. Example 2: { "zip_code": { "range": { "low": 12345, "high": 20000 } } } A single slice containing data where the zip_codes between 12345 and 20000 For this example, data with the zip_code of 12345 will be in this slice. Example 3: { "zip_code": { "range": { "low": 10000, "high": 20000 } }, "country": { "value": { "string_value": "US" } } } A single slice containing data where the zip_codes between 10000 and 20000 has the country "US". For this example, data with the zip_code of 12345 and country "US" will be in this slice. Example 4: { "country": {"all_values": { "value": true } } } Three slices are computed, one for each unique country in the dataset. Example 5: { "country": { "all_values": { "value": true } }, "zip_code": { "value": { "float_value": 12345.0 } } } Three slices are computed, one for each unique country in the dataset where the zip_code is also 12345. For this example, data with zip_code 12345 and country "US" will be in one slice, zip_code 12345 and country "Canada" in another slice, and zip_code 12345 and country "Mexico" in another slice, totaling 3 slices. Fields: allValues: If all_values is set to true, then all possible labels of the keyed feature will have another slice computed. Example: `{"all_values":{"value":true}}` range: A range of values for a numerical feature. Example: `{"range":{"low":10000.0,"high":50000.0}}` will capture 12345 and 23334 in the slice. value: A unique specific value for a given feature. Example: `{ "value": { "string_value": "12345" } }` """ allValues = _messages.BooleanField(1) range = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecRange', 2) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecValue', 3) class GoogleCloudAiplatformV1beta1ModelEvaluationSliceSliceSliceSpecValue(_messages.Message): r"""Single value that supports strings and floats. Fields: floatValue: Float type. stringValue: String type. """ floatValue = _messages.FloatField(1, variant=_messages.Variant.FLOAT) stringValue = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ModelExplanation(_messages.Message): r"""Aggregated explanation metrics for a Model over a set of instances. Fields: meanAttributions: Output only. Aggregated attributions explaining the Model's prediction outputs over the set of instances. The attributions are grouped by outputs. For Models that predict only one output, such as regression Models that predict only one score, there is only one attibution that explains the predicted output. For Models that predict multiple outputs, such as multiclass Models that predict multiple classes, each element explains one specific item. Attribution.output_index can be used to identify which output this attribution is explaining. The baselineOutputValue, instanceOutputValue and featureAttributions fields are averaged over the test data. NOTE: Currently AutoML tabular classification Models produce only one attribution, which averages attributions over all the classes it predicts. Attribution.approximation_error is not populated. """ meanAttributions = _messages.MessageField('GoogleCloudAiplatformV1beta1Attribution', 1, repeated=True) class GoogleCloudAiplatformV1beta1ModelExportFormat(_messages.Message): r"""Represents export format supported by the Model. All formats export to Google Cloud Storage. Enums: ExportableContentsValueListEntryValuesEnum: Fields: exportableContents: Output only. The content of this Model that may be exported. id: Output only. The ID of the export format. The possible format IDs are: * `tflite` Used for Android mobile devices. * `edgetpu-tflite` Used for [Edge TPU](https://cloud.google.com/edge-tpu/) devices. * `tf-saved- model` A tensorflow model in SavedModel format. * `tf-js` A [TensorFlow.js](https://www.tensorflow.org/js) model that can be used in the browser and in Node.js using JavaScript. * `core-ml` Used for iOS mobile devices. * `custom-trained` A Model that was uploaded or trained by custom code. * `genie` A tuned Model Garden model. """ class ExportableContentsValueListEntryValuesEnum(_messages.Enum): r"""ExportableContentsValueListEntryValuesEnum enum type. Values: EXPORTABLE_CONTENT_UNSPECIFIED: Should not be used. ARTIFACT: Model artifact and any of its supported files. Will be exported to the location specified by the `artifactDestination` field of the ExportModelRequest.output_config object. IMAGE: The container image that is to be used when deploying this Model. Will be exported to the location specified by the `imageDestination` field of the ExportModelRequest.output_config object. """ EXPORTABLE_CONTENT_UNSPECIFIED = 0 ARTIFACT = 1 IMAGE = 2 exportableContents = _messages.EnumField('ExportableContentsValueListEntryValuesEnum', 1, repeated=True) id = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ModelGardenSource(_messages.Message): r"""Contains information about the source of the models generated from Model Garden. Fields: publicModelName: Required. The model garden source model resource name. skipHfModelCache: Optional. Whether to avoid pulling the model from the HF cache. versionId: Optional. The model garden source model version ID. """ publicModelName = _messages.StringField(1) skipHfModelCache = _messages.BooleanField(2) versionId = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ModelMonitor(_messages.Message): r"""Vertex AI Model Monitoring Service serves as a central hub for the analysis and visualization of data quality and performance related to models. ModelMonitor stands as a top level resource for overseeing your model monitoring tasks. Fields: createTime: Output only. Timestamp when this ModelMonitor was created. displayName: The display name of the ModelMonitor. The name can be up to 128 characters long and can consist of any UTF-8. encryptionSpec: Customer-managed encryption key spec for a ModelMonitor. If set, this ModelMonitor and all sub-resources of this ModelMonitor will be secured by this key. explanationSpec: Optional model explanation spec. It is used for feature attribution monitoring. modelMonitoringSchema: Monitoring Schema is to specify the model's features, prediction outputs and ground truth properties. It is used to extract pertinent data from the dataset and to process features based on their properties. Make sure that the schema aligns with your dataset, if it does not, we will be unable to extract data from the dataset. It is required for most models, but optional for Vertex AI AutoML Tables unless the schem information is not available. modelMonitoringTarget: The entity that is subject to analysis. Currently only models in Vertex AI Model Registry are supported. If you want to analyze the model which is outside the Vertex AI, you could register a model in Vertex AI Model Registry using just a display name. name: Immutable. Resource name of the ModelMonitor. Format: `projects/{project}/locations/{location}/modelMonitors/{model_monitor}`. notificationSpec: Optional default notification spec, it can be overridden in the ModelMonitoringJob notification spec. outputSpec: Optional default monitoring metrics/logs export spec, it can be overridden in the ModelMonitoringJob output spec. If not specified, a default Google Cloud Storage bucket will be created under your project. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. tabularObjective: Optional default tabular model monitoring objective. trainingDataset: Optional training dataset used to train the model. It can serve as a reference dataset to identify changes in production. updateTime: Output only. Timestamp when this ModelMonitor was updated most recently. """ createTime = _messages.StringField(1) displayName = _messages.StringField(2) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 3) explanationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationSpec', 4) modelMonitoringSchema = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringSchema', 5) modelMonitoringTarget = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTarget', 6) name = _messages.StringField(7) notificationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpec', 8) outputSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringOutputSpec', 9) satisfiesPzi = _messages.BooleanField(10) satisfiesPzs = _messages.BooleanField(11) tabularObjective = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective', 12) trainingDataset = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringInput', 13) updateTime = _messages.StringField(14) class GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTarget(_messages.Message): r"""The monitoring target refers to the entity that is subject to analysis. e.g. Vertex AI Model version. Fields: vertexModel: Model in Vertex AI Model Registry. """ vertexModel = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTargetVertexModelSource', 1) class GoogleCloudAiplatformV1beta1ModelMonitorModelMonitoringTargetVertexModelSource(_messages.Message): r"""Model in Vertex AI Model Registry. Fields: model: Model resource name. Format: projects/{project}/locations/{location}/models/{model}. modelVersionId: Model version id. """ model = _messages.StringField(1) modelVersionId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ModelMonitoringAlert(_messages.Message): r"""Represents a single monitoring alert. This is currently used in the SearchModelMonitoringAlerts api, thus the alert wrapped in this message belongs to the resource asked in the request. Fields: alertTime: Alert creation time. anomaly: Anomaly details. objectiveType: One of the supported monitoring objectives: `raw-feature- drift` `prediction-output-drift` `feature-attribution` statsName: The stats name. """ alertTime = _messages.StringField(1) anomaly = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringAnomaly', 2) objectiveType = _messages.StringField(3) statsName = _messages.StringField(4) class GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition(_messages.Message): r"""Monitoring alert triggered condition. Fields: threshold: A condition that compares a stats value against a threshold. Alert will be triggered if value above the threshold. """ threshold = _messages.FloatField(1) class GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig(_messages.Message): r"""The alert config for model monitoring. Fields: emailAlertConfig: Email alert config. enableLogging: Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto ModelMonitoringStatsAnomalies. This can be further synced to Pub/Sub or any other services supported by Cloud Logging. notificationChannels: Resource names of the NotificationChannels to send alert. Must be of the format `projects//notificationChannels/` """ emailAlertConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfigEmailAlertConfig', 1) enableLogging = _messages.BooleanField(2) notificationChannels = _messages.StringField(3, repeated=True) class GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfigEmailAlertConfig(_messages.Message): r"""The config for email alert. Fields: userEmails: The email addresses to send the alert. """ userEmails = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1ModelMonitoringAnomaly(_messages.Message): r"""Represents a single model monitoring anomaly. Fields: algorithm: Algorithm used to calculated the metrics, eg: jensen_shannon_divergence, l_infinity. modelMonitoringJob: Model monitoring job resource name. tabularAnomaly: Tabular anomaly. """ algorithm = _messages.StringField(1) modelMonitoringJob = _messages.StringField(2) tabularAnomaly = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringAnomalyTabularAnomaly', 3) class GoogleCloudAiplatformV1beta1ModelMonitoringAnomalyTabularAnomaly(_messages.Message): r"""Tabular anomaly details. Fields: anomaly: Anomaly body. anomalyUri: Additional anomaly information. e.g. Google Cloud Storage uri. condition: The alert condition associated with this anomaly. summary: Overview of this anomaly. triggerTime: The time the anomaly was triggered. """ anomaly = _messages.MessageField('extra_types.JsonValue', 1) anomalyUri = _messages.StringField(2) condition = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition', 3) summary = _messages.StringField(4) triggerTime = _messages.StringField(5) class GoogleCloudAiplatformV1beta1ModelMonitoringConfig(_messages.Message): r"""The model monitoring configuration used for Batch Prediction Job. Fields: alertConfig: Model monitoring alert config. analysisInstanceSchemaUri: YAML schema file uri in Cloud Storage describing the format of a single instance that you want Tensorflow Data Validation (TFDV) to analyze. If there are any data type differences between predict instance and TFDV instance, this field can be used to override the schema. For models trained with Vertex AI, this field must be set as all the fields in predict instance formatted as string. objectiveConfigs: Model monitoring objective config. statsAnomaliesBaseDirectory: A Google Cloud Storage location for batch prediction model monitoring to dump statistics and anomalies. If not provided, a folder will be created in customer project to hold statistics and anomalies. """ alertConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig', 1) analysisInstanceSchemaUri = _messages.StringField(2) objectiveConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfig', 3, repeated=True) statsAnomaliesBaseDirectory = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 4) class GoogleCloudAiplatformV1beta1ModelMonitoringInput(_messages.Message): r"""Model monitoring data input spec. Fields: batchPredictionOutput: Vertex AI Batch prediction Job. columnizedDataset: Columnized dataset. timeInterval: The time interval (pair of start_time and end_time) for which results should be returned. timeOffset: The time offset setting for which results should be returned. vertexEndpointLogs: Vertex AI Endpoint request & response logging. """ batchPredictionOutput = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringInputBatchPredictionOutput', 1) columnizedDataset = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDataset', 2) timeInterval = _messages.MessageField('GoogleTypeInterval', 3) timeOffset = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringInputTimeOffset', 4) vertexEndpointLogs = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringInputVertexEndpointLogs', 5) class GoogleCloudAiplatformV1beta1ModelMonitoringInputBatchPredictionOutput(_messages.Message): r"""Data from Vertex AI Batch prediction job output. Fields: batchPredictionJob: Vertex AI Batch prediction job resource name. The job must match the model version specified in [ModelMonitor].[model_monitoring_target]. """ batchPredictionJob = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDataset(_messages.Message): r"""Input dataset spec. Fields: bigquerySource: BigQuery data source. gcsSource: Google Cloud Storage data source. timestampField: The timestamp field. Usually for serving data. vertexDataset: Resource name of the Vertex AI managed dataset. """ bigquerySource = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringBigQuerySource', 1) gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringGcsSource', 2) timestampField = _messages.StringField(3) vertexDataset = _messages.StringField(4) class GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringBigQuerySource(_messages.Message): r"""Dataset spec for data sotred in BigQuery. Fields: query: Standard SQL to be used instead of the `table_uri`. tableUri: BigQuery URI to a table, up to 2000 characters long. All the columns in the table will be selected. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`. """ query = _messages.StringField(1) tableUri = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ModelMonitoringInputModelMonitoringDatasetModelMonitoringGcsSource(_messages.Message): r"""Dataset spec for data stored in Google Cloud Storage. Enums: FormatValueValuesEnum: Data format of the dataset. Fields: format: Data format of the dataset. gcsUri: Google Cloud Storage URI to the input file(s). May contain wildcards. For more information on wildcards, see https://cloud.google.com/storage/docs/wildcards. """ class FormatValueValuesEnum(_messages.Enum): r"""Data format of the dataset. Values: DATA_FORMAT_UNSPECIFIED: Data format unspecified, used when this field is unset. CSV: CSV files. TF_RECORD: TfRecord files JSONL: JsonL files. """ DATA_FORMAT_UNSPECIFIED = 0 CSV = 1 TF_RECORD = 2 JSONL = 3 format = _messages.EnumField('FormatValueValuesEnum', 1) gcsUri = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ModelMonitoringInputTimeOffset(_messages.Message): r"""Time offset setting. Fields: offset: [offset] is the time difference from the cut-off time. For scheduled jobs, the cut-off time is the scheduled time. For non- scheduled jobs, it's the time when the job was created. Currently we support the following format: 'w|W': Week, 'd|D': Day, 'h|H': Hour E.g. '1h' stands for 1 hour, '2d' stands for 2 days. window: [window] refers to the scope of data selected for analysis. It allows you to specify the quantity of data you wish to examine. Currently we support the following format: 'w|W': Week, 'd|D': Day, 'h|H': Hour E.g. '1h' stands for 1 hour, '2d' stands for 2 days. """ offset = _messages.StringField(1) window = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ModelMonitoringInputVertexEndpointLogs(_messages.Message): r"""Data from Vertex AI Endpoint request response logging. Fields: endpoints: List of endpoint resource names. The endpoints must enable the logging with the [Endpoint].[request_response_logging_config], and must contain the deployed model corresponding to the model version specified in [ModelMonitor].[model_monitoring_target]. """ endpoints = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1ModelMonitoringJob(_messages.Message): r"""Represents a model monitoring job that analyze dataset using different monitoring algorithm. Enums: StateValueValuesEnum: Output only. The state of the monitoring job. * When the job is still creating, the state will be 'JOB_STATE_PENDING'. * Once the job is successfully created, the state will be 'JOB_STATE_RUNNING'. * Once the job is finished, the state will be one of 'JOB_STATE_FAILED', 'JOB_STATE_SUCCEEDED', 'JOB_STATE_PARTIALLY_SUCCEEDED'. Fields: createTime: Output only. Timestamp when this ModelMonitoringJob was created. displayName: The display name of the ModelMonitoringJob. The name can be up to 128 characters long and can consist of any UTF-8. jobExecutionDetail: Output only. Execution results for all the monitoring objectives. modelMonitoringSpec: Monitoring monitoring job spec. It outlines the specifications for monitoring objectives, notifications, and result exports. If left blank, the default monitoring specifications from the top-level resource 'ModelMonitor' will be applied. If provided, we will use the specification defined here rather than the default one. name: Output only. Resource name of a ModelMonitoringJob. Format: `project s/{project_id}/locations/{location_id}/modelMonitors/{model_monitor_id}/ modelMonitoringJobs/{model_monitoring_job_id}` schedule: Output only. Schedule resource name. It will only appear when this job is triggered by a schedule. scheduleTime: Output only. Timestamp when this ModelMonitoringJob was scheduled. It will only appear when this job is triggered by a schedule. state: Output only. The state of the monitoring job. * When the job is still creating, the state will be 'JOB_STATE_PENDING'. * Once the job is successfully created, the state will be 'JOB_STATE_RUNNING'. * Once the job is finished, the state will be one of 'JOB_STATE_FAILED', 'JOB_STATE_SUCCEEDED', 'JOB_STATE_PARTIALLY_SUCCEEDED'. updateTime: Output only. Timestamp when this ModelMonitoringJob was updated most recently. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The state of the monitoring job. * When the job is still creating, the state will be 'JOB_STATE_PENDING'. * Once the job is successfully created, the state will be 'JOB_STATE_RUNNING'. * Once the job is finished, the state will be one of 'JOB_STATE_FAILED', 'JOB_STATE_SUCCEEDED', 'JOB_STATE_PARTIALLY_SUCCEEDED'. Values: JOB_STATE_UNSPECIFIED: The job state is unspecified. JOB_STATE_QUEUED: The job has been just created or resumed and processing has not yet begun. JOB_STATE_PENDING: The service is preparing to run the job. JOB_STATE_RUNNING: The job is in progress. JOB_STATE_SUCCEEDED: The job completed successfully. JOB_STATE_FAILED: The job failed. JOB_STATE_CANCELLING: The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. JOB_STATE_CANCELLED: The job has been cancelled. JOB_STATE_PAUSED: The job has been stopped, and can be resumed. JOB_STATE_EXPIRED: The job has expired. JOB_STATE_UPDATING: The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state. JOB_STATE_PARTIALLY_SUCCEEDED: The job is partially succeeded, some results may be missing due to errors. """ JOB_STATE_UNSPECIFIED = 0 JOB_STATE_QUEUED = 1 JOB_STATE_PENDING = 2 JOB_STATE_RUNNING = 3 JOB_STATE_SUCCEEDED = 4 JOB_STATE_FAILED = 5 JOB_STATE_CANCELLING = 6 JOB_STATE_CANCELLED = 7 JOB_STATE_PAUSED = 8 JOB_STATE_EXPIRED = 9 JOB_STATE_UPDATING = 10 JOB_STATE_PARTIALLY_SUCCEEDED = 11 createTime = _messages.StringField(1) displayName = _messages.StringField(2) jobExecutionDetail = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetail', 3) modelMonitoringSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringSpec', 4) name = _messages.StringField(5) schedule = _messages.StringField(6) scheduleTime = _messages.StringField(7) state = _messages.EnumField('StateValueValuesEnum', 8) updateTime = _messages.StringField(9) class GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetail(_messages.Message): r"""Represent the execution details of the job. Messages: ObjectiveStatusValue: Status of data processing for each monitoring objective. Key is the objective. Fields: baselineDatasets: Processed baseline datasets. error: Additional job error status. objectiveStatus: Status of data processing for each monitoring objective. Key is the objective. targetDatasets: Processed target datasets. """ @encoding.MapUnrecognizedFields('additionalProperties') class ObjectiveStatusValue(_messages.Message): r"""Status of data processing for each monitoring objective. Key is the objective. Messages: AdditionalProperty: An additional property for a ObjectiveStatusValue object. Fields: additionalProperties: Additional properties of type ObjectiveStatusValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ObjectiveStatusValue object. Fields: key: Name of the additional property. value: A GoogleRpcStatus attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleRpcStatus', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) baselineDatasets = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetailProcessedDataset', 1, repeated=True) error = _messages.MessageField('GoogleRpcStatus', 2) objectiveStatus = _messages.MessageField('ObjectiveStatusValue', 3) targetDatasets = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetailProcessedDataset', 4, repeated=True) class GoogleCloudAiplatformV1beta1ModelMonitoringJobExecutionDetailProcessedDataset(_messages.Message): r"""Processed dataset information. Fields: location: Actual data location of the processed dataset. timeRange: Dataset time range information if any. """ location = _messages.StringField(1) timeRange = _messages.MessageField('GoogleTypeInterval', 2) class GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpec(_messages.Message): r"""Notification spec(email, notification channel) for model monitoring statistics/alerts. Fields: emailConfig: Email alert config. enableCloudLogging: Dump the anomalies to Cloud Logging. The anomalies will be put to json payload encoded from proto google.cloud.aiplatform.logging.ModelMonitoringAnomaliesLogEntry. This can be further sinked to Pub/Sub or any other services supported by Cloud Logging. notificationChannelConfigs: Notification channel config. """ emailConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecEmailConfig', 1) enableCloudLogging = _messages.BooleanField(2) notificationChannelConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecNotificationChannelConfig', 3, repeated=True) class GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecEmailConfig(_messages.Message): r"""The config for email alerts. Fields: userEmails: The email addresses to send the alerts. """ userEmails = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpecNotificationChannelConfig(_messages.Message): r"""Google Cloud Notification Channel config. Fields: notificationChannel: Resource names of the NotificationChannels. Must be of the format `projects//notificationChannels/` """ notificationChannel = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfig(_messages.Message): r"""The objective configuration for model monitoring, including the information needed to detect anomalies for one particular model. Fields: explanationConfig: The config for integrating with Vertex Explainable AI. predictionDriftDetectionConfig: The config for drift of prediction data. trainingDataset: Training dataset for models. This field has to be set only if TrainingPredictionSkewDetectionConfig is specified. trainingPredictionSkewDetectionConfig: The config for skew between training data and prediction data. """ explanationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfig', 1) predictionDriftDetectionConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig', 2) trainingDataset = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingDataset', 3) trainingPredictionSkewDetectionConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig', 4) class GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfig(_messages.Message): r"""The config for integrating with Vertex Explainable AI. Only applicable if the Model has explanation_spec populated. Fields: enableFeatureAttributes: If want to analyze the Vertex Explainable AI feature attribute scores or not. If set to true, Vertex AI will log the feature attributions from explain response and do the skew/drift detection for them. explanationBaseline: Predictions generated by the BatchPredictionJob using baseline dataset. """ enableFeatureAttributes = _messages.BooleanField(1) explanationBaseline = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline', 2) class GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigExplanationConfigExplanationBaseline(_messages.Message): r"""Output from BatchPredictionJob for Model Monitoring baseline dataset, which can be used to generate baseline attribution scores. Enums: PredictionFormatValueValuesEnum: The storage format of the predictions generated BatchPrediction job. Fields: bigquery: BigQuery location for BatchExplain output. gcs: Cloud Storage location for BatchExplain output. predictionFormat: The storage format of the predictions generated BatchPrediction job. """ class PredictionFormatValueValuesEnum(_messages.Enum): r"""The storage format of the predictions generated BatchPrediction job. Values: PREDICTION_FORMAT_UNSPECIFIED: Should not be set. JSONL: Predictions are in JSONL files. BIGQUERY: Predictions are in BigQuery. """ PREDICTION_FORMAT_UNSPECIFIED = 0 JSONL = 1 BIGQUERY = 2 bigquery = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQueryDestination', 1) gcs = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 2) predictionFormat = _messages.EnumField('PredictionFormatValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigPredictionDriftDetectionConfig(_messages.Message): r"""The config for Prediction data drift detection. Messages: AttributionScoreDriftThresholdsValue: Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows. DriftThresholdsValue: Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws. Fields: attributionScoreDriftThresholds: Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows. defaultDriftThreshold: Drift anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features. driftThresholds: Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws. """ @encoding.MapUnrecognizedFields('additionalProperties') class AttributionScoreDriftThresholdsValue(_messages.Message): r"""Key is the feature name and value is the threshold. The threshold here is against attribution score distance between different time windows. Messages: AdditionalProperty: An additional property for a AttributionScoreDriftThresholdsValue object. Fields: additionalProperties: Additional properties of type AttributionScoreDriftThresholdsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a AttributionScoreDriftThresholdsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ThresholdConfig attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ThresholdConfig', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class DriftThresholdsValue(_messages.Message): r"""Key is the feature name and value is the threshold. If a feature needs to be monitored for drift, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between different time windws. Messages: AdditionalProperty: An additional property for a DriftThresholdsValue object. Fields: additionalProperties: Additional properties of type DriftThresholdsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a DriftThresholdsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ThresholdConfig attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ThresholdConfig', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) attributionScoreDriftThresholds = _messages.MessageField('AttributionScoreDriftThresholdsValue', 1) defaultDriftThreshold = _messages.MessageField('GoogleCloudAiplatformV1beta1ThresholdConfig', 2) driftThresholds = _messages.MessageField('DriftThresholdsValue', 3) class GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingDataset(_messages.Message): r"""Training Dataset information. Fields: bigquerySource: The BigQuery table of the unmanaged Dataset used to train this Model. dataFormat: Data format of the dataset, only applicable if the input is from Google Cloud Storage. The possible formats are: "tf-record" The source file is a TFRecord file. "csv" The source file is a CSV file. "jsonl" The source file is a JSONL file. dataset: The resource name of the Dataset used to train this Model. gcsSource: The Google Cloud Storage uri of the unmanaged Dataset used to train this Model. loggingSamplingStrategy: Strategy to sample data from Training Dataset. If not set, we process the whole dataset. targetField: The target field name the model is to predict. This field will be excluded when doing Predict and (or) Explain for the training data. """ bigquerySource = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQuerySource', 1) dataFormat = _messages.StringField(2) dataset = _messages.StringField(3) gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsSource', 4) loggingSamplingStrategy = _messages.MessageField('GoogleCloudAiplatformV1beta1SamplingStrategy', 5) targetField = _messages.StringField(6) class GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveConfigTrainingPredictionSkewDetectionConfig(_messages.Message): r"""The config for Training & Prediction data skew detection. It specifies the training dataset sources and the skew detection parameters. Messages: AttributionScoreSkewThresholdsValue: Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature. SkewThresholdsValue: Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature. Fields: attributionScoreSkewThresholds: Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature. defaultSkewThreshold: Skew anomaly detection threshold used by all features. When the per-feature thresholds are not set, this field can be used to specify a threshold for all features. skewThresholds: Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature. """ @encoding.MapUnrecognizedFields('additionalProperties') class AttributionScoreSkewThresholdsValue(_messages.Message): r"""Key is the feature name and value is the threshold. The threshold here is against attribution score distance between the training and prediction feature. Messages: AdditionalProperty: An additional property for a AttributionScoreSkewThresholdsValue object. Fields: additionalProperties: Additional properties of type AttributionScoreSkewThresholdsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a AttributionScoreSkewThresholdsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ThresholdConfig attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ThresholdConfig', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class SkewThresholdsValue(_messages.Message): r"""Key is the feature name and value is the threshold. If a feature needs to be monitored for skew, a value threshold must be configured for that feature. The threshold here is against feature distribution distance between the training and prediction feature. Messages: AdditionalProperty: An additional property for a SkewThresholdsValue object. Fields: additionalProperties: Additional properties of type SkewThresholdsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a SkewThresholdsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ThresholdConfig attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ThresholdConfig', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) attributionScoreSkewThresholds = _messages.MessageField('AttributionScoreSkewThresholdsValue', 1) defaultSkewThreshold = _messages.MessageField('GoogleCloudAiplatformV1beta1ThresholdConfig', 2) skewThresholds = _messages.MessageField('SkewThresholdsValue', 3) class GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpec(_messages.Message): r"""Monitoring objectives spec. Fields: baselineDataset: Baseline dataset. It could be the training dataset or production serving dataset from a previous period. explanationSpec: The explanation spec. This spec is required when the objectives spec includes feature attribution objectives. tabularObjective: Tabular monitoring objective. targetDataset: Target dataset. """ baselineDataset = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringInput', 1) explanationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ExplanationSpec', 2) tabularObjective = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective', 3) targetDataset = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringInput', 4) class GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec(_messages.Message): r"""Data drift monitoring spec. Data drift measures the distribution distance between the current dataset and a baseline dataset. A typical use case is to detect data drift between the recent production serving dataset and the training dataset, or to compare the recent production dataset with a dataset from a previous period. Messages: FeatureAlertConditionsValue: Per feature alert condition will override default alert condition. Fields: categoricalMetricType: Supported metrics type: * l_infinity * jensen_shannon_divergence defaultCategoricalAlertCondition: Default alert condition for all the categorical features. defaultNumericAlertCondition: Default alert condition for all the numeric features. featureAlertConditions: Per feature alert condition will override default alert condition. features: Feature names / Prediction output names interested in monitoring. These should be a subset of the input feature names or prediction output names specified in the monitoring schema. If the field is not specified all features / prediction outputs outlied in the monitoring schema will be used. numericMetricType: Supported metrics type: * jensen_shannon_divergence """ @encoding.MapUnrecognizedFields('additionalProperties') class FeatureAlertConditionsValue(_messages.Message): r"""Per feature alert condition will override default alert condition. Messages: AdditionalProperty: An additional property for a FeatureAlertConditionsValue object. Fields: additionalProperties: Additional properties of type FeatureAlertConditionsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a FeatureAlertConditionsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) categoricalMetricType = _messages.StringField(1) defaultCategoricalAlertCondition = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition', 2) defaultNumericAlertCondition = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition', 3) featureAlertConditions = _messages.MessageField('FeatureAlertConditionsValue', 4) features = _messages.StringField(5, repeated=True) numericMetricType = _messages.StringField(6) class GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecFeatureAttributionSpec(_messages.Message): r"""Feature attribution monitoring spec. Messages: FeatureAlertConditionsValue: Per feature alert condition will override default alert condition. Fields: batchExplanationDedicatedResources: The config of resources used by the Model Monitoring during the batch explanation for non-AutoML models. If not set, `n1-standard-2` machine type will be used by default. defaultAlertCondition: Default alert condition for all the features. featureAlertConditions: Per feature alert condition will override default alert condition. features: Feature names interested in monitoring. These should be a subset of the input feature names specified in the monitoring schema. If the field is not specified all features outlied in the monitoring schema will be used. """ @encoding.MapUnrecognizedFields('additionalProperties') class FeatureAlertConditionsValue(_messages.Message): r"""Per feature alert condition will override default alert condition. Messages: AdditionalProperty: An additional property for a FeatureAlertConditionsValue object. Fields: additionalProperties: Additional properties of type FeatureAlertConditionsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a FeatureAlertConditionsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) batchExplanationDedicatedResources = _messages.MessageField('GoogleCloudAiplatformV1beta1BatchDedicatedResources', 1) defaultAlertCondition = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringAlertCondition', 2) featureAlertConditions = _messages.MessageField('FeatureAlertConditionsValue', 3) features = _messages.StringField(4, repeated=True) class GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecTabularObjective(_messages.Message): r"""Tabular monitoring objective. Fields: featureAttributionSpec: Feature attribution monitoring spec. featureDriftSpec: Input feature distribution drift monitoring spec. predictionOutputDriftSpec: Prediction output distribution drift monitoring spec. """ featureAttributionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecFeatureAttributionSpec', 1) featureDriftSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec', 2) predictionOutputDriftSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpecDataDriftSpec', 3) class GoogleCloudAiplatformV1beta1ModelMonitoringOutputSpec(_messages.Message): r"""Specification for the export destination of monitoring results, including metrics, logs, etc. Fields: gcsBaseDirectory: Google Cloud Storage base folder path for metrics, error logs, etc. """ gcsBaseDirectory = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 1) class GoogleCloudAiplatformV1beta1ModelMonitoringSchema(_messages.Message): r"""The Model Monitoring Schema definition. Fields: featureFields: Feature names of the model. Vertex AI will try to match the features from your dataset as follows: * For 'csv' files, the header names are required, and we will extract the corresponding feature values when the header names align with the feature names. * For 'jsonl' files, we will extract the corresponding feature values if the key names match the feature names. Note: Nested features are not supported, so please ensure your features are flattened. Ensure the feature values are scalar or an array of scalars. * For 'bigquery' dataset, we will extract the corresponding feature values if the column names match the feature names. Note: The column type can be a scalar or an array of scalars. STRUCT or JSON types are not supported. You may use SQL queries to select or aggregate the relevant features from your original table. However, ensure that the 'schema' of the query results meets our requirements. * For the Vertex AI Endpoint Request Response Logging table or Vertex AI Batch Prediction Job results. If the instance_type is an array, ensure that the sequence in feature_fields matches the order of features in the prediction instance. We will match the feature with the array in the order specified in [feature_fields]. groundTruthFields: Target /ground truth names of the model. predictionFields: Prediction output names of the model. The requirements are the same as the feature_fields. For AutoML Tables, the prediction output name presented in schema will be: `predicted_{target_column}`, the `target_column` is the one you specified when you train the model. For Prediction output drift analysis: * AutoML Classification, the distribution of the argmax label will be analyzed. * AutoML Regression, the distribution of the value will be analyzed. """ featureFields = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema', 1, repeated=True) groundTruthFields = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema', 2, repeated=True) predictionFields = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema', 3, repeated=True) class GoogleCloudAiplatformV1beta1ModelMonitoringSchemaFieldSchema(_messages.Message): r"""Schema field definition. Fields: dataType: Supported data types are: `float` `integer` `boolean` `string` `categorical` name: Field name. repeated: Describes if the schema field is an array of given data type. """ dataType = _messages.StringField(1) name = _messages.StringField(2) repeated = _messages.BooleanField(3) class GoogleCloudAiplatformV1beta1ModelMonitoringSpec(_messages.Message): r"""Monitoring monitoring job spec. It outlines the specifications for monitoring objectives, notifications, and result exports. Fields: notificationSpec: The model monitoring notification spec. objectiveSpec: The monitoring objective spec. outputSpec: The Output destination spec for metrics, error logs, etc. """ notificationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringNotificationSpec', 1) objectiveSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringObjectiveSpec', 2) outputSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringOutputSpec', 3) class GoogleCloudAiplatformV1beta1ModelMonitoringStats(_messages.Message): r"""Represents the collection of statistics for a metric. Fields: tabularStats: Generated tabular statistics. """ tabularStats = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringTabularStats', 1) class GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies(_messages.Message): r"""Statistics and anomalies generated by Model Monitoring. Enums: ObjectiveValueValuesEnum: Model Monitoring Objective those stats and anomalies belonging to. Fields: anomalyCount: Number of anomalies within all stats. deployedModelId: Deployed Model ID. featureStats: A list of historical Stats and Anomalies generated for all Features. objective: Model Monitoring Objective those stats and anomalies belonging to. """ class ObjectiveValueValuesEnum(_messages.Enum): r"""Model Monitoring Objective those stats and anomalies belonging to. Values: MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_TYPE_UNSPECIFIED: Default value, should not be set. RAW_FEATURE_SKEW: Raw feature values' stats to detect skew between Training-Prediction datasets. RAW_FEATURE_DRIFT: Raw feature values' stats to detect drift between Serving-Prediction datasets. FEATURE_ATTRIBUTION_SKEW: Feature attribution scores to detect skew between Training-Prediction datasets. FEATURE_ATTRIBUTION_DRIFT: Feature attribution scores to detect skew between Prediction datasets collected within different time windows. """ MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_TYPE_UNSPECIFIED = 0 RAW_FEATURE_SKEW = 1 RAW_FEATURE_DRIFT = 2 FEATURE_ATTRIBUTION_SKEW = 3 FEATURE_ATTRIBUTION_DRIFT = 4 anomalyCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) deployedModelId = _messages.StringField(2) featureStats = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies', 3, repeated=True) objective = _messages.EnumField('ObjectiveValueValuesEnum', 4) class GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomaliesFeatureHistoricStatsAnomalies(_messages.Message): r"""Historical Stats (and Anomalies) for a specific Feature. Fields: featureDisplayName: Display Name of the Feature. predictionStats: A list of historical stats generated by different time window's Prediction Dataset. threshold: Threshold for anomaly detection. trainingStats: Stats calculated for the Training Dataset. """ featureDisplayName = _messages.StringField(1) predictionStats = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureStatsAnomaly', 2, repeated=True) threshold = _messages.MessageField('GoogleCloudAiplatformV1beta1ThresholdConfig', 3) trainingStats = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureStatsAnomaly', 4) class GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPoint(_messages.Message): r"""Represents a single statistics data point. Fields: algorithm: Algorithm used to calculated the metrics, eg: jensen_shannon_divergence, l_infinity. baselineStats: Statistics from baseline dataset. createTime: Statistics create time. currentStats: Statistics from current dataset. hasAnomaly: Indicate if the statistics has anomaly. modelMonitoringJob: Model monitoring job resource name. schedule: Schedule resource name. thresholdValue: Threshold value. """ algorithm = _messages.StringField(1) baselineStats = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValue', 2) createTime = _messages.StringField(3) currentStats = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValue', 4) hasAnomaly = _messages.BooleanField(5) modelMonitoringJob = _messages.StringField(6) schedule = _messages.StringField(7) thresholdValue = _messages.FloatField(8) class GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValue(_messages.Message): r"""Typed value of the statistics. Fields: distributionValue: Distribution. doubleValue: Double. """ distributionValue = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValueDistributionDataValue', 1) doubleValue = _messages.FloatField(2) class GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPointTypedValueDistributionDataValue(_messages.Message): r"""Summary statistics for a population of values. Fields: distribution: Predictive monitoring drift distribution in `tensorflow.metadata.v0.DatasetFeatureStatistics` format. distributionDeviation: Distribution distance deviation from the current dataset's statistics to baseline dataset's statistics. * For categorical feature, the distribution distance is calculated by L-inifinity norm or Jensen\u2013Shannon divergence. * For numerical feature, the distribution distance is calculated by Jensen\u2013Shannon divergence. """ distribution = _messages.MessageField('extra_types.JsonValue', 1) distributionDeviation = _messages.FloatField(2) class GoogleCloudAiplatformV1beta1ModelMonitoringTabularStats(_messages.Message): r"""A collection of data points that describes the time-varying values of a tabular metric. Fields: dataPoints: The data points of this time series. When listing time series, points are returned in reverse time order. objectiveType: One of the supported monitoring objectives: `raw-feature- drift` `prediction-output-drift` `feature-attribution` statsName: The stats name. """ dataPoints = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringStatsDataPoint', 1, repeated=True) objectiveType = _messages.StringField(2) statsName = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ModelOriginalModelInfo(_messages.Message): r"""Contains information about the original Model if this Model is a copy. Fields: model: Output only. The resource name of the Model this Model is a copy of, including the revision. Format: `projects/{project}/locations/{location}/models/{model_id}@{version_id}` """ model = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ModelSourceInfo(_messages.Message): r"""Detail description of the source information of the model. Enums: SourceTypeValueValuesEnum: Type of the model source. Fields: copy: If this Model is copy of another Model. If true then source_type pertains to the original. sourceType: Type of the model source. """ class SourceTypeValueValuesEnum(_messages.Enum): r"""Type of the model source. Values: MODEL_SOURCE_TYPE_UNSPECIFIED: Should not be used. AUTOML: The Model is uploaded by automl training pipeline. CUSTOM: The Model is uploaded by user or custom training pipeline. BQML: The Model is registered and sync'ed from BigQuery ML. MODEL_GARDEN: The Model is saved or tuned from Model Garden. GENIE: The Model is saved or tuned from Genie. CUSTOM_TEXT_EMBEDDING: The Model is uploaded by text embedding finetuning pipeline. MARKETPLACE: The Model is saved or tuned from Marketplace. """ MODEL_SOURCE_TYPE_UNSPECIFIED = 0 AUTOML = 1 CUSTOM = 2 BQML = 3 MODEL_GARDEN = 4 GENIE = 5 CUSTOM_TEXT_EMBEDDING = 6 MARKETPLACE = 7 copy = _messages.BooleanField(1) sourceType = _messages.EnumField('SourceTypeValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1ModelVersionCheckpoint(_messages.Message): r"""Describes the machine learning model version checkpoint. Fields: checkpointId: The ID of the checkpoint. epoch: The epoch of the checkpoint. step: The step of the checkpoint. """ checkpointId = _messages.StringField(1) epoch = _messages.IntegerField(2) step = _messages.IntegerField(3) class GoogleCloudAiplatformV1beta1MultiSpeakerVoiceConfig(_messages.Message): r"""Configuration for a multi-speaker text-to-speech request. Fields: speakerVoiceConfigs: Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided. """ speakerVoiceConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1SpeakerVoiceConfig', 1, repeated=True) class GoogleCloudAiplatformV1beta1MutateDeployedIndexOperationMetadata(_messages.Message): r"""Runtime operation information for IndexEndpointService.MutateDeployedIndex. Fields: deployedIndexId: The unique index id specified by user genericMetadata: The operation generic information. """ deployedIndexId = _messages.StringField(1) genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 2) class GoogleCloudAiplatformV1beta1MutateDeployedIndexResponse(_messages.Message): r"""Response message for IndexEndpointService.MutateDeployedIndex. Fields: deployedIndex: The DeployedIndex that had been updated in the IndexEndpoint. """ deployedIndex = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedIndex', 1) class GoogleCloudAiplatformV1beta1MutateDeployedModelOperationMetadata(_messages.Message): r"""Runtime operation information for EndpointService.MutateDeployedModel. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1MutateDeployedModelRequest(_messages.Message): r"""Request message for EndpointService.MutateDeployedModel. Fields: deployedModel: Required. The DeployedModel to be mutated within the Endpoint. Only the following fields can be mutated: * `min_replica_count` in either DedicatedResources or AutomaticResources * `max_replica_count` in either DedicatedResources or AutomaticResources * `required_replica_count` in DedicatedResources * autoscaling_metric_specs * `disable_container_logging` (v1 only) * `enable_container_logging` (v1beta1 only) * `scale_to_zero_spec` in DedicatedResources (v1beta1 only) * `initial_replica_count` in DedicatedResources (v1beta1 only) updateMask: Required. The update mask applies to the resource. See google.protobuf.FieldMask. """ deployedModel = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedModel', 1) updateMask = _messages.StringField(2) class GoogleCloudAiplatformV1beta1MutateDeployedModelResponse(_messages.Message): r"""Response message for EndpointService.MutateDeployedModel. Fields: deployedModel: The DeployedModel that's being mutated. """ deployedModel = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedModel', 1) class GoogleCloudAiplatformV1beta1NasJob(_messages.Message): r"""Represents a Neural Architecture Search (NAS) job. Enums: StateValueValuesEnum: Output only. The detailed state of the job. Messages: LabelsValue: The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: createTime: Output only. Time when the NasJob was created. displayName: Required. The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. enableRestrictedImageTraining: Optional. Enable a separation of Custom model training and restricted image training for tenant project. encryptionSpec: Customer-managed encryption key options for a NasJob. If this is set, then all resources created by the NasJob will be encrypted with the provided encryption key. endTime: Output only. Time when the NasJob entered any of the following states: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`. error: Output only. Only populated when job's state is JOB_STATE_FAILED or JOB_STATE_CANCELLED. labels: The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. name: Output only. Resource name of the NasJob. nasJobOutput: Output only. Output of the NasJob. nasJobSpec: Required. The specification of a NasJob. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. startTime: Output only. Time when the NasJob for the first time entered the `JOB_STATE_RUNNING` state. state: Output only. The detailed state of the job. updateTime: Output only. Time when the NasJob was most recently updated. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of the job. Values: JOB_STATE_UNSPECIFIED: The job state is unspecified. JOB_STATE_QUEUED: The job has been just created or resumed and processing has not yet begun. JOB_STATE_PENDING: The service is preparing to run the job. JOB_STATE_RUNNING: The job is in progress. JOB_STATE_SUCCEEDED: The job completed successfully. JOB_STATE_FAILED: The job failed. JOB_STATE_CANCELLING: The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. JOB_STATE_CANCELLED: The job has been cancelled. JOB_STATE_PAUSED: The job has been stopped, and can be resumed. JOB_STATE_EXPIRED: The job has expired. JOB_STATE_UPDATING: The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state. JOB_STATE_PARTIALLY_SUCCEEDED: The job is partially succeeded, some results may be missing due to errors. """ JOB_STATE_UNSPECIFIED = 0 JOB_STATE_QUEUED = 1 JOB_STATE_PENDING = 2 JOB_STATE_RUNNING = 3 JOB_STATE_SUCCEEDED = 4 JOB_STATE_FAILED = 5 JOB_STATE_CANCELLING = 6 JOB_STATE_CANCELLED = 7 JOB_STATE_PAUSED = 8 JOB_STATE_EXPIRED = 9 JOB_STATE_UPDATING = 10 JOB_STATE_PARTIALLY_SUCCEEDED = 11 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize NasJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) displayName = _messages.StringField(2) enableRestrictedImageTraining = _messages.BooleanField(3) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 4) endTime = _messages.StringField(5) error = _messages.MessageField('GoogleRpcStatus', 6) labels = _messages.MessageField('LabelsValue', 7) name = _messages.StringField(8) nasJobOutput = _messages.MessageField('GoogleCloudAiplatformV1beta1NasJobOutput', 9) nasJobSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1NasJobSpec', 10) satisfiesPzi = _messages.BooleanField(11) satisfiesPzs = _messages.BooleanField(12) startTime = _messages.StringField(13) state = _messages.EnumField('StateValueValuesEnum', 14) updateTime = _messages.StringField(15) class GoogleCloudAiplatformV1beta1NasJobOutput(_messages.Message): r"""Represents a uCAIP NasJob output. Fields: multiTrialJobOutput: Output only. The output of this multi-trial Neural Architecture Search (NAS) job. """ multiTrialJobOutput = _messages.MessageField('GoogleCloudAiplatformV1beta1NasJobOutputMultiTrialJobOutput', 1) class GoogleCloudAiplatformV1beta1NasJobOutputMultiTrialJobOutput(_messages.Message): r"""The output of a multi-trial Neural Architecture Search (NAS) jobs. Fields: searchTrials: Output only. List of NasTrials that were started as part of search stage. trainTrials: Output only. List of NasTrials that were started as part of train stage. """ searchTrials = _messages.MessageField('GoogleCloudAiplatformV1beta1NasTrial', 1, repeated=True) trainTrials = _messages.MessageField('GoogleCloudAiplatformV1beta1NasTrial', 2, repeated=True) class GoogleCloudAiplatformV1beta1NasJobSpec(_messages.Message): r"""Represents the spec of a NasJob. Fields: enableNasControllerMigration: Indicate if nas should launch controller migrated pipeline. This flag is for internal testing only, and will be removed once the migration is completed. multiTrialAlgorithmSpec: The spec of multi-trial algorithms. resumeNasJobId: The ID of the existing NasJob in the same Project and Location which will be used to resume search. search_space_spec and nas_algorithm_spec are obtained from previous NasJob hence should not provide them again for this NasJob. searchSpaceSpec: It defines the search space for Neural Architecture Search (NAS). """ enableNasControllerMigration = _messages.BooleanField(1) multiTrialAlgorithmSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpec', 2) resumeNasJobId = _messages.StringField(3) searchSpaceSpec = _messages.StringField(4) class GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpec(_messages.Message): r"""The spec of multi-trial Neural Architecture Search (NAS). Enums: MultiTrialAlgorithmValueValuesEnum: The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`. Fields: metric: Metric specs for the NAS job. Validation for this field is done at `multi_trial_algorithm_spec` field. multiTrialAlgorithm: The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`. searchTrialSpec: Required. Spec for search trials. trainTrialSpec: Spec for train trials. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched. """ class MultiTrialAlgorithmValueValuesEnum(_messages.Enum): r"""The multi-trial Neural Architecture Search (NAS) algorithm type. Defaults to `REINFORCEMENT_LEARNING`. Values: MULTI_TRIAL_ALGORITHM_UNSPECIFIED: Defaults to `REINFORCEMENT_LEARNING`. REINFORCEMENT_LEARNING: The Reinforcement Learning Algorithm for Multi- trial Neural Architecture Search (NAS). GRID_SEARCH: The Grid Search Algorithm for Multi-trial Neural Architecture Search (NAS). """ MULTI_TRIAL_ALGORITHM_UNSPECIFIED = 0 REINFORCEMENT_LEARNING = 1 GRID_SEARCH = 2 metric = _messages.MessageField('GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecMetricSpec', 1) multiTrialAlgorithm = _messages.EnumField('MultiTrialAlgorithmValueValuesEnum', 2) searchTrialSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec', 3) trainTrialSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec', 4) class GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecMetricSpec(_messages.Message): r"""Represents a metric to optimize. Enums: GoalValueValuesEnum: Required. The optimization goal of the metric. Fields: goal: Required. The optimization goal of the metric. metricId: Required. The ID of the metric. Must not contain whitespaces. """ class GoalValueValuesEnum(_messages.Enum): r"""Required. The optimization goal of the metric. Values: GOAL_TYPE_UNSPECIFIED: Goal Type will default to maximize. MAXIMIZE: Maximize the goal metric. MINIMIZE: Minimize the goal metric. """ GOAL_TYPE_UNSPECIFIED = 0 MAXIMIZE = 1 MINIMIZE = 2 goal = _messages.EnumField('GoalValueValuesEnum', 1) metricId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecSearchTrialSpec(_messages.Message): r"""Represent spec for search trials. Fields: maxFailedTrialCount: The number of failed trials that need to be seen before failing the NasJob. If set to 0, Vertex AI decides how many trials must fail before the whole job fails. maxParallelTrialCount: Required. The maximum number of trials to run in parallel. maxTrialCount: Required. The maximum number of Neural Architecture Search (NAS) trials to run. searchTrialJobSpec: Required. The spec of a search trial job. The same spec applies to all search trials. """ maxFailedTrialCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) maxParallelTrialCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) maxTrialCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) searchTrialJobSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomJobSpec', 4) class GoogleCloudAiplatformV1beta1NasJobSpecMultiTrialAlgorithmSpecTrainTrialSpec(_messages.Message): r"""Represent spec for train trials. Fields: frequency: Required. Frequency of search trials to start train stage. Top N [TrainTrialSpec.max_parallel_trial_count] search trials will be trained for every M [TrainTrialSpec.frequency] trials searched. maxParallelTrialCount: Required. The maximum number of trials to run in parallel. trainTrialJobSpec: Required. The spec of a train trial job. The same spec applies to all train trials. """ frequency = _messages.IntegerField(1, variant=_messages.Variant.INT32) maxParallelTrialCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) trainTrialJobSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomJobSpec', 3) class GoogleCloudAiplatformV1beta1NasTrial(_messages.Message): r"""Represents a uCAIP NasJob trial. Enums: StateValueValuesEnum: Output only. The detailed state of the NasTrial. Fields: endTime: Output only. Time when the NasTrial's status changed to `SUCCEEDED` or `INFEASIBLE`. finalMeasurement: Output only. The final measurement containing the objective value. id: Output only. The identifier of the NasTrial assigned by the service. startTime: Output only. Time when the NasTrial was started. state: Output only. The detailed state of the NasTrial. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of the NasTrial. Values: STATE_UNSPECIFIED: The NasTrial state is unspecified. REQUESTED: Indicates that a specific NasTrial has been requested, but it has not yet been suggested by the service. ACTIVE: Indicates that the NasTrial has been suggested. STOPPING: Indicates that the NasTrial should stop according to the service. SUCCEEDED: Indicates that the NasTrial is completed successfully. INFEASIBLE: Indicates that the NasTrial should not be attempted again. The service will set a NasTrial to INFEASIBLE when it's done but missing the final_measurement. """ STATE_UNSPECIFIED = 0 REQUESTED = 1 ACTIVE = 2 STOPPING = 3 SUCCEEDED = 4 INFEASIBLE = 5 endTime = _messages.StringField(1) finalMeasurement = _messages.MessageField('GoogleCloudAiplatformV1beta1Measurement', 2) id = _messages.StringField(3) startTime = _messages.StringField(4) state = _messages.EnumField('StateValueValuesEnum', 5) class GoogleCloudAiplatformV1beta1NasTrialDetail(_messages.Message): r"""Represents a NasTrial details along with its parameters. If there is a corresponding train NasTrial, the train NasTrial is also returned. Fields: name: Output only. Resource name of the NasTrialDetail. parameters: The parameters for the NasJob NasTrial. searchTrial: The requested search NasTrial. trainTrial: The train NasTrial corresponding to search_trial. Only populated if search_trial is used for training. """ name = _messages.StringField(1) parameters = _messages.StringField(2) searchTrial = _messages.MessageField('GoogleCloudAiplatformV1beta1NasTrial', 3) trainTrial = _messages.MessageField('GoogleCloudAiplatformV1beta1NasTrial', 4) class GoogleCloudAiplatformV1beta1NearestNeighborQuery(_messages.Message): r"""A query to find a number of similar entities. Fields: embedding: Optional. The embedding vector that be used for similar search. entityId: Optional. The entity id whose similar entities should be searched for. If embedding is set, search will use embedding instead of entity_id. neighborCount: Optional. The number of similar entities to be retrieved from feature view for each query. numericFilters: Optional. The list of numeric filters. parameters: Optional. Parameters that can be set to tune query on the fly. perCrowdingAttributeNeighborCount: Optional. Crowding is a constraint on a neighbor list produced by nearest neighbor search requiring that no more than sper_crowding_attribute_neighbor_count of the k neighbors returned have the same value of crowding_attribute. It's used for improving result diversity. stringFilters: Optional. The list of string filters. """ embedding = _messages.MessageField('GoogleCloudAiplatformV1beta1NearestNeighborQueryEmbedding', 1) entityId = _messages.StringField(2) neighborCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) numericFilters = _messages.MessageField('GoogleCloudAiplatformV1beta1NearestNeighborQueryNumericFilter', 4, repeated=True) parameters = _messages.MessageField('GoogleCloudAiplatformV1beta1NearestNeighborQueryParameters', 5) perCrowdingAttributeNeighborCount = _messages.IntegerField(6, variant=_messages.Variant.INT32) stringFilters = _messages.MessageField('GoogleCloudAiplatformV1beta1NearestNeighborQueryStringFilter', 7, repeated=True) class GoogleCloudAiplatformV1beta1NearestNeighborQueryEmbedding(_messages.Message): r"""The embedding vector. Fields: value: Optional. Individual value in the embedding. """ value = _messages.FloatField(1, repeated=True, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1NearestNeighborQueryNumericFilter(_messages.Message): r"""Numeric filter is used to search a subset of the entities by using boolean rules on numeric columns. For example: Database Point 0: {name: "a" value_int: 42} {name: "b" value_float: 1.0} Database Point 1: {name: "a" value_int: 10} {name: "b" value_float: 2.0} Database Point 2: {name: "a" value_int: -1} {name: "b" value_float: 3.0} Query: {name: "a" value_int: 12 operator: LESS} // Matches Point 1, 2 {name: "b" value_float: 2.0 operator: EQUAL} // Matches Point 1 Enums: OpValueValuesEnum: Optional. This MUST be specified for queries and must NOT be specified for database points. Fields: name: Required. Column name in BigQuery that used as filters. op: Optional. This MUST be specified for queries and must NOT be specified for database points. valueDouble: double value type. valueFloat: float value type. valueInt: int value type. """ class OpValueValuesEnum(_messages.Enum): r"""Optional. This MUST be specified for queries and must NOT be specified for database points. Values: OPERATOR_UNSPECIFIED: Unspecified operator. LESS: Entities are eligible if their value is < the query's. LESS_EQUAL: Entities are eligible if their value is <= the query's. EQUAL: Entities are eligible if their value is == the query's. GREATER_EQUAL: Entities are eligible if their value is >= the query's. GREATER: Entities are eligible if their value is > the query's. NOT_EQUAL: Entities are eligible if their value is != the query's. """ OPERATOR_UNSPECIFIED = 0 LESS = 1 LESS_EQUAL = 2 EQUAL = 3 GREATER_EQUAL = 4 GREATER = 5 NOT_EQUAL = 6 name = _messages.StringField(1) op = _messages.EnumField('OpValueValuesEnum', 2) valueDouble = _messages.FloatField(3) valueFloat = _messages.FloatField(4, variant=_messages.Variant.FLOAT) valueInt = _messages.IntegerField(5) class GoogleCloudAiplatformV1beta1NearestNeighborQueryParameters(_messages.Message): r"""Parameters that can be overrided in each query to tune query latency and recall. Fields: approximateNeighborCandidates: Optional. The number of neighbors to find via approximate search before exact reordering is performed; if set, this value must be > neighbor_count. leafNodesSearchFraction: Optional. The fraction of the number of leaves to search, set at query time allows user to tune search performance. This value increase result in both search accuracy and latency increase. The value should be between 0.0 and 1.0. """ approximateNeighborCandidates = _messages.IntegerField(1, variant=_messages.Variant.INT32) leafNodesSearchFraction = _messages.FloatField(2) class GoogleCloudAiplatformV1beta1NearestNeighborQueryStringFilter(_messages.Message): r"""String filter is used to search a subset of the entities by using boolean rules on string columns. For example: if a query specifies string filter with 'name = color, allow_tokens = {red, blue}, deny_tokens = {purple}',' then that query will match entities that are red or blue, but if those points are also purple, then they will be excluded even if they are red/blue. Only string filter is supported for now, numeric filter will be supported in the near future. Fields: allowTokens: Optional. The allowed tokens. denyTokens: Optional. The denied tokens. name: Required. Column names in BigQuery that used as filters. """ allowTokens = _messages.StringField(1, repeated=True) denyTokens = _messages.StringField(2, repeated=True) name = _messages.StringField(3) class GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadata(_messages.Message): r"""Runtime operation metadata with regard to Matching Engine Index. Fields: contentValidationStats: The validation stats of the content (per file) to be inserted or updated on the Matching Engine Index resource. Populated if contentsDeltaUri is provided as part of Index.metadata. Please note that, currently for those files that are broken or has unsupported file format, we will not have the stats for those files. dataBytesCount: The ingested data size in bytes. """ contentValidationStats = _messages.MessageField('GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataContentValidationStats', 1, repeated=True) dataBytesCount = _messages.IntegerField(2) class GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataContentValidationStats(_messages.Message): r"""A GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataCont entValidationStats object. Fields: invalidRecordCount: Number of records in this file we skipped due to validate errors. invalidSparseRecordCount: Number of sparse records in this file we skipped due to validate errors. partialErrors: The detail information of the partial failures encountered for those invalid records that couldn't be parsed. Up to 50 partial errors will be reported. sourceGcsUri: Cloud Storage URI pointing to the original file in user's bucket. validRecordCount: Number of records in this file that were successfully processed. validSparseRecordCount: Number of sparse records in this file that were successfully processed. """ invalidRecordCount = _messages.IntegerField(1) invalidSparseRecordCount = _messages.IntegerField(2) partialErrors = _messages.MessageField('GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataRecordError', 3, repeated=True) sourceGcsUri = _messages.StringField(4) validRecordCount = _messages.IntegerField(5) validSparseRecordCount = _messages.IntegerField(6) class GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataRecordError(_messages.Message): r"""A GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadataReco rdError object. Enums: ErrorTypeValueValuesEnum: The error type of this record. Fields: embeddingId: Empty if the embedding id is failed to parse. errorMessage: A human-readable message that is shown to the user to help them fix the error. Note that this message may change from time to time, your code should check against error_type as the source of truth. errorType: The error type of this record. rawRecord: The original content of this record. sourceGcsUri: Cloud Storage URI pointing to the original file in user's bucket. """ class ErrorTypeValueValuesEnum(_messages.Enum): r"""The error type of this record. Values: ERROR_TYPE_UNSPECIFIED: Default, shall not be used. EMPTY_LINE: The record is empty. INVALID_JSON_SYNTAX: Invalid json format. INVALID_CSV_SYNTAX: Invalid csv format. INVALID_AVRO_SYNTAX: Invalid avro format. INVALID_EMBEDDING_ID: The embedding id is not valid. EMBEDDING_SIZE_MISMATCH: The size of the dense embedding vectors does not match with the specified dimension. NAMESPACE_MISSING: The `namespace` field is missing. PARSING_ERROR: Generic catch-all error. Only used for validation failure where the root cause cannot be easily retrieved programmatically. DUPLICATE_NAMESPACE: There are multiple restricts with the same `namespace` value. OP_IN_DATAPOINT: Numeric restrict has operator specified in datapoint. MULTIPLE_VALUES: Numeric restrict has multiple values specified. INVALID_NUMERIC_VALUE: Numeric restrict has invalid numeric value specified. INVALID_ENCODING: File is not in UTF_8 format. INVALID_SPARSE_DIMENSIONS: Error parsing sparse dimensions field. INVALID_TOKEN_VALUE: Token restrict value is invalid. INVALID_SPARSE_EMBEDDING: Invalid sparse embedding. INVALID_EMBEDDING: Invalid dense embedding. INVALID_EMBEDDING_METADATA: Invalid embedding metadata. EMBEDDING_METADATA_EXCEEDS_SIZE_LIMIT: Embedding metadata exceeds size limit. """ ERROR_TYPE_UNSPECIFIED = 0 EMPTY_LINE = 1 INVALID_JSON_SYNTAX = 2 INVALID_CSV_SYNTAX = 3 INVALID_AVRO_SYNTAX = 4 INVALID_EMBEDDING_ID = 5 EMBEDDING_SIZE_MISMATCH = 6 NAMESPACE_MISSING = 7 PARSING_ERROR = 8 DUPLICATE_NAMESPACE = 9 OP_IN_DATAPOINT = 10 MULTIPLE_VALUES = 11 INVALID_NUMERIC_VALUE = 12 INVALID_ENCODING = 13 INVALID_SPARSE_DIMENSIONS = 14 INVALID_TOKEN_VALUE = 15 INVALID_SPARSE_EMBEDDING = 16 INVALID_EMBEDDING = 17 INVALID_EMBEDDING_METADATA = 18 EMBEDDING_METADATA_EXCEEDS_SIZE_LIMIT = 19 embeddingId = _messages.StringField(1) errorMessage = _messages.StringField(2) errorType = _messages.EnumField('ErrorTypeValueValuesEnum', 3) rawRecord = _messages.StringField(4) sourceGcsUri = _messages.StringField(5) class GoogleCloudAiplatformV1beta1NearestNeighbors(_messages.Message): r"""Nearest neighbors for one query. Fields: neighbors: All its neighbors. """ neighbors = _messages.MessageField('GoogleCloudAiplatformV1beta1NearestNeighborsNeighbor', 1, repeated=True) class GoogleCloudAiplatformV1beta1NearestNeighborsNeighbor(_messages.Message): r"""A neighbor of the query vector. Fields: distance: The distance between the neighbor and the query vector. entityId: The id of the similar entity. entityKeyValues: The attributes of the neighbor, e.g. filters, crowding and metadata Note that full entities are returned only when "return_full_entity" is set to true. Otherwise, only the "entity_id" and "distance" fields are populated. """ distance = _messages.FloatField(1) entityId = _messages.StringField(2) entityKeyValues = _messages.MessageField('GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse', 3) class GoogleCloudAiplatformV1beta1Neighbor(_messages.Message): r"""Neighbors for example-based explanations. Fields: neighborDistance: Output only. The neighbor distance. neighborId: Output only. The neighbor id. """ neighborDistance = _messages.FloatField(1) neighborId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1NetworkSpec(_messages.Message): r"""Network spec. Fields: enableInternetAccess: Whether to enable public internet access. Default false. network: The full name of the Google Compute Engine [network](https://cloud.google.com//compute/docs/networks-and- firewalls#networks) subnetwork: The name of the subnet that this instance is in. Format: `proj ects/{project_id_or_number}/regions/{region}/subnetworks/{subnetwork_id} ` """ enableInternetAccess = _messages.BooleanField(1) network = _messages.StringField(2) subnetwork = _messages.StringField(3) class GoogleCloudAiplatformV1beta1NfsMount(_messages.Message): r"""Represents a mount configuration for Network File System (NFS) to mount. Fields: mountPoint: Required. Destination mount path. The NFS will be mounted for the user under /mnt/nfs/ path: Required. Source path exported from NFS server. Has to start with '/', and combined with the ip address, it indicates the source mount path in the form of `server:path` server: Required. IP address of the NFS server. """ mountPoint = _messages.StringField(1) path = _messages.StringField(2) server = _messages.StringField(3) class GoogleCloudAiplatformV1beta1NotebookEucConfig(_messages.Message): r"""The euc configuration of NotebookRuntimeTemplate. Fields: bypassActasCheck: Output only. Whether ActAs check is bypassed for service account attached to the VM. If false, we need ActAs check for the default Compute Engine Service account. When a Runtime is created, a VM is allocated using Default Compute Engine Service Account. Any user requesting to use this Runtime requires Service Account User (ActAs) permission over this SA. If true, Runtime owner is using EUC and does not require the above permission as VM no longer use default Compute Engine SA, but a P4SA. eucDisabled: Input only. Whether EUC is disabled in this NotebookRuntimeTemplate. In proto3, the default value of a boolean is false. In this way, by default EUC will be enabled for NotebookRuntimeTemplate. """ bypassActasCheck = _messages.BooleanField(1) eucDisabled = _messages.BooleanField(2) class GoogleCloudAiplatformV1beta1NotebookExecutionJob(_messages.Message): r"""NotebookExecutionJob represents an instance of a notebook execution. Enums: JobStateValueValuesEnum: Output only. The state of the NotebookExecutionJob. Messages: LabelsValue: The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: createTime: Output only. Timestamp when this NotebookExecutionJob was created. customEnvironmentSpec: The custom compute configuration for an execution job. dataformRepositorySource: The Dataform Repository pointing to a single file notebook repository. directNotebookSource: The contents of an input notebook file. displayName: The display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters. encryptionSpec: Customer-managed encryption key spec for the notebook execution job. This field is auto-populated if the NotebookRuntimeTemplate has an encryption spec. executionTimeout: Max running time of the execution job in seconds (default 86400s / 24 hrs). executionUser: The user email to run the execution as. Only supported by Colab runtimes. gcsNotebookSource: The Cloud Storage url pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb` gcsOutputUri: The Cloud Storage location to upload the result to. Format: `gs://bucket-name` jobState: Output only. The state of the NotebookExecutionJob. kernelName: The name of the kernel to use during notebook execution. If unset, the default kernel is used. labels: The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. name: Output only. The resource name of this NotebookExecutionJob. Format: `projects/{project_id}/locations/{location}/notebookExecutionJobs/{job_i d}` notebookRuntimeTemplateResourceName: The NotebookRuntimeTemplate to source compute configuration from. scheduleResourceName: The Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}` serviceAccount: The service account to run the execution as. status: Output only. Populated when the NotebookExecutionJob is completed. When there is an error during notebook execution, the error details are populated. updateTime: Output only. Timestamp when this NotebookExecutionJob was most recently updated. workbenchRuntime: The Workbench runtime configuration to use for the notebook execution. """ class JobStateValueValuesEnum(_messages.Enum): r"""Output only. The state of the NotebookExecutionJob. Values: JOB_STATE_UNSPECIFIED: The job state is unspecified. JOB_STATE_QUEUED: The job has been just created or resumed and processing has not yet begun. JOB_STATE_PENDING: The service is preparing to run the job. JOB_STATE_RUNNING: The job is in progress. JOB_STATE_SUCCEEDED: The job completed successfully. JOB_STATE_FAILED: The job failed. JOB_STATE_CANCELLING: The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. JOB_STATE_CANCELLED: The job has been cancelled. JOB_STATE_PAUSED: The job has been stopped, and can be resumed. JOB_STATE_EXPIRED: The job has expired. JOB_STATE_UPDATING: The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state. JOB_STATE_PARTIALLY_SUCCEEDED: The job is partially succeeded, some results may be missing due to errors. """ JOB_STATE_UNSPECIFIED = 0 JOB_STATE_QUEUED = 1 JOB_STATE_PENDING = 2 JOB_STATE_RUNNING = 3 JOB_STATE_SUCCEEDED = 4 JOB_STATE_FAILED = 5 JOB_STATE_CANCELLING = 6 JOB_STATE_CANCELLED = 7 JOB_STATE_PAUSED = 8 JOB_STATE_EXPIRED = 9 JOB_STATE_UPDATING = 10 JOB_STATE_PARTIALLY_SUCCEEDED = 11 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize NotebookExecutionJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) customEnvironmentSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookExecutionJobCustomEnvironmentSpec', 2) dataformRepositorySource = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookExecutionJobDataformRepositorySource', 3) directNotebookSource = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookExecutionJobDirectNotebookSource', 4) displayName = _messages.StringField(5) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 6) executionTimeout = _messages.StringField(7) executionUser = _messages.StringField(8) gcsNotebookSource = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookExecutionJobGcsNotebookSource', 9) gcsOutputUri = _messages.StringField(10) jobState = _messages.EnumField('JobStateValueValuesEnum', 11) kernelName = _messages.StringField(12) labels = _messages.MessageField('LabelsValue', 13) name = _messages.StringField(14) notebookRuntimeTemplateResourceName = _messages.StringField(15) scheduleResourceName = _messages.StringField(16) serviceAccount = _messages.StringField(17) status = _messages.MessageField('GoogleRpcStatus', 18) updateTime = _messages.StringField(19) workbenchRuntime = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookExecutionJobWorkbenchRuntime', 20) class GoogleCloudAiplatformV1beta1NotebookExecutionJobCustomEnvironmentSpec(_messages.Message): r"""Compute configuration to use for an execution job. Fields: machineSpec: The specification of a single machine for the execution job. networkSpec: The network configuration to use for the execution job. persistentDiskSpec: The specification of a persistent disk to attach for the execution job. """ machineSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1MachineSpec', 1) networkSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1NetworkSpec', 2) persistentDiskSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PersistentDiskSpec', 3) class GoogleCloudAiplatformV1beta1NotebookExecutionJobDataformRepositorySource(_messages.Message): r"""The Dataform Repository containing the input notebook. Fields: commitSha: The commit SHA to read repository with. If unset, the file will be read at HEAD. dataformRepositoryResourceName: The resource name of the Dataform Repository. Format: `projects/{project_id}/locations/{location}/reposito ries/{repository_id}` """ commitSha = _messages.StringField(1) dataformRepositoryResourceName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1NotebookExecutionJobDirectNotebookSource(_messages.Message): r"""The content of the input notebook in ipynb format. Fields: content: The base64-encoded contents of the input notebook file. """ content = _messages.BytesField(1) class GoogleCloudAiplatformV1beta1NotebookExecutionJobGcsNotebookSource(_messages.Message): r"""The Cloud Storage uri for the input notebook. Fields: generation: The version of the Cloud Storage object to read. If unset, the current version of the object is read. See https://cloud.google.com/storage/docs/metadata#generation-number. uri: The Cloud Storage uri pointing to the ipynb file. Format: `gs://bucket/notebook_file.ipynb` """ generation = _messages.StringField(1) uri = _messages.StringField(2) class GoogleCloudAiplatformV1beta1NotebookExecutionJobWorkbenchRuntime(_messages.Message): r"""Configuration for a Workbench Instances-based environment.""" class GoogleCloudAiplatformV1beta1NotebookIdleShutdownConfig(_messages.Message): r"""The idle shutdown configuration of NotebookRuntimeTemplate, which contains the idle_timeout as required field. Fields: idleShutdownDisabled: Whether Idle Shutdown is disabled in this NotebookRuntimeTemplate. idleTimeout: Required. Duration is accurate to the second. In Notebook, Idle Timeout is accurate to minute so the range of idle_timeout (second) is: 10 * 60 ~ 1440 * 60. """ idleShutdownDisabled = _messages.BooleanField(1) idleTimeout = _messages.StringField(2) class GoogleCloudAiplatformV1beta1NotebookReservationAffinity(_messages.Message): r"""Notebook Reservation Affinity for consuming Zonal reservation. Enums: ConsumeReservationTypeValueValuesEnum: Required. Specifies the type of reservation from which this instance can consume resources: RESERVATION_ANY (default), RESERVATION_SPECIFIC, or RESERVATION_NONE. See Consuming reserved instances for examples. Fields: consumeReservationType: Required. Specifies the type of reservation from which this instance can consume resources: RESERVATION_ANY (default), RESERVATION_SPECIFIC, or RESERVATION_NONE. See Consuming reserved instances for examples. key: Optional. Corresponds to the label key of a reservation resource. To target a RESERVATION_SPECIFIC by name, use compute.googleapis.com/reservation-name as the key and specify the name of your reservation as its value. values: Optional. Corresponds to the label values of a reservation resource. This must be the full path name of Reservation. """ class ConsumeReservationTypeValueValuesEnum(_messages.Enum): r"""Required. Specifies the type of reservation from which this instance can consume resources: RESERVATION_ANY (default), RESERVATION_SPECIFIC, or RESERVATION_NONE. See Consuming reserved instances for examples. Values: RESERVATION_AFFINITY_TYPE_UNSPECIFIED: Default type. RESERVATION_NONE: Do not consume from any allocated capacity. RESERVATION_ANY: Consume any reservation available. RESERVATION_SPECIFIC: Must consume from a specific reservation. Must specify key value fields for specifying the reservations. """ RESERVATION_AFFINITY_TYPE_UNSPECIFIED = 0 RESERVATION_NONE = 1 RESERVATION_ANY = 2 RESERVATION_SPECIFIC = 3 consumeReservationType = _messages.EnumField('ConsumeReservationTypeValueValuesEnum', 1) key = _messages.StringField(2) values = _messages.StringField(3, repeated=True) class GoogleCloudAiplatformV1beta1NotebookRuntime(_messages.Message): r"""A runtime is a virtual machine allocated to a particular user for a particular Notebook file on temporary basis with lifetime. Default runtimes have a lifetime of 18 hours, while custom runtimes last for 6 months from their creation or last upgrade. Enums: HealthStateValueValuesEnum: Output only. The health state of the NotebookRuntime. NotebookRuntimeTypeValueValuesEnum: Output only. The type of the notebook runtime. RuntimeStateValueValuesEnum: Output only. The runtime (instance) state of the NotebookRuntime. Messages: LabelsValue: The labels with user-defined metadata to organize your NotebookRuntime. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one NotebookRuntime (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for NotebookRuntime: * "aiplatform.googleapis.com/notebook_runtime_gce_instance_id": output only, its value is the Compute Engine instance id. * "aiplatform.googleapis.com/colab_enterprise_entry_service": its value is either "bigquery" or "vertex"; if absent, it should be "vertex". This is to describe the entry service, either BigQuery or Vertex. Fields: createTime: Output only. Timestamp when this NotebookRuntime was created. dataPersistentDiskSpec: Output only. The specification of persistent disk attached to the notebook runtime as data disk storage. description: The description of the NotebookRuntime. displayName: Required. The display name of the NotebookRuntime. The name can be up to 128 characters long and can consist of any UTF-8 characters. encryptionSpec: Output only. Customer-managed encryption key spec for the notebook runtime. eucConfig: Output only. EUC configuration of the notebook runtime. expirationTime: Output only. Timestamp when this NotebookRuntime will be expired: 1. System Predefined NotebookRuntime: 24 hours after creation. After expiration, system predifined runtime will be deleted. 2. User created NotebookRuntime: 6 months after last upgrade. After expiration, user created runtime will be stopped and allowed for upgrade. healthState: Output only. The health state of the NotebookRuntime. idleShutdownConfig: Output only. The idle shutdown configuration of the notebook runtime. isUpgradable: Output only. Whether NotebookRuntime is upgradable. labels: The labels with user-defined metadata to organize your NotebookRuntime. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one NotebookRuntime (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for NotebookRuntime: * "aiplatform.googleapis.com/notebook_runtime_gce_instance_id": output only, its value is the Compute Engine instance id. * "aiplatform.googleapis.com/colab_enterprise_entry_service": its value is either "bigquery" or "vertex"; if absent, it should be "vertex". This is to describe the entry service, either BigQuery or Vertex. machineSpec: Output only. The specification of a single machine used by the notebook runtime. name: Output only. The resource name of the NotebookRuntime. networkSpec: Output only. Network spec of the notebook runtime. networkTags: Optional. The Compute Engine tags to add to runtime (see [Tagging instances](https://cloud.google.com/vpc/docs/add-remove- network-tags)). notebookRuntimeTemplateRef: Output only. The pointer to NotebookRuntimeTemplate this NotebookRuntime is created from. notebookRuntimeType: Output only. The type of the notebook runtime. proxyUri: Output only. The proxy endpoint used to access the NotebookRuntime. reservationAffinity: Output only. Reservation Affinity of the notebook runtime. runtimeState: Output only. The runtime (instance) state of the NotebookRuntime. runtimeUser: Required. The user email of the NotebookRuntime. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. serviceAccount: Output only. Deprecated: This field is no longer used and the "Vertex AI Notebook Service Account" (service-PROJECT_NUMBER@gcp-sa- aiplatform-vm.iam.gserviceaccount.com) is used for the runtime workload identity. See https://cloud.google.com/iam/docs/service-agents#vertex- ai-notebook-service-account for more details. The service account that the NotebookRuntime workload runs as. shieldedVmConfig: Output only. Runtime Shielded VM spec. softwareConfig: Output only. Software config of the notebook runtime. updateTime: Output only. Timestamp when this NotebookRuntime was most recently updated. version: Output only. The VM os image version of NotebookRuntime. """ class HealthStateValueValuesEnum(_messages.Enum): r"""Output only. The health state of the NotebookRuntime. Values: HEALTH_STATE_UNSPECIFIED: Unspecified health state. HEALTHY: NotebookRuntime is in healthy state. Applies to ACTIVE state. UNHEALTHY: NotebookRuntime is in unhealthy state. Applies to ACTIVE state. """ HEALTH_STATE_UNSPECIFIED = 0 HEALTHY = 1 UNHEALTHY = 2 class NotebookRuntimeTypeValueValuesEnum(_messages.Enum): r"""Output only. The type of the notebook runtime. Values: NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED: Unspecified notebook runtime type, NotebookRuntimeType will default to USER_DEFINED. USER_DEFINED: runtime or template with coustomized configurations from user. ONE_CLICK: runtime or template with system defined configurations. """ NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED = 0 USER_DEFINED = 1 ONE_CLICK = 2 class RuntimeStateValueValuesEnum(_messages.Enum): r"""Output only. The runtime (instance) state of the NotebookRuntime. Values: RUNTIME_STATE_UNSPECIFIED: Unspecified runtime state. RUNNING: NotebookRuntime is in running state. BEING_STARTED: NotebookRuntime is in starting state. This is when the runtime is being started from a stopped state. BEING_STOPPED: NotebookRuntime is in stopping state. STOPPED: NotebookRuntime is in stopped state. BEING_UPGRADED: NotebookRuntime is in upgrading state. It is in the middle of upgrading process. ERROR: NotebookRuntime was unable to start/stop properly. INVALID: NotebookRuntime is in invalid state. Cannot be recovered. """ RUNTIME_STATE_UNSPECIFIED = 0 RUNNING = 1 BEING_STARTED = 2 BEING_STOPPED = 3 STOPPED = 4 BEING_UPGRADED = 5 ERROR = 6 INVALID = 7 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your NotebookRuntime. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one NotebookRuntime (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Following system labels exist for NotebookRuntime: * "aiplatform.googleapis.com/notebook_runtime_gce_instance_id": output only, its value is the Compute Engine instance id. * "aiplatform.googleapis.com/colab_enterprise_entry_service": its value is either "bigquery" or "vertex"; if absent, it should be "vertex". This is to describe the entry service, either BigQuery or Vertex. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) dataPersistentDiskSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PersistentDiskSpec', 2) description = _messages.StringField(3) displayName = _messages.StringField(4) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 5) eucConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookEucConfig', 6) expirationTime = _messages.StringField(7) healthState = _messages.EnumField('HealthStateValueValuesEnum', 8) idleShutdownConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookIdleShutdownConfig', 9) isUpgradable = _messages.BooleanField(10) labels = _messages.MessageField('LabelsValue', 11) machineSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1MachineSpec', 12) name = _messages.StringField(13) networkSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1NetworkSpec', 14) networkTags = _messages.StringField(15, repeated=True) notebookRuntimeTemplateRef = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookRuntimeTemplateRef', 16) notebookRuntimeType = _messages.EnumField('NotebookRuntimeTypeValueValuesEnum', 17) proxyUri = _messages.StringField(18) reservationAffinity = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookReservationAffinity', 19) runtimeState = _messages.EnumField('RuntimeStateValueValuesEnum', 20) runtimeUser = _messages.StringField(21) satisfiesPzi = _messages.BooleanField(22) satisfiesPzs = _messages.BooleanField(23) serviceAccount = _messages.StringField(24) shieldedVmConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ShieldedVmConfig', 25) softwareConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookSoftwareConfig', 26) updateTime = _messages.StringField(27) version = _messages.StringField(28) class GoogleCloudAiplatformV1beta1NotebookRuntimeTemplate(_messages.Message): r"""A template that specifies runtime configurations such as machine type, runtime version, network configurations, etc. Multiple runtimes can be created from a runtime template. Enums: NotebookRuntimeTypeValueValuesEnum: Optional. Immutable. The type of the notebook runtime template. Messages: LabelsValue: The labels with user-defined metadata to organize the NotebookRuntimeTemplates. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: createTime: Output only. Timestamp when this NotebookRuntimeTemplate was created. dataPersistentDiskSpec: Optional. The specification of persistent disk attached to the runtime as data disk storage. description: The description of the NotebookRuntimeTemplate. displayName: Required. The display name of the NotebookRuntimeTemplate. The name can be up to 128 characters long and can consist of any UTF-8 characters. encryptionSpec: Customer-managed encryption key spec for the notebook runtime. etag: Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. eucConfig: EUC configuration of the NotebookRuntimeTemplate. idleShutdownConfig: The idle shutdown configuration of NotebookRuntimeTemplate. This config will only be set when idle shutdown is enabled. isDefault: Output only. Deprecated: This field has no behavior. Use notebook_runtime_type = 'ONE_CLICK' instead. The default template to use if not specified. labels: The labels with user-defined metadata to organize the NotebookRuntimeTemplates. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. machineSpec: Optional. Immutable. The specification of a single machine for the template. name: The resource name of the NotebookRuntimeTemplate. networkSpec: Optional. Network spec. networkTags: Optional. The Compute Engine tags to add to runtime (see [Tagging instances](https://cloud.google.com/vpc/docs/add-remove- network-tags)). notebookRuntimeType: Optional. Immutable. The type of the notebook runtime template. reservationAffinity: Optional. Reservation Affinity of the notebook runtime template. serviceAccount: Deprecated: This field is ignored and the "Vertex AI Notebook Service Account" (service-PROJECT_NUMBER@gcp-sa-aiplatform- vm.iam.gserviceaccount.com) is used for the runtime workload identity. See https://cloud.google.com/iam/docs/service-agents#vertex-ai-notebook- service-account for more details. For NotebookExecutionJob, use NotebookExecutionJob.service_account instead. The service account that the runtime workload runs as. You can use any service account within the same project, but you must have the service account user permission to use the instance. If not specified, the [Compute Engine default service account](https://cloud.google.com/compute/docs/access/service- accounts#default_service_account) is used. shieldedVmConfig: Optional. Immutable. Runtime Shielded VM spec. softwareConfig: Optional. The notebook software configuration of the notebook runtime. updateTime: Output only. Timestamp when this NotebookRuntimeTemplate was most recently updated. """ class NotebookRuntimeTypeValueValuesEnum(_messages.Enum): r"""Optional. Immutable. The type of the notebook runtime template. Values: NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED: Unspecified notebook runtime type, NotebookRuntimeType will default to USER_DEFINED. USER_DEFINED: runtime or template with coustomized configurations from user. ONE_CLICK: runtime or template with system defined configurations. """ NOTEBOOK_RUNTIME_TYPE_UNSPECIFIED = 0 USER_DEFINED = 1 ONE_CLICK = 2 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize the NotebookRuntimeTemplates. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) dataPersistentDiskSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PersistentDiskSpec', 2) description = _messages.StringField(3) displayName = _messages.StringField(4) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 5) etag = _messages.StringField(6) eucConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookEucConfig', 7) idleShutdownConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookIdleShutdownConfig', 8) isDefault = _messages.BooleanField(9) labels = _messages.MessageField('LabelsValue', 10) machineSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1MachineSpec', 11) name = _messages.StringField(12) networkSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1NetworkSpec', 13) networkTags = _messages.StringField(14, repeated=True) notebookRuntimeType = _messages.EnumField('NotebookRuntimeTypeValueValuesEnum', 15) reservationAffinity = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookReservationAffinity', 16) serviceAccount = _messages.StringField(17) shieldedVmConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ShieldedVmConfig', 18) softwareConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1NotebookSoftwareConfig', 19) updateTime = _messages.StringField(20) class GoogleCloudAiplatformV1beta1NotebookRuntimeTemplateRef(_messages.Message): r"""Points to a NotebookRuntimeTemplateRef. Fields: notebookRuntimeTemplate: Immutable. A resource name of the NotebookRuntimeTemplate. """ notebookRuntimeTemplate = _messages.StringField(1) class GoogleCloudAiplatformV1beta1NotebookSoftwareConfig(_messages.Message): r"""Notebook Software Config. This is passed to the backend when user makes software configurations in UI. Fields: colabImage: Optional. Google-managed NotebookRuntime colab image. env: Optional. Environment variables to be passed to the container. Maximum limit is 100. postStartupScriptConfig: Optional. Post startup script config. """ colabImage = _messages.MessageField('GoogleCloudAiplatformV1beta1ColabImage', 1) env = _messages.MessageField('GoogleCloudAiplatformV1beta1EnvVar', 2, repeated=True) postStartupScriptConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PostStartupScriptConfig', 3) class GoogleCloudAiplatformV1beta1OptimizePromptRequest(_messages.Message): r"""Request message for GenAiTuningService.OptimizePrompt. Enums: OptimizationTargetValueValuesEnum: Optional. The target model to optimize the prompt for. Fields: content: Required. The content to optimize. optimizationTarget: Optional. The target model to optimize the prompt for. """ class OptimizationTargetValueValuesEnum(_messages.Enum): r"""Optional. The target model to optimize the prompt for. Values: OPTIMIZATION_TARGET_UNSPECIFIED: Unspecified optimization target. Default to OPTIMIZATION_TARGET_GENERAL. OPTIMIZATION_TARGET_GENERAL: Optimize the prompt for quality. OPTIMIZATION_TARGET_GEMINI_NANO: Optimize the prompt for Gemini Nano. """ OPTIMIZATION_TARGET_UNSPECIFIED = 0 OPTIMIZATION_TARGET_GENERAL = 1 OPTIMIZATION_TARGET_GEMINI_NANO = 2 content = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1) optimizationTarget = _messages.EnumField('OptimizationTargetValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1OptimizePromptResponse(_messages.Message): r"""Response message for GenAiTuningService.OptimizePrompt Fields: content: Output only. The optimized prompt content. """ content = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1) class GoogleCloudAiplatformV1beta1OutputConfig(_messages.Message): r"""Config for evaluation output. Fields: gcsDestination: Cloud storage destination for evaluation output. """ gcsDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 1) class GoogleCloudAiplatformV1beta1OutputFieldSpec(_messages.Message): r"""Defines a specification for a single output field. Enums: FieldTypeValueValuesEnum: Optional. The data type of the field. Defaults to CONTENT if not set. Fields: fieldName: Required. The name of the output field. fieldType: Optional. The data type of the field. Defaults to CONTENT if not set. guidance: Optional. Optional, but recommended. Additional guidance specific to this field to provide targeted instructions for the LLM to generate the content of a single output field. While the LLM can sometimes infer content from the field name, providing explicit guidance is preferred. """ class FieldTypeValueValuesEnum(_messages.Enum): r"""Optional. The data type of the field. Defaults to CONTENT if not set. Values: FIELD_TYPE_UNSPECIFIED: Field type is unspecified. CONTENT: Arbitrary content field type. TEXT: Text field type. IMAGE: Image field type. AUDIO: Audio field type. """ FIELD_TYPE_UNSPECIFIED = 0 CONTENT = 1 TEXT = 2 IMAGE = 3 AUDIO = 4 fieldName = _messages.StringField(1) fieldType = _messages.EnumField('FieldTypeValueValuesEnum', 2) guidance = _messages.StringField(3) class GoogleCloudAiplatformV1beta1OutputInfo(_messages.Message): r"""Describes the info for output of EvaluationService.EvaluateDataset. Fields: gcsOutputDirectory: Output only. The full path of the Cloud Storage directory created, into which the evaluation results and aggregation results are written. """ gcsOutputDirectory = _messages.StringField(1) class GoogleCloudAiplatformV1beta1PSCAutomationConfig(_messages.Message): r"""PSC config that is used to automatically create PSC endpoints in the user projects. Enums: StateValueValuesEnum: Output only. The state of the PSC service automation. Fields: errorMessage: Output only. Error message if the PSC service automation failed. forwardingRule: Output only. Forwarding rule created by the PSC service automation. ipAddress: Output only. IP address rule created by the PSC service automation. network: Required. The full name of the Google Compute Engine [network](https://cloud.google.com/compute/docs/networks-and- firewalls#networks). [Format](https://cloud.google.com/compute/docs/refe rence/rest/v1/networks/get): `projects/{project}/global/networks/{network}`. projectId: Required. Project id used to create forwarding rule. state: Output only. The state of the PSC service automation. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The state of the PSC service automation. Values: PSC_AUTOMATION_STATE_UNSPECIFIED: Should not be used. PSC_AUTOMATION_STATE_SUCCESSFUL: The PSC service automation is successful. PSC_AUTOMATION_STATE_FAILED: The PSC service automation has failed. """ PSC_AUTOMATION_STATE_UNSPECIFIED = 0 PSC_AUTOMATION_STATE_SUCCESSFUL = 1 PSC_AUTOMATION_STATE_FAILED = 2 errorMessage = _messages.StringField(1) forwardingRule = _messages.StringField(2) ipAddress = _messages.StringField(3) network = _messages.StringField(4) projectId = _messages.StringField(5) state = _messages.EnumField('StateValueValuesEnum', 6) class GoogleCloudAiplatformV1beta1PairwiseMetricInput(_messages.Message): r"""Input for pairwise metric. Fields: instance: Required. Pairwise metric instance. metricSpec: Required. Spec for pairwise metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseMetricInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseMetricSpec', 2) class GoogleCloudAiplatformV1beta1PairwiseMetricInstance(_messages.Message): r"""Pairwise metric instance. Usually one instance corresponds to one row in an evaluation dataset. Fields: contentMapInstance: Key-value contents for the mutlimodality input, including text, image, video, audio, and pdf, etc. The key is placeholder in metric prompt template, and the value is the multimodal content. jsonInstance: Instance specified as a json string. String key-value pairs are expected in the json_instance to render PairwiseMetricSpec.instance_prompt_template. """ contentMapInstance = _messages.MessageField('GoogleCloudAiplatformV1beta1ContentMap', 1) jsonInstance = _messages.StringField(2) class GoogleCloudAiplatformV1beta1PairwiseMetricResult(_messages.Message): r"""Spec for pairwise metric result. Enums: PairwiseChoiceValueValuesEnum: Output only. Pairwise metric choice. Fields: customOutput: Output only. Spec for custom output. explanation: Output only. Explanation for pairwise metric score. pairwiseChoice: Output only. Pairwise metric choice. """ class PairwiseChoiceValueValuesEnum(_messages.Enum): r"""Output only. Pairwise metric choice. Values: PAIRWISE_CHOICE_UNSPECIFIED: Unspecified prediction choice. BASELINE: Baseline prediction wins CANDIDATE: Candidate prediction wins TIE: Winner cannot be determined """ PAIRWISE_CHOICE_UNSPECIFIED = 0 BASELINE = 1 CANDIDATE = 2 TIE = 3 customOutput = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomOutput', 1) explanation = _messages.StringField(2) pairwiseChoice = _messages.EnumField('PairwiseChoiceValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1PairwiseMetricSpec(_messages.Message): r"""Spec for pairwise metric. Fields: baselineResponseFieldName: Optional. The field name of the baseline response. candidateResponseFieldName: Optional. The field name of the candidate response. customOutputFormatConfig: Optional. CustomOutputFormatConfig allows customization of metric output. When this config is set, the default output is replaced with the raw output string. If a custom format is chosen, the `pairwise_choice` and `explanation` fields in the corresponding metric result will be empty. metricPromptTemplate: Required. Metric prompt template for pairwise metric. systemInstruction: Optional. System instructions for pairwise metric. """ baselineResponseFieldName = _messages.StringField(1) candidateResponseFieldName = _messages.StringField(2) customOutputFormatConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomOutputFormatConfig', 3) metricPromptTemplate = _messages.StringField(4) systemInstruction = _messages.StringField(5) class GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInput(_messages.Message): r"""Input for pairwise question answering quality metric. Fields: instance: Required. Pairwise question answering quality instance. metricSpec: Required. Spec for pairwise question answering quality score metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualitySpec', 2) class GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityInstance(_messages.Message): r"""Spec for pairwise question answering quality instance. Fields: baselinePrediction: Required. Output of the baseline model. context: Required. Text to answer the question. instruction: Required. Question Answering prompt for LLM. prediction: Required. Output of the candidate model. reference: Optional. Ground truth used to compare against the prediction. """ baselinePrediction = _messages.StringField(1) context = _messages.StringField(2) instruction = _messages.StringField(3) prediction = _messages.StringField(4) reference = _messages.StringField(5) class GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualityResult(_messages.Message): r"""Spec for pairwise question answering quality result. Enums: PairwiseChoiceValueValuesEnum: Output only. Pairwise question answering prediction choice. Fields: confidence: Output only. Confidence for question answering quality score. explanation: Output only. Explanation for question answering quality score. pairwiseChoice: Output only. Pairwise question answering prediction choice. """ class PairwiseChoiceValueValuesEnum(_messages.Enum): r"""Output only. Pairwise question answering prediction choice. Values: PAIRWISE_CHOICE_UNSPECIFIED: Unspecified prediction choice. BASELINE: Baseline prediction wins CANDIDATE: Candidate prediction wins TIE: Winner cannot be determined """ PAIRWISE_CHOICE_UNSPECIFIED = 0 BASELINE = 1 CANDIDATE = 2 TIE = 3 confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) pairwiseChoice = _messages.EnumField('PairwiseChoiceValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1PairwiseQuestionAnsweringQualitySpec(_messages.Message): r"""Spec for pairwise question answering quality score metric. Fields: useReference: Optional. Whether to use instance.reference to compute question answering quality. version: Optional. Which version to use for evaluation. """ useReference = _messages.BooleanField(1) version = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInput(_messages.Message): r"""Input for pairwise summarization quality metric. Fields: instance: Required. Pairwise summarization quality instance. metricSpec: Required. Spec for pairwise summarization quality score metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PairwiseSummarizationQualitySpec', 2) class GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityInstance(_messages.Message): r"""Spec for pairwise summarization quality instance. Fields: baselinePrediction: Required. Output of the baseline model. context: Required. Text to be summarized. instruction: Required. Summarization prompt for LLM. prediction: Required. Output of the candidate model. reference: Optional. Ground truth used to compare against the prediction. """ baselinePrediction = _messages.StringField(1) context = _messages.StringField(2) instruction = _messages.StringField(3) prediction = _messages.StringField(4) reference = _messages.StringField(5) class GoogleCloudAiplatformV1beta1PairwiseSummarizationQualityResult(_messages.Message): r"""Spec for pairwise summarization quality result. Enums: PairwiseChoiceValueValuesEnum: Output only. Pairwise summarization prediction choice. Fields: confidence: Output only. Confidence for summarization quality score. explanation: Output only. Explanation for summarization quality score. pairwiseChoice: Output only. Pairwise summarization prediction choice. """ class PairwiseChoiceValueValuesEnum(_messages.Enum): r"""Output only. Pairwise summarization prediction choice. Values: PAIRWISE_CHOICE_UNSPECIFIED: Unspecified prediction choice. BASELINE: Baseline prediction wins CANDIDATE: Candidate prediction wins TIE: Winner cannot be determined """ PAIRWISE_CHOICE_UNSPECIFIED = 0 BASELINE = 1 CANDIDATE = 2 TIE = 3 confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) pairwiseChoice = _messages.EnumField('PairwiseChoiceValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1PairwiseSummarizationQualitySpec(_messages.Message): r"""Spec for pairwise summarization quality score metric. Fields: useReference: Optional. Whether to use instance.reference to compute pairwise summarization quality. version: Optional. Which version to use for evaluation. """ useReference = _messages.BooleanField(1) version = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1Part(_messages.Message): r"""A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes. Fields: codeExecutionResult: Optional. The result of executing the ExecutableCode. executableCode: Optional. Code generated by the model that is intended to be executed. fileData: Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage. functionCall: Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function. functionResponse: Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted. inlineData: Optional. The inline data content of the part. This can be used to include images, audio, or video in a request. text: Optional. The text content of the part. thought: Optional. Indicates whether the `part` represents the model's thought process or reasoning. thoughtSignature: Optional. An opaque signature for the thought so it can be reused in subsequent requests. videoMetadata: Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data. """ codeExecutionResult = _messages.MessageField('GoogleCloudAiplatformV1beta1CodeExecutionResult', 1) executableCode = _messages.MessageField('GoogleCloudAiplatformV1beta1ExecutableCode', 2) fileData = _messages.MessageField('GoogleCloudAiplatformV1beta1FileData', 3) functionCall = _messages.MessageField('GoogleCloudAiplatformV1beta1FunctionCall', 4) functionResponse = _messages.MessageField('GoogleCloudAiplatformV1beta1FunctionResponse', 5) inlineData = _messages.MessageField('GoogleCloudAiplatformV1beta1Blob', 6) text = _messages.StringField(7) thought = _messages.BooleanField(8) thoughtSignature = _messages.BytesField(9) videoMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1VideoMetadata', 10) class GoogleCloudAiplatformV1beta1PartnerModelTuningSpec(_messages.Message): r"""Tuning spec for Partner models. Messages: HyperParametersValue: Hyperparameters for tuning. The accepted hyper_parameters and their valid range of values will differ depending on the base model. Fields: hyperParameters: Hyperparameters for tuning. The accepted hyper_parameters and their valid range of values will differ depending on the base model. trainingDatasetUri: Required. Cloud Storage path to file containing training dataset for tuning. The dataset must be formatted as a JSONL file. validationDatasetUri: Optional. Cloud Storage path to file containing validation dataset for tuning. The dataset must be formatted as a JSONL file. """ @encoding.MapUnrecognizedFields('additionalProperties') class HyperParametersValue(_messages.Message): r"""Hyperparameters for tuning. The accepted hyper_parameters and their valid range of values will differ depending on the base model. Messages: AdditionalProperty: An additional property for a HyperParametersValue object. Fields: additionalProperties: Additional properties of type HyperParametersValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a HyperParametersValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) hyperParameters = _messages.MessageField('HyperParametersValue', 1) trainingDatasetUri = _messages.StringField(2) validationDatasetUri = _messages.StringField(3) class GoogleCloudAiplatformV1beta1PauseModelDeploymentMonitoringJobRequest(_messages.Message): r"""Request message for JobService.PauseModelDeploymentMonitoringJob.""" class GoogleCloudAiplatformV1beta1PauseScheduleRequest(_messages.Message): r"""Request message for ScheduleService.PauseSchedule.""" class GoogleCloudAiplatformV1beta1PersistentDiskSpec(_messages.Message): r"""Represents the spec of persistent disk options. Fields: diskSizeGb: Size in GB of the disk (default is 100GB). diskType: Type of the disk (default is "pd-standard"). Valid values: "pd- ssd" (Persistent Disk Solid State Drive) "pd-standard" (Persistent Disk Hard Disk Drive) "pd-balanced" (Balanced Persistent Disk) "pd-extreme" (Extreme Persistent Disk) """ diskSizeGb = _messages.IntegerField(1) diskType = _messages.StringField(2) class GoogleCloudAiplatformV1beta1PersistentResource(_messages.Message): r"""Represents long-lasting resources that are dedicated to users to runs custom workloads. A PersistentResource can have multiple node pools and each node pool can have its own machine spec. Enums: StateValueValuesEnum: Output only. The detailed state of a Study. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize PersistentResource. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: createTime: Output only. Time when the PersistentResource was created. displayName: Optional. The display name of the PersistentResource. The name can be up to 128 characters long and can consist of any UTF-8 characters. encryptionSpec: Optional. Customer-managed encryption key spec for a PersistentResource. If set, this PersistentResource and all sub- resources of this PersistentResource will be secured by this key. error: Output only. Only populated when persistent resource's state is `STOPPING` or `ERROR`. labels: Optional. The labels with user-defined metadata to organize PersistentResource. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. name: Immutable. Resource name of a PersistentResource. network: Optional. The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to peered with Vertex AI to host the persistent resources. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. To specify this field, you must have already [configured VPC Network Peering for Vertex AI](https://cloud.google.com/vertex- ai/docs/general/vpc-peering). If this field is left unspecified, the resources aren't peered with any network. pscInterfaceConfig: Optional. Configuration for PSC-I for PersistentResource. reservedIpRanges: Optional. A list of names for the reserved IP ranges under the VPC network that can be used for this persistent resource. If set, we will deploy the persistent resource within the provided IP ranges. Otherwise, the persistent resource is deployed to any IP ranges under the provided VPC network. Example: ['vertex-ai-ip-range']. resourcePools: Required. The spec of the pools of different resources. resourceRuntime: Output only. Runtime information of the Persistent Resource. resourceRuntimeSpec: Optional. Persistent Resource runtime spec. For example, used for Ray cluster configuration. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. startTime: Output only. Time when the PersistentResource for the first time entered the `RUNNING` state. state: Output only. The detailed state of a Study. updateTime: Output only. Time when the PersistentResource was most recently updated. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of a Study. Values: STATE_UNSPECIFIED: Not set. PROVISIONING: The PROVISIONING state indicates the persistent resources is being created. RUNNING: The RUNNING state indicates the persistent resource is healthy and fully usable. STOPPING: The STOPPING state indicates the persistent resource is being deleted. ERROR: The ERROR state indicates the persistent resource may be unusable. Details can be found in the `error` field. REBOOTING: The REBOOTING state indicates the persistent resource is being rebooted (PR is not available right now but is expected to be ready again later). UPDATING: The UPDATING state indicates the persistent resource is being updated. """ STATE_UNSPECIFIED = 0 PROVISIONING = 1 RUNNING = 2 STOPPING = 3 ERROR = 4 REBOOTING = 5 UPDATING = 6 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize PersistentResource. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) displayName = _messages.StringField(2) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 3) error = _messages.MessageField('GoogleRpcStatus', 4) labels = _messages.MessageField('LabelsValue', 5) name = _messages.StringField(6) network = _messages.StringField(7) pscInterfaceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PscInterfaceConfig', 8) reservedIpRanges = _messages.StringField(9, repeated=True) resourcePools = _messages.MessageField('GoogleCloudAiplatformV1beta1ResourcePool', 10, repeated=True) resourceRuntime = _messages.MessageField('GoogleCloudAiplatformV1beta1ResourceRuntime', 11) resourceRuntimeSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ResourceRuntimeSpec', 12) satisfiesPzi = _messages.BooleanField(13) satisfiesPzs = _messages.BooleanField(14) startTime = _messages.StringField(15) state = _messages.EnumField('StateValueValuesEnum', 16) updateTime = _messages.StringField(17) class GoogleCloudAiplatformV1beta1PipelineJob(_messages.Message): r"""An instance of a machine learning PipelineJob. Enums: StateValueValuesEnum: Output only. The detailed state of the job. Messages: LabelsValue: The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided. PipelineSpecValue: The spec of the pipeline. Fields: createTime: Output only. Pipeline creation time. displayName: The display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters. encryptionSpec: Customer-managed encryption key spec for a pipelineJob. If set, this PipelineJob and all of its sub-resources will be secured by this key. endTime: Output only. Pipeline end time. error: Output only. The error that occurred during pipeline execution. Only populated when the pipeline's state is FAILED or CANCELLED. jobDetail: Output only. The details of pipeline run. Not available in the list view. labels: The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai- pipelines-run-billing-id`, user set value will get overrided. name: Output only. The resource name of the PipelineJob. network: The full name of the Compute Engine [network](/compute/docs/networks-and-firewalls#networks) to which the Pipeline Job's workload should be peered. For example, `projects/12345/global/networks/myVPC`. [Format](/compute/docs/reference/rest/v1/networks/insert) is of the form `projects/{project}/global/networks/{network}`. Where {project} is a project number, as in `12345`, and {network} is a network name. Private services access must already be configured for the network. Pipeline job will apply the network configuration to the Google Cloud resources being launched, if applied, such as Vertex AI Training or Dataflow job. If left unspecified, the workload is not peered with any network. originalPipelineJobId: Optional. The original pipeline job id if this pipeline job is a rerun of a previous pipeline job. pipelineSpec: The spec of the pipeline. pipelineTaskRerunConfigs: Optional. The rerun configs for each task in the pipeline job. By default, the rerun will: 1. Use the same input artifacts as the original run. 2. Use the same input parameters as the original run. 3. Skip all the tasks that are already succeeded in the original run. 4. Rerun all the tasks that are not succeeded in the original run. By providing this field, users can override the default behavior and specify the rerun config for each task. preflightValidations: Optional. Whether to do component level validations before job creation. pscInterfaceConfig: Optional. Configuration for PSC-I for PipelineJob. reservedIpRanges: A list of names for the reserved ip ranges under the VPC network that can be used for this Pipeline Job's workload. If set, we will deploy the Pipeline Job's workload within the provided ip ranges. Otherwise, the job will be deployed to any ip ranges under the provided VPC network. Example: ['vertex-ai-ip-range']. runtimeConfig: Runtime config of the pipeline. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. scheduleName: Output only. The schedule resource name. Only returned if the Pipeline is created by Schedule API. serviceAccount: The service account that the pipeline workload runs as. If not specified, the Compute Engine default service account in the project will be used. See https://cloud.google.com/compute/docs/access/service- accounts#default_service_account Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account. startTime: Output only. Pipeline start time. state: Output only. The detailed state of the job. templateMetadata: Output only. Pipeline template metadata. Will fill up fields if PipelineJob.template_uri is from supported template registry. templateUri: A template uri from where the PipelineJob.pipeline_spec, if empty, will be downloaded. Currently, only uri from Vertex Template Registry & Gallery is supported. Reference to https://cloud.google.com/vertex-ai/docs/pipelines/create-pipeline- template. updateTime: Output only. Timestamp when this PipelineJob was most recently updated. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of the job. Values: PIPELINE_STATE_UNSPECIFIED: The pipeline state is unspecified. PIPELINE_STATE_QUEUED: The pipeline has been created or resumed, and processing has not yet begun. PIPELINE_STATE_PENDING: The service is preparing to run the pipeline. PIPELINE_STATE_RUNNING: The pipeline is in progress. PIPELINE_STATE_SUCCEEDED: The pipeline completed successfully. PIPELINE_STATE_FAILED: The pipeline failed. PIPELINE_STATE_CANCELLING: The pipeline is being cancelled. From this state, the pipeline may only go to either PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED or PIPELINE_STATE_CANCELLED. PIPELINE_STATE_CANCELLED: The pipeline has been cancelled. PIPELINE_STATE_PAUSED: The pipeline has been stopped, and can be resumed. """ PIPELINE_STATE_UNSPECIFIED = 0 PIPELINE_STATE_QUEUED = 1 PIPELINE_STATE_PENDING = 2 PIPELINE_STATE_RUNNING = 3 PIPELINE_STATE_SUCCEEDED = 4 PIPELINE_STATE_FAILED = 5 PIPELINE_STATE_CANCELLING = 6 PIPELINE_STATE_CANCELLED = 7 PIPELINE_STATE_PAUSED = 8 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize PipelineJob. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Note there is some reserved label key for Vertex AI Pipelines. - `vertex-ai-pipelines-run-billing-id`, user set value will get overrided. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class PipelineSpecValue(_messages.Message): r"""The spec of the pipeline. Messages: AdditionalProperty: An additional property for a PipelineSpecValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a PipelineSpecValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) displayName = _messages.StringField(2) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 3) endTime = _messages.StringField(4) error = _messages.MessageField('GoogleRpcStatus', 5) jobDetail = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineJobDetail', 6) labels = _messages.MessageField('LabelsValue', 7) name = _messages.StringField(8) network = _messages.StringField(9) originalPipelineJobId = _messages.IntegerField(10) pipelineSpec = _messages.MessageField('PipelineSpecValue', 11) pipelineTaskRerunConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineTaskRerunConfig', 12, repeated=True) preflightValidations = _messages.BooleanField(13) pscInterfaceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PscInterfaceConfig', 14) reservedIpRanges = _messages.StringField(15, repeated=True) runtimeConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfig', 16) satisfiesPzi = _messages.BooleanField(17) satisfiesPzs = _messages.BooleanField(18) scheduleName = _messages.StringField(19) serviceAccount = _messages.StringField(20) startTime = _messages.StringField(21) state = _messages.EnumField('StateValueValuesEnum', 22) templateMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineTemplateMetadata', 23) templateUri = _messages.StringField(24) updateTime = _messages.StringField(25) class GoogleCloudAiplatformV1beta1PipelineJobDetail(_messages.Message): r"""The runtime detail of PipelineJob. Fields: pipelineContext: Output only. The context of the pipeline. pipelineRunContext: Output only. The context of the current pipeline run. taskDetails: Output only. The runtime details of the tasks under the pipeline. """ pipelineContext = _messages.MessageField('GoogleCloudAiplatformV1beta1Context', 1) pipelineRunContext = _messages.MessageField('GoogleCloudAiplatformV1beta1Context', 2) taskDetails = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineTaskDetail', 3, repeated=True) class GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfig(_messages.Message): r"""The runtime config of a PipelineJob. Enums: FailurePolicyValueValuesEnum: Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion. Messages: InputArtifactsValue: The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact. ParameterValuesValue: The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL. ParametersValue: Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower. Fields: defaultRuntime: Optional. The default runtime for the PipelineJob. If not set, Standard Vertex Custom Job(https://cloud.google.com/vertex- ai/docs/training/overview) is used as the runtime. If set, all pipeline tasks will run on the default runtime unless a task is a GCPC custom job component (https://cloud.google.com/vertex-ai/docs/pipelines/customjob- component) based task. If the task is based on a GCPC custom job component, it runs solely according to the component's configuration. failurePolicy: Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion. gcsOutputDirectory: Required. A path in a Cloud Storage bucket, which will be treated as the root output directory of the pipeline. It is used by the system to generate the paths of output artifacts. The artifact paths are generated with a sub-path pattern `{job_id}/{task_id}/{output_key}` under the specified output directory. The service account specified in this pipeline must have the `storage.objects.get` and `storage.objects.create` permissions for this bucket. inputArtifacts: The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact. parameterValues: The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL. parameters: Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower. """ class FailurePolicyValueValuesEnum(_messages.Enum): r"""Represents the failure policy of a pipeline. Currently, the default of a pipeline is that the pipeline will continue to run until no more tasks can be executed, also known as PIPELINE_FAILURE_POLICY_FAIL_SLOW. However, if a pipeline is set to PIPELINE_FAILURE_POLICY_FAIL_FAST, it will stop scheduling any new tasks when a task has failed. Any scheduled tasks will continue to completion. Values: PIPELINE_FAILURE_POLICY_UNSPECIFIED: Default value, and follows fail slow behavior. PIPELINE_FAILURE_POLICY_FAIL_SLOW: Indicates that the pipeline should continue to run until all possible tasks have been scheduled and completed. PIPELINE_FAILURE_POLICY_FAIL_FAST: Indicates that the pipeline should stop scheduling new tasks after a task has failed. """ PIPELINE_FAILURE_POLICY_UNSPECIFIED = 0 PIPELINE_FAILURE_POLICY_FAIL_SLOW = 1 PIPELINE_FAILURE_POLICY_FAIL_FAST = 2 @encoding.MapUnrecognizedFields('additionalProperties') class InputArtifactsValue(_messages.Message): r"""The runtime artifacts of the PipelineJob. The key will be the input artifact name and the value would be one of the InputArtifact. Messages: AdditionalProperty: An additional property for a InputArtifactsValue object. Fields: additionalProperties: Additional properties of type InputArtifactsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a InputArtifactsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigInputArtifact attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigInputArtifact', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class ParameterValuesValue(_messages.Message): r"""The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.1.0, such as pipelines built using Kubeflow Pipelines SDK 1.9 or higher and the v2 DSL. Messages: AdditionalProperty: An additional property for a ParameterValuesValue object. Fields: additionalProperties: Additional properties of type ParameterValuesValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ParameterValuesValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class ParametersValue(_messages.Message): r"""Deprecated. Use RuntimeConfig.parameter_values instead. The runtime parameters of the PipelineJob. The parameters will be passed into PipelineJob.pipeline_spec to replace the placeholders at runtime. This field is used by pipelines built using `PipelineJob.pipeline_spec.schema_version` 2.0.0 or lower, such as pipelines built using Kubeflow Pipelines SDK 1.8 or lower. Messages: AdditionalProperty: An additional property for a ParametersValue object. Fields: additionalProperties: Additional properties of type ParametersValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ParametersValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1Value attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1Value', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) defaultRuntime = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigDefaultRuntime', 1) failurePolicy = _messages.EnumField('FailurePolicyValueValuesEnum', 2) gcsOutputDirectory = _messages.StringField(3) inputArtifacts = _messages.MessageField('InputArtifactsValue', 4) parameterValues = _messages.MessageField('ParameterValuesValue', 5) parameters = _messages.MessageField('ParametersValue', 6) class GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigDefaultRuntime(_messages.Message): r"""The default runtime for the PipelineJob. Fields: persistentResourceRuntimeDetail: Persistent resource based runtime detail. """ persistentResourceRuntimeDetail = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigPersistentResourceRuntimeDetail', 1) class GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigInputArtifact(_messages.Message): r"""The type of an input artifact. Fields: artifactId: Artifact resource id from MLMD. Which is the last portion of an artifact resource name: `projects/{project}/locations/{location}/meta dataStores/default/artifacts/{artifact_id}`. The artifact must stay within the same project, location and default metadatastore as the pipeline. """ artifactId = _messages.StringField(1) class GoogleCloudAiplatformV1beta1PipelineJobRuntimeConfigPersistentResourceRuntimeDetail(_messages.Message): r"""Persistent resource based runtime detail. For more information about persistent resource, refer to https://cloud.google.com/vertex- ai/docs/training/persistent-resource-overview Enums: TaskResourceUnavailableTimeoutBehaviorValueValuesEnum: Specifies the behavior to take if the timeout is reached. Fields: persistentResourceName: Persistent resource name. Format: `projects/{proje ct}/locations/{location}/persistentResources/{persistent_resource}` taskResourceUnavailableTimeoutBehavior: Specifies the behavior to take if the timeout is reached. taskResourceUnavailableWaitTimeMs: The max time a pipeline task waits for the required CPU, memory, or accelerator resource to become available from the specified persistent resource. Default wait time is 0. """ class TaskResourceUnavailableTimeoutBehaviorValueValuesEnum(_messages.Enum): r"""Specifies the behavior to take if the timeout is reached. Values: TASK_RESOURCE_UNAVAILABLE_TIMEOUT_BEHAVIOR_UNSPECIFIED: Unspecified. Behavior is same as `FAIL`. FAIL: Fail the task if the timeout is reached. FALL_BACK_TO_ON_DEMAND: Fall back to on-demand execution if the timeout is reached. """ TASK_RESOURCE_UNAVAILABLE_TIMEOUT_BEHAVIOR_UNSPECIFIED = 0 FAIL = 1 FALL_BACK_TO_ON_DEMAND = 2 persistentResourceName = _messages.StringField(1) taskResourceUnavailableTimeoutBehavior = _messages.EnumField('TaskResourceUnavailableTimeoutBehaviorValueValuesEnum', 2) taskResourceUnavailableWaitTimeMs = _messages.IntegerField(3) class GoogleCloudAiplatformV1beta1PipelineTaskDetail(_messages.Message): r"""The runtime detail of a task execution. Enums: StateValueValuesEnum: Output only. State of the task. Messages: InputsValue: Output only. The runtime input artifacts of the task. OutputsValue: Output only. The runtime output artifacts of the task. Fields: createTime: Output only. Task create time. endTime: Output only. Task end time. error: Output only. The error that occurred during task execution. Only populated when the task's state is FAILED or CANCELLED. execution: Output only. The execution metadata of the task. executorDetail: Output only. The detailed execution info. inputs: Output only. The runtime input artifacts of the task. outputs: Output only. The runtime output artifacts of the task. parentTaskId: Output only. The id of the parent task if the task is within a component scope. Empty if the task is at the root level. pipelineTaskStatus: Output only. A list of task status. This field keeps a record of task status evolving over time. startTime: Output only. Task start time. state: Output only. State of the task. taskId: Output only. The system generated ID of the task. taskName: Output only. The user specified name of the task that is defined in pipeline_spec. taskUniqueName: Output only. The unique name of a task. This field is used by rerun pipeline job. Console UI and Vertex AI SDK will support triggering pipeline job reruns. The name is constructed by concatenating all the parent tasks name with the task name. For example, if a task named "child_task" has a parent task named "parent_task_1" and parent task 1 has a parent task named "parent_task_2", the task unique name will be "parent_task_2.parent_task_1.child_task". """ class StateValueValuesEnum(_messages.Enum): r"""Output only. State of the task. Values: STATE_UNSPECIFIED: Unspecified. PENDING: Specifies pending state for the task. RUNNING: Specifies task is being executed. SUCCEEDED: Specifies task completed successfully. CANCEL_PENDING: Specifies Task cancel is in pending state. CANCELLING: Specifies task is being cancelled. CANCELLED: Specifies task was cancelled. FAILED: Specifies task failed. SKIPPED: Specifies task was skipped due to cache hit. NOT_TRIGGERED: Specifies that the task was not triggered because the task's trigger policy is not satisfied. The trigger policy is specified in the `condition` field of PipelineJob.pipeline_spec. """ STATE_UNSPECIFIED = 0 PENDING = 1 RUNNING = 2 SUCCEEDED = 3 CANCEL_PENDING = 4 CANCELLING = 5 CANCELLED = 6 FAILED = 7 SKIPPED = 8 NOT_TRIGGERED = 9 @encoding.MapUnrecognizedFields('additionalProperties') class InputsValue(_messages.Message): r"""Output only. The runtime input artifacts of the task. Messages: AdditionalProperty: An additional property for a InputsValue object. Fields: additionalProperties: Additional properties of type InputsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a InputsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class OutputsValue(_messages.Message): r"""Output only. The runtime output artifacts of the task. Messages: AdditionalProperty: An additional property for a OutputsValue object. Fields: additionalProperties: Additional properties of type OutputsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a OutputsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) endTime = _messages.StringField(2) error = _messages.MessageField('GoogleRpcStatus', 3) execution = _messages.MessageField('GoogleCloudAiplatformV1beta1Execution', 4) executorDetail = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetail', 5) inputs = _messages.MessageField('InputsValue', 6) outputs = _messages.MessageField('OutputsValue', 7) parentTaskId = _messages.IntegerField(8) pipelineTaskStatus = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineTaskDetailPipelineTaskStatus', 9, repeated=True) startTime = _messages.StringField(10) state = _messages.EnumField('StateValueValuesEnum', 11) taskId = _messages.IntegerField(12) taskName = _messages.StringField(13) taskUniqueName = _messages.StringField(14) class GoogleCloudAiplatformV1beta1PipelineTaskDetailArtifactList(_messages.Message): r"""A list of artifact metadata. Fields: artifacts: Output only. A list of artifact metadata. """ artifacts = _messages.MessageField('GoogleCloudAiplatformV1beta1Artifact', 1, repeated=True) class GoogleCloudAiplatformV1beta1PipelineTaskDetailPipelineTaskStatus(_messages.Message): r"""A single record of the task status. Enums: StateValueValuesEnum: Output only. The state of the task. Fields: error: Output only. The error that occurred during the state. May be set when the state is any of the non-final state (PENDING/RUNNING/CANCELLING) or FAILED state. If the state is FAILED, the error here is final and not going to be retried. If the state is a non-final state, the error indicates a system-error being retried. state: Output only. The state of the task. updateTime: Output only. Update time of this status. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The state of the task. Values: STATE_UNSPECIFIED: Unspecified. PENDING: Specifies pending state for the task. RUNNING: Specifies task is being executed. SUCCEEDED: Specifies task completed successfully. CANCEL_PENDING: Specifies Task cancel is in pending state. CANCELLING: Specifies task is being cancelled. CANCELLED: Specifies task was cancelled. FAILED: Specifies task failed. SKIPPED: Specifies task was skipped due to cache hit. NOT_TRIGGERED: Specifies that the task was not triggered because the task's trigger policy is not satisfied. The trigger policy is specified in the `condition` field of PipelineJob.pipeline_spec. """ STATE_UNSPECIFIED = 0 PENDING = 1 RUNNING = 2 SUCCEEDED = 3 CANCEL_PENDING = 4 CANCELLING = 5 CANCELLED = 6 FAILED = 7 SKIPPED = 8 NOT_TRIGGERED = 9 error = _messages.MessageField('GoogleRpcStatus', 1) state = _messages.EnumField('StateValueValuesEnum', 2) updateTime = _messages.StringField(3) class GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetail(_messages.Message): r"""The runtime detail of a pipeline executor. Fields: containerDetail: Output only. The detailed info for a container executor. customJobDetail: Output only. The detailed info for a custom job executor. """ containerDetail = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailContainerDetail', 1) customJobDetail = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailCustomJobDetail', 2) class GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailContainerDetail(_messages.Message): r"""The detail of a container execution. It contains the job names of the lifecycle of a container execution. Fields: failedMainJobs: Output only. The names of the previously failed CustomJob for the main container executions. The list includes the all attempts in chronological order. failedPreCachingCheckJobs: Output only. The names of the previously failed CustomJob for the pre-caching-check container executions. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. The list includes the all attempts in chronological order. mainJob: Output only. The name of the CustomJob for the main container execution. preCachingCheckJob: Output only. The name of the CustomJob for the pre- caching-check container execution. This job will be available if the PipelineJob.pipeline_spec specifies the `pre_caching_check` hook in the lifecycle events. """ failedMainJobs = _messages.StringField(1, repeated=True) failedPreCachingCheckJobs = _messages.StringField(2, repeated=True) mainJob = _messages.StringField(3) preCachingCheckJob = _messages.StringField(4) class GoogleCloudAiplatformV1beta1PipelineTaskExecutorDetailCustomJobDetail(_messages.Message): r"""The detailed info for a custom job executor. Fields: failedJobs: Output only. The names of the previously failed CustomJob. The list includes the all attempts in chronological order. job: Output only. The name of the CustomJob. """ failedJobs = _messages.StringField(1, repeated=True) job = _messages.StringField(2) class GoogleCloudAiplatformV1beta1PipelineTaskRerunConfig(_messages.Message): r"""User provided rerun config to submit a rerun pipelinejob. This includes 1. Which task to rerun 2. User override input parameters and artifacts. Fields: inputs: Optional. The runtime input of the task overridden by the user. skipDownstreamTasks: Optional. Whether to skip downstream tasks. Default value is False. skipTask: Optional. Whether to skip this task. Default value is False. taskId: Optional. The system generated ID of the task. Retrieved from original run. taskName: Optional. The name of the task. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineTaskRerunConfigInputs', 1) skipDownstreamTasks = _messages.BooleanField(2) skipTask = _messages.BooleanField(3) taskId = _messages.IntegerField(4) taskName = _messages.StringField(5) class GoogleCloudAiplatformV1beta1PipelineTaskRerunConfigArtifactList(_messages.Message): r"""A list of artifact metadata. Fields: artifacts: Optional. A list of artifact metadata. """ artifacts = _messages.MessageField('GoogleCloudAiplatformV1beta1RuntimeArtifact', 1, repeated=True) class GoogleCloudAiplatformV1beta1PipelineTaskRerunConfigInputs(_messages.Message): r"""Runtime inputs data of the task. Messages: ArtifactsValue: Optional. Input artifacts. ParameterValuesValue: Optional. Input parameters. Fields: artifacts: Optional. Input artifacts. parameterValues: Optional. Input parameters. """ @encoding.MapUnrecognizedFields('additionalProperties') class ArtifactsValue(_messages.Message): r"""Optional. Input artifacts. Messages: AdditionalProperty: An additional property for a ArtifactsValue object. Fields: additionalProperties: Additional properties of type ArtifactsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ArtifactsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1PipelineTaskRerunConfigArtifactList attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1PipelineTaskRerunConfigArtifactList', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class ParameterValuesValue(_messages.Message): r"""Optional. Input parameters. Messages: AdditionalProperty: An additional property for a ParameterValuesValue object. Fields: additionalProperties: Additional properties of type ParameterValuesValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ParameterValuesValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) artifacts = _messages.MessageField('ArtifactsValue', 1) parameterValues = _messages.MessageField('ParameterValuesValue', 2) class GoogleCloudAiplatformV1beta1PipelineTemplateMetadata(_messages.Message): r"""Pipeline template metadata if PipelineJob.template_uri is from supported template registry. Currently, the only supported registry is Artifact Registry. Fields: version: The version_name in artifact registry. Will always be presented in output if the PipelineJob.template_uri is from supported template registry. Format is "sha256:abcdef123456...". """ version = _messages.StringField(1) class GoogleCloudAiplatformV1beta1PointwiseMetricInput(_messages.Message): r"""Input for pointwise metric. Fields: instance: Required. Pointwise metric instance. metricSpec: Required. Spec for pointwise metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1PointwiseMetricInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PointwiseMetricSpec', 2) class GoogleCloudAiplatformV1beta1PointwiseMetricInstance(_messages.Message): r"""Pointwise metric instance. Usually one instance corresponds to one row in an evaluation dataset. Fields: contentMapInstance: Key-value contents for the mutlimodality input, including text, image, video, audio, and pdf, etc. The key is placeholder in metric prompt template, and the value is the multimodal content. jsonInstance: Instance specified as a json string. String key-value pairs are expected in the json_instance to render PointwiseMetricSpec.instance_prompt_template. """ contentMapInstance = _messages.MessageField('GoogleCloudAiplatformV1beta1ContentMap', 1) jsonInstance = _messages.StringField(2) class GoogleCloudAiplatformV1beta1PointwiseMetricResult(_messages.Message): r"""Spec for pointwise metric result. Fields: customOutput: Output only. Spec for custom output. explanation: Output only. Explanation for pointwise metric score. score: Output only. Pointwise metric score. """ customOutput = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomOutput', 1) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1PointwiseMetricSpec(_messages.Message): r"""Spec for pointwise metric. Fields: customOutputFormatConfig: Optional. CustomOutputFormatConfig allows customization of metric output. By default, metrics return a score and explanation. When this config is set, the default output is replaced with either: - The raw output string. - A parsed output based on a user- defined schema. If a custom format is chosen, the `score` and `explanation` fields in the corresponding metric result will be empty. metricPromptTemplate: Required. Metric prompt template for pointwise metric. systemInstruction: Optional. System instructions for pointwise metric. """ customOutputFormatConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomOutputFormatConfig', 1) metricPromptTemplate = _messages.StringField(2) systemInstruction = _messages.StringField(3) class GoogleCloudAiplatformV1beta1Port(_messages.Message): r"""Represents a network port in a container. Fields: containerPort: The number of the port to expose on the pod's IP address. Must be a valid port number, between 1 and 65535 inclusive. """ containerPort = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1PostStartupScriptConfig(_messages.Message): r"""Post startup script config. Enums: PostStartupScriptBehaviorValueValuesEnum: Optional. Post startup script behavior that defines download and execution behavior. Fields: postStartupScript: Optional. Post startup script to run after runtime is started. postStartupScriptBehavior: Optional. Post startup script behavior that defines download and execution behavior. postStartupScriptUrl: Optional. Post startup script url to download. Example: `gs://bucket/script.sh` """ class PostStartupScriptBehaviorValueValuesEnum(_messages.Enum): r"""Optional. Post startup script behavior that defines download and execution behavior. Values: POST_STARTUP_SCRIPT_BEHAVIOR_UNSPECIFIED: Unspecified post startup script behavior. RUN_ONCE: Run post startup script after runtime is started. RUN_EVERY_START: Run post startup script after runtime is stopped. DOWNLOAD_AND_RUN_EVERY_START: Download and run post startup script every time runtime is started. """ POST_STARTUP_SCRIPT_BEHAVIOR_UNSPECIFIED = 0 RUN_ONCE = 1 RUN_EVERY_START = 2 DOWNLOAD_AND_RUN_EVERY_START = 3 postStartupScript = _messages.StringField(1) postStartupScriptBehavior = _messages.EnumField('PostStartupScriptBehaviorValueValuesEnum', 2) postStartupScriptUrl = _messages.StringField(3) class GoogleCloudAiplatformV1beta1PreTunedModel(_messages.Message): r"""A pre-tuned model for continuous tuning. Fields: baseModel: Output only. The name of the base model this PreTunedModel was tuned from. checkpointId: Optional. The source checkpoint id. If not specified, the default checkpoint will be used. tunedModelName: The resource name of the Model. E.g., a model resource name with a specified version id or alias: `projects/{project}/locations/{location}/models/{model}@{version_id}` `projects/{project}/locations/{location}/models/{model}@{alias}` Or, omit the version id to use the default version: `projects/{project}/locations/{location}/models/{model}` """ baseModel = _messages.StringField(1) checkpointId = _messages.StringField(2) tunedModelName = _messages.StringField(3) class GoogleCloudAiplatformV1beta1PrebuiltVoiceConfig(_messages.Message): r"""Configuration for a prebuilt voice. Fields: voiceName: The name of the prebuilt voice to use. """ voiceName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1PredefinedMetricSpec(_messages.Message): r"""The spec for a pre-defined metric. Messages: MetricSpecParametersValue: Optional. The parameters needed to run the pre- defined metric. Fields: metricSpecName: Required. The name of a pre-defined metric, such as "instruction_following_v1" or "text_quality_v1". metricSpecParameters: Optional. The parameters needed to run the pre- defined metric. """ @encoding.MapUnrecognizedFields('additionalProperties') class MetricSpecParametersValue(_messages.Message): r"""Optional. The parameters needed to run the pre-defined metric. Messages: AdditionalProperty: An additional property for a MetricSpecParametersValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a MetricSpecParametersValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) metricSpecName = _messages.StringField(1) metricSpecParameters = _messages.MessageField('MetricSpecParametersValue', 2) class GoogleCloudAiplatformV1beta1PredefinedSplit(_messages.Message): r"""Assigns input data to training, validation, and test sets based on the value of a provided key. Supported only for tabular Datasets. Fields: key: Required. The key is a name of one of the Dataset's data columns. The value of the key (either the label's value or value in the column) must be one of {`training`, `validation`, `test`}, and it defines to which set the given piece of data is assigned. If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline. """ key = _messages.StringField(1) class GoogleCloudAiplatformV1beta1PredictLongRunningMetadata(_messages.Message): r"""Metadata for PredictLongRunning long running operations.""" class GoogleCloudAiplatformV1beta1PredictLongRunningRequest(_messages.Message): r"""Request message for PredictionService.PredictLongRunning. Fields: instances: Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri. parameters: Optional. The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri. """ instances = _messages.MessageField('extra_types.JsonValue', 1, repeated=True) parameters = _messages.MessageField('extra_types.JsonValue', 2) class GoogleCloudAiplatformV1beta1PredictLongRunningResponse(_messages.Message): r"""Response message for [PredictionService.PredictLongRunning] Fields: generateVideoResponse: The response of the video generation prediction. """ generateVideoResponse = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerateVideoResponse', 1) class GoogleCloudAiplatformV1beta1PredictRequest(_messages.Message): r"""Request message for PredictionService.Predict. Messages: LabelsValue: Optional. The user labels for Imagen billing usage only. Only Imagen supports labels. For other use cases, it will be ignored. Fields: instances: Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri. labels: Optional. The user labels for Imagen billing usage only. Only Imagen supports labels. For other use cases, it will be ignored. parameters: The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The user labels for Imagen billing usage only. Only Imagen supports labels. For other use cases, it will be ignored. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) instances = _messages.MessageField('extra_types.JsonValue', 1, repeated=True) labels = _messages.MessageField('LabelsValue', 2) parameters = _messages.MessageField('extra_types.JsonValue', 3) class GoogleCloudAiplatformV1beta1PredictRequestResponseLoggingConfig(_messages.Message): r"""Configuration for logging request-response to a BigQuery table. Fields: bigqueryDestination: BigQuery table for logging. If only given a project, a new dataset will be created with name `logging__` where will be made BigQuery-dataset-name compatible (e.g. most special characters will become underscores). If no table name is given, a new table will be created with name `request_response_logging` enableOtelLogging: This field is used for large models. If true, in addition to the original large model logs, logs will be converted in OTel schema format, and saved in otel_log column. Default value is false. enabled: If logging is enabled or not. requestResponseLoggingSchemaVersion: Output only. The schema version used in creating the BigQuery table for the request response logging. The versions are "v1" and "v2". The current default version is "v1". samplingRate: Percentage of requests to be logged, expressed as a fraction in range(0,1]. """ bigqueryDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1BigQueryDestination', 1) enableOtelLogging = _messages.BooleanField(2) enabled = _messages.BooleanField(3) requestResponseLoggingSchemaVersion = _messages.StringField(4) samplingRate = _messages.FloatField(5) class GoogleCloudAiplatformV1beta1PredictResponse(_messages.Message): r"""Response message for PredictionService.Predict. Fields: deployedModelId: ID of the Endpoint's DeployedModel that served this prediction. metadata: Output only. Request-level metadata returned by the model. The metadata type will be dependent upon the model implementation. model: Output only. The resource name of the Model which is deployed as the DeployedModel that this prediction hits. modelDisplayName: Output only. The display name of the Model which is deployed as the DeployedModel that this prediction hits. modelVersionId: Output only. The version ID of the Model which is deployed as the DeployedModel that this prediction hits. predictions: The predictions that are the output of the predictions call. The schema of any single prediction may be specified via Endpoint's DeployedModels' Model's PredictSchemata's prediction_schema_uri. """ deployedModelId = _messages.StringField(1) metadata = _messages.MessageField('extra_types.JsonValue', 2) model = _messages.StringField(3) modelDisplayName = _messages.StringField(4) modelVersionId = _messages.StringField(5) predictions = _messages.MessageField('extra_types.JsonValue', 6, repeated=True) class GoogleCloudAiplatformV1beta1PredictSchemata(_messages.Message): r"""Contains the schemata used in Model's predictions and explanations via PredictionService.Predict, PredictionService.Explain and BatchPredictionJob. Fields: instanceSchemaUri: Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single instance, which are used in PredictRequest.instances, ExplainRequest.instances and BatchPredictionJob.input_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI- Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access. parametersSchemaUri: Immutable. Points to a YAML file stored on Google Cloud Storage describing the parameters of prediction and explanation via PredictRequest.parameters, ExplainRequest.parameters and BatchPredictionJob.model_parameters. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI- Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI, if no parameters are supported, then it is set to an empty string. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access. predictionSchemaUri: Immutable. Points to a YAML file stored on Google Cloud Storage describing the format of a single prediction produced by this Model, which are returned via PredictResponse.predictions, ExplainResponse.explanations, and BatchPredictionJob.output_config. The schema is defined as an OpenAPI 3.0.2 [Schema Object](https://github.com/OAI/OpenAPI- Specification/blob/main/versions/3.0.2.md#schemaObject). AutoML Models always have this field populated by Vertex AI. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access. """ instanceSchemaUri = _messages.StringField(1) parametersSchemaUri = _messages.StringField(2) predictionSchemaUri = _messages.StringField(3) class GoogleCloudAiplatformV1beta1PreferenceOptimizationDataStats(_messages.Message): r"""Statistics computed for datasets used for preference optimization. Fields: droppedExampleIndices: Output only. A partial sample of the indices (starting from 1) of the dropped examples. droppedExampleReasons: Output only. For each index in `dropped_example_indices`, the user-facing reason why the example was dropped. scoreVariancePerExampleDistribution: Output only. Dataset distributions for scores variance per example. scoresDistribution: Output only. Dataset distributions for scores. totalBillableTokenCount: Output only. Number of billable tokens in the tuning dataset. tuningDatasetExampleCount: Output only. Number of examples in the tuning dataset. tuningStepCount: Output only. Number of tuning steps for this Tuning Job. userDatasetExamples: Output only. Sample user examples in the training dataset. userInputTokenDistribution: Output only. Dataset distributions for the user input tokens. userOutputTokenDistribution: Output only. Dataset distributions for the user output tokens. """ droppedExampleIndices = _messages.IntegerField(1, repeated=True) droppedExampleReasons = _messages.StringField(2, repeated=True) scoreVariancePerExampleDistribution = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetDistribution', 3) scoresDistribution = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetDistribution', 4) totalBillableTokenCount = _messages.IntegerField(5) tuningDatasetExampleCount = _messages.IntegerField(6) tuningStepCount = _messages.IntegerField(7) userDatasetExamples = _messages.MessageField('GoogleCloudAiplatformV1beta1GeminiPreferenceExample', 8, repeated=True) userInputTokenDistribution = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetDistribution', 9) userOutputTokenDistribution = _messages.MessageField('GoogleCloudAiplatformV1beta1DatasetDistribution', 10) class GoogleCloudAiplatformV1beta1PreferenceOptimizationHyperParameters(_messages.Message): r"""Hyperparameters for Preference Optimization. Enums: AdapterSizeValueValuesEnum: Optional. Adapter size for preference optimization. Fields: adapterSize: Optional. Adapter size for preference optimization. beta: Optional. Weight for KL Divergence regularization. epochCount: Optional. Number of complete passes the model makes over the entire training dataset during training. learningRateMultiplier: Optional. Multiplier for adjusting the default learning rate. """ class AdapterSizeValueValuesEnum(_messages.Enum): r"""Optional. Adapter size for preference optimization. Values: ADAPTER_SIZE_UNSPECIFIED: Adapter size is unspecified. ADAPTER_SIZE_ONE: Adapter size 1. ADAPTER_SIZE_TWO: Adapter size 2. ADAPTER_SIZE_FOUR: Adapter size 4. ADAPTER_SIZE_EIGHT: Adapter size 8. ADAPTER_SIZE_SIXTEEN: Adapter size 16. ADAPTER_SIZE_THIRTY_TWO: Adapter size 32. """ ADAPTER_SIZE_UNSPECIFIED = 0 ADAPTER_SIZE_ONE = 1 ADAPTER_SIZE_TWO = 2 ADAPTER_SIZE_FOUR = 3 ADAPTER_SIZE_EIGHT = 4 ADAPTER_SIZE_SIXTEEN = 5 ADAPTER_SIZE_THIRTY_TWO = 6 adapterSize = _messages.EnumField('AdapterSizeValueValuesEnum', 1) beta = _messages.FloatField(2) epochCount = _messages.IntegerField(3) learningRateMultiplier = _messages.FloatField(4) class GoogleCloudAiplatformV1beta1PreferenceOptimizationSpec(_messages.Message): r"""Tuning Spec for Preference Optimization. Fields: exportLastCheckpointOnly: Optional. If set to true, disable intermediate checkpoints for Preference Optimization and only the last checkpoint will be exported. Otherwise, enable intermediate checkpoints for Preference Optimization. Default is false. hyperParameters: Optional. Hyperparameters for Preference Optimization. trainingDatasetUri: Required. Cloud Storage path to file containing training dataset for preference optimization tuning. The dataset must be formatted as a JSONL file. validationDatasetUri: Optional. Cloud Storage path to file containing validation dataset for preference optimization tuning. The dataset must be formatted as a JSONL file. """ exportLastCheckpointOnly = _messages.BooleanField(1) hyperParameters = _messages.MessageField('GoogleCloudAiplatformV1beta1PreferenceOptimizationHyperParameters', 2) trainingDatasetUri = _messages.StringField(3) validationDatasetUri = _messages.StringField(4) class GoogleCloudAiplatformV1beta1Presets(_messages.Message): r"""Preset configuration for example-based explanations Enums: ModalityValueValuesEnum: The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type. QueryValueValuesEnum: Preset option controlling parameters for speed- precision trade-off when querying for examples. If omitted, defaults to `PRECISE`. Fields: modality: The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type. query: Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`. """ class ModalityValueValuesEnum(_messages.Enum): r"""The modality of the uploaded model, which automatically configures the distance measurement and feature normalization for the underlying example index and queries. If your model does not precisely fit one of these types, it is okay to choose the closest type. Values: MODALITY_UNSPECIFIED: Should not be set. Added as a recommended best practice for enums IMAGE: IMAGE modality TEXT: TEXT modality TABULAR: TABULAR modality """ MODALITY_UNSPECIFIED = 0 IMAGE = 1 TEXT = 2 TABULAR = 3 class QueryValueValuesEnum(_messages.Enum): r"""Preset option controlling parameters for speed-precision trade-off when querying for examples. If omitted, defaults to `PRECISE`. Values: PRECISE: More precise neighbors as a trade-off against slower response. FAST: Faster response as a trade-off against less precise neighbors. """ PRECISE = 0 FAST = 1 modality = _messages.EnumField('ModalityValueValuesEnum', 1) query = _messages.EnumField('QueryValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1PrivateEndpoints(_messages.Message): r"""PrivateEndpoints proto is used to provide paths for users to send requests privately. To send request via private service access, use predict_http_uri, explain_http_uri or health_http_uri. To send request via private service connect, use service_attachment. Fields: explainHttpUri: Output only. Http(s) path to send explain requests. healthHttpUri: Output only. Http(s) path to send health check requests. predictHttpUri: Output only. Http(s) path to send prediction requests. serviceAttachment: Output only. The name of the service attachment resource. Populated if private service connect is enabled. """ explainHttpUri = _messages.StringField(1) healthHttpUri = _messages.StringField(2) predictHttpUri = _messages.StringField(3) serviceAttachment = _messages.StringField(4) class GoogleCloudAiplatformV1beta1PrivateServiceConnectConfig(_messages.Message): r"""Represents configuration for private service connect. Fields: enablePrivateServiceConnect: Required. If true, expose the IndexEndpoint via private service connect. enableSecurePrivateServiceConnect: Optional. If set to true, enable secure private service connect with IAM authorization. Otherwise, private service connect will be done without authorization. Note latency will be slightly increased if authorization is enabled. projectAllowlist: A list of Projects from which the forwarding rule will target the service attachment. pscAutomationConfigs: Optional. List of projects and networks where the PSC endpoints will be created. This field is used by Online Inference(Prediction) only. serviceAttachment: Output only. The name of the generated service attachment resource. This is only populated if the endpoint is deployed with PrivateServiceConnect. """ enablePrivateServiceConnect = _messages.BooleanField(1) enableSecurePrivateServiceConnect = _messages.BooleanField(2) projectAllowlist = _messages.StringField(3, repeated=True) pscAutomationConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1PSCAutomationConfig', 4, repeated=True) serviceAttachment = _messages.StringField(5) class GoogleCloudAiplatformV1beta1Probe(_messages.Message): r"""Probe describes a health check to be performed against a container to determine whether it is alive or ready to receive traffic. Fields: exec_: ExecAction probes the health of a container by executing a command. failureThreshold: Number of consecutive failures before the probe is considered failed. Defaults to 3. Minimum value is 1. Maps to Kubernetes probe argument 'failureThreshold'. grpc: GrpcAction probes the health of a container by sending a gRPC request. httpGet: HttpGetAction probes the health of a container by sending an HTTP GET request. initialDelaySeconds: Number of seconds to wait before starting the probe. Defaults to 0. Minimum value is 0. Maps to Kubernetes probe argument 'initialDelaySeconds'. periodSeconds: How often (in seconds) to perform the probe. Default to 10 seconds. Minimum value is 1. Must be less than timeout_seconds. Maps to Kubernetes probe argument 'periodSeconds'. successThreshold: Number of consecutive successes before the probe is considered successful. Defaults to 1. Minimum value is 1. Maps to Kubernetes probe argument 'successThreshold'. tcpSocket: TcpSocketAction probes the health of a container by opening a TCP socket connection. timeoutSeconds: Number of seconds after which the probe times out. Defaults to 1 second. Minimum value is 1. Must be greater or equal to period_seconds. Maps to Kubernetes probe argument 'timeoutSeconds'. """ exec_ = _messages.MessageField('GoogleCloudAiplatformV1beta1ProbeExecAction', 1) failureThreshold = _messages.IntegerField(2, variant=_messages.Variant.INT32) grpc = _messages.MessageField('GoogleCloudAiplatformV1beta1ProbeGrpcAction', 3) httpGet = _messages.MessageField('GoogleCloudAiplatformV1beta1ProbeHttpGetAction', 4) initialDelaySeconds = _messages.IntegerField(5, variant=_messages.Variant.INT32) periodSeconds = _messages.IntegerField(6, variant=_messages.Variant.INT32) successThreshold = _messages.IntegerField(7, variant=_messages.Variant.INT32) tcpSocket = _messages.MessageField('GoogleCloudAiplatformV1beta1ProbeTcpSocketAction', 8) timeoutSeconds = _messages.IntegerField(9, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1ProbeExecAction(_messages.Message): r"""ExecAction specifies a command to execute. Fields: command: Command is the command line to execute inside the container, the working directory for the command is root ('/') in the container's filesystem. The command is simply exec'd, it is not run inside a shell, so traditional shell instructions ('|', etc) won't work. To use a shell, you need to explicitly call out to that shell. Exit status of 0 is treated as live/healthy and non-zero is unhealthy. """ command = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1ProbeGrpcAction(_messages.Message): r"""GrpcAction checks the health of a container using a gRPC service. Fields: port: Port number of the gRPC service. Number must be in the range 1 to 65535. service: Service is the name of the service to place in the gRPC HealthCheckRequest. See https://github.com/grpc/grpc/blob/master/doc/health-checking.md. If this is not specified, the default behavior is defined by gRPC. """ port = _messages.IntegerField(1, variant=_messages.Variant.INT32) service = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ProbeHttpGetAction(_messages.Message): r"""HttpGetAction describes an action based on HTTP Get requests. Fields: host: Host name to connect to, defaults to the model serving container's IP. You probably want to set "Host" in httpHeaders instead. httpHeaders: Custom headers to set in the request. HTTP allows repeated headers. path: Path to access on the HTTP server. port: Number of the port to access on the container. Number must be in the range 1 to 65535. scheme: Scheme to use for connecting to the host. Defaults to HTTP. Acceptable values are "HTTP" or "HTTPS". """ host = _messages.StringField(1) httpHeaders = _messages.MessageField('GoogleCloudAiplatformV1beta1ProbeHttpHeader', 2, repeated=True) path = _messages.StringField(3) port = _messages.IntegerField(4, variant=_messages.Variant.INT32) scheme = _messages.StringField(5) class GoogleCloudAiplatformV1beta1ProbeHttpHeader(_messages.Message): r"""HttpHeader describes a custom header to be used in HTTP probes Fields: name: The header field name. This will be canonicalized upon output, so case-variant names will be understood as the same header. value: The header field value """ name = _messages.StringField(1) value = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ProbeTcpSocketAction(_messages.Message): r"""TcpSocketAction probes the health of a container by opening a TCP socket connection. Fields: host: Optional: Host name to connect to, defaults to the model serving container's IP. port: Number of the port to access on the container. Number must be in the range 1 to 65535. """ host = _messages.StringField(1) port = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1PscAutomatedEndpoints(_messages.Message): r"""PscAutomatedEndpoints defines the output of the forwarding rule automatically created by each PscAutomationConfig. Fields: matchAddress: Ip Address created by the automated forwarding rule. network: Corresponding network in pscAutomationConfigs. projectId: Corresponding project_id in pscAutomationConfigs """ matchAddress = _messages.StringField(1) network = _messages.StringField(2) projectId = _messages.StringField(3) class GoogleCloudAiplatformV1beta1PscInterfaceConfig(_messages.Message): r"""Configuration for PSC-I. Fields: dnsPeeringConfigs: Optional. DNS peering configurations. When specified, Vertex AI will attempt to configure DNS peering zones in the tenant project VPC to resolve the specified domains using the target network's Cloud DNS. The user must grant the dns.peer role to the Vertex AI Service Agent on the target project. networkAttachment: Optional. The name of the Compute Engine [network attachment](https://cloud.google.com/vpc/docs/about-network-attachments) to attach to the resource within the region and user project. To specify this field, you must have already [created a network attachment] (https://cloud.google.com/vpc/docs/create-manage-network- attachments#create-network-attachments). This field is only used for resources using PSC-I. """ dnsPeeringConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1DnsPeeringConfig', 1, repeated=True) networkAttachment = _messages.StringField(2) class GoogleCloudAiplatformV1beta1PublisherModel(_messages.Message): r"""A Model Garden Publisher Model. Enums: LaunchStageValueValuesEnum: Optional. Indicates the launch stage of the model. OpenSourceCategoryValueValuesEnum: Required. Indicates the open source category of the publisher model. VersionStateValueValuesEnum: Optional. Indicates the state of the model version. Fields: frameworks: Optional. Additional information about the model's Frameworks. launchStage: Optional. Indicates the launch stage of the model. name: Output only. The resource name of the PublisherModel. openSourceCategory: Required. Indicates the open source category of the publisher model. parent: Optional. The parent that this model was customized from. E.g., Vision API, Natural Language API, LaMDA, T5, etc. Foundation models don't have parents. predictSchemata: Optional. The schemata that describes formats of the PublisherModel's predictions and explanations as given and returned via PredictionService.Predict. publisherModelTemplate: Optional. Output only. Immutable. Used to indicate this model has a publisher model and provide the template of the publisher model resource name. supportedActions: Optional. Supported call-to-action options. versionId: Output only. Immutable. The version ID of the PublisherModel. A new version is committed when a new model version is uploaded under an existing model id. It is an auto-incrementing decimal number in string representation. versionState: Optional. Indicates the state of the model version. """ class LaunchStageValueValuesEnum(_messages.Enum): r"""Optional. Indicates the launch stage of the model. Values: LAUNCH_STAGE_UNSPECIFIED: The model launch stage is unspecified. EXPERIMENTAL: Used to indicate the PublisherModel is at Experimental launch stage, available to a small set of customers. PRIVATE_PREVIEW: Used to indicate the PublisherModel is at Private Preview launch stage, only available to a small set of customers, although a larger set of customers than an Experimental launch. Previews are the first launch stage used to get feedback from customers. PUBLIC_PREVIEW: Used to indicate the PublisherModel is at Public Preview launch stage, available to all customers, although not supported for production workloads. GA: Used to indicate the PublisherModel is at GA launch stage, available to all customers and ready for production workload. """ LAUNCH_STAGE_UNSPECIFIED = 0 EXPERIMENTAL = 1 PRIVATE_PREVIEW = 2 PUBLIC_PREVIEW = 3 GA = 4 class OpenSourceCategoryValueValuesEnum(_messages.Enum): r"""Required. Indicates the open source category of the publisher model. Values: OPEN_SOURCE_CATEGORY_UNSPECIFIED: The open source category is unspecified, which should not be used. PROPRIETARY: Used to indicate the PublisherModel is not open sourced. GOOGLE_OWNED_OSS_WITH_GOOGLE_CHECKPOINT: Used to indicate the PublisherModel is a Google-owned open source model w/ Google checkpoint. THIRD_PARTY_OWNED_OSS_WITH_GOOGLE_CHECKPOINT: Used to indicate the PublisherModel is a 3p-owned open source model w/ Google checkpoint. GOOGLE_OWNED_OSS: Used to indicate the PublisherModel is a Google-owned pure open source model. THIRD_PARTY_OWNED_OSS: Used to indicate the PublisherModel is a 3p-owned pure open source model. """ OPEN_SOURCE_CATEGORY_UNSPECIFIED = 0 PROPRIETARY = 1 GOOGLE_OWNED_OSS_WITH_GOOGLE_CHECKPOINT = 2 THIRD_PARTY_OWNED_OSS_WITH_GOOGLE_CHECKPOINT = 3 GOOGLE_OWNED_OSS = 4 THIRD_PARTY_OWNED_OSS = 5 class VersionStateValueValuesEnum(_messages.Enum): r"""Optional. Indicates the state of the model version. Values: VERSION_STATE_UNSPECIFIED: The version state is unspecified. VERSION_STATE_STABLE: Used to indicate the version is stable. VERSION_STATE_UNSTABLE: Used to indicate the version is unstable. """ VERSION_STATE_UNSPECIFIED = 0 VERSION_STATE_STABLE = 1 VERSION_STATE_UNSTABLE = 2 frameworks = _messages.StringField(1, repeated=True) launchStage = _messages.EnumField('LaunchStageValueValuesEnum', 2) name = _messages.StringField(3) openSourceCategory = _messages.EnumField('OpenSourceCategoryValueValuesEnum', 4) parent = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelParent', 5) predictSchemata = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictSchemata', 6) publisherModelTemplate = _messages.StringField(7) supportedActions = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToAction', 8) versionId = _messages.StringField(9) versionState = _messages.EnumField('VersionStateValueValuesEnum', 10) class GoogleCloudAiplatformV1beta1PublisherModelCallToAction(_messages.Message): r"""Actions could take on this Publisher Model. Fields: createApplication: Optional. Create application using the PublisherModel. deploy: Optional. Deploy the PublisherModel to Vertex Endpoint. deployGke: Optional. Deploy PublisherModel to Google Kubernetes Engine. multiDeployVertex: Optional. Multiple setups to deploy the PublisherModel to Vertex Endpoint. openEvaluationPipeline: Optional. Open evaluation pipeline of the PublisherModel. openFineTuningPipeline: Optional. Open fine-tuning pipeline of the PublisherModel. openFineTuningPipelines: Optional. Open fine-tuning pipelines of the PublisherModel. openGenerationAiStudio: Optional. Open in Generation AI Studio. openGenie: Optional. Open Genie / Playground. openNotebook: Optional. Open notebook of the PublisherModel. openNotebooks: Optional. Open notebooks of the PublisherModel. openPromptTuningPipeline: Optional. Open prompt-tuning pipeline of the PublisherModel. requestAccess: Optional. Request for access. viewRestApi: Optional. To view Rest API docs. """ createApplication = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences', 1) deploy = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeploy', 2) deployGke = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployGke', 3) multiDeployVertex = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployVertex', 4) openEvaluationPipeline = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences', 5) openFineTuningPipeline = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences', 6) openFineTuningPipelines = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenFineTuningPipelines', 7) openGenerationAiStudio = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences', 8) openGenie = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences', 9) openNotebook = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences', 10) openNotebooks = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenNotebooks', 11) openPromptTuningPipeline = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences', 12) requestAccess = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences', 13) viewRestApi = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionViewRestApi', 14) class GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeploy(_messages.Message): r"""Model metadata that is needed for UploadModel or DeployModel/CreateEndpoint requests. Fields: artifactUri: Optional. The path to the directory containing the Model artifact and any of its supporting files. automaticResources: A description of resources that to large degree are decided by Vertex AI, and require only a modest additional configuration. containerSpec: Optional. The specification of the container that is to be used when deploying this Model in Vertex AI. Not present for Large Models. dedicatedResources: A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration. deployMetadata: Optional. Metadata information about this deployment config. deployTaskName: Optional. The name of the deploy task (e.g., "text to image generation"). largeModelReference: Optional. Large model reference. When this is set, model_artifact_spec is not needed. modelDisplayName: Optional. Default model display name. publicArtifactUri: Optional. The signed URI for ephemeral Cloud Storage access to model artifact. sharedResources: The resource name of the shared DeploymentResourcePool to deploy on. Format: `projects/{project}/locations/{location}/deploymentRe sourcePools/{deployment_resource_pool}` title: Required. The title of the regional resource reference. """ artifactUri = _messages.StringField(1) automaticResources = _messages.MessageField('GoogleCloudAiplatformV1beta1AutomaticResources', 2) containerSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelContainerSpec', 3) dedicatedResources = _messages.MessageField('GoogleCloudAiplatformV1beta1DedicatedResources', 4) deployMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployDeployMetadata', 5) deployTaskName = _messages.StringField(6) largeModelReference = _messages.MessageField('GoogleCloudAiplatformV1beta1LargeModelReference', 7) modelDisplayName = _messages.StringField(8) publicArtifactUri = _messages.StringField(9) sharedResources = _messages.StringField(10) title = _messages.StringField(11) class GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployDeployMetadata(_messages.Message): r"""Metadata information about the deployment for managing deployment config. Messages: LabelsValue: Optional. Labels for the deployment config. For managing deployment config like verifying, source of deployment config, etc. Fields: labels: Optional. Labels for the deployment config. For managing deployment config like verifying, source of deployment config, etc. sampleRequest: Optional. Sample request for deployed endpoint. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. Labels for the deployment config. For managing deployment config like verifying, source of deployment config, etc. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) labels = _messages.MessageField('LabelsValue', 1) sampleRequest = _messages.StringField(2) class GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployGke(_messages.Message): r"""Configurations for PublisherModel GKE deployment Fields: gkeYamlConfigs: Optional. GKE deployment configuration in yaml format. """ gkeYamlConfigs = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeployVertex(_messages.Message): r"""Multiple setups to deploy the PublisherModel. Fields: multiDeployVertex: Optional. One click deployment configurations. """ multiDeployVertex = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionDeploy', 1, repeated=True) class GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenFineTuningPipelines(_messages.Message): r"""Open fine tuning pipelines. Fields: fineTuningPipelines: Required. Regional resource references to fine tuning pipelines. """ fineTuningPipelines = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences', 1, repeated=True) class GoogleCloudAiplatformV1beta1PublisherModelCallToActionOpenNotebooks(_messages.Message): r"""Open notebooks. Fields: notebooks: Required. Regional resource references to notebooks. """ notebooks = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences', 1, repeated=True) class GoogleCloudAiplatformV1beta1PublisherModelCallToActionRegionalResourceReferences(_messages.Message): r"""The regional resource name or the URI. Key is region, e.g., us-central1, europe-west2, global, etc.. Messages: ReferencesValue: Required. Fields: colabNotebookDisabled: Optional. For notebook resource. When set to true, the Colab Enterprise link will be disabled in the "open notebook" dialog in UI. references: Required. resourceDescription: Optional. Description of the resource. resourceTitle: Optional. Title of the resource. resourceUseCase: Optional. Use case (CUJ) of the resource. supportsWorkbench: Optional. For notebook resource, whether the notebook supports Workbench. title: Required. """ @encoding.MapUnrecognizedFields('additionalProperties') class ReferencesValue(_messages.Message): r"""Required. Messages: AdditionalProperty: An additional property for a ReferencesValue object. Fields: additionalProperties: Additional properties of type ReferencesValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ReferencesValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1PublisherModelResourceReference attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelResourceReference', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) colabNotebookDisabled = _messages.BooleanField(1) references = _messages.MessageField('ReferencesValue', 2) resourceDescription = _messages.StringField(3) resourceTitle = _messages.StringField(4) resourceUseCase = _messages.StringField(5) supportsWorkbench = _messages.BooleanField(6) title = _messages.StringField(7) class GoogleCloudAiplatformV1beta1PublisherModelCallToActionViewRestApi(_messages.Message): r"""Rest API docs. Fields: documentations: Required. title: Required. The title of the view rest API. """ documentations = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelDocumentation', 1, repeated=True) title = _messages.StringField(2) class GoogleCloudAiplatformV1beta1PublisherModelConfig(_messages.Message): r"""This message contains configs of a publisher model. Fields: loggingConfig: The prediction request/response logging config. """ loggingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictRequestResponseLoggingConfig', 1) class GoogleCloudAiplatformV1beta1PublisherModelDocumentation(_messages.Message): r"""A named piece of documentation. Fields: content: Required. Content of this piece of document (in Markdown format). title: Required. E.g., OVERVIEW, USE CASES, DOCUMENTATION, SDK & SAMPLES, JAVA, NODE.JS, etc.. """ content = _messages.StringField(1) title = _messages.StringField(2) class GoogleCloudAiplatformV1beta1PublisherModelEulaAcceptance(_messages.Message): r"""Response message for ModelGardenService.UpdatePublisherModelEula. Fields: projectNumber: The project number requesting access for named model. publisherModel: The publisher model resource name. publisherModelEulaAcked: The EULA content acceptance status. """ projectNumber = _messages.IntegerField(1) publisherModel = _messages.StringField(2) publisherModelEulaAcked = _messages.BooleanField(3) class GoogleCloudAiplatformV1beta1PublisherModelParent(_messages.Message): r"""The information about the parent of a model. Fields: displayName: Required. The display name of the parent. E.g., LaMDA, T5, Vision API, Natural Language API. reference: Optional. The Google Cloud resource name or the URI reference. """ displayName = _messages.StringField(1) reference = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelResourceReference', 2) class GoogleCloudAiplatformV1beta1PublisherModelResourceReference(_messages.Message): r"""Reference to a resource. Fields: description: Description of the resource. resourceName: The resource name of the Google Cloud resource. uri: The URI of the resource. useCase: Use case (CUJ) of the resource. """ description = _messages.StringField(1) resourceName = _messages.StringField(2) uri = _messages.StringField(3) useCase = _messages.StringField(4) class GoogleCloudAiplatformV1beta1PurgeArtifactsMetadata(_messages.Message): r"""Details of operations that perform MetadataService.PurgeArtifacts. Fields: genericMetadata: Operation metadata for purging Artifacts. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1PurgeArtifactsRequest(_messages.Message): r"""Request message for MetadataService.PurgeArtifacts. Fields: filter: Required. A required filter matching the Artifacts to be purged. E.g., `update_time <= 2020-11-19T11:30:00-04:00`. force: Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Artifact names that would be deleted. """ filter = _messages.StringField(1) force = _messages.BooleanField(2) class GoogleCloudAiplatformV1beta1PurgeArtifactsResponse(_messages.Message): r"""Response message for MetadataService.PurgeArtifacts. Fields: purgeCount: The number of Artifacts that this request deleted (or, if `force` is false, the number of Artifacts that will be deleted). This can be an estimate. purgeSample: A sample of the Artifact names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer). """ purgeCount = _messages.IntegerField(1) purgeSample = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1PurgeContextsMetadata(_messages.Message): r"""Details of operations that perform MetadataService.PurgeContexts. Fields: genericMetadata: Operation metadata for purging Contexts. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1PurgeContextsRequest(_messages.Message): r"""Request message for MetadataService.PurgeContexts. Fields: filter: Required. A required filter matching the Contexts to be purged. E.g., `update_time <= 2020-11-19T11:30:00-04:00`. force: Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Context names that would be deleted. """ filter = _messages.StringField(1) force = _messages.BooleanField(2) class GoogleCloudAiplatformV1beta1PurgeContextsResponse(_messages.Message): r"""Response message for MetadataService.PurgeContexts. Fields: purgeCount: The number of Contexts that this request deleted (or, if `force` is false, the number of Contexts that will be deleted). This can be an estimate. purgeSample: A sample of the Context names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer). """ purgeCount = _messages.IntegerField(1) purgeSample = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1PurgeExecutionsMetadata(_messages.Message): r"""Details of operations that perform MetadataService.PurgeExecutions. Fields: genericMetadata: Operation metadata for purging Executions. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1PurgeExecutionsRequest(_messages.Message): r"""Request message for MetadataService.PurgeExecutions. Fields: filter: Required. A required filter matching the Executions to be purged. E.g., `update_time <= 2020-11-19T11:30:00-04:00`. force: Optional. Flag to indicate to actually perform the purge. If `force` is set to false, the method will return a sample of Execution names that would be deleted. """ filter = _messages.StringField(1) force = _messages.BooleanField(2) class GoogleCloudAiplatformV1beta1PurgeExecutionsResponse(_messages.Message): r"""Response message for MetadataService.PurgeExecutions. Fields: purgeCount: The number of Executions that this request deleted (or, if `force` is false, the number of Executions that will be deleted). This can be an estimate. purgeSample: A sample of the Execution names that will be deleted. Only populated if `force` is set to false. The maximum number of samples is 100 (it is possible to return fewer). """ purgeCount = _messages.IntegerField(1) purgeSample = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1PurgeMemoriesRequest(_messages.Message): r"""Request message for MemoryBankService.PurgeMemories. Fields: filter: Required. The standard list filter to determine which memories to purge. More detail in [AIP-160](https://google.aip.dev/160). force: Optional. If true, the memories will actually be purged. If false, the purge request will be validated but not executed. """ filter = _messages.StringField(1) force = _messages.BooleanField(2) class GoogleCloudAiplatformV1beta1PythonPackageSpec(_messages.Message): r"""The spec of a Python packaged code. Fields: args: Command line arguments to be passed to the Python task. env: Environment variables to be passed to the python module. Maximum limit is 100. executorImageUri: Required. The URI of a container image in Artifact Registry that will run the provided Python package. Vertex AI provides a wide range of executor images with pre-installed packages to meet users' various use cases. See the list of [pre-built containers for training](https://cloud.google.com/vertex-ai/docs/training/pre-built- containers). You must use an image from this list. packageUris: Required. The Google Cloud Storage location of the Python package files which are the training program and its dependent packages. The maximum number of package URIs is 100. pythonModule: Required. The Python module name to run after installing the packages. """ args = _messages.StringField(1, repeated=True) env = _messages.MessageField('GoogleCloudAiplatformV1beta1EnvVar', 2, repeated=True) executorImageUri = _messages.StringField(3) packageUris = _messages.StringField(4, repeated=True) pythonModule = _messages.StringField(5) class GoogleCloudAiplatformV1beta1QueryDeployedModelsResponse(_messages.Message): r"""Response message for QueryDeployedModels method. Fields: deployedModelRefs: References to the DeployedModels that share the specified deploymentResourcePool. deployedModels: DEPRECATED Use deployed_model_refs instead. nextPageToken: A token, which can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages. totalDeployedModelCount: The total number of DeployedModels on this DeploymentResourcePool. totalEndpointCount: The total number of Endpoints that have DeployedModels on this DeploymentResourcePool. """ deployedModelRefs = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedModelRef', 1, repeated=True) deployedModels = _messages.MessageField('GoogleCloudAiplatformV1beta1DeployedModel', 2, repeated=True) nextPageToken = _messages.StringField(3) totalDeployedModelCount = _messages.IntegerField(4, variant=_messages.Variant.INT32) totalEndpointCount = _messages.IntegerField(5, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1QueryExtensionRequest(_messages.Message): r"""Request message for ExtensionExecutionService.QueryExtension. Fields: contents: Required. The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi- turn queries, this is a repeated field that contains conversation history + latest request. """ contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1, repeated=True) class GoogleCloudAiplatformV1beta1QueryExtensionResponse(_messages.Message): r"""Response message for ExtensionExecutionService.QueryExtension. Fields: failureMessage: Failure message if any. steps: Steps of extension or LLM interaction, can contain function call, function response, or text response. The last step contains the final response to the query. """ failureMessage = _messages.StringField(1) steps = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 2, repeated=True) class GoogleCloudAiplatformV1beta1QueryReasoningEngineRequest(_messages.Message): r"""Request message for ReasoningEngineExecutionService.Query. Messages: InputValue: Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc. Fields: classMethod: Optional. Class method to be used for the query. It is optional and defaults to "query" if unspecified. input: Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc. """ @encoding.MapUnrecognizedFields('additionalProperties') class InputValue(_messages.Message): r"""Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc. Messages: AdditionalProperty: An additional property for a InputValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a InputValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) classMethod = _messages.StringField(1) input = _messages.MessageField('InputValue', 2) class GoogleCloudAiplatformV1beta1QueryReasoningEngineResponse(_messages.Message): r"""Response message for ReasoningEngineExecutionService.Query Fields: output: Response provided by users in JSON object format. """ output = _messages.MessageField('extra_types.JsonValue', 1) class GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInput(_messages.Message): r"""Input for question answering correctness metric. Fields: instance: Required. Question answering correctness instance. metricSpec: Required. Spec for question answering correctness score metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessSpec', 2) class GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessInstance(_messages.Message): r"""Spec for question answering correctness instance. Fields: context: Optional. Text provided as context to answer the question. instruction: Required. The question asked and other instruction in the inference prompt. prediction: Required. Output of the evaluated model. reference: Optional. Ground truth used to compare against the prediction. """ context = _messages.StringField(1) instruction = _messages.StringField(2) prediction = _messages.StringField(3) reference = _messages.StringField(4) class GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessResult(_messages.Message): r"""Spec for question answering correctness result. Fields: confidence: Output only. Confidence for question answering correctness score. explanation: Output only. Explanation for question answering correctness score. score: Output only. Question Answering Correctness score. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1QuestionAnsweringCorrectnessSpec(_messages.Message): r"""Spec for question answering correctness metric. Fields: useReference: Optional. Whether to use instance.reference to compute question answering correctness. version: Optional. Which version to use for evaluation. """ useReference = _messages.BooleanField(1) version = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInput(_messages.Message): r"""Input for question answering helpfulness metric. Fields: instance: Required. Question answering helpfulness instance. metricSpec: Required. Spec for question answering helpfulness score metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessSpec', 2) class GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessInstance(_messages.Message): r"""Spec for question answering helpfulness instance. Fields: context: Optional. Text provided as context to answer the question. instruction: Required. The question asked and other instruction in the inference prompt. prediction: Required. Output of the evaluated model. reference: Optional. Ground truth used to compare against the prediction. """ context = _messages.StringField(1) instruction = _messages.StringField(2) prediction = _messages.StringField(3) reference = _messages.StringField(4) class GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessResult(_messages.Message): r"""Spec for question answering helpfulness result. Fields: confidence: Output only. Confidence for question answering helpfulness score. explanation: Output only. Explanation for question answering helpfulness score. score: Output only. Question Answering Helpfulness score. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1QuestionAnsweringHelpfulnessSpec(_messages.Message): r"""Spec for question answering helpfulness metric. Fields: useReference: Optional. Whether to use instance.reference to compute question answering helpfulness. version: Optional. Which version to use for evaluation. """ useReference = _messages.BooleanField(1) version = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInput(_messages.Message): r"""Input for question answering quality metric. Fields: instance: Required. Question answering quality instance. metricSpec: Required. Spec for question answering quality score metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringQualitySpec', 2) class GoogleCloudAiplatformV1beta1QuestionAnsweringQualityInstance(_messages.Message): r"""Spec for question answering quality instance. Fields: context: Required. Text to answer the question. instruction: Required. Question Answering prompt for LLM. prediction: Required. Output of the evaluated model. reference: Optional. Ground truth used to compare against the prediction. """ context = _messages.StringField(1) instruction = _messages.StringField(2) prediction = _messages.StringField(3) reference = _messages.StringField(4) class GoogleCloudAiplatformV1beta1QuestionAnsweringQualityResult(_messages.Message): r"""Spec for question answering quality result. Fields: confidence: Output only. Confidence for question answering quality score. explanation: Output only. Explanation for question answering quality score. score: Output only. Question Answering Quality score. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1QuestionAnsweringQualitySpec(_messages.Message): r"""Spec for question answering quality score metric. Fields: useReference: Optional. Whether to use instance.reference to compute question answering quality. version: Optional. Which version to use for evaluation. """ useReference = _messages.BooleanField(1) version = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInput(_messages.Message): r"""Input for question answering relevance metric. Fields: instance: Required. Question answering relevance instance. metricSpec: Required. Spec for question answering relevance score metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceSpec', 2) class GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceInstance(_messages.Message): r"""Spec for question answering relevance instance. Fields: context: Optional. Text provided as context to answer the question. instruction: Required. The question asked and other instruction in the inference prompt. prediction: Required. Output of the evaluated model. reference: Optional. Ground truth used to compare against the prediction. """ context = _messages.StringField(1) instruction = _messages.StringField(2) prediction = _messages.StringField(3) reference = _messages.StringField(4) class GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceResult(_messages.Message): r"""Spec for question answering relevance result. Fields: confidence: Output only. Confidence for question answering relevance score. explanation: Output only. Explanation for question answering relevance score. score: Output only. Question Answering Relevance score. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1QuestionAnsweringRelevanceSpec(_messages.Message): r"""Spec for question answering relevance metric. Fields: useReference: Optional. Whether to use instance.reference to compute question answering relevance. version: Optional. Which version to use for evaluation. """ useReference = _messages.BooleanField(1) version = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1RagChunk(_messages.Message): r"""A RagChunk includes the content of a chunk of a RagFile, and associated metadata. Fields: pageSpan: If populated, represents where the chunk starts and ends in the document. text: The content of the chunk. """ pageSpan = _messages.MessageField('GoogleCloudAiplatformV1beta1RagChunkPageSpan', 1) text = _messages.StringField(2) class GoogleCloudAiplatformV1beta1RagChunkPageSpan(_messages.Message): r"""Represents where the chunk starts and ends in the document. Fields: firstPage: Page where chunk starts in the document. Inclusive. 1-indexed. lastPage: Page where chunk ends in the document. Inclusive. 1-indexed. """ firstPage = _messages.IntegerField(1, variant=_messages.Variant.INT32) lastPage = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1RagContexts(_messages.Message): r"""Relevant contexts for one query. Fields: contexts: All its contexts. """ contexts = _messages.MessageField('GoogleCloudAiplatformV1beta1RagContextsContext', 1, repeated=True) class GoogleCloudAiplatformV1beta1RagContextsContext(_messages.Message): r"""A context of the query. Fields: chunk: Context of the retrieved chunk. distance: The distance between the query dense embedding vector and the context text vector. score: According to the underlying Vector DB and the selected metric type, the score can be either the distance or the similarity between the query and the context and its range depends on the metric type. For example, if the metric type is COSINE_DISTANCE, it represents the distance between the query and the context. The larger the distance, the less relevant the context is to the query. The range is [0, 2], while 0 means the most relevant and 2 means the least relevant. sourceDisplayName: The file display name. sourceUri: If the file is imported from Cloud Storage or Google Drive, source_uri will be original file URI in Cloud Storage or Google Drive; if file is uploaded, source_uri will be file display name. sparseDistance: The distance between the query sparse embedding vector and the context text vector. text: The text chunk. """ chunk = _messages.MessageField('GoogleCloudAiplatformV1beta1RagChunk', 1) distance = _messages.FloatField(2) score = _messages.FloatField(3) sourceDisplayName = _messages.StringField(4) sourceUri = _messages.StringField(5) sparseDistance = _messages.FloatField(6) text = _messages.StringField(7) class GoogleCloudAiplatformV1beta1RagCorpus(_messages.Message): r"""A RagCorpus is a RagFile container and a project can have multiple RagCorpora. Fields: corpusStatus: Output only. RagCorpus state. corpusTypeConfig: Optional. The corpus type config of the RagCorpus. createTime: Output only. Timestamp when this RagCorpus was created. description: Optional. The description of the RagCorpus. displayName: Required. The display name of the RagCorpus. The name can be up to 128 characters long and can consist of any UTF-8 characters. encryptionSpec: Optional. Immutable. The CMEK key name used to encrypt at- rest data related to this Corpus. Only applicable to RagManagedDb option for Vector DB. This field can only be set at corpus creation time, and cannot be updated or deleted. name: Output only. The resource name of the RagCorpus. ragEmbeddingModelConfig: Optional. Immutable. The embedding model config of the RagCorpus. ragFilesCount: Output only. Number of RagFiles in the RagCorpus. NOTE: This field is not populated in the response of VertexRagDataService.ListRagCorpora. ragVectorDbConfig: Optional. Immutable. The Vector DB config of the RagCorpus. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. updateTime: Output only. Timestamp when this RagCorpus was last updated. vectorDbConfig: Optional. Immutable. The config for the Vector DBs. vertexAiSearchConfig: Optional. Immutable. The config for the Vertex AI Search. """ corpusStatus = _messages.MessageField('GoogleCloudAiplatformV1beta1CorpusStatus', 1) corpusTypeConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfig', 2) createTime = _messages.StringField(3) description = _messages.StringField(4) displayName = _messages.StringField(5) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 6) name = _messages.StringField(7) ragEmbeddingModelConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagEmbeddingModelConfig', 8) ragFilesCount = _messages.IntegerField(9, variant=_messages.Variant.INT32) ragVectorDbConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagVectorDbConfig', 10) satisfiesPzi = _messages.BooleanField(11) satisfiesPzs = _messages.BooleanField(12) updateTime = _messages.StringField(13) vectorDbConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagVectorDbConfig', 14) vertexAiSearchConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1VertexAiSearchConfig', 15) class GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfig(_messages.Message): r"""The config for the corpus type of the RagCorpus. Fields: documentCorpus: Optional. Config for the document corpus. memoryCorpus: Optional. Config for the memory corpus. """ documentCorpus = _messages.MessageField('GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfigDocumentCorpus', 1) memoryCorpus = _messages.MessageField('GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfigMemoryCorpus', 2) class GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfigDocumentCorpus(_messages.Message): r"""Config for the document corpus.""" class GoogleCloudAiplatformV1beta1RagCorpusCorpusTypeConfigMemoryCorpus(_messages.Message): r"""Config for the memory corpus. Fields: llmParser: The LLM parser to use for the memory corpus. """ llmParser = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileParsingConfigLlmParser', 1) class GoogleCloudAiplatformV1beta1RagEmbeddingModelConfig(_messages.Message): r"""Config for the embedding model to use for RAG. Fields: hybridSearchConfig: Configuration for hybrid search. vertexPredictionEndpoint: The Vertex AI Prediction Endpoint that either refers to a publisher model or an endpoint that is hosting a 1P fine- tuned text embedding model. Endpoints hosting non-1P fine-tuned text embedding models are currently not supported. This is used for dense vector search. """ hybridSearchConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigHybridSearchConfig', 1) vertexPredictionEndpoint = _messages.MessageField('GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigVertexPredictionEndpoint', 2) class GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigHybridSearchConfig(_messages.Message): r"""Config for hybrid search. Fields: denseEmbeddingModelPredictionEndpoint: Required. The Vertex AI Prediction Endpoint that hosts the embedding model for dense embedding generations. sparseEmbeddingConfig: Optional. The configuration for sparse embedding generation. This field is optional the default behavior depends on the vector database choice on the RagCorpus. """ denseEmbeddingModelPredictionEndpoint = _messages.MessageField('GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigVertexPredictionEndpoint', 1) sparseEmbeddingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigSparseEmbeddingConfig', 2) class GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigSparseEmbeddingConfig(_messages.Message): r"""Configuration for sparse emebdding generation. Fields: bm25: Use BM25 scoring algorithm. """ bm25 = _messages.MessageField('GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigSparseEmbeddingConfigBm25', 1) class GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigSparseEmbeddingConfigBm25(_messages.Message): r"""Message for BM25 parameters. Fields: b: Optional. The parameter to control document length normalization. It determines how much the document length affects the final score. b is in the range of [0, 1]. The default value is 0.75. k1: Optional. The parameter to control term frequency saturation. It determines the scaling between the matching term frequency and final score. k1 is in the range of [1.2, 3]. The default value is 1.2. multilingual: Optional. Use multilingual tokenizer if set to true. """ b = _messages.FloatField(1, variant=_messages.Variant.FLOAT) k1 = _messages.FloatField(2, variant=_messages.Variant.FLOAT) multilingual = _messages.BooleanField(3) class GoogleCloudAiplatformV1beta1RagEmbeddingModelConfigVertexPredictionEndpoint(_messages.Message): r"""Config representing a model hosted on Vertex Prediction Endpoint. Fields: endpoint: Required. The endpoint resource name. Format: `projects/{project }/locations/{location}/publishers/{publisher}/models/{model}` or `projects/{project}/locations/{location}/endpoints/{endpoint}` model: Output only. The resource name of the model that is deployed on the endpoint. Present only when the endpoint is not a publisher model. Pattern: `projects/{project}/locations/{location}/models/{model}` modelVersionId: Output only. Version ID of the model that is deployed on the endpoint. Present only when the endpoint is not a publisher model. """ endpoint = _messages.StringField(1) model = _messages.StringField(2) modelVersionId = _messages.StringField(3) class GoogleCloudAiplatformV1beta1RagEngineConfig(_messages.Message): r"""Config for RagEngine. Fields: name: Identifier. The name of the RagEngineConfig. Format: `projects/{project}/locations/{location}/ragEngineConfig` ragManagedDbConfig: The config of the RagManagedDb used by RagEngine. """ name = _messages.StringField(1) ragManagedDbConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagManagedDbConfig', 2) class GoogleCloudAiplatformV1beta1RagFile(_messages.Message): r"""A RagFile contains user data for chunking, embedding and indexing. Enums: RagFileTypeValueValuesEnum: Output only. The type of the RagFile. Fields: createTime: Output only. Timestamp when this RagFile was created. description: Optional. The description of the RagFile. directUploadSource: Output only. The RagFile is encapsulated and uploaded in the UploadRagFile request. displayName: Required. The display name of the RagFile. The name can be up to 128 characters long and can consist of any UTF-8 characters. fileStatus: Output only. State of the RagFile. gcsSource: Output only. Google Cloud Storage location of the RagFile. It does not support wildcards in the Cloud Storage uri for now. googleDriveSource: Output only. Google Drive location. Supports importing individual files as well as Google Drive folders. jiraSource: The RagFile is imported from a Jira query. name: Output only. The resource name of the RagFile. ragFileType: Output only. The type of the RagFile. sharePointSources: The RagFile is imported from a SharePoint source. sizeBytes: Output only. The size of the RagFile in bytes. slackSource: The RagFile is imported from a Slack channel. updateTime: Output only. Timestamp when this RagFile was last updated. userMetadata: Output only. The metadata for metadata search. The user_metadata Needs to be in JSON format. """ class RagFileTypeValueValuesEnum(_messages.Enum): r"""Output only. The type of the RagFile. Values: RAG_FILE_TYPE_UNSPECIFIED: RagFile type is unspecified. RAG_FILE_TYPE_TXT: RagFile type is TXT. RAG_FILE_TYPE_PDF: RagFile type is PDF. """ RAG_FILE_TYPE_UNSPECIFIED = 0 RAG_FILE_TYPE_TXT = 1 RAG_FILE_TYPE_PDF = 2 createTime = _messages.StringField(1) description = _messages.StringField(2) directUploadSource = _messages.MessageField('GoogleCloudAiplatformV1beta1DirectUploadSource', 3) displayName = _messages.StringField(4) fileStatus = _messages.MessageField('GoogleCloudAiplatformV1beta1FileStatus', 5) gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsSource', 6) googleDriveSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GoogleDriveSource', 7) jiraSource = _messages.MessageField('GoogleCloudAiplatformV1beta1JiraSource', 8) name = _messages.StringField(9) ragFileType = _messages.EnumField('RagFileTypeValueValuesEnum', 10) sharePointSources = _messages.MessageField('GoogleCloudAiplatformV1beta1SharePointSources', 11) sizeBytes = _messages.IntegerField(12) slackSource = _messages.MessageField('GoogleCloudAiplatformV1beta1SlackSource', 13) updateTime = _messages.StringField(14) userMetadata = _messages.StringField(15) class GoogleCloudAiplatformV1beta1RagFileChunkingConfig(_messages.Message): r"""Specifies the size and overlap of chunks for RagFiles. Fields: chunkOverlap: The overlap between chunks. chunkSize: The size of the chunks. fixedLengthChunking: Specifies the fixed length chunking config. """ chunkOverlap = _messages.IntegerField(1, variant=_messages.Variant.INT32) chunkSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) fixedLengthChunking = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileChunkingConfigFixedLengthChunking', 3) class GoogleCloudAiplatformV1beta1RagFileChunkingConfigFixedLengthChunking(_messages.Message): r"""Specifies the fixed length chunking config. Fields: chunkOverlap: The overlap between chunks. chunkSize: The size of the chunks. """ chunkOverlap = _messages.IntegerField(1, variant=_messages.Variant.INT32) chunkSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1RagFileMetadataConfig(_messages.Message): r"""Metadata config for RagFile. Fields: gcsMetadataSchemaSource: Google Cloud Storage location. Supports importing individual files as well as entire Google Cloud Storage directories. Sample formats: - `gs://bucket_name/my_directory/object_name/metadata_schema.json` - `gs://bucket_name/my_directory` If the user provides a directory, the metadata schema will be read from the files that ends with "metadata_schema.json" in the directory. gcsMetadataSource: Google Cloud Storage location. Supports importing individual files as well as entire Google Cloud Storage directories. Sample formats: - `gs://bucket_name/my_directory/object_name/metadata.json` - `gs://bucket_name/my_directory` If the user provides a directory, the metadata will be read from the files that ends with "metadata.json" in the directory. googleDriveMetadataSchemaSource: Google Drive location. Supports importing individual files as well as Google Drive folders. If the user provides a folder, the metadata schema will be read from the files that ends with "metadata_schema.json" in the directory. googleDriveMetadataSource: Google Drive location. Supports importing individual files as well as Google Drive folders. If the user provides a directory, the metadata will be read from the files that ends with "metadata.json" in the directory. inlineMetadataSchemaSource: Inline metadata schema source. Must be a JSON string. inlineMetadataSource: Inline metadata source. Must be a JSON string. """ gcsMetadataSchemaSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsSource', 1) gcsMetadataSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsSource', 2) googleDriveMetadataSchemaSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GoogleDriveSource', 3) googleDriveMetadataSource = _messages.MessageField('GoogleCloudAiplatformV1beta1GoogleDriveSource', 4) inlineMetadataSchemaSource = _messages.StringField(5) inlineMetadataSource = _messages.StringField(6) class GoogleCloudAiplatformV1beta1RagFileParsingConfig(_messages.Message): r"""Specifies the parsing config for RagFiles. Fields: advancedParser: The Advanced Parser to use for RagFiles. layoutParser: The Layout Parser to use for RagFiles. llmParser: The LLM Parser to use for RagFiles. useAdvancedPdfParsing: Whether to use advanced PDF parsing. """ advancedParser = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileParsingConfigAdvancedParser', 1) layoutParser = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileParsingConfigLayoutParser', 2) llmParser = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileParsingConfigLlmParser', 3) useAdvancedPdfParsing = _messages.BooleanField(4) class GoogleCloudAiplatformV1beta1RagFileParsingConfigAdvancedParser(_messages.Message): r"""Specifies the advanced parsing for RagFiles. Fields: useAdvancedPdfParsing: Whether to use advanced PDF parsing. """ useAdvancedPdfParsing = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1RagFileParsingConfigLayoutParser(_messages.Message): r"""Document AI Layout Parser config. Fields: globalMaxParsingRequestsPerMin: The maximum number of requests the job is allowed to make to the Document AI processor per minute in this project. Consult https://cloud.google.com/document-ai/quotas and the Quota page for your project to set an appropriate value here. If this value is not specified, max_parsing_requests_per_min will be used by indexing pipeline as the global limit. maxParsingRequestsPerMin: The maximum number of requests the job is allowed to make to the Document AI processor per minute. Consult https://cloud.google.com/document-ai/quotas and the Quota page for your project to set an appropriate value here. If unspecified, a default value of 120 QPM would be used. processorName: The full resource name of a Document AI processor or processor version. The processor must have type `LAYOUT_PARSER_PROCESSOR`. If specified, the `additional_config.parse_as_scanned_pdf` field must be false. Format: * `projects/{project_id}/locations/{location}/processors/{processor_id}` * `projects/{project_id}/locations/{location}/processors/{processor_id}/pr ocessorVersions/{processor_version_id}` """ globalMaxParsingRequestsPerMin = _messages.IntegerField(1, variant=_messages.Variant.INT32) maxParsingRequestsPerMin = _messages.IntegerField(2, variant=_messages.Variant.INT32) processorName = _messages.StringField(3) class GoogleCloudAiplatformV1beta1RagFileParsingConfigLlmParser(_messages.Message): r"""Specifies the LLM parsing for RagFiles. Fields: customParsingPrompt: The prompt to use for parsing. If not specified, a default prompt will be used. globalMaxParsingRequestsPerMin: The maximum number of requests the job is allowed to make to the LLM model per minute in this project. Consult https://cloud.google.com/vertex-ai/generative-ai/docs/quotas and your document size to set an appropriate value here. If this value is not specified, max_parsing_requests_per_min will be used by indexing pipeline job as the global limit. maxParsingRequestsPerMin: The maximum number of requests the job is allowed to make to the LLM model per minute. Consult https://cloud.google.com/vertex-ai/generative-ai/docs/quotas and your document size to set an appropriate value here. If unspecified, a default value of 5000 QPM would be used. modelName: The name of a LLM model used for parsing. Format: * `projects/{ project_id}/locations/{location}/publishers/{publisher}/models/{model}` """ customParsingPrompt = _messages.StringField(1) globalMaxParsingRequestsPerMin = _messages.IntegerField(2, variant=_messages.Variant.INT32) maxParsingRequestsPerMin = _messages.IntegerField(3, variant=_messages.Variant.INT32) modelName = _messages.StringField(4) class GoogleCloudAiplatformV1beta1RagFileTransformationConfig(_messages.Message): r"""Specifies the transformation config for RagFiles. Fields: ragFileChunkingConfig: Specifies the chunking config for RagFiles. """ ragFileChunkingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileChunkingConfig', 1) class GoogleCloudAiplatformV1beta1RagManagedDbConfig(_messages.Message): r"""Configuration message for RagManagedDb used by RagEngine. Fields: basic: Sets the RagManagedDb to the Basic tier. enterprise: Sets the RagManagedDb to the Enterprise tier. scaled: Sets the RagManagedDb to the Scaled tier. This is the default tier if not explicitly chosen. unprovisioned: Sets the RagManagedDb to the Unprovisioned tier. """ basic = _messages.MessageField('GoogleCloudAiplatformV1beta1RagManagedDbConfigBasic', 1) enterprise = _messages.MessageField('GoogleCloudAiplatformV1beta1RagManagedDbConfigEnterprise', 2) scaled = _messages.MessageField('GoogleCloudAiplatformV1beta1RagManagedDbConfigScaled', 3) unprovisioned = _messages.MessageField('GoogleCloudAiplatformV1beta1RagManagedDbConfigUnprovisioned', 4) class GoogleCloudAiplatformV1beta1RagManagedDbConfigBasic(_messages.Message): r"""Basic tier is a cost-effective and low compute tier suitable for the following cases: * Experimenting with RagManagedDb. * Small data size. * Latency insensitive workload. * Only using RAG Engine with external vector DBs. NOTE: This is the default tier if not explicitly chosen. """ class GoogleCloudAiplatformV1beta1RagManagedDbConfigEnterprise(_messages.Message): r"""Enterprise tier offers production grade performance along with autoscaling functionality. It is suitable for customers with large amounts of data or performance sensitive workloads. """ class GoogleCloudAiplatformV1beta1RagManagedDbConfigScaled(_messages.Message): r"""Scaled tier offers production grade performance along with autoscaling functionality. It is suitable for customers with large amounts of data or performance sensitive workloads. """ class GoogleCloudAiplatformV1beta1RagManagedDbConfigUnprovisioned(_messages.Message): r"""Disables the RAG Engine service and deletes all your data held within this service. This will halt the billing of the service. NOTE: Once deleted the data cannot be recovered. To start using RAG Engine again, you will need to update the tier by calling the UpdateRagEngineConfig API. """ class GoogleCloudAiplatformV1beta1RagQuery(_messages.Message): r"""A query to retrieve relevant contexts. Fields: ragRetrievalConfig: Optional. The retrieval config for the query. ranking: Optional. Configurations for hybrid search results ranking. similarityTopK: Optional. The number of contexts to retrieve. text: Optional. The query in text format to get relevant contexts. """ ragRetrievalConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagRetrievalConfig', 1) ranking = _messages.MessageField('GoogleCloudAiplatformV1beta1RagQueryRanking', 2) similarityTopK = _messages.IntegerField(3, variant=_messages.Variant.INT32) text = _messages.StringField(4) class GoogleCloudAiplatformV1beta1RagQueryRanking(_messages.Message): r"""Configurations for hybrid search results ranking. Fields: alpha: Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally. """ alpha = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1RagRetrievalConfig(_messages.Message): r"""Specifies the context retrieval config. Fields: filter: Optional. Config for filters. hybridSearch: Optional. Config for Hybrid Search. ranking: Optional. Config for ranking and reranking. topK: Optional. The number of contexts to retrieve. """ filter = _messages.MessageField('GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter', 1) hybridSearch = _messages.MessageField('GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch', 2) ranking = _messages.MessageField('GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking', 3) topK = _messages.IntegerField(4, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1RagRetrievalConfigFilter(_messages.Message): r"""Config for filters. Fields: metadataFilter: Optional. String for metadata filtering. vectorDistanceThreshold: Optional. Only returns contexts with vector distance smaller than the threshold. vectorSimilarityThreshold: Optional. Only returns contexts with vector similarity larger than the threshold. """ metadataFilter = _messages.StringField(1) vectorDistanceThreshold = _messages.FloatField(2) vectorSimilarityThreshold = _messages.FloatField(3) class GoogleCloudAiplatformV1beta1RagRetrievalConfigHybridSearch(_messages.Message): r"""Config for Hybrid Search. Fields: alpha: Optional. Alpha value controls the weight between dense and sparse vector search results. The range is [0, 1], while 0 means sparse vector search only and 1 means dense vector search only. The default value is 0.5 which balances sparse and dense vector search equally. """ alpha = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1RagRetrievalConfigRanking(_messages.Message): r"""Config for ranking and reranking. Fields: llmRanker: Optional. Config for LlmRanker. rankService: Optional. Config for Rank Service. """ llmRanker = _messages.MessageField('GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker', 1) rankService = _messages.MessageField('GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService', 2) class GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingLlmRanker(_messages.Message): r"""Config for LlmRanker. Fields: modelName: Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model- reference/inference#supported-models). """ modelName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1RagRetrievalConfigRankingRankService(_messages.Message): r"""Config for Rank Service. Fields: modelName: Optional. The model name of the rank service. Format: `semantic-ranker-512@latest` """ modelName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1RagVectorDbConfig(_messages.Message): r"""Config for the Vector DB to use for RAG. Fields: apiAuth: Authentication config for the chosen Vector DB. pinecone: The config for the Pinecone. ragEmbeddingModelConfig: Optional. Immutable. The embedding model config of the Vector DB. ragManagedDb: The config for the RAG-managed Vector DB. vertexFeatureStore: The config for the Vertex Feature Store. vertexVectorSearch: The config for the Vertex Vector Search. weaviate: The config for the Weaviate. """ apiAuth = _messages.MessageField('GoogleCloudAiplatformV1beta1ApiAuth', 1) pinecone = _messages.MessageField('GoogleCloudAiplatformV1beta1RagVectorDbConfigPinecone', 2) ragEmbeddingModelConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagEmbeddingModelConfig', 3) ragManagedDb = _messages.MessageField('GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDb', 4) vertexFeatureStore = _messages.MessageField('GoogleCloudAiplatformV1beta1RagVectorDbConfigVertexFeatureStore', 5) vertexVectorSearch = _messages.MessageField('GoogleCloudAiplatformV1beta1RagVectorDbConfigVertexVectorSearch', 6) weaviate = _messages.MessageField('GoogleCloudAiplatformV1beta1RagVectorDbConfigWeaviate', 7) class GoogleCloudAiplatformV1beta1RagVectorDbConfigPinecone(_messages.Message): r"""The config for the Pinecone. Fields: indexName: Pinecone index name. This value cannot be changed after it's set. """ indexName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDb(_messages.Message): r"""The config for the default RAG-managed Vector DB. Fields: ann: Performs an ANN search on RagCorpus. Use this if you have a lot of files (> 10K) in your RagCorpus and want to reduce the search latency. knn: Performs a KNN search on RagCorpus. Default choice if not specified. """ ann = _messages.MessageField('GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDbANN', 1) knn = _messages.MessageField('GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDbKNN', 2) class GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDbANN(_messages.Message): r"""Config for ANN search. RagManagedDb uses a tree-based structure to partition data and facilitate faster searches. As a tradeoff, it requires longer indexing time and manual triggering of index rebuild via the ImportRagFiles and UpdateRagCorpus API. Fields: leafCount: Number of leaf nodes in the tree-based structure. Each leaf node contains groups of closely related vectors along with their corresponding centroid. Recommended value is 10 * sqrt(num of RagFiles in your RagCorpus). Default value is 500. treeDepth: The depth of the tree-based structure. Only depth values of 2 and 3 are supported. Recommended value is 2 if you have if you have O(10K) files in the RagCorpus and set this to 3 if more than that. Default value is 2. """ leafCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) treeDepth = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1RagVectorDbConfigRagManagedDbKNN(_messages.Message): r"""Config for KNN search.""" class GoogleCloudAiplatformV1beta1RagVectorDbConfigVertexFeatureStore(_messages.Message): r"""The config for the Vertex Feature Store. Fields: featureViewResourceName: The resource name of the FeatureView. Format: `pr ojects/{project}/locations/{location}/featureOnlineStores/{feature_onlin e_store}/featureViews/{feature_view}` """ featureViewResourceName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1RagVectorDbConfigVertexVectorSearch(_messages.Message): r"""The config for the Vertex Vector Search. Fields: index: The resource name of the Index. Format: `projects/{project}/locations/{location}/indexes/{index}` indexEndpoint: The resource name of the Index Endpoint. Format: `projects/{project}/locations/{location}/indexEndpoints/{index_endpoint} ` """ index = _messages.StringField(1) indexEndpoint = _messages.StringField(2) class GoogleCloudAiplatformV1beta1RagVectorDbConfigWeaviate(_messages.Message): r"""The config for the Weaviate. Fields: collectionName: The corresponding collection this corpus maps to. This value cannot be changed after it's set. httpEndpoint: Weaviate DB instance HTTP endpoint. e.g. 34.56.78.90:8080 Vertex RAG only supports HTTP connection to Weaviate. This value cannot be changed after it's set. """ collectionName = _messages.StringField(1) httpEndpoint = _messages.StringField(2) class GoogleCloudAiplatformV1beta1RawOutput(_messages.Message): r"""Raw output. Fields: rawOutput: Output only. Raw output string. """ rawOutput = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1RawPredictRequest(_messages.Message): r"""Request message for PredictionService.RawPredict. Fields: httpBody: The prediction input. Supports HTTP headers and arbitrary data payload. A DeployedModel may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the RawPredict method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the predict_schemata.instance_schema_uri field when you create a Model. This schema applies when you deploy the `Model` as a `DeployedModel` to an Endpoint and use the `RawPredict` method. """ httpBody = _messages.MessageField('GoogleApiHttpBody', 1) class GoogleCloudAiplatformV1beta1RayLogsSpec(_messages.Message): r"""Configuration for the Ray OSS Logs. Fields: disabled: Optional. Flag to disable the export of Ray OSS logs to Cloud Logging. """ disabled = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1RayMetricSpec(_messages.Message): r"""Configuration for the Ray metrics. Fields: disabled: Optional. Flag to disable the Ray metrics collection. """ disabled = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1RaySpec(_messages.Message): r"""Configuration information for the Ray cluster. For experimental launch, Ray cluster creation and Persistent cluster creation are 1:1 mapping: We will provision all the nodes within the Persistent cluster as Ray nodes. Messages: ResourcePoolImagesValue: Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { "ray_head_node_pool": "head image" "ray_worker_node_pool1": "worker image" "ray_worker_node_pool2": "another worker image" } Fields: headNodeResourcePoolId: Optional. This will be used to indicate which resource pool will serve as the Ray head node(the first node within that pool). Will use the machine from the first workerpool as the head node by default if this field isn't set. imageUri: Optional. Default image for user to choose a preferred ML framework (for example, TensorFlow or Pytorch) by choosing from [Vertex prebuilt images](https://cloud.google.com/vertex-ai/docs/training/pre- built-containers). Either this or the resource_pool_images is required. Use this field if you need all the resource pools to have the same Ray image. Otherwise, use the {@code resource_pool_images} field. nfsMounts: Optional. Use if you want to mount to any NFS storages. rayLogsSpec: Optional. OSS Ray logging configurations. rayMetricSpec: Optional. Ray metrics configurations. resourcePoolImages: Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { "ray_head_node_pool": "head image" "ray_worker_node_pool1": "worker image" "ray_worker_node_pool2": "another worker image" } """ @encoding.MapUnrecognizedFields('additionalProperties') class ResourcePoolImagesValue(_messages.Message): r"""Optional. Required if image_uri isn't set. A map of resource_pool_id to prebuild Ray image if user need to use different images for different head/worker pools. This map needs to cover all the resource pool ids. Example: { "ray_head_node_pool": "head image" "ray_worker_node_pool1": "worker image" "ray_worker_node_pool2": "another worker image" } Messages: AdditionalProperty: An additional property for a ResourcePoolImagesValue object. Fields: additionalProperties: Additional properties of type ResourcePoolImagesValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ResourcePoolImagesValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) headNodeResourcePoolId = _messages.StringField(1) imageUri = _messages.StringField(2) nfsMounts = _messages.MessageField('GoogleCloudAiplatformV1beta1NfsMount', 3, repeated=True) rayLogsSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1RayLogsSpec', 4) rayMetricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1RayMetricSpec', 5) resourcePoolImages = _messages.MessageField('ResourcePoolImagesValue', 6) class GoogleCloudAiplatformV1beta1ReadFeatureValuesRequest(_messages.Message): r"""Request message for FeaturestoreOnlineServingService.ReadFeatureValues. Fields: entityId: Required. ID for a specific entity. For example, for a machine learning model predicting user clicks on a website, an entity ID could be `user_123`. featureSelector: Required. Selector choosing Features of the target EntityType. """ entityId = _messages.StringField(1) featureSelector = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureSelector', 2) class GoogleCloudAiplatformV1beta1ReadFeatureValuesResponse(_messages.Message): r"""Response message for FeaturestoreOnlineServingService.ReadFeatureValues. Fields: entityView: Entity view with Feature values. This may be the entity in the Featurestore if values for all Features were requested, or a projection of the entity in the Featurestore if values for only some Features were requested. header: Response header. """ entityView = _messages.MessageField('GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityView', 1) header = _messages.MessageField('GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseHeader', 2) class GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityView(_messages.Message): r"""Entity view with Feature values. Fields: data: Each piece of data holds the k requested values for one requested Feature. If no values for the requested Feature exist, the corresponding cell will be empty. This has the same size and is in the same order as the features from the header ReadFeatureValuesResponse.header. entityId: ID of the requested entity. """ data = _messages.MessageField('GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityViewData', 1, repeated=True) entityId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseEntityViewData(_messages.Message): r"""Container to hold value(s), successive in time, for one Feature from the request. Fields: value: Feature value if a single value is requested. values: Feature values list if values, successive in time, are requested. If the requested number of values is greater than the number of existing Feature values, nonexistent values are omitted instead of being returned as empty. """ value = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureValue', 1) values = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureValueList', 2) class GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseFeatureDescriptor(_messages.Message): r"""Metadata for requested Features. Fields: id: Feature ID. """ id = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseHeader(_messages.Message): r"""Response header with metadata for the requested ReadFeatureValuesRequest.entity_type and Features. Fields: entityType: The resource name of the EntityType from the ReadFeatureValuesRequest. Value format: `projects/{project}/locations/{l ocation}/featurestores/{featurestore}/entityTypes/{entityType}`. featureDescriptors: List of Feature metadata corresponding to each piece of ReadFeatureValuesResponse.EntityView.data. """ entityType = _messages.StringField(1) featureDescriptors = _messages.MessageField('GoogleCloudAiplatformV1beta1ReadFeatureValuesResponseFeatureDescriptor', 2, repeated=True) class GoogleCloudAiplatformV1beta1ReadIndexDatapointsRequest(_messages.Message): r"""The request message for MatchService.ReadIndexDatapoints. Fields: deployedIndexId: The ID of the DeployedIndex that will serve the request. ids: IDs of the datapoints to be searched for. """ deployedIndexId = _messages.StringField(1) ids = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1ReadIndexDatapointsResponse(_messages.Message): r"""The response message for MatchService.ReadIndexDatapoints. Fields: datapoints: The result list of datapoints. """ datapoints = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexDatapoint', 1, repeated=True) class GoogleCloudAiplatformV1beta1ReadTensorboardBlobDataResponse(_messages.Message): r"""Response message for TensorboardService.ReadTensorboardBlobData. Fields: blobs: Blob messages containing blob bytes. """ blobs = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardBlob', 1, repeated=True) class GoogleCloudAiplatformV1beta1ReadTensorboardSizeResponse(_messages.Message): r"""Response message for TensorboardService.ReadTensorboardSize. Fields: storageSizeByte: Payload storage size for the TensorBoard """ storageSizeByte = _messages.IntegerField(1) class GoogleCloudAiplatformV1beta1ReadTensorboardTimeSeriesDataResponse(_messages.Message): r"""Response message for TensorboardService.ReadTensorboardTimeSeriesData. Fields: timeSeriesData: The returned time series data. """ timeSeriesData = _messages.MessageField('GoogleCloudAiplatformV1beta1TimeSeriesData', 1) class GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponse(_messages.Message): r"""Response message for TensorboardService.ReadTensorboardUsage. Messages: MonthlyUsageDataValue: Maps year-month (YYYYMM) string to per month usage data. Fields: monthlyUsageData: Maps year-month (YYYYMM) string to per month usage data. """ @encoding.MapUnrecognizedFields('additionalProperties') class MonthlyUsageDataValue(_messages.Message): r"""Maps year-month (YYYYMM) string to per month usage data. Messages: AdditionalProperty: An additional property for a MonthlyUsageDataValue object. Fields: additionalProperties: Additional properties of type MonthlyUsageDataValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a MonthlyUsageDataValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerMo nthUsageData attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerMonthUsageData', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) monthlyUsageData = _messages.MessageField('MonthlyUsageDataValue', 1) class GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerMonthUsageData(_messages.Message): r"""Per month usage data Fields: userUsageData: Usage data for each user in the given month. """ userUsageData = _messages.MessageField('GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerUserUsageData', 1, repeated=True) class GoogleCloudAiplatformV1beta1ReadTensorboardUsageResponsePerUserUsageData(_messages.Message): r"""Per user usage data. Fields: username: User's username viewCount: Number of times the user has read data within the Tensorboard. """ username = _messages.StringField(1) viewCount = _messages.IntegerField(2) class GoogleCloudAiplatformV1beta1ReasoningEngine(_messages.Message): r"""ReasoningEngine provides a customizable runtime for models to determine which actions to take and in which order. Messages: LabelsValue: Labels for the ReasoningEngine. Fields: contextSpec: Optional. Configuration for how Agent Engine sub-resources should manage context. createTime: Output only. Timestamp when this ReasoningEngine was created. description: Optional. The description of the ReasoningEngine. displayName: Required. The display name of the ReasoningEngine. encryptionSpec: Customer-managed encryption key spec for a ReasoningEngine. If set, this ReasoningEngine and all sub-resources of this ReasoningEngine will be secured by this key. etag: Optional. Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: Labels for the ReasoningEngine. name: Identifier. The resource name of the ReasoningEngine. Format: `proje cts/{project}/locations/{location}/reasoningEngines/{reasoning_engine}` spec: Optional. Configurations of the ReasoningEngine updateTime: Output only. Timestamp when this ReasoningEngine was most recently updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Labels for the ReasoningEngine. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) contextSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngineContextSpec', 1) createTime = _messages.StringField(2) description = _messages.StringField(3) displayName = _messages.StringField(4) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 5) etag = _messages.StringField(6) labels = _messages.MessageField('LabelsValue', 7) name = _messages.StringField(8) spec = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngineSpec', 9) updateTime = _messages.StringField(10) class GoogleCloudAiplatformV1beta1ReasoningEngineContextSpec(_messages.Message): r"""Configuration for how Agent Engine sub-resources should manage context. Fields: memoryBankConfig: Optional. Specification for a Memory Bank, which manages memories for the Agent Engine. """ memoryBankConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfig', 1) class GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfig(_messages.Message): r"""Specification for a Memory Bank. Fields: customizationConfigs: Optional. Configuration for how to customize Memory Bank behavior for a particular scope. disableMemoryRevisions: If true, no memory revisions will be created for any requests to the Memory Bank. generationConfig: Optional. Configuration for how to generate memories for the Memory Bank. similaritySearchConfig: Optional. Configuration for how to perform similarity search on memories. If not set, the Memory Bank will use the default embedding model `text-embedding-005`. ttlConfig: Optional. Configuration for automatic TTL ("time-to-live") of the memories in the Memory Bank. If not set, TTL will not be applied automatically. The TTL can be explicitly set by modifying the `expire_time` of each Memory resource. """ customizationConfigs = _messages.MessageField('GoogleCloudAiplatformV1beta1MemoryBankCustomizationConfig', 1, repeated=True) disableMemoryRevisions = _messages.BooleanField(2) generationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigGenerationConfig', 3) similaritySearchConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigSimilaritySearchConfig', 4) ttlConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigTtlConfig', 5) class GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigGenerationConfig(_messages.Message): r"""Configuration for how to generate memories. Fields: model: Required. The model used to generate memories. Format: `projects/{p roject}/locations/{location}/publishers/google/models/{model}`. """ model = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigSimilaritySearchConfig(_messages.Message): r"""Configuration for how to perform similarity search on memories. Fields: embeddingModel: Required. The model used to generate embeddings to lookup similar memories. Format: `projects/{project}/locations/{location}/publi shers/google/models/{model}`. """ embeddingModel = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigTtlConfig(_messages.Message): r"""Configuration for automatically setting the TTL ("time-to-live") of the memories in the Memory Bank. Fields: defaultTtl: Optional. The default TTL duration of the memories in the Memory Bank. This applies to all operations that create or update a memory. granularTtlConfig: Optional. The granular TTL configuration of the memories in the Memory Bank. memoryRevisionDefaultTtl: Optional. The default TTL duration of the memory revisions in the Memory Bank. This applies to all operations that create a memory revision. If not set, a default TTL of 365 days will be used. """ defaultTtl = _messages.StringField(1) granularTtlConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigTtlConfigGranularTtlConfig', 2) memoryRevisionDefaultTtl = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ReasoningEngineContextSpecMemoryBankConfigTtlConfigGranularTtlConfig(_messages.Message): r"""Configuration for TTL of the memories in the Memory Bank based on the action that created or updated the memory. Fields: createTtl: Optional. The TTL duration for memories uploaded via CreateMemory. generateCreatedTtl: Optional. The TTL duration for memories newly generated via GenerateMemories (GenerateMemoriesResponse.GeneratedMemory.Action.CREATED). generateUpdatedTtl: Optional. The TTL duration for memories updated via GenerateMemories (GenerateMemoriesResponse.GeneratedMemory.Action.UPDATED). In the case of an UPDATE action, the `expire_time` of the existing memory will be updated to the new value (now + TTL). """ createTtl = _messages.StringField(1) generateCreatedTtl = _messages.StringField(2) generateUpdatedTtl = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ReasoningEngineSpec(_messages.Message): r"""ReasoningEngine configurations Enums: IdentityTypeValueValuesEnum: Optional. The identity type to use for the Reasoning Engine. If not specified, the `service_account` field will be used if set, otherwise the default Vertex AI Reasoning Engine Service Agent in the project will be used. Messages: AgentCardValue: Optional. The A2A Agent Card for the agent (if available). It follows the specification at https://a2a-protocol.org/latest/specification/#5-agent-discovery-the- agent-card. ClassMethodsValueListEntry: A ClassMethodsValueListEntry object. Fields: agentCard: Optional. The A2A Agent Card for the agent (if available). It follows the specification at https://a2a-protocol.org/latest/specification/#5-agent-discovery-the- agent-card. agentFramework: Optional. The OSS agent framework used to develop the agent. Currently supported values: "google-adk", "langchain", "langgraph", "ag2", "llama-index", "custom". classMethods: Optional. Declarations for object class methods in OpenAPI specification format. deploymentSpec: Optional. The specification of a Reasoning Engine deployment. effectiveIdentity: Output only. The identity to use for the Reasoning Engine. It can contain one of the following values: * service-{project}@gcp-sa-aiplatform-re.googleapis.com (for SERVICE_AGENT identity type) * {name}@{project}.gserviceaccount.com (for SERVICE_ACCOUNT identity type) * agents.global.{org}.system.id.goog/reso urces/aiplatform/projects/{project}/locations/{location}/reasoningEngine s/{reasoning_engine} (for AGENT_IDENTITY identity type) identityType: Optional. The identity type to use for the Reasoning Engine. If not specified, the `service_account` field will be used if set, otherwise the default Vertex AI Reasoning Engine Service Agent in the project will be used. packageSpec: Optional. User provided package spec of the ReasoningEngine. Ignored when users directly specify a deployment image through `deployment_spec.first_party_image_override`, but keeping the field_behavior to avoid introducing breaking changes. The `deployment_source` field should not be set if `package_spec` is specified. serviceAccount: Optional. The service account that the Reasoning Engine artifact runs as. It should have "roles/storage.objectViewer" for reading the user project's Cloud Storage and "roles/aiplatform.user" for using Vertex extensions. If not specified, the Vertex AI Reasoning Engine Service Agent in the project will be used. sourceCodeSpec: Deploy from source code files with a defined entrypoint. """ class IdentityTypeValueValuesEnum(_messages.Enum): r"""Optional. The identity type to use for the Reasoning Engine. If not specified, the `service_account` field will be used if set, otherwise the default Vertex AI Reasoning Engine Service Agent in the project will be used. Values: IDENTITY_TYPE_UNSPECIFIED: Default value. Use a custom service account if the `service_account` field is set, otherwise use the default Vertex AI Reasoning Engine Service Agent in the project. Same behavior as SERVICE_ACCOUNT. SERVICE_ACCOUNT: Use a custom service account if the `service_account` field is set, otherwise use the default Vertex AI Reasoning Engine Service Agent in the project. AGENT_IDENTITY: Use Agent Identity. The `service_account` field must not be set. """ IDENTITY_TYPE_UNSPECIFIED = 0 SERVICE_ACCOUNT = 1 AGENT_IDENTITY = 2 @encoding.MapUnrecognizedFields('additionalProperties') class AgentCardValue(_messages.Message): r"""Optional. The A2A Agent Card for the agent (if available). It follows the specification at https://a2a-protocol.org/latest/specification/#5-agent-discovery-the- agent-card. Messages: AdditionalProperty: An additional property for a AgentCardValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a AgentCardValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class ClassMethodsValueListEntry(_messages.Message): r"""A ClassMethodsValueListEntry object. Messages: AdditionalProperty: An additional property for a ClassMethodsValueListEntry object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a ClassMethodsValueListEntry object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) agentCard = _messages.MessageField('AgentCardValue', 1) agentFramework = _messages.StringField(2) classMethods = _messages.MessageField('ClassMethodsValueListEntry', 3, repeated=True) deploymentSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpec', 4) effectiveIdentity = _messages.StringField(5) identityType = _messages.EnumField('IdentityTypeValueValuesEnum', 6) packageSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngineSpecPackageSpec', 7) serviceAccount = _messages.StringField(8) sourceCodeSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpec', 9) class GoogleCloudAiplatformV1beta1ReasoningEngineSpecDeploymentSpec(_messages.Message): r"""The specification of a Reasoning Engine deployment. Enums: AgentServerModeValueValuesEnum: The agent server mode. Messages: ResourceLimitsValue: Optional. Resource limits for each container. Only 'cpu' and 'memory' keys are supported. Defaults to {"cpu": "4", "memory": "4Gi"}. * The only supported values for CPU are '1', '2', '4', '6' and '8'. For more information, go to https://cloud.google.com/run/docs/configuring/cpu. * The only supported values for memory are '1Gi', '2Gi', ... '32 Gi'. * For required cpu on different memory values, go to https://cloud.google.com/run/docs/configuring/memory-limits Fields: agentServerMode: The agent server mode. containerConcurrency: Optional. Concurrency for each container and agent server. Recommended value: 2 * cpu + 1. Defaults to 9. env: Optional. Environment variables to be set with the Reasoning Engine deployment. The environment variables can be updated through the UpdateReasoningEngine API. maxInstances: Optional. The maximum number of application instances that can be launched to handle increased traffic. Defaults to 100. Range: [1, 1000]. If VPC-SC or PSC-I is enabled, the acceptable range is [1, 100]. minInstances: Optional. The minimum number of application instances that will be kept running at all times. Defaults to 1. Range: [0, 10]. pscInterfaceConfig: Optional. Configuration for PSC-I. resourceLimits: Optional. Resource limits for each container. Only 'cpu' and 'memory' keys are supported. Defaults to {"cpu": "4", "memory": "4Gi"}. * The only supported values for CPU are '1', '2', '4', '6' and '8'. For more information, go to https://cloud.google.com/run/docs/configuring/cpu. * The only supported values for memory are '1Gi', '2Gi', ... '32 Gi'. * For required cpu on different memory values, go to https://cloud.google.com/run/docs/configuring/memory-limits secretEnv: Optional. Environment variables where the value is a secret in Cloud Secret Manager. To use this feature, add 'Secret Manager Secret Accessor' role (roles/secretmanager.secretAccessor) to AI Platform Reasoning Engine Service Agent. """ class AgentServerModeValueValuesEnum(_messages.Enum): r"""The agent server mode. Values: AGENT_SERVER_MODE_UNSPECIFIED: Unspecified agent server mode. Do not use. STABLE: Stable agent server mode. This mode has everything stable and well-tested features agent engine offers. EXPERIMENTAL: Experimental agent server mode. This mode contains experimental features. """ AGENT_SERVER_MODE_UNSPECIFIED = 0 STABLE = 1 EXPERIMENTAL = 2 @encoding.MapUnrecognizedFields('additionalProperties') class ResourceLimitsValue(_messages.Message): r"""Optional. Resource limits for each container. Only 'cpu' and 'memory' keys are supported. Defaults to {"cpu": "4", "memory": "4Gi"}. * The only supported values for CPU are '1', '2', '4', '6' and '8'. For more information, go to https://cloud.google.com/run/docs/configuring/cpu. * The only supported values for memory are '1Gi', '2Gi', ... '32 Gi'. * For required cpu on different memory values, go to https://cloud.google.com/run/docs/configuring/memory-limits Messages: AdditionalProperty: An additional property for a ResourceLimitsValue object. Fields: additionalProperties: Additional properties of type ResourceLimitsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ResourceLimitsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) agentServerMode = _messages.EnumField('AgentServerModeValueValuesEnum', 1) containerConcurrency = _messages.IntegerField(2, variant=_messages.Variant.INT32) env = _messages.MessageField('GoogleCloudAiplatformV1beta1EnvVar', 3, repeated=True) maxInstances = _messages.IntegerField(4, variant=_messages.Variant.INT32) minInstances = _messages.IntegerField(5, variant=_messages.Variant.INT32) pscInterfaceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PscInterfaceConfig', 6) resourceLimits = _messages.MessageField('ResourceLimitsValue', 7) secretEnv = _messages.MessageField('GoogleCloudAiplatformV1beta1SecretEnvVar', 8, repeated=True) class GoogleCloudAiplatformV1beta1ReasoningEngineSpecPackageSpec(_messages.Message): r"""User-provided package specification, containing pickled object and package requirements. Fields: dependencyFilesGcsUri: Optional. The Cloud Storage URI of the dependency files in tar.gz format. pickleObjectGcsUri: Optional. The Cloud Storage URI of the pickled python object. pythonVersion: Optional. The Python version. Supported values are 3.9, 3.10, 3.11, 3.12, 3.13. If not specified, the default value is 3.10. requirementsGcsUri: Optional. The Cloud Storage URI of the `requirements.txt` file """ dependencyFilesGcsUri = _messages.StringField(1) pickleObjectGcsUri = _messages.StringField(2) pythonVersion = _messages.StringField(3) requirementsGcsUri = _messages.StringField(4) class GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpec(_messages.Message): r"""Specification for deploying from source code. Fields: inlineSource: Source code is provided directly in the request. pythonSpec: Configuration for a Python application. """ inlineSource = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecInlineSource', 1) pythonSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecPythonSpec', 2) class GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecInlineSource(_messages.Message): r"""Specifies source code provided as a byte stream. Fields: sourceArchive: Required. Input only. The application source code archive, provided as a compressed tarball (.tar.gz) file. """ sourceArchive = _messages.BytesField(1) class GoogleCloudAiplatformV1beta1ReasoningEngineSpecSourceCodeSpecPythonSpec(_messages.Message): r"""Specification for running a Python application from source. Fields: entrypointModule: Optional. The Python module to load as the entrypoint, specified as a fully qualified module name. For example: path.to.agent. If not specified, defaults to "agent". The project root will be added to Python sys.path, allowing imports to be specified relative to the root. entrypointObject: Optional. The name of the callable object within the `entrypoint_module` to use as the application If not specified, defaults to "root_agent". requirementsFile: Optional. The path to the requirements file, relative to the source root. If not specified, defaults to "requirements.txt". version: Optional. The version of Python to use. Support version includes 3.9, 3.10, 3.11, 3.12, 3.13. If not specified, default value is 3.10. """ entrypointModule = _messages.StringField(1) entrypointObject = _messages.StringField(2) requirementsFile = _messages.StringField(3) version = _messages.StringField(4) class GoogleCloudAiplatformV1beta1RebaseTunedModelRequest(_messages.Message): r"""Request message for GenAiTuningService.RebaseTunedModel. Fields: artifactDestination: Optional. The Google Cloud Storage location to write the artifacts. deployToSameEndpoint: Optional. By default, bison to gemini migration will always create new model/endpoint, but for gemini-1.0 to gemini-1.5 migration, we default deploy to the same endpoint. See details in this Section. tunedModelRef: Required. TunedModel reference to retrieve the legacy model information. tuningJob: Optional. The TuningJob to be updated. Users can use this TuningJob field to overwrite tuning configs. """ artifactDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 1) deployToSameEndpoint = _messages.BooleanField(2) tunedModelRef = _messages.MessageField('GoogleCloudAiplatformV1beta1TunedModelRef', 3) tuningJob = _messages.MessageField('GoogleCloudAiplatformV1beta1TuningJob', 4) class GoogleCloudAiplatformV1beta1RebootPersistentResourceOperationMetadata(_messages.Message): r"""Details of operations that perform reboot PersistentResource. Fields: genericMetadata: Operation metadata for PersistentResource. progressMessage: Progress Message for Reboot LRO """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) progressMessage = _messages.StringField(2) class GoogleCloudAiplatformV1beta1RebootPersistentResourceRequest(_messages.Message): r"""Request message for PersistentResourceService.RebootPersistentResource. """ class GoogleCloudAiplatformV1beta1RecommendSpecRequest(_messages.Message): r"""Request message for ModelService.RecommendSpec. Fields: checkMachineAvailability: Optional. If true, check machine availability for the recommended regions. Only return the machine spec in regions where the machine is available. checkUserQuota: Optional. If true, check user quota for the recommended regions. Returns all the machine spec in regions they are available, and also the user quota state for each machine type in each region. gcsUri: Required. The Google Cloud Storage URI of the custom model, storing weights and config files (which can be used to infer the base model). """ checkMachineAvailability = _messages.BooleanField(1) checkUserQuota = _messages.BooleanField(2) gcsUri = _messages.StringField(3) class GoogleCloudAiplatformV1beta1RecommendSpecResponse(_messages.Message): r"""Response message for ModelService.RecommendSpec. Fields: baseModel: Output only. The base model used to finetune the custom model. recommendations: Output only. Recommendations of deployment options for the given custom weights model. specs: Output only. The machine and model container specs. """ baseModel = _messages.StringField(1) recommendations = _messages.MessageField('GoogleCloudAiplatformV1beta1RecommendSpecResponseRecommendation', 2, repeated=True) specs = _messages.MessageField('GoogleCloudAiplatformV1beta1RecommendSpecResponseMachineAndModelContainerSpec', 3, repeated=True) class GoogleCloudAiplatformV1beta1RecommendSpecResponseMachineAndModelContainerSpec(_messages.Message): r"""A machine and model container spec. Fields: containerSpec: Output only. The model container spec. machineSpec: Output only. The machine spec. """ containerSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelContainerSpec', 1) machineSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1MachineSpec', 2) class GoogleCloudAiplatformV1beta1RecommendSpecResponseRecommendation(_messages.Message): r"""Recommendation of one deployment option for the given custom weights model in one region. Contains the machine and container spec, and user accelerator quota state. Enums: UserQuotaStateValueValuesEnum: Output only. The user accelerator quota state. Fields: region: The region for the deployment spec (machine). spec: Output only. The machine and model container specs. userQuotaState: Output only. The user accelerator quota state. """ class UserQuotaStateValueValuesEnum(_messages.Enum): r"""Output only. The user accelerator quota state. Values: QUOTA_STATE_UNSPECIFIED: Unspecified quota state. Quota information not available. QUOTA_STATE_USER_HAS_QUOTA: User has enough accelerator quota for the machine type. QUOTA_STATE_NO_USER_QUOTA: User does not have enough accelerator quota for the machine type. """ QUOTA_STATE_UNSPECIFIED = 0 QUOTA_STATE_USER_HAS_QUOTA = 1 QUOTA_STATE_NO_USER_QUOTA = 2 region = _messages.StringField(1) spec = _messages.MessageField('GoogleCloudAiplatformV1beta1RecommendSpecResponseMachineAndModelContainerSpec', 2) userQuotaState = _messages.EnumField('UserQuotaStateValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1RemoveContextChildrenRequest(_messages.Message): r"""Request message for MetadataService.DeleteContextChildrenRequest. Fields: childContexts: The resource names of the child Contexts. """ childContexts = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1RemoveContextChildrenResponse(_messages.Message): r"""Response message for MetadataService.RemoveContextChildren.""" class GoogleCloudAiplatformV1beta1RemoveDatapointsRequest(_messages.Message): r"""Request message for IndexService.RemoveDatapoints Fields: datapointIds: A list of datapoint ids to be deleted. """ datapointIds = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1RemoveDatapointsResponse(_messages.Message): r"""Response message for IndexService.RemoveDatapoints""" class GoogleCloudAiplatformV1beta1RemoveExamplesRequest(_messages.Message): r"""Request message for ExampleStoreService.RemoveExamples. Fields: exampleIds: Optional. Example IDs to remove. If both metadata filters and Example IDs are specified, the metadata filters will be applied to the specified examples in order to identify which should be removed. storedContentsExampleFilter: The metadata filters for StoredContentsExamples. """ exampleIds = _messages.StringField(1, repeated=True) storedContentsExampleFilter = _messages.MessageField('GoogleCloudAiplatformV1beta1StoredContentsExampleFilter', 2) class GoogleCloudAiplatformV1beta1RemoveExamplesResponse(_messages.Message): r"""Response message for ExampleStoreService.RemoveExamples. Fields: exampleIds: The IDs for the removed examples. """ exampleIds = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1ReportExecutionEventRequest(_messages.Message): r"""Request message for NotebookInternalService.ReportExecutionEvent. Enums: EventTypeValueValuesEnum: Required. The type of the event. Fields: eventType: Required. The type of the event. status: Optional. The error details of the event. vmToken: Required. The VM identity token (a JWT) for authenticating the VM. https://cloud.google.com/compute/docs/instances/verifying-instance- identity """ class EventTypeValueValuesEnum(_messages.Enum): r"""Required. The type of the event. Values: EVENT_TYPE_UNSPECIFIED: Unspecified. ACTIVE: Notebook execution process has started. Expect this message within expected time to provision compute. DONE: Notebook execution process is completed. Expect this message within timeout. FAILED: Notebook execution process has failed. Expect this message within timeout. """ EVENT_TYPE_UNSPECIFIED = 0 ACTIVE = 1 DONE = 2 FAILED = 3 eventType = _messages.EnumField('EventTypeValueValuesEnum', 1) status = _messages.MessageField('GoogleRpcStatus', 2) vmToken = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ReportExecutionEventResponse(_messages.Message): r"""Response message for NotebookInternalService.ReportExecutionEvent.""" class GoogleCloudAiplatformV1beta1ReportRuntimeEventRequest(_messages.Message): r"""Request message for NotebookInternalService.ReportRuntimeEvent. Enums: EventTypeValueValuesEnum: Required. The type of the event. Messages: EventDetailsValue: Optional. The details of the request for debug. Fields: eventDetails: Optional. The details of the request for debug. eventType: Required. The type of the event. internalOsServiceStateInstance: The details of the internal os service states. internalOsServiceStateInstances: Optional. The details of the internal os service states. vmToken: Required. The VM identity token (a JWT) for authenticating the VM. https://cloud.google.com/compute/docs/instances/verifying-instance- identity """ class EventTypeValueValuesEnum(_messages.Enum): r"""Required. The type of the event. Values: EVENT_TYPE_UNSPECIFIED: Unspecified. HEARTBEAT: Used for readiness reporting. IDLE: Used for idle reporting. """ EVENT_TYPE_UNSPECIFIED = 0 HEARTBEAT = 1 IDLE = 2 @encoding.MapUnrecognizedFields('additionalProperties') class EventDetailsValue(_messages.Message): r"""Optional. The details of the request for debug. Messages: AdditionalProperty: An additional property for a EventDetailsValue object. Fields: additionalProperties: Additional properties of type EventDetailsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a EventDetailsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) eventDetails = _messages.MessageField('EventDetailsValue', 1) eventType = _messages.EnumField('EventTypeValueValuesEnum', 2) internalOsServiceStateInstance = _messages.MessageField('GoogleCloudAiplatformV1beta1InternalOsServiceStateInstance', 3, repeated=True) internalOsServiceStateInstances = _messages.MessageField('GoogleCloudAiplatformV1beta1InternalOsServiceStateInstance', 4, repeated=True) vmToken = _messages.StringField(5) class GoogleCloudAiplatformV1beta1ReportRuntimeEventResponse(_messages.Message): r"""Response message for NotebookInternalService.ReportRuntimeEvent. Fields: idleShutdownMessage: If the idle shutdown is blocked by CP, CP will send the block message. Otherwise, this field is not set. """ idleShutdownMessage = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ReservationAffinity(_messages.Message): r"""A ReservationAffinity can be used to configure a Vertex AI resource (e.g., a DeployedModel) to draw its Compute Engine resources from a Shared Reservation, or exclusively from on-demand capacity. Enums: ReservationAffinityTypeValueValuesEnum: Required. Specifies the reservation affinity type. Fields: key: Optional. Corresponds to the label key of a reservation resource. To target a SPECIFIC_RESERVATION by name, use `compute.googleapis.com/reservation-name` as the key and specify the name of your reservation as its value. reservationAffinityType: Required. Specifies the reservation affinity type. values: Optional. Corresponds to the label values of a reservation resource. This must be the full resource name of the reservation or reservation block. """ class ReservationAffinityTypeValueValuesEnum(_messages.Enum): r"""Required. Specifies the reservation affinity type. Values: TYPE_UNSPECIFIED: Default value. This should not be used. NO_RESERVATION: Do not consume from any reserved capacity, only use on- demand. ANY_RESERVATION: Consume any reservation available, falling back to on- demand. SPECIFIC_RESERVATION: Consume from a specific reservation. When chosen, the reservation must be identified via the `key` and `values` fields. """ TYPE_UNSPECIFIED = 0 NO_RESERVATION = 1 ANY_RESERVATION = 2 SPECIFIC_RESERVATION = 3 key = _messages.StringField(1) reservationAffinityType = _messages.EnumField('ReservationAffinityTypeValueValuesEnum', 2) values = _messages.StringField(3, repeated=True) class GoogleCloudAiplatformV1beta1ResourcePool(_messages.Message): r"""Represents the spec of a group of resources of the same type, for example machine type, disk, and accelerators, in a PersistentResource. Fields: autoscalingSpec: Optional. Optional spec to configure GKE or Ray-on-Vertex autoscaling diskSpec: Optional. Disk spec for the machine in this node pool. id: Immutable. The unique ID in a PersistentResource for referring to this resource pool. User can specify it if necessary. Otherwise, it's generated automatically. machineSpec: Required. Immutable. The specification of a single machine. replicaCount: Optional. The total number of machines to use for this resource pool. usedReplicaCount: Output only. The number of machines currently in use by training jobs for this resource pool. Will replace idle_replica_count. """ autoscalingSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpec', 1) diskSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1DiskSpec', 2) id = _messages.StringField(3) machineSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1MachineSpec', 4) replicaCount = _messages.IntegerField(5) usedReplicaCount = _messages.IntegerField(6) class GoogleCloudAiplatformV1beta1ResourcePoolAutoscalingSpec(_messages.Message): r"""The min/max number of replicas allowed if enabling autoscaling Fields: maxReplicaCount: Optional. max replicas in the node pool, must be \u2265 replica_count and > min_replica_count or will throw error minReplicaCount: Optional. min replicas in the node pool, must be \u2264 replica_count and < max_replica_count or will throw error. For autoscaling enabled Ray-on-Vertex, we allow min_replica_count of a resource_pool to be 0 to match the OSS Ray behavior(https://docs.ray.io/en/latest/cluster/vms/user- guides/configuring-autoscaling.html#cluster-config-parameters). As for Persistent Resource, the min_replica_count must be > 0, we added a corresponding validation inside CreatePersistentResourceRequestValidator.java. """ maxReplicaCount = _messages.IntegerField(1) minReplicaCount = _messages.IntegerField(2) class GoogleCloudAiplatformV1beta1ResourceRuntime(_messages.Message): r"""Persistent Cluster runtime information as output Messages: AccessUrisValue: Output only. URIs for user to connect to the Cluster. Example: { "RAY_HEAD_NODE_INTERNAL_IP": "head-node-IP:10001" "RAY_DASHBOARD_URI": "ray-dashboard-address:8888" } Fields: accessUris: Output only. URIs for user to connect to the Cluster. Example: { "RAY_HEAD_NODE_INTERNAL_IP": "head-node-IP:10001" "RAY_DASHBOARD_URI": "ray-dashboard-address:8888" } notebookRuntimeTemplate: Output only. The resource name of NotebookRuntimeTemplate for the RoV Persistent Cluster The NotebokRuntimeTemplate is created in the same VPC (if set), and with the same Ray and Python version as the Persistent Cluster. Example: "projects/1000/locations/us-central1/notebookRuntimeTemplates/abc123" """ @encoding.MapUnrecognizedFields('additionalProperties') class AccessUrisValue(_messages.Message): r"""Output only. URIs for user to connect to the Cluster. Example: { "RAY_HEAD_NODE_INTERNAL_IP": "head-node-IP:10001" "RAY_DASHBOARD_URI": "ray-dashboard-address:8888" } Messages: AdditionalProperty: An additional property for a AccessUrisValue object. Fields: additionalProperties: Additional properties of type AccessUrisValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a AccessUrisValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) accessUris = _messages.MessageField('AccessUrisValue', 1) notebookRuntimeTemplate = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ResourceRuntimeSpec(_messages.Message): r"""Configuration for the runtime on a PersistentResource instance, including but not limited to: * Service accounts used to run the workloads. * Whether to make it a dedicated Ray Cluster. Fields: raySpec: Optional. Ray cluster configuration. Required when creating a dedicated RayCluster on the PersistentResource. serviceAccountSpec: Optional. Configure the use of workload identity on the PersistentResource """ raySpec = _messages.MessageField('GoogleCloudAiplatformV1beta1RaySpec', 1) serviceAccountSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ServiceAccountSpec', 2) class GoogleCloudAiplatformV1beta1ResourcesConsumed(_messages.Message): r"""Statistics information about resource consumption. Fields: replicaHours: Output only. The number of replica hours used. Note that many replicas may run in parallel, and additionally any given work may be queued for some time. Therefore this value is not strictly related to wall time. """ replicaHours = _messages.FloatField(1) class GoogleCloudAiplatformV1beta1RestoreDatasetVersionOperationMetadata(_messages.Message): r"""Runtime operation information for DatasetService.RestoreDatasetVersion. Fields: genericMetadata: The common part of the operation metadata. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1ResumeModelDeploymentMonitoringJobRequest(_messages.Message): r"""Request message for JobService.ResumeModelDeploymentMonitoringJob.""" class GoogleCloudAiplatformV1beta1ResumeScheduleRequest(_messages.Message): r"""Request message for ScheduleService.ResumeSchedule. Fields: catchUp: Optional. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. This will also update Schedule.catch_up field. Default to false. """ catchUp = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1Retrieval(_messages.Message): r"""Defines a retrieval tool that model can call to access external knowledge. Fields: disableAttribution: Optional. Deprecated. This option is no longer supported. externalApi: Use data source powered by external API for grounding. vertexAiSearch: Set to use data source powered by Vertex AI Search. vertexRagStore: Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService. """ disableAttribution = _messages.BooleanField(1) externalApi = _messages.MessageField('GoogleCloudAiplatformV1beta1ExternalApi', 2) vertexAiSearch = _messages.MessageField('GoogleCloudAiplatformV1beta1VertexAISearch', 3) vertexRagStore = _messages.MessageField('GoogleCloudAiplatformV1beta1VertexRagStore', 4) class GoogleCloudAiplatformV1beta1RetrievalConfig(_messages.Message): r"""Retrieval config. Fields: languageCode: The language code of the user. latLng: The location of the user. """ languageCode = _messages.StringField(1) latLng = _messages.MessageField('GoogleTypeLatLng', 2) class GoogleCloudAiplatformV1beta1RetrievalMetadata(_messages.Message): r"""Metadata related to the retrieval grounding source. This is part of the `GroundingMetadata` returned when grounding is enabled. Fields: googleSearchDynamicRetrievalScore: Optional. A score indicating how likely it is that a Google Search query could help answer the prompt. The score is in the range of `[0, 1]`. A score of 1 means the model is confident that a search will be helpful, and 0 means it is not. This score is populated only when Google Search grounding and dynamic retrieval are enabled. The score is used to determine whether to trigger a search. """ googleSearchDynamicRetrievalScore = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1RetrieveContextsRequest(_messages.Message): r"""Request message for VertexRagService.RetrieveContexts. Fields: query: Required. Single RAG retrieve query. vertexRagStore: The data source for Vertex RagStore. """ query = _messages.MessageField('GoogleCloudAiplatformV1beta1RagQuery', 1) vertexRagStore = _messages.MessageField('GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStore', 2) class GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStore(_messages.Message): r"""The data source for Vertex RagStore. Fields: ragCorpora: Optional. Deprecated. Please use rag_resources to specify the data source. ragResources: Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support. vectorDistanceThreshold: Optional. Only return contexts with vector distance smaller than the threshold. """ ragCorpora = _messages.StringField(1, repeated=True) ragResources = _messages.MessageField('GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStoreRagResource', 2, repeated=True) vectorDistanceThreshold = _messages.FloatField(3) class GoogleCloudAiplatformV1beta1RetrieveContextsRequestVertexRagStoreRagResource(_messages.Message): r"""The definition of the Rag resource. Fields: ragCorpus: Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}` ragFileIds: Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field. """ ragCorpus = _messages.StringField(1) ragFileIds = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1RetrieveContextsResponse(_messages.Message): r"""Response message for VertexRagService.RetrieveContexts. Fields: contexts: The contexts of the query. """ contexts = _messages.MessageField('GoogleCloudAiplatformV1beta1RagContexts', 1) class GoogleCloudAiplatformV1beta1RetrieveMemoriesRequest(_messages.Message): r"""Request message for MemoryBankService.RetrieveMemories. Messages: ScopeValue: Required. The scope of the memories to retrieve. A memory must have exactly the same scope (`Memory.scope`) as the scope provided here to be retrieved (same keys and values). Order does not matter, but it is case-sensitive. Fields: filter: Optional. The standard list filter that will be applied to the retrieved memories. More detail in [AIP-160](https://google.aip.dev/160). Supported fields: * `fact` * `create_time` * `update_time` * `topics` (i.e. `topics.custom_memory_topic_label: "example topic" OR topics.managed_memory_topic: USER_PREFERENCES`) scope: Required. The scope of the memories to retrieve. A memory must have exactly the same scope (`Memory.scope`) as the scope provided here to be retrieved (same keys and values). Order does not matter, but it is case- sensitive. similaritySearchParams: Parameters for semantic similarity search based retrieval. simpleRetrievalParams: Parameters for simple (non-similarity search) retrieval. """ @encoding.MapUnrecognizedFields('additionalProperties') class ScopeValue(_messages.Message): r"""Required. The scope of the memories to retrieve. A memory must have exactly the same scope (`Memory.scope`) as the scope provided here to be retrieved (same keys and values). Order does not matter, but it is case- sensitive. Messages: AdditionalProperty: An additional property for a ScopeValue object. Fields: additionalProperties: Additional properties of type ScopeValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ScopeValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) filter = _messages.StringField(1) scope = _messages.MessageField('ScopeValue', 2) similaritySearchParams = _messages.MessageField('GoogleCloudAiplatformV1beta1RetrieveMemoriesRequestSimilaritySearchParams', 3) simpleRetrievalParams = _messages.MessageField('GoogleCloudAiplatformV1beta1RetrieveMemoriesRequestSimpleRetrievalParams', 4) class GoogleCloudAiplatformV1beta1RetrieveMemoriesRequestSimilaritySearchParams(_messages.Message): r"""Parameters for semantic similarity search based retrieval. Fields: searchQuery: Required. Query to use for similarity search retrieval. If provided, then the parent ReasoningEngine must have ReasoningEngineContextSpec.MemoryBankConfig.SimilaritySearchConfig set. topK: Optional. The maximum number of memories to return. The service may return fewer than this value. If unspecified, at most 3 memories will be returned. The maximum value is 100; values above 100 will be coerced to 100. """ searchQuery = _messages.StringField(1) topK = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1RetrieveMemoriesRequestSimpleRetrievalParams(_messages.Message): r"""Parameters for simple (non-similarity search) retrieval. Fields: pageSize: Optional. The maximum number of memories to return. The service may return fewer than this value. If unspecified, at most 3 memories will be returned. The maximum value is 100; values above 100 will be coerced to 100. pageToken: Optional. A page token, received from a previous `RetrieveMemories` call. Provide this to retrieve the subsequent page. """ pageSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) pageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1RetrieveMemoriesResponse(_messages.Message): r"""Response message for MemoryBankService.RetrieveMemories. Fields: nextPageToken: A token that can be sent as `page_token` to retrieve the next page. If this field is omitted, there are no subsequent pages. This token is not set if similarity search was used for retrieval. retrievedMemories: The retrieved memories. """ nextPageToken = _messages.StringField(1) retrievedMemories = _messages.MessageField('GoogleCloudAiplatformV1beta1RetrieveMemoriesResponseRetrievedMemory', 2, repeated=True) class GoogleCloudAiplatformV1beta1RetrieveMemoriesResponseRetrievedMemory(_messages.Message): r"""A retrieved memory. Fields: distance: The distance between the query and the retrieved Memory. Smaller values indicate more similar memories. This is only set if similarity search was used for retrieval. memory: The retrieved Memory. """ distance = _messages.FloatField(1) memory = _messages.MessageField('GoogleCloudAiplatformV1beta1Memory', 2) class GoogleCloudAiplatformV1beta1RollbackMemoryRequest(_messages.Message): r"""Request message for MemoryBankService.RollbackMemory. Fields: targetRevisionId: Required. The ID of the revision to rollback to. """ targetRevisionId = _messages.IntegerField(1) class GoogleCloudAiplatformV1beta1RolloutOptions(_messages.Message): r"""Configuration for rolling deployments. Fields: maxSurgePercentage: Percentage of allowed additional replicas. For autoscaling deployments, this refers to the target replica count. maxSurgeReplicas: Absolute count of allowed additional replicas. maxUnavailablePercentage: Percentage of replicas allowed to be unavailable. For autoscaling deployments, this refers to the target replica count. maxUnavailableReplicas: Absolute count of replicas allowed to be unavailable. previousDeployedModel: ID of the DeployedModel that this deployment should replace. revisionNumber: Output only. Read-only. Revision number determines the relative priority of DeployedModels in the same rollout. The DeployedModel with the largest revision number specifies the intended state of the deployment. """ maxSurgePercentage = _messages.IntegerField(1, variant=_messages.Variant.INT32) maxSurgeReplicas = _messages.IntegerField(2, variant=_messages.Variant.INT32) maxUnavailablePercentage = _messages.IntegerField(3, variant=_messages.Variant.INT32) maxUnavailableReplicas = _messages.IntegerField(4, variant=_messages.Variant.INT32) previousDeployedModel = _messages.StringField(5) revisionNumber = _messages.IntegerField(6, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1RougeInput(_messages.Message): r"""Input for rouge metric. Fields: instances: Required. Repeated rouge instances. metricSpec: Required. Spec for rouge score metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1RougeInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1RougeSpec', 2) class GoogleCloudAiplatformV1beta1RougeInstance(_messages.Message): r"""Spec for rouge instance. Fields: prediction: Required. Output of the evaluated model. reference: Required. Ground truth used to compare against the prediction. """ prediction = _messages.StringField(1) reference = _messages.StringField(2) class GoogleCloudAiplatformV1beta1RougeMetricValue(_messages.Message): r"""Rouge metric value for an instance. Fields: score: Output only. Rouge score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1RougeResults(_messages.Message): r"""Results for rouge metric. Fields: rougeMetricValues: Output only. Rouge metric values. """ rougeMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1RougeMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1RougeSpec(_messages.Message): r"""Spec for rouge score metric - calculates the recall of n-grams in prediction as compared to reference - returns a score ranging between 0 and 1. Fields: rougeType: Optional. Supported rouge types are rougen[1-9], rougeL, and rougeLsum. splitSummaries: Optional. Whether to split summaries while using rougeLsum. useStemmer: Optional. Whether to use stemmer to compute rouge score. """ rougeType = _messages.StringField(1) splitSummaries = _messages.BooleanField(2) useStemmer = _messages.BooleanField(3) class GoogleCloudAiplatformV1beta1Rubric(_messages.Message): r"""Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics. Enums: ImportanceValueValuesEnum: Optional. The relative importance of this rubric. Fields: content: Required. The actual testable criteria for the rubric. importance: Optional. The relative importance of this rubric. rubricId: Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict. type: Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE". """ class ImportanceValueValuesEnum(_messages.Enum): r"""Optional. The relative importance of this rubric. Values: IMPORTANCE_UNSPECIFIED: Importance is not specified. HIGH: High importance. MEDIUM: Medium importance. LOW: Low importance. """ IMPORTANCE_UNSPECIFIED = 0 HIGH = 1 MEDIUM = 2 LOW = 3 content = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricContent', 1) importance = _messages.EnumField('ImportanceValueValuesEnum', 2) rubricId = _messages.StringField(3) type = _messages.StringField(4) class GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingInput(_messages.Message): r"""Instance and metric spec for RubricBasedInstructionFollowing metric. Fields: instance: Required. Instance for RubricBasedInstructionFollowing metric. metricSpec: Required. Spec for RubricBasedInstructionFollowing metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingSpec', 2) class GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingInstance(_messages.Message): r"""Instance for RubricBasedInstructionFollowing metric - one instance corresponds to one row in an evaluation dataset. Fields: jsonInstance: Required. Instance specified as a json string. String key- value pairs are expected in the json_instance to render RubricBasedInstructionFollowing prompt templates. """ jsonInstance = _messages.StringField(1) class GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingResult(_messages.Message): r"""Result for RubricBasedInstructionFollowing metric. Fields: rubricCritiqueResults: Output only. List of per rubric critique results. score: Output only. Overall score for the instruction following. """ rubricCritiqueResults = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricCritiqueResult', 1, repeated=True) score = _messages.FloatField(2, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1RubricBasedInstructionFollowingSpec(_messages.Message): r"""Spec for RubricBasedInstructionFollowing metric - returns rubrics and verdicts corresponding to rubrics along with overall score. """ class GoogleCloudAiplatformV1beta1RubricContent(_messages.Message): r"""Content of the rubric, defining the testable criteria. Fields: property: Evaluation criteria based on a specific property. """ property = _messages.MessageField('GoogleCloudAiplatformV1beta1RubricContentProperty', 1) class GoogleCloudAiplatformV1beta1RubricContentProperty(_messages.Message): r"""Defines criteria based on a specific property. Fields: description: Description of the property being evaluated. Example: "The model's response is grammatically correct." """ description = _messages.StringField(1) class GoogleCloudAiplatformV1beta1RubricCritiqueResult(_messages.Message): r"""Rubric critique result. Fields: rubric: Output only. Rubric to be evaluated. verdict: Output only. Verdict for the rubric - true if the rubric is met, false otherwise. """ rubric = _messages.StringField(1) verdict = _messages.BooleanField(2) class GoogleCloudAiplatformV1beta1RubricGenerationSpec(_messages.Message): r"""Specification for how rubrics should be generated. Enums: RubricContentTypeValueValuesEnum: The type of rubric content to be generated. Fields: modelConfig: Configuration for the model used in rubric generation. Configs including sampling count and base model can be specified here. Flipping is not supported for rubric generation. promptTemplate: Template for the prompt used to generate rubrics. The details should be updated based on the most-recent recipe requirements. rubricContentType: The type of rubric content to be generated. rubricTypeOntology: Optional. An optional, pre-defined list of allowed types for generated rubrics. If this field is provided, it implies `include_rubric_type` should be true, and the generated rubric types should be chosen from this ontology. """ class RubricContentTypeValueValuesEnum(_messages.Enum): r"""The type of rubric content to be generated. Values: RUBRIC_CONTENT_TYPE_UNSPECIFIED: The content type to generate is not specified. PROPERTY: Generate rubrics based on properties. NL_QUESTION_ANSWER: Generate rubrics in an NL question answer format. PYTHON_CODE_ASSERTION: Generate rubrics in a unit test format. """ RUBRIC_CONTENT_TYPE_UNSPECIFIED = 0 PROPERTY = 1 NL_QUESTION_ANSWER = 2 PYTHON_CODE_ASSERTION = 3 modelConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1AutoraterConfig', 1) promptTemplate = _messages.StringField(2) rubricContentType = _messages.EnumField('RubricContentTypeValueValuesEnum', 3) rubricTypeOntology = _messages.StringField(4, repeated=True) class GoogleCloudAiplatformV1beta1RubricGroup(_messages.Message): r"""A group of rubrics, used for grouping rubrics based on a metric or a version. Fields: displayName: Human-readable name for the group. This should be unique within a given context if used for display or selection. Example: "Instruction Following V1", "Content Quality - Summarization Task". groupId: Unique identifier for the group. rubrics: Rubrics that are part of this group. """ displayName = _messages.StringField(1) groupId = _messages.StringField(2) rubrics = _messages.MessageField('GoogleCloudAiplatformV1beta1Rubric', 3, repeated=True) class GoogleCloudAiplatformV1beta1RubricVerdict(_messages.Message): r"""Represents the verdict of an evaluation against a single rubric. Fields: evaluatedRubric: Required. The full rubric definition that was evaluated. Storing this ensures the verdict is self-contained and understandable, especially if the original rubric definition changes or was dynamically generated. reasoning: Optional. Human-readable reasoning or explanation for the verdict. This can include specific examples or details from the evaluated content that justify the given verdict. verdict: Required. Outcome of the evaluation against the rubric, represented as a boolean. `true` indicates a "Pass", `false` indicates a "Fail". """ evaluatedRubric = _messages.MessageField('GoogleCloudAiplatformV1beta1Rubric', 1) reasoning = _messages.StringField(2) verdict = _messages.BooleanField(3) class GoogleCloudAiplatformV1beta1RuntimeArtifact(_messages.Message): r"""The definition of a runtime artifact. Messages: CustomPropertiesValue: The custom properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead. MetadataValue: Properties of the Artifact. PropertiesValue: The properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead. Fields: customProperties: The custom properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead. metadata: Properties of the Artifact. name: The name of an artifact. properties: The properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead. type: The type of the artifact. uri: The URI of the artifact. """ @encoding.MapUnrecognizedFields('additionalProperties') class CustomPropertiesValue(_messages.Message): r"""The custom properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead. Messages: AdditionalProperty: An additional property for a CustomPropertiesValue object. Fields: additionalProperties: Additional properties of type CustomPropertiesValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a CustomPropertiesValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1Value attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1Value', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class MetadataValue(_messages.Message): r"""Properties of the Artifact. Messages: AdditionalProperty: An additional property for a MetadataValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a MetadataValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class PropertiesValue(_messages.Message): r"""The properties of the artifact. Deprecated. Use RuntimeArtifact.metadata instead. Messages: AdditionalProperty: An additional property for a PropertiesValue object. Fields: additionalProperties: Additional properties of type PropertiesValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a PropertiesValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1Value attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1Value', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) customProperties = _messages.MessageField('CustomPropertiesValue', 1) metadata = _messages.MessageField('MetadataValue', 2) name = _messages.StringField(3) properties = _messages.MessageField('PropertiesValue', 4) type = _messages.MessageField('GoogleCloudAiplatformV1beta1ArtifactTypeSchema', 5) uri = _messages.StringField(6) class GoogleCloudAiplatformV1beta1RuntimeConfig(_messages.Message): r"""Runtime configuration to run the extension. Messages: DefaultParamsValue: Optional. Default parameters that will be set for all the execution of this extension. If specified, the parameter values can be overridden by values in [[ExecuteExtensionRequest.operation_params]] at request time. The struct should be in a form of map with param name as the key and actual param value as the value. E.g. If this operation requires a param "name" to be set to "abc". you can set this to something like {"name": "abc"}. Fields: codeInterpreterRuntimeConfig: Code execution runtime configurations for code interpreter extension. defaultParams: Optional. Default parameters that will be set for all the execution of this extension. If specified, the parameter values can be overridden by values in [[ExecuteExtensionRequest.operation_params]] at request time. The struct should be in a form of map with param name as the key and actual param value as the value. E.g. If this operation requires a param "name" to be set to "abc". you can set this to something like {"name": "abc"}. vertexAiSearchRuntimeConfig: Runtime configuration for Vertex AI Search extension. """ @encoding.MapUnrecognizedFields('additionalProperties') class DefaultParamsValue(_messages.Message): r"""Optional. Default parameters that will be set for all the execution of this extension. If specified, the parameter values can be overridden by values in [[ExecuteExtensionRequest.operation_params]] at request time. The struct should be in a form of map with param name as the key and actual param value as the value. E.g. If this operation requires a param "name" to be set to "abc". you can set this to something like {"name": "abc"}. Messages: AdditionalProperty: An additional property for a DefaultParamsValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a DefaultParamsValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) codeInterpreterRuntimeConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RuntimeConfigCodeInterpreterRuntimeConfig', 1) defaultParams = _messages.MessageField('DefaultParamsValue', 2) vertexAiSearchRuntimeConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RuntimeConfigVertexAISearchRuntimeConfig', 3) class GoogleCloudAiplatformV1beta1RuntimeConfigCodeInterpreterRuntimeConfig(_messages.Message): r"""A GoogleCloudAiplatformV1beta1RuntimeConfigCodeInterpreterRuntimeConfig object. Fields: fileInputGcsBucket: Optional. The Cloud Storage bucket for file input of this Extension. If specified, support input from the Cloud Storage bucket. Vertex Extension Custom Code Service Agent should be granted file reader to this bucket. If not specified, the extension will only accept file contents from request body and reject Cloud Storage file inputs. fileOutputGcsBucket: Optional. The Cloud Storage bucket for file output of this Extension. If specified, write all output files to the Cloud Storage bucket. Vertex Extension Custom Code Service Agent should be granted file writer to this bucket. If not specified, the file content will be output in response body. """ fileInputGcsBucket = _messages.StringField(1) fileOutputGcsBucket = _messages.StringField(2) class GoogleCloudAiplatformV1beta1RuntimeConfigVertexAISearchRuntimeConfig(_messages.Message): r"""A GoogleCloudAiplatformV1beta1RuntimeConfigVertexAISearchRuntimeConfig object. Fields: engineId: Optional. Vertex AI Search engine ID. This is used to construct the search request. By setting this engine_id, API will construct the serving config using the default value to call search API for the user. The engine_id and serving_config_name cannot both be empty at the same time. servingConfigName: Optional. Vertex AI Search serving config name. Format: `projects/{project}/locations/{location}/collections/{collection}/engine s/{engine}/servingConfigs/{serving_config}` """ engineId = _messages.StringField(1) servingConfigName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SafetyInput(_messages.Message): r"""Input for safety metric. Fields: instance: Required. Safety instance. metricSpec: Required. Spec for safety metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1SafetyInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1SafetySpec', 2) class GoogleCloudAiplatformV1beta1SafetyInstance(_messages.Message): r"""Spec for safety instance. Fields: prediction: Required. Output of the evaluated model. """ prediction = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SafetyRating(_messages.Message): r"""A safety rating for a piece of content. The safety rating contains the harm category and the harm probability level. Enums: CategoryValueValuesEnum: Output only. The harm category of this rating. OverwrittenThresholdValueValuesEnum: Output only. The overwritten threshold for the safety category of Gemini 2.0 image out. If minors are detected in the output image, the threshold of each safety category will be overwritten if user sets a lower threshold. ProbabilityValueValuesEnum: Output only. The probability of harm for this category. SeverityValueValuesEnum: Output only. The severity of harm for this category. Fields: blocked: Output only. Indicates whether the content was blocked because of this rating. category: Output only. The harm category of this rating. overwrittenThreshold: Output only. The overwritten threshold for the safety category of Gemini 2.0 image out. If minors are detected in the output image, the threshold of each safety category will be overwritten if user sets a lower threshold. probability: Output only. The probability of harm for this category. probabilityScore: Output only. The probability score of harm for this category. severity: Output only. The severity of harm for this category. severityScore: Output only. The severity score of harm for this category. """ class CategoryValueValuesEnum(_messages.Enum): r"""Output only. The harm category of this rating. Values: HARM_CATEGORY_UNSPECIFIED: Default value. This value is unused. HARM_CATEGORY_HATE_SPEECH: Content that promotes violence or incites hatred against individuals or groups based on certain attributes. HARM_CATEGORY_DANGEROUS_CONTENT: Content that promotes, facilitates, or enables dangerous activities. HARM_CATEGORY_HARASSMENT: Abusive, threatening, or content intended to bully, torment, or ridicule. HARM_CATEGORY_SEXUALLY_EXPLICIT: Content that contains sexually explicit material. HARM_CATEGORY_CIVIC_INTEGRITY: Deprecated: Election filter is not longer supported. The harm category is civic integrity. HARM_CATEGORY_IMAGE_HATE: Images that contain hate speech. HARM_CATEGORY_IMAGE_DANGEROUS_CONTENT: Images that contain dangerous content. HARM_CATEGORY_IMAGE_HARASSMENT: Images that contain harassment. HARM_CATEGORY_IMAGE_SEXUALLY_EXPLICIT: Images that contain sexually explicit content. HARM_CATEGORY_JAILBREAK: Prompts designed to bypass safety filters. """ HARM_CATEGORY_UNSPECIFIED = 0 HARM_CATEGORY_HATE_SPEECH = 1 HARM_CATEGORY_DANGEROUS_CONTENT = 2 HARM_CATEGORY_HARASSMENT = 3 HARM_CATEGORY_SEXUALLY_EXPLICIT = 4 HARM_CATEGORY_CIVIC_INTEGRITY = 5 HARM_CATEGORY_IMAGE_HATE = 6 HARM_CATEGORY_IMAGE_DANGEROUS_CONTENT = 7 HARM_CATEGORY_IMAGE_HARASSMENT = 8 HARM_CATEGORY_IMAGE_SEXUALLY_EXPLICIT = 9 HARM_CATEGORY_JAILBREAK = 10 class OverwrittenThresholdValueValuesEnum(_messages.Enum): r"""Output only. The overwritten threshold for the safety category of Gemini 2.0 image out. If minors are detected in the output image, the threshold of each safety category will be overwritten if user sets a lower threshold. Values: HARM_BLOCK_THRESHOLD_UNSPECIFIED: The harm block threshold is unspecified. BLOCK_LOW_AND_ABOVE: Block content with a low harm probability or higher. BLOCK_MEDIUM_AND_ABOVE: Block content with a medium harm probability or higher. BLOCK_ONLY_HIGH: Block content with a high harm probability. BLOCK_NONE: Do not block any content, regardless of its harm probability. OFF: Turn off the safety filter entirely. """ HARM_BLOCK_THRESHOLD_UNSPECIFIED = 0 BLOCK_LOW_AND_ABOVE = 1 BLOCK_MEDIUM_AND_ABOVE = 2 BLOCK_ONLY_HIGH = 3 BLOCK_NONE = 4 OFF = 5 class ProbabilityValueValuesEnum(_messages.Enum): r"""Output only. The probability of harm for this category. Values: HARM_PROBABILITY_UNSPECIFIED: The harm probability is unspecified. NEGLIGIBLE: The harm probability is negligible. LOW: The harm probability is low. MEDIUM: The harm probability is medium. HIGH: The harm probability is high. """ HARM_PROBABILITY_UNSPECIFIED = 0 NEGLIGIBLE = 1 LOW = 2 MEDIUM = 3 HIGH = 4 class SeverityValueValuesEnum(_messages.Enum): r"""Output only. The severity of harm for this category. Values: HARM_SEVERITY_UNSPECIFIED: The harm severity is unspecified. HARM_SEVERITY_NEGLIGIBLE: The harm severity is negligible. HARM_SEVERITY_LOW: The harm severity is low. HARM_SEVERITY_MEDIUM: The harm severity is medium. HARM_SEVERITY_HIGH: The harm severity is high. """ HARM_SEVERITY_UNSPECIFIED = 0 HARM_SEVERITY_NEGLIGIBLE = 1 HARM_SEVERITY_LOW = 2 HARM_SEVERITY_MEDIUM = 3 HARM_SEVERITY_HIGH = 4 blocked = _messages.BooleanField(1) category = _messages.EnumField('CategoryValueValuesEnum', 2) overwrittenThreshold = _messages.EnumField('OverwrittenThresholdValueValuesEnum', 3) probability = _messages.EnumField('ProbabilityValueValuesEnum', 4) probabilityScore = _messages.FloatField(5, variant=_messages.Variant.FLOAT) severity = _messages.EnumField('SeverityValueValuesEnum', 6) severityScore = _messages.FloatField(7, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SafetyResult(_messages.Message): r"""Spec for safety result. Fields: confidence: Output only. Confidence for safety score. explanation: Output only. Explanation for safety score. score: Output only. Safety score. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SafetySetting(_messages.Message): r"""A safety setting that affects the safety-blocking behavior. A SafetySetting consists of a harm category and a threshold for that category. Enums: CategoryValueValuesEnum: Required. The harm category to be blocked. MethodValueValuesEnum: Optional. The method for blocking content. If not specified, the default behavior is to use the probability score. ThresholdValueValuesEnum: Required. The threshold for blocking content. If the harm probability exceeds this threshold, the content will be blocked. Fields: category: Required. The harm category to be blocked. method: Optional. The method for blocking content. If not specified, the default behavior is to use the probability score. threshold: Required. The threshold for blocking content. If the harm probability exceeds this threshold, the content will be blocked. """ class CategoryValueValuesEnum(_messages.Enum): r"""Required. The harm category to be blocked. Values: HARM_CATEGORY_UNSPECIFIED: Default value. This value is unused. HARM_CATEGORY_HATE_SPEECH: Content that promotes violence or incites hatred against individuals or groups based on certain attributes. HARM_CATEGORY_DANGEROUS_CONTENT: Content that promotes, facilitates, or enables dangerous activities. HARM_CATEGORY_HARASSMENT: Abusive, threatening, or content intended to bully, torment, or ridicule. HARM_CATEGORY_SEXUALLY_EXPLICIT: Content that contains sexually explicit material. HARM_CATEGORY_CIVIC_INTEGRITY: Deprecated: Election filter is not longer supported. The harm category is civic integrity. HARM_CATEGORY_IMAGE_HATE: Images that contain hate speech. HARM_CATEGORY_IMAGE_DANGEROUS_CONTENT: Images that contain dangerous content. HARM_CATEGORY_IMAGE_HARASSMENT: Images that contain harassment. HARM_CATEGORY_IMAGE_SEXUALLY_EXPLICIT: Images that contain sexually explicit content. HARM_CATEGORY_JAILBREAK: Prompts designed to bypass safety filters. """ HARM_CATEGORY_UNSPECIFIED = 0 HARM_CATEGORY_HATE_SPEECH = 1 HARM_CATEGORY_DANGEROUS_CONTENT = 2 HARM_CATEGORY_HARASSMENT = 3 HARM_CATEGORY_SEXUALLY_EXPLICIT = 4 HARM_CATEGORY_CIVIC_INTEGRITY = 5 HARM_CATEGORY_IMAGE_HATE = 6 HARM_CATEGORY_IMAGE_DANGEROUS_CONTENT = 7 HARM_CATEGORY_IMAGE_HARASSMENT = 8 HARM_CATEGORY_IMAGE_SEXUALLY_EXPLICIT = 9 HARM_CATEGORY_JAILBREAK = 10 class MethodValueValuesEnum(_messages.Enum): r"""Optional. The method for blocking content. If not specified, the default behavior is to use the probability score. Values: HARM_BLOCK_METHOD_UNSPECIFIED: The harm block method is unspecified. SEVERITY: The harm block method uses both probability and severity scores. PROBABILITY: The harm block method uses the probability score. """ HARM_BLOCK_METHOD_UNSPECIFIED = 0 SEVERITY = 1 PROBABILITY = 2 class ThresholdValueValuesEnum(_messages.Enum): r"""Required. The threshold for blocking content. If the harm probability exceeds this threshold, the content will be blocked. Values: HARM_BLOCK_THRESHOLD_UNSPECIFIED: The harm block threshold is unspecified. BLOCK_LOW_AND_ABOVE: Block content with a low harm probability or higher. BLOCK_MEDIUM_AND_ABOVE: Block content with a medium harm probability or higher. BLOCK_ONLY_HIGH: Block content with a high harm probability. BLOCK_NONE: Do not block any content, regardless of its harm probability. OFF: Turn off the safety filter entirely. """ HARM_BLOCK_THRESHOLD_UNSPECIFIED = 0 BLOCK_LOW_AND_ABOVE = 1 BLOCK_MEDIUM_AND_ABOVE = 2 BLOCK_ONLY_HIGH = 3 BLOCK_NONE = 4 OFF = 5 category = _messages.EnumField('CategoryValueValuesEnum', 1) method = _messages.EnumField('MethodValueValuesEnum', 2) threshold = _messages.EnumField('ThresholdValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1SafetySpec(_messages.Message): r"""Spec for safety metric. Fields: version: Optional. Which version to use for evaluation. """ version = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SampleConfig(_messages.Message): r"""Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy. Enums: SampleStrategyValueValuesEnum: Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch. Fields: followingBatchSamplePercentage: The percentage of data needed to be labeled in each following batch (except the first batch). initialBatchSamplePercentage: The percentage of data needed to be labeled in the first batch. sampleStrategy: Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch. """ class SampleStrategyValueValuesEnum(_messages.Enum): r"""Field to choose sampling strategy. Sampling strategy will decide which data should be selected for human labeling in every batch. Values: SAMPLE_STRATEGY_UNSPECIFIED: Default will be treated as UNCERTAINTY. UNCERTAINTY: Sample the most uncertain data to label. """ SAMPLE_STRATEGY_UNSPECIFIED = 0 UNCERTAINTY = 1 followingBatchSamplePercentage = _messages.IntegerField(1, variant=_messages.Variant.INT32) initialBatchSamplePercentage = _messages.IntegerField(2, variant=_messages.Variant.INT32) sampleStrategy = _messages.EnumField('SampleStrategyValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1SampledShapleyAttribution(_messages.Message): r"""An attribution method that approximates Shapley values for features that contribute to the label being predicted. A sampling strategy is used to approximate the value rather than considering all subsets of features. Fields: pathCount: Required. The number of feature permutations to consider when approximating the Shapley values. Valid range of its value is [1, 50], inclusively. """ pathCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SamplingStrategy(_messages.Message): r"""Sampling Strategy for logging, can be for both training and prediction dataset. Fields: randomSampleConfig: Random sample config. Will support more sampling strategies later. """ randomSampleConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SamplingStrategyRandomSampleConfig', 1) class GoogleCloudAiplatformV1beta1SamplingStrategyRandomSampleConfig(_messages.Message): r"""Requests are randomly selected. Fields: sampleRate: Sample rate (0, 1] """ sampleRate = _messages.FloatField(1) class GoogleCloudAiplatformV1beta1SandboxEnvironment(_messages.Message): r"""SandboxEnvironment is a containerized environment that provides a customizable secure execution runtime for AI agents. Enums: StateValueValuesEnum: Output only. The runtime state of the SandboxEnvironment. Fields: connectionInfo: Output only. The connection information of the SandboxEnvironment. createTime: Output only. The timestamp when this SandboxEnvironment was created. displayName: Required. The display name of the SandboxEnvironment. expireTime: Optional. Timestamp in UTC of when this SandboxEnvironment is considered expired. This is *always* provided on output, regardless of what `expiration` was sent on input. name: Identifier. The name of the SandboxEnvironment. spec: Optional. The configuration of the SandboxEnvironment. state: Output only. The runtime state of the SandboxEnvironment. ttl: Optional. Input only. The TTL for the sandbox environment. The expiration time is computed: now + TTL. updateTime: Output only. The timestamp when this SandboxEnvironment was most recently updated. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The runtime state of the SandboxEnvironment. Values: STATE_UNSPECIFIED: The default value. This value is unused. STATE_PROVISIONING: Runtime resources are being allocated for the sandbox environment. STATE_RUNNING: Sandbox runtime is ready for serving. STATE_DEPROVISIONING: Sandbox runtime is halted, performing tear down tasks. STATE_TERMINATED: Sandbox has terminated with underlying runtime failure. STATE_DELETED: Sandbox runtime has been deleted. """ STATE_UNSPECIFIED = 0 STATE_PROVISIONING = 1 STATE_RUNNING = 2 STATE_DEPROVISIONING = 3 STATE_TERMINATED = 4 STATE_DELETED = 5 connectionInfo = _messages.MessageField('GoogleCloudAiplatformV1beta1SandboxEnvironmentConnectionInfo', 1) createTime = _messages.StringField(2) displayName = _messages.StringField(3) expireTime = _messages.StringField(4) name = _messages.StringField(5) spec = _messages.MessageField('GoogleCloudAiplatformV1beta1SandboxEnvironmentSpec', 6) state = _messages.EnumField('StateValueValuesEnum', 7) ttl = _messages.StringField(8) updateTime = _messages.StringField(9) class GoogleCloudAiplatformV1beta1SandboxEnvironmentConnectionInfo(_messages.Message): r"""The connection information of the SandboxEnvironment. Fields: loadBalancerHostname: Output only. The hostname of the load balancer. loadBalancerIp: Output only. The IP address of the load balancer. sandboxInternalIp: Output only. The internal IP address of the SandboxEnvironment. """ loadBalancerHostname = _messages.StringField(1) loadBalancerIp = _messages.StringField(2) sandboxInternalIp = _messages.StringField(3) class GoogleCloudAiplatformV1beta1SandboxEnvironmentSpec(_messages.Message): r"""The specification of a SandboxEnvironment. Fields: codeExecutionEnvironment: Optional. The code execution environment. computerUseEnvironment: Optional. The computer use environment. """ codeExecutionEnvironment = _messages.MessageField('GoogleCloudAiplatformV1beta1SandboxEnvironmentSpecCodeExecutionEnvironment', 1) computerUseEnvironment = _messages.MessageField('GoogleCloudAiplatformV1beta1SandboxEnvironmentSpecComputerUseEnvironment', 2) class GoogleCloudAiplatformV1beta1SandboxEnvironmentSpecCodeExecutionEnvironment(_messages.Message): r"""The code execution environment with customized settings. Enums: CodeLanguageValueValuesEnum: The coding language supported in this environment. MachineConfigValueValuesEnum: The machine config of the code execution environment. Fields: codeLanguage: The coding language supported in this environment. machineConfig: The machine config of the code execution environment. """ class CodeLanguageValueValuesEnum(_messages.Enum): r"""The coding language supported in this environment. Values: LANGUAGE_UNSPECIFIED: The default value. This value is unused. LANGUAGE_PYTHON: The coding language is Python. LANGUAGE_JAVASCRIPT: The coding language is JavaScript. """ LANGUAGE_UNSPECIFIED = 0 LANGUAGE_PYTHON = 1 LANGUAGE_JAVASCRIPT = 2 class MachineConfigValueValuesEnum(_messages.Enum): r"""The machine config of the code execution environment. Values: MACHINE_CONFIG_UNSPECIFIED: The default value: milligcu 2000, memory 1.5Gib MACHINE_CONFIG_VCPU4_RAM4GIB: The default value: milligcu 4000, memory 4 Gib """ MACHINE_CONFIG_UNSPECIFIED = 0 MACHINE_CONFIG_VCPU4_RAM4GIB = 1 codeLanguage = _messages.EnumField('CodeLanguageValueValuesEnum', 1) machineConfig = _messages.EnumField('MachineConfigValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1SandboxEnvironmentSpecComputerUseEnvironment(_messages.Message): r"""The computer use environment with customized settings.""" class GoogleCloudAiplatformV1beta1SavedQuery(_messages.Message): r"""A SavedQuery is a view of the dataset. It references a subset of annotations by problem type and filters. Fields: annotationFilter: Output only. Filters on the Annotations in the dataset. annotationSpecCount: Output only. Number of AnnotationSpecs in the context of the SavedQuery. createTime: Output only. Timestamp when this SavedQuery was created. displayName: Required. The user-defined name of the SavedQuery. The name can be up to 128 characters long and can consist of any UTF-8 characters. etag: Used to perform a consistent read-modify-write update. If not set, a blind "overwrite" update happens. metadata: Some additional information about the SavedQuery. name: Output only. Resource name of the SavedQuery. problemType: Required. Problem type of the SavedQuery. Allowed values: * IMAGE_CLASSIFICATION_SINGLE_LABEL * IMAGE_CLASSIFICATION_MULTI_LABEL * IMAGE_BOUNDING_POLY * IMAGE_BOUNDING_BOX * TEXT_CLASSIFICATION_SINGLE_LABEL * TEXT_CLASSIFICATION_MULTI_LABEL * TEXT_EXTRACTION * TEXT_SENTIMENT * VIDEO_CLASSIFICATION * VIDEO_OBJECT_TRACKING supportAutomlTraining: Output only. If the Annotations belonging to the SavedQuery can be used for AutoML training. updateTime: Output only. Timestamp when SavedQuery was last updated. """ annotationFilter = _messages.StringField(1) annotationSpecCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) createTime = _messages.StringField(3) displayName = _messages.StringField(4) etag = _messages.StringField(5) metadata = _messages.MessageField('extra_types.JsonValue', 6) name = _messages.StringField(7) problemType = _messages.StringField(8) supportAutomlTraining = _messages.BooleanField(9) updateTime = _messages.StringField(10) class GoogleCloudAiplatformV1beta1Scalar(_messages.Message): r"""One point viewable on a scalar metric plot. Fields: value: Value of the point at this step / timestamp. """ value = _messages.FloatField(1) class GoogleCloudAiplatformV1beta1Schedule(_messages.Message): r"""An instance of a Schedule periodically schedules runs to make API calls based on user specified time specification and API request type. Enums: StateValueValuesEnum: Output only. The state of this Schedule. Fields: allowQueueing: Optional. Whether new scheduled runs can be queued when max_concurrent_runs limit is reached. If set to true, new runs will be queued instead of skipped. Default to false. catchUp: Output only. Whether to backfill missed runs when the schedule is resumed from PAUSED state. If set to true, all missed runs will be scheduled. New runs will be scheduled after the backfill is complete. Default to false. createModelMonitoringJobRequest: Request for ModelMonitoringService.CreateModelMonitoringJob. createNotebookExecutionJobRequest: Request for NotebookService.CreateNotebookExecutionJob. createPipelineJobRequest: Request for PipelineService.CreatePipelineJob. CreatePipelineJobRequest.parent field is required (format: projects/{project}/locations/{location}). createTime: Output only. Timestamp when this Schedule was created. cron: Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *". displayName: Required. User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters. endTime: Optional. Timestamp after which no new runs can be scheduled. If specified, The schedule will be completed when either end_time is reached or when scheduled_run_count >= max_run_count. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified. lastPauseTime: Output only. Timestamp when this Schedule was last paused. Unset if never paused. lastResumeTime: Output only. Timestamp when this Schedule was last resumed. Unset if never resumed from pause. lastScheduledRunResponse: Output only. Response of the last scheduled run. This is the response for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). Unset if no run has been scheduled yet. maxConcurrentRunCount: Required. Maximum number of runs that can be started concurrently for this Schedule. This is the limit for starting the scheduled requests and not the execution of the operations/jobs created by the requests (if applicable). maxRunCount: Optional. Maximum run count of the schedule. If specified, The schedule will be completed when either started_run_count >= max_run_count or when end_time is reached. If not specified, new runs will keep getting scheduled until this Schedule is paused or deleted. Already scheduled runs will be allowed to complete. Unset if not specified. name: Immutable. The resource name of the Schedule. nextRunTime: Output only. Timestamp when this Schedule should schedule the next run. Having a next_run_time in the past means the runs are being started behind schedule. startTime: Optional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified. startedRunCount: Output only. The number of runs started by this schedule. state: Output only. The state of this Schedule. updateTime: Output only. Timestamp when this Schedule was updated. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The state of this Schedule. Values: STATE_UNSPECIFIED: Unspecified. ACTIVE: The Schedule is active. Runs are being scheduled on the user- specified timespec. PAUSED: The schedule is paused. No new runs will be created until the schedule is resumed. Already started runs will be allowed to complete. COMPLETED: The Schedule is completed. No new runs will be scheduled. Already started runs will be allowed to complete. Schedules in completed state cannot be paused or resumed. """ STATE_UNSPECIFIED = 0 ACTIVE = 1 PAUSED = 2 COMPLETED = 3 allowQueueing = _messages.BooleanField(1) catchUp = _messages.BooleanField(2) createModelMonitoringJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CreateModelMonitoringJobRequest', 3) createNotebookExecutionJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CreateNotebookExecutionJobRequest', 4) createPipelineJobRequest = _messages.MessageField('GoogleCloudAiplatformV1beta1CreatePipelineJobRequest', 5) createTime = _messages.StringField(6) cron = _messages.StringField(7) displayName = _messages.StringField(8) endTime = _messages.StringField(9) lastPauseTime = _messages.StringField(10) lastResumeTime = _messages.StringField(11) lastScheduledRunResponse = _messages.MessageField('GoogleCloudAiplatformV1beta1ScheduleRunResponse', 12) maxConcurrentRunCount = _messages.IntegerField(13) maxRunCount = _messages.IntegerField(14) name = _messages.StringField(15) nextRunTime = _messages.StringField(16) startTime = _messages.StringField(17) startedRunCount = _messages.IntegerField(18) state = _messages.EnumField('StateValueValuesEnum', 19) updateTime = _messages.StringField(20) class GoogleCloudAiplatformV1beta1ScheduleConfig(_messages.Message): r"""Schedule configuration for the FeatureMonitor. Fields: cron: Cron schedule (https://en.wikipedia.org/wiki/Cron) to launch scheduled runs. To explicitly set a timezone to the cron tab, apply a prefix in the cron tab: "CRON_TZ=${IANA_TIME_ZONE}" or "TZ=${IANA_TIME_ZONE}". The ${IANA_TIME_ZONE} may only be a valid string from IANA time zone database. For example, "CRON_TZ=America/New_York 1 * * * *", or "TZ=America/New_York 1 * * * *". """ cron = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ScheduleRunResponse(_messages.Message): r"""Status of a scheduled run. Fields: runResponse: The response of the scheduled run. scheduledRunTime: The scheduled run time based on the user-specified schedule. """ runResponse = _messages.StringField(1) scheduledRunTime = _messages.StringField(2) class GoogleCloudAiplatformV1beta1Scheduling(_messages.Message): r"""All parameters related to queuing and scheduling of custom jobs. Enums: StrategyValueValuesEnum: Optional. This determines which type of scheduling strategy to use. Fields: disableRetries: Optional. Indicates if the job should retry for internal errors after the job starts running. If true, overrides `Scheduling.restart_job_on_worker_restart` to false. maxWaitDuration: Optional. This is the maximum duration that a job will wait for the requested resources to be provisioned if the scheduling strategy is set to [Strategy.DWS_FLEX_START]. If set to 0, the job will wait indefinitely. The default is 24 hours. restartJobOnWorkerRestart: Optional. Restarts the entire CustomJob if a worker gets restarted. This feature can be used by distributed training jobs that are not resilient to workers leaving and joining a job. strategy: Optional. This determines which type of scheduling strategy to use. timeout: Optional. The maximum job running time. The default is 7 days. """ class StrategyValueValuesEnum(_messages.Enum): r"""Optional. This determines which type of scheduling strategy to use. Values: STRATEGY_UNSPECIFIED: Strategy will default to STANDARD. ON_DEMAND: Deprecated. Regular on-demand provisioning strategy. LOW_COST: Deprecated. Low cost by making potential use of spot resources. STANDARD: Standard provisioning strategy uses regular on-demand resources. SPOT: Spot provisioning strategy uses spot resources. FLEX_START: Flex Start strategy uses DWS to queue for resources. """ STRATEGY_UNSPECIFIED = 0 ON_DEMAND = 1 LOW_COST = 2 STANDARD = 3 SPOT = 4 FLEX_START = 5 disableRetries = _messages.BooleanField(1) maxWaitDuration = _messages.StringField(2) restartJobOnWorkerRestart = _messages.BooleanField(3) strategy = _messages.EnumField('StrategyValueValuesEnum', 4) timeout = _messages.StringField(5) class GoogleCloudAiplatformV1beta1Schema(_messages.Message): r"""Schema is used to define the format of input/output data. Represents a select subset of an [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema-object). More fields may be added in the future as needed. Enums: TypeValueValuesEnum: Optional. The type of the data. Messages: DefsValue: Optional. A map of definitions for use by `ref` Only allowed at the root of the schema. PropertiesValue: Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT. Fields: additionalProperties: Optional. Can either be a boolean or an object; controls the presence of additional properties. anyOf: Optional. The value should be validated against any (one or more) of the subschemas in the list. default: Optional. Default value of the data. defs: Optional. A map of definitions for use by `ref` Only allowed at the root of the schema. description: Optional. The description of the data. enum: Optional. Possible values of the element of primitive type with enum format. Examples: 1. We can define direction as : {type:STRING, format:enum, enum:["EAST", NORTH", "SOUTH", "WEST"]} 2. We can define apartment number as : {type:INTEGER, format:enum, enum:["101", "201", "301"]} example: Optional. Example of the object. Will only populated when the object is the root. format: Optional. The format of the data. Supported formats: for NUMBER type: "float", "double" for INTEGER type: "int32", "int64" for STRING type: "email", "byte", etc items: Optional. SCHEMA FIELDS FOR TYPE ARRAY Schema of the elements of Type.ARRAY. maxItems: Optional. Maximum number of the elements for Type.ARRAY. maxLength: Optional. Maximum length of the Type.STRING maxProperties: Optional. Maximum number of the properties for Type.OBJECT. maximum: Optional. Maximum value of the Type.INTEGER and Type.NUMBER minItems: Optional. Minimum number of the elements for Type.ARRAY. minLength: Optional. SCHEMA FIELDS FOR TYPE STRING Minimum length of the Type.STRING minProperties: Optional. Minimum number of the properties for Type.OBJECT. minimum: Optional. SCHEMA FIELDS FOR TYPE INTEGER and NUMBER Minimum value of the Type.INTEGER and Type.NUMBER nullable: Optional. Indicates if the value may be null. pattern: Optional. Pattern of the Type.STRING to restrict a string to a regular expression. properties: Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT. propertyOrdering: Optional. The order of the properties. Not a standard field in open api spec. Only used to support the order of the properties. ref: Optional. Allows indirect references between schema nodes. The value should be a valid reference to a child of the root `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json- schema.org/understanding-json-schema/structuring required: Optional. Required properties of Type.OBJECT. title: Optional. The title of the Schema. type: Optional. The type of the data. """ class TypeValueValuesEnum(_messages.Enum): r"""Optional. The type of the data. Values: TYPE_UNSPECIFIED: Not specified, should not be used. STRING: OpenAPI string type NUMBER: OpenAPI number type INTEGER: OpenAPI integer type BOOLEAN: OpenAPI boolean type ARRAY: OpenAPI array type OBJECT: OpenAPI object type NULL: Null type """ TYPE_UNSPECIFIED = 0 STRING = 1 NUMBER = 2 INTEGER = 3 BOOLEAN = 4 ARRAY = 5 OBJECT = 6 NULL = 7 @encoding.MapUnrecognizedFields('additionalProperties') class DefsValue(_messages.Message): r"""Optional. A map of definitions for use by `ref` Only allowed at the root of the schema. Messages: AdditionalProperty: An additional property for a DefsValue object. Fields: additionalProperties: Additional properties of type DefsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a DefsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1Schema attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1Schema', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class PropertiesValue(_messages.Message): r"""Optional. SCHEMA FIELDS FOR TYPE OBJECT Properties of Type.OBJECT. Messages: AdditionalProperty: An additional property for a PropertiesValue object. Fields: additionalProperties: Additional properties of type PropertiesValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a PropertiesValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1Schema attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1Schema', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) additionalProperties = _messages.MessageField('extra_types.JsonValue', 1) anyOf = _messages.MessageField('GoogleCloudAiplatformV1beta1Schema', 2, repeated=True) default = _messages.MessageField('extra_types.JsonValue', 3) defs = _messages.MessageField('DefsValue', 4) description = _messages.StringField(5) enum = _messages.StringField(6, repeated=True) example = _messages.MessageField('extra_types.JsonValue', 7) format = _messages.StringField(8) items = _messages.MessageField('GoogleCloudAiplatformV1beta1Schema', 9) maxItems = _messages.IntegerField(10) maxLength = _messages.IntegerField(11) maxProperties = _messages.IntegerField(12) maximum = _messages.FloatField(13) minItems = _messages.IntegerField(14) minLength = _messages.IntegerField(15) minProperties = _messages.IntegerField(16) minimum = _messages.FloatField(17) nullable = _messages.BooleanField(18) pattern = _messages.StringField(19) properties = _messages.MessageField('PropertiesValue', 20) propertyOrdering = _messages.StringField(21, repeated=True) ref = _messages.StringField(22) required = _messages.StringField(23, repeated=True) title = _messages.StringField(24) type = _messages.EnumField('TypeValueValuesEnum', 25) class GoogleCloudAiplatformV1beta1SchemaAnnotationSpecColor(_messages.Message): r"""An entry of mapping between color and AnnotationSpec. The mapping is used in segmentation mask. Fields: color: The color of the AnnotationSpec in a segmentation mask. displayName: The display name of the AnnotationSpec represented by the color in the segmentation mask. id: The ID of the AnnotationSpec represented by the color in the segmentation mask. """ color = _messages.MessageField('GoogleTypeColor', 1) displayName = _messages.StringField(2) id = _messages.StringField(3) class GoogleCloudAiplatformV1beta1SchemaImageBoundingBoxAnnotation(_messages.Message): r"""Annotation details specific to image object detection. Fields: annotationSpecId: The resource Id of the AnnotationSpec that this Annotation pertains to. displayName: The display name of the AnnotationSpec that this Annotation pertains to. xMax: The rightmost coordinate of the bounding box. xMin: The leftmost coordinate of the bounding box. yMax: The bottommost coordinate of the bounding box. yMin: The topmost coordinate of the bounding box. """ annotationSpecId = _messages.StringField(1) displayName = _messages.StringField(2) xMax = _messages.FloatField(3) xMin = _messages.FloatField(4) yMax = _messages.FloatField(5) yMin = _messages.FloatField(6) class GoogleCloudAiplatformV1beta1SchemaImageClassificationAnnotation(_messages.Message): r"""Annotation details specific to image classification. Fields: annotationSpecId: The resource Id of the AnnotationSpec that this Annotation pertains to. displayName: The display name of the AnnotationSpec that this Annotation pertains to. """ annotationSpecId = _messages.StringField(1) displayName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaImageDataItem(_messages.Message): r"""Payload of Image DataItem. Fields: gcsUri: Required. Google Cloud Storage URI points to the original image in user's bucket. The image is up to 30MB in size. mimeType: Output only. The mime type of the content of the image. Only the images in below listed mime types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon """ gcsUri = _messages.StringField(1) mimeType = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaImageDatasetMetadata(_messages.Message): r"""The metadata of Datasets that contain Image DataItems. Fields: dataItemSchemaUri: Points to a YAML file stored on Google Cloud Storage describing payload of the Image DataItems that belong to this Dataset. gcsBucket: Google Cloud Storage Bucket name that contains the blob data of this Dataset. """ dataItemSchemaUri = _messages.StringField(1) gcsBucket = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotation(_messages.Message): r"""Annotation details specific to image segmentation. Fields: maskAnnotation: Mask based segmentation annotation. Only one mask annotation can exist for one image. polygonAnnotation: Polygon annotation. polylineAnnotation: Polyline annotation. """ maskAnnotation = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationMaskAnnotation', 1) polygonAnnotation = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolygonAnnotation', 2) polylineAnnotation = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolylineAnnotation', 3) class GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationMaskAnnotation(_messages.Message): r"""The mask based segmentation annotation. Fields: annotationSpecColors: The mapping between color and AnnotationSpec for this Annotation. maskGcsUri: Google Cloud Storage URI that points to the mask image. The image must be in PNG format. It must have the same size as the DataItem's image. Each pixel in the image mask represents the AnnotationSpec which the pixel in the image DataItem belong to. Each color is mapped to one AnnotationSpec based on annotation_spec_colors. """ annotationSpecColors = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaAnnotationSpecColor', 1, repeated=True) maskGcsUri = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolygonAnnotation(_messages.Message): r"""Represents a polygon in image. Fields: annotationSpecId: The resource Id of the AnnotationSpec that this Annotation pertains to. displayName: The display name of the AnnotationSpec that this Annotation pertains to. vertexes: The vertexes are connected one by one and the last vertex is connected to the first one to represent a polygon. """ annotationSpecId = _messages.StringField(1) displayName = _messages.StringField(2) vertexes = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaVertex', 3, repeated=True) class GoogleCloudAiplatformV1beta1SchemaImageSegmentationAnnotationPolylineAnnotation(_messages.Message): r"""Represents a polyline in image. Fields: annotationSpecId: The resource Id of the AnnotationSpec that this Annotation pertains to. displayName: The display name of the AnnotationSpec that this Annotation pertains to. vertexes: The vertexes are connected one by one and the last vertex in not connected to the first one. """ annotationSpecId = _messages.StringField(1) displayName = _messages.StringField(2) vertexes = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaVertex', 3, repeated=True) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetrics(_messages.Message): r"""Bounding box matching model metrics for a single intersection-over-union threshold and multiple label match confidence thresholds. Fields: confidenceMetrics: Metrics for each label-match confidence_threshold from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is derived from them. iouThreshold: The intersection-over-union threshold value used to compute this metrics entry. meanAveragePrecision: The mean average precision, most often close to `auPrc`. """ confidenceMetrics = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics', 1, repeated=True) iouThreshold = _messages.FloatField(2, variant=_messages.Variant.FLOAT) meanAveragePrecision = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetricsConfidenceMetrics(_messages.Message): r"""Metrics for a single confidence threshold. Fields: confidenceThreshold: The confidence threshold value used to compute the metrics. f1Score: The harmonic mean of recall and precision. precision: Precision under the given confidence threshold. recall: Recall under the given confidence threshold. """ confidenceThreshold = _messages.FloatField(1, variant=_messages.Variant.FLOAT) f1Score = _messages.FloatField(2, variant=_messages.Variant.FLOAT) precision = _messages.FloatField(3, variant=_messages.Variant.FLOAT) recall = _messages.FloatField(4, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetrics(_messages.Message): r"""Metrics for classification evaluation results. Fields: auPrc: The Area Under Precision-Recall Curve metric. Micro-averaged for the overall evaluation. auRoc: The Area Under Receiver Operating Characteristic curve metric. Micro-averaged for the overall evaluation. confidenceMetrics: Metrics for each `confidenceThreshold` in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and `positionThreshold` = INT32_MAX_VALUE. ROC and precision-recall curves, and other aggregated metrics are derived from them. The confidence metrics entries may also be supplied for additional values of `positionThreshold`, but from these no aggregated metrics are computed. confusionMatrix: Confusion matrix of the evaluation. logLoss: The Log Loss metric. """ auPrc = _messages.FloatField(1, variant=_messages.Variant.FLOAT) auRoc = _messages.FloatField(2, variant=_messages.Variant.FLOAT) confidenceMetrics = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics', 3, repeated=True) confusionMatrix = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix', 4) logLoss = _messages.FloatField(5, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassificationEvaluationMetricsConfidenceMetrics(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsClassification EvaluationMetricsConfidenceMetrics object. Fields: confidenceThreshold: Metrics are computed with an assumption that the Model never returns predictions with score lower than this value. confusionMatrix: Confusion matrix of the evaluation for this confidence_threshold. f1Score: The harmonic mean of recall and precision. For summary metrics, it computes the micro-averaged F1 score. f1ScoreAt1: The harmonic mean of recallAt1 and precisionAt1. f1ScoreMacro: Macro-averaged F1 Score. f1ScoreMicro: Micro-averaged F1 Score. falseNegativeCount: The number of ground truth labels that are not matched by a Model created label. falsePositiveCount: The number of Model created labels that do not match a ground truth label. falsePositiveRate: False Positive Rate for the given confidence threshold. falsePositiveRateAt1: The False Positive Rate when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem. maxPredictions: Metrics are computed with an assumption that the Model always returns at most this many predictions (ordered by their score, descendingly), but they all still need to meet the `confidenceThreshold`. precision: Precision for the given confidence threshold. precisionAt1: The precision when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem. recall: Recall (True Positive Rate) for the given confidence threshold. recallAt1: The Recall (True Positive Rate) when only considering the label that has the highest prediction score and not below the confidence threshold for each DataItem. trueNegativeCount: The number of labels that were not created by the Model, but if they would, they would not match a ground truth label. truePositiveCount: The number of Model created labels that match a ground truth label. """ confidenceThreshold = _messages.FloatField(1, variant=_messages.Variant.FLOAT) confusionMatrix = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix', 2) f1Score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) f1ScoreAt1 = _messages.FloatField(4, variant=_messages.Variant.FLOAT) f1ScoreMacro = _messages.FloatField(5, variant=_messages.Variant.FLOAT) f1ScoreMicro = _messages.FloatField(6, variant=_messages.Variant.FLOAT) falseNegativeCount = _messages.IntegerField(7) falsePositiveCount = _messages.IntegerField(8) falsePositiveRate = _messages.FloatField(9, variant=_messages.Variant.FLOAT) falsePositiveRateAt1 = _messages.FloatField(10, variant=_messages.Variant.FLOAT) maxPredictions = _messages.IntegerField(11, variant=_messages.Variant.INT32) precision = _messages.FloatField(12, variant=_messages.Variant.FLOAT) precisionAt1 = _messages.FloatField(13, variant=_messages.Variant.FLOAT) recall = _messages.FloatField(14, variant=_messages.Variant.FLOAT) recallAt1 = _messages.FloatField(15, variant=_messages.Variant.FLOAT) trueNegativeCount = _messages.IntegerField(16) truePositiveCount = _messages.IntegerField(17) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix object. Messages: RowsValueListEntry: Single entry in a RowsValue. Fields: annotationSpecs: AnnotationSpecs used in the confusion matrix. For AutoML Text Extraction, a special negative AnnotationSpec with empty `id` and `displayName` of "NULL" will be added as the last element. rows: Rows in the confusion matrix. The number of rows is equal to the size of `annotationSpecs`. `rowsi` is the number of DataItems that have ground truth of the `annotationSpecs[i]` and are predicted as `annotationSpecs[j]` by the Model being evaluated. For Text Extraction, when `annotationSpecs[i]` is the last element in `annotationSpecs`, i.e. the special negative AnnotationSpec, `rowsi` is the number of predicted entities of `annoatationSpec[j]` that are not labeled as any of the ground truth AnnotationSpec. When annotationSpecs[j] is the special negative AnnotationSpec, `rowsi` is the number of entities have ground truth of `annotationSpec[i]` that are not predicted as an entity by the Model. The value of the last cell, i.e. `rowi` where i == j and `annotationSpec[i]` is the special negative AnnotationSpec, is always 0. """ class RowsValueListEntry(_messages.Message): r"""Single entry in a RowsValue. Fields: entry: A extra_types.JsonValue attribute. """ entry = _messages.MessageField('extra_types.JsonValue', 1, repeated=True) annotationSpecs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef', 1, repeated=True) rows = _messages.MessageField('RowsValueListEntry', 2, repeated=True) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrixAnnotationSpecRef(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatri xAnnotationSpecRef object. Fields: displayName: Display name of the AnnotationSpec. id: ID of the AnnotationSpec. """ displayName = _messages.StringField(1) id = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetrics(_messages.Message): r"""Metrics for forecasting evaluation results. Fields: meanAbsoluteError: Mean Absolute Error (MAE). meanAbsolutePercentageError: Mean absolute percentage error. Infinity when there are zeros in the ground truth. quantileMetrics: The quantile metrics entries for each quantile. rSquared: Coefficient of determination as Pearson correlation coefficient. Undefined when ground truth or predictions are constant or near constant. rootMeanSquaredError: Root Mean Squared Error (RMSE). rootMeanSquaredLogError: Root mean squared log error. Undefined when there are negative ground truth values or predictions. rootMeanSquaredPercentageError: Root Mean Square Percentage Error. Square root of MSPE. Undefined/imaginary when MSPE is negative. weightedAbsolutePercentageError: Weighted Absolute Percentage Error. Does not use weights, this is just what the metric is called. Undefined if actual values sum to zero. Will be very large if actual values sum to a very small number. """ meanAbsoluteError = _messages.FloatField(1, variant=_messages.Variant.FLOAT) meanAbsolutePercentageError = _messages.FloatField(2, variant=_messages.Variant.FLOAT) quantileMetrics = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry', 3, repeated=True) rSquared = _messages.FloatField(4, variant=_messages.Variant.FLOAT) rootMeanSquaredError = _messages.FloatField(5, variant=_messages.Variant.FLOAT) rootMeanSquaredLogError = _messages.FloatField(6, variant=_messages.Variant.FLOAT) rootMeanSquaredPercentageError = _messages.FloatField(7, variant=_messages.Variant.FLOAT) weightedAbsolutePercentageError = _messages.FloatField(8, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsForecastingEvaluationMetricsQuantileMetricsEntry(_messages.Message): r"""Entry for the Quantiles loss type optimization objective. Fields: observedQuantile: This is a custom metric that calculates the percentage of true values that were less than the predicted value for that quantile. Only populated when optimization_objective is minimize- quantile-loss and each entry corresponds to an entry in quantiles The percent value can be used to compare with the quantile value, which is the target value. quantile: The quantile for this entry. scaledPinballLoss: The scaled pinball loss of this quantile. """ observedQuantile = _messages.FloatField(1) quantile = _messages.FloatField(2) scaledPinballLoss = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsGeneralTextGenerationEvaluationMetrics(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsGeneralTextGen erationEvaluationMetrics object. Fields: bleu: BLEU (bilingual evaluation understudy) scores based on sacrebleu implementation. rougeLSum: ROUGE-L (Longest Common Subsequence) scoring at summary level. """ bleu = _messages.FloatField(1, variant=_messages.Variant.FLOAT) rougeLSum = _messages.FloatField(2, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageObjectDetectionEvaluationMetrics(_messages.Message): r"""Metrics for image object detection evaluation results. Fields: boundingBoxMeanAveragePrecision: The single metric for bounding boxes evaluation: the `meanAveragePrecision` averaged over all `boundingBoxMetricsEntries`. boundingBoxMetrics: The bounding boxes match metrics for each intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair. evaluatedBoundingBoxCount: The total number of bounding boxes (i.e. summed over all images) the ground truth used to create this evaluation had. """ boundingBoxMeanAveragePrecision = _messages.FloatField(1, variant=_messages.Variant.FLOAT) boundingBoxMetrics = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetrics', 2, repeated=True) evaluatedBoundingBoxCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetrics(_messages.Message): r"""Metrics for image segmentation evaluation results. Fields: confidenceMetricsEntries: Metrics for each confidenceThreshold in 0.00,0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 Precision-recall curve can be derived from it. """ confidenceMetricsEntries = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry', 1, repeated=True) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentationEvaluationMetricsConfidenceMetricsEntry(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsImageSegmentat ionEvaluationMetricsConfidenceMetricsEntry object. Fields: confidenceThreshold: Metrics are computed with an assumption that the model never returns predictions with score lower than this value. confusionMatrix: Confusion matrix for the given confidence threshold. diceScoreCoefficient: DSC or the F1 score, The harmonic mean of recall and precision. iouScore: The intersection-over-union score. The measure of overlap of the annotation's category mask with ground truth category mask on the DataItem. precision: Precision for the given confidence threshold. recall: Recall (True Positive Rate) for the given confidence threshold. """ confidenceThreshold = _messages.FloatField(1, variant=_messages.Variant.FLOAT) confusionMatrix = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix', 2) diceScoreCoefficient = _messages.FloatField(3, variant=_messages.Variant.FLOAT) iouScore = _messages.FloatField(4, variant=_messages.Variant.FLOAT) precision = _messages.FloatField(5, variant=_messages.Variant.FLOAT) recall = _messages.FloatField(6, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics(_messages.Message): r"""Metrics for general pairwise text generation evaluation results. Fields: accuracy: Fraction of cases where the autorater agreed with the human raters. baselineModelWinRate: Percentage of time the autorater decided the baseline model had the better response. cohensKappa: A measurement of agreement between the autorater and human raters that takes the likelihood of random agreement into account. f1Score: Harmonic mean of precision and recall. falseNegativeCount: Number of examples where the autorater chose the baseline model, but humans preferred the model. falsePositiveCount: Number of examples where the autorater chose the model, but humans preferred the baseline model. humanPreferenceBaselineModelWinRate: Percentage of time humans decided the baseline model had the better response. humanPreferenceModelWinRate: Percentage of time humans decided the model had the better response. modelWinRate: Percentage of time the autorater decided the model had the better response. precision: Fraction of cases where the autorater and humans thought the model had a better response out of all cases where the autorater thought the model had a better response. True positive divided by all positive. recall: Fraction of cases where the autorater and humans thought the model had a better response out of all cases where the humans thought the model had a better response. trueNegativeCount: Number of examples where both the autorater and humans decided that the model had the worse response. truePositiveCount: Number of examples where both the autorater and humans decided that the model had the better response. """ accuracy = _messages.FloatField(1, variant=_messages.Variant.FLOAT) baselineModelWinRate = _messages.FloatField(2, variant=_messages.Variant.FLOAT) cohensKappa = _messages.FloatField(3, variant=_messages.Variant.FLOAT) f1Score = _messages.FloatField(4, variant=_messages.Variant.FLOAT) falseNegativeCount = _messages.IntegerField(5) falsePositiveCount = _messages.IntegerField(6) humanPreferenceBaselineModelWinRate = _messages.FloatField(7, variant=_messages.Variant.FLOAT) humanPreferenceModelWinRate = _messages.FloatField(8, variant=_messages.Variant.FLOAT) modelWinRate = _messages.FloatField(9, variant=_messages.Variant.FLOAT) precision = _messages.FloatField(10, variant=_messages.Variant.FLOAT) recall = _messages.FloatField(11, variant=_messages.Variant.FLOAT) trueNegativeCount = _messages.IntegerField(12) truePositiveCount = _messages.IntegerField(13) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsQuestionAnsweringEvaluationMetrics(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsQuestionAnswer ingEvaluationMetrics object. Fields: exactMatch: The rate at which the input predicted strings exactly match their references. """ exactMatch = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsRegressionEvaluationMetrics(_messages.Message): r"""Metrics for regression evaluation results. Fields: meanAbsoluteError: Mean Absolute Error (MAE). meanAbsolutePercentageError: Mean absolute percentage error. Infinity when there are zeros in the ground truth. rSquared: Coefficient of determination as Pearson correlation coefficient. Undefined when ground truth or predictions are constant or near constant. rootMeanSquaredError: Root Mean Squared Error (RMSE). rootMeanSquaredLogError: Root mean squared log error. Undefined when there are negative ground truth values or predictions. """ meanAbsoluteError = _messages.FloatField(1, variant=_messages.Variant.FLOAT) meanAbsolutePercentageError = _messages.FloatField(2, variant=_messages.Variant.FLOAT) rSquared = _messages.FloatField(3, variant=_messages.Variant.FLOAT) rootMeanSquaredError = _messages.FloatField(4, variant=_messages.Variant.FLOAT) rootMeanSquaredLogError = _messages.FloatField(5, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsSummarizationEvaluationMetrics(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsSummarizationE valuationMetrics object. Fields: rougeLSum: ROUGE-L (Longest Common Subsequence) scoring at summary level. """ rougeLSum = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetrics(_messages.Message): r"""Metrics for text extraction evaluation results. Fields: confidenceMetrics: Metrics that have confidence thresholds. Precision- recall curve can be derived from them. confusionMatrix: Confusion matrix of the evaluation. Only set for Models where number of AnnotationSpecs is no more than 10. Only set for ModelEvaluations, not for ModelEvaluationSlices. """ confidenceMetrics = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics', 1, repeated=True) confusionMatrix = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix', 2) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtractionEvaluationMetricsConfidenceMetrics(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextExtraction EvaluationMetricsConfidenceMetrics object. Fields: confidenceThreshold: Metrics are computed with an assumption that the Model never returns predictions with score lower than this value. f1Score: The harmonic mean of recall and precision. precision: Precision for the given confidence threshold. recall: Recall (True Positive Rate) for the given confidence threshold. """ confidenceThreshold = _messages.FloatField(1, variant=_messages.Variant.FLOAT) f1Score = _messages.FloatField(2, variant=_messages.Variant.FLOAT) precision = _messages.FloatField(3, variant=_messages.Variant.FLOAT) recall = _messages.FloatField(4, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTextSentimentEvaluationMetrics(_messages.Message): r"""Model evaluation metrics for text sentiment problems. Fields: confusionMatrix: Confusion matrix of the evaluation. Only set for ModelEvaluations, not for ModelEvaluationSlices. f1Score: The harmonic mean of recall and precision. linearKappa: Linear weighted kappa. Only set for ModelEvaluations, not for ModelEvaluationSlices. meanAbsoluteError: Mean absolute error. Only set for ModelEvaluations, not for ModelEvaluationSlices. meanSquaredError: Mean squared error. Only set for ModelEvaluations, not for ModelEvaluationSlices. precision: Precision. quadraticKappa: Quadratic weighted kappa. Only set for ModelEvaluations, not for ModelEvaluationSlices. recall: Recall. """ confusionMatrix = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsConfusionMatrix', 1) f1Score = _messages.FloatField(2, variant=_messages.Variant.FLOAT) linearKappa = _messages.FloatField(3, variant=_messages.Variant.FLOAT) meanAbsoluteError = _messages.FloatField(4, variant=_messages.Variant.FLOAT) meanSquaredError = _messages.FloatField(5, variant=_messages.Variant.FLOAT) precision = _messages.FloatField(6, variant=_messages.Variant.FLOAT) quadraticKappa = _messages.FloatField(7, variant=_messages.Variant.FLOAT) recall = _messages.FloatField(8, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetrics(_messages.Message): r"""UNIMPLEMENTED. Track matching model metrics for a single track match threshold and multiple label match confidence thresholds. Fields: confidenceMetrics: Metrics for each label-match `confidenceThreshold` from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. Precision-recall curve is derived from them. iouThreshold: The intersection-over-union threshold value between bounding boxes across frames used to compute this metric entry. meanBoundingBoxIou: The mean bounding box iou over all confidence thresholds. meanMismatchRate: The mean mismatch rate over all confidence thresholds. meanTrackingAveragePrecision: The mean average precision over all confidence thresholds. """ confidenceMetrics = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics', 1, repeated=True) iouThreshold = _messages.FloatField(2, variant=_messages.Variant.FLOAT) meanBoundingBoxIou = _messages.FloatField(3, variant=_messages.Variant.FLOAT) meanMismatchRate = _messages.FloatField(4, variant=_messages.Variant.FLOAT) meanTrackingAveragePrecision = _messages.FloatField(5, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetricsConfidenceMetrics(_messages.Message): r"""Metrics for a single confidence threshold. Fields: boundingBoxIou: Bounding box intersection-over-union precision. Measures how well the bounding boxes overlap between each other (e.g. complete overlap or just barely above iou_threshold). confidenceThreshold: The confidence threshold value used to compute the metrics. mismatchRate: Mismatch rate, which measures the tracking consistency, i.e. correctness of instance ID continuity. trackingPrecision: Tracking precision. trackingRecall: Tracking recall. """ boundingBoxIou = _messages.FloatField(1, variant=_messages.Variant.FLOAT) confidenceThreshold = _messages.FloatField(2, variant=_messages.Variant.FLOAT) mismatchRate = _messages.FloatField(3, variant=_messages.Variant.FLOAT) trackingPrecision = _messages.FloatField(4, variant=_messages.Variant.FLOAT) trackingRecall = _messages.FloatField(5, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetrics(_messages.Message): r"""The Evaluation metrics given a specific precision_window_length. Fields: confidenceMetrics: Metrics for each label-match confidence_threshold from 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99. meanAveragePrecision: The mean average precision. precisionWindowLength: This VideoActionMetrics is calculated based on this prediction window length. If the predicted action's timestamp is inside the time window whose center is the ground truth action's timestamp with this specific length, the prediction result is treated as a true positive. """ confidenceMetrics = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics', 1, repeated=True) meanAveragePrecision = _messages.FloatField(2, variant=_messages.Variant.FLOAT) precisionWindowLength = _messages.StringField(3) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetricsConfidenceMetrics(_messages.Message): r"""Metrics for a single confidence threshold. Fields: confidenceThreshold: Output only. The confidence threshold value used to compute the metrics. f1Score: Output only. The harmonic mean of recall and precision. precision: Output only. Precision for the given confidence threshold. recall: Output only. Recall for the given confidence threshold. """ confidenceThreshold = _messages.FloatField(1, variant=_messages.Variant.FLOAT) f1Score = _messages.FloatField(2, variant=_messages.Variant.FLOAT) precision = _messages.FloatField(3, variant=_messages.Variant.FLOAT) recall = _messages.FloatField(4, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionRecognitionMetrics(_messages.Message): r"""Model evaluation metrics for video action recognition. Fields: evaluatedActionCount: The number of ground truth actions used to create this evaluation. videoActionMetrics: The metric entries for precision window lengths: 1s,2s,3s. """ evaluatedActionCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) videoActionMetrics = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoActionMetrics', 2, repeated=True) class GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsVideoObjectTrackingMetrics(_messages.Message): r"""Model evaluation metrics for video object tracking problems. Evaluates prediction quality of both labeled bounding boxes and labeled tracks (i.e. series of bounding boxes sharing same label and instance ID). Fields: boundingBoxMeanAveragePrecision: The single metric for bounding boxes evaluation: the `meanAveragePrecision` averaged over all `boundingBoxMetrics`. boundingBoxMetrics: The bounding boxes match metrics for each intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair. evaluatedBoundingBoxCount: UNIMPLEMENTED. The total number of bounding boxes (i.e. summed over all frames) the ground truth used to create this evaluation had. evaluatedFrameCount: UNIMPLEMENTED. The number of video frames used to create this evaluation. evaluatedTrackCount: UNIMPLEMENTED. The total number of tracks (i.e. as seen across all frames) the ground truth used to create this evaluation had. trackMeanAveragePrecision: UNIMPLEMENTED. The single metric for tracks accuracy evaluation: the `meanAveragePrecision` averaged over all `trackMetrics`. trackMeanBoundingBoxIou: UNIMPLEMENTED. The single metric for tracks bounding box iou evaluation: the `meanBoundingBoxIou` averaged over all `trackMetrics`. trackMeanMismatchRate: UNIMPLEMENTED. The single metric for tracking consistency evaluation: the `meanMismatchRate` averaged over all `trackMetrics`. trackMetrics: UNIMPLEMENTED. The tracks match metrics for each intersection-over-union threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 and each label confidence threshold 0.05,0.10,...,0.95,0.96,0.97,0.98,0.99 pair. """ boundingBoxMeanAveragePrecision = _messages.FloatField(1, variant=_messages.Variant.FLOAT) boundingBoxMetrics = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsBoundingBoxMetrics', 2, repeated=True) evaluatedBoundingBoxCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) evaluatedFrameCount = _messages.IntegerField(4, variant=_messages.Variant.INT32) evaluatedTrackCount = _messages.IntegerField(5, variant=_messages.Variant.INT32) trackMeanAveragePrecision = _messages.FloatField(6, variant=_messages.Variant.FLOAT) trackMeanBoundingBoxIou = _messages.FloatField(7, variant=_messages.Variant.FLOAT) trackMeanMismatchRate = _messages.FloatField(8, variant=_messages.Variant.FLOAT) trackMetrics = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaModelevaluationMetricsTrackMetrics', 9, repeated=True) class GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageClassificationPredictionInstance(_messages.Message): r"""Prediction input format for Image Classification. Fields: content: The image bytes or Cloud Storage URI to make the prediction on. mimeType: The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon """ content = _messages.StringField(1) mimeType = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageObjectDetectionPredictionInstance(_messages.Message): r"""Prediction input format for Image Object Detection. Fields: content: The image bytes or Cloud Storage URI to make the prediction on. mimeType: The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/gif - image/png - image/webp - image/bmp - image/tiff - image/vnd.microsoft.icon """ content = _messages.StringField(1) mimeType = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaPredictInstanceImageSegmentationPredictionInstance(_messages.Message): r"""Prediction input format for Image Segmentation. Fields: content: The image bytes to make the predictions on. mimeType: The MIME type of the content of the image. Only the images in below listed MIME types are supported. - image/jpeg - image/png """ content = _messages.StringField(1) mimeType = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextClassificationPredictionInstance(_messages.Message): r"""Prediction input format for Text Classification. Fields: content: The text snippet to make the predictions on. mimeType: The MIME type of the text snippet. The supported MIME types are listed below. - text/plain """ content = _messages.StringField(1) mimeType = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextExtractionPredictionInstance(_messages.Message): r"""Prediction input format for Text Extraction. Fields: content: The text snippet to make the predictions on. key: This field is only used for batch prediction. If a key is provided, the batch prediction result will by mapped to this key. If omitted, then the batch prediction result will contain the entire input instance. Vertex AI will not check if keys in the request are duplicates, so it is up to the caller to ensure the keys are unique. mimeType: The MIME type of the text snippet. The supported MIME types are listed below. - text/plain """ content = _messages.StringField(1) key = _messages.StringField(2) mimeType = _messages.StringField(3) class GoogleCloudAiplatformV1beta1SchemaPredictInstanceTextSentimentPredictionInstance(_messages.Message): r"""Prediction input format for Text Sentiment. Fields: content: The text snippet to make the predictions on. mimeType: The MIME type of the text snippet. The supported MIME types are listed below. - text/plain """ content = _messages.StringField(1) mimeType = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoActionRecognitionPredictionInstance(_messages.Message): r"""Prediction input format for Video Action Recognition. Fields: content: The Google Cloud Storage location of the video on which to perform the prediction. mimeType: The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime timeSegmentEnd: The end, exclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with "s" appended at the end. Fractions are allowed, up to a microsecond precision, and "inf" or "Infinity" is allowed, which means the end of the video. timeSegmentStart: The beginning, inclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with "s" appended at the end. Fractions are allowed, up to a microsecond precision. """ content = _messages.StringField(1) mimeType = _messages.StringField(2) timeSegmentEnd = _messages.StringField(3) timeSegmentStart = _messages.StringField(4) class GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoClassificationPredictionInstance(_messages.Message): r"""Prediction input format for Video Classification. Fields: content: The Google Cloud Storage location of the video on which to perform the prediction. mimeType: The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime timeSegmentEnd: The end, exclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with "s" appended at the end. Fractions are allowed, up to a microsecond precision, and "inf" or "Infinity" is allowed, which means the end of the video. timeSegmentStart: The beginning, inclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with "s" appended at the end. Fractions are allowed, up to a microsecond precision. """ content = _messages.StringField(1) mimeType = _messages.StringField(2) timeSegmentEnd = _messages.StringField(3) timeSegmentStart = _messages.StringField(4) class GoogleCloudAiplatformV1beta1SchemaPredictInstanceVideoObjectTrackingPredictionInstance(_messages.Message): r"""Prediction input format for Video Object Tracking. Fields: content: The Google Cloud Storage location of the video on which to perform the prediction. mimeType: The MIME type of the content of the video. Only the following are supported: video/mp4 video/avi video/quicktime timeSegmentEnd: The end, exclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with "s" appended at the end. Fractions are allowed, up to a microsecond precision, and "inf" or "Infinity" is allowed, which means the end of the video. timeSegmentStart: The beginning, inclusive, of the video's time segment on which to perform the prediction. Expressed as a number of seconds as measured from the start of the video, with "s" appended at the end. Fractions are allowed, up to a microsecond precision. """ content = _messages.StringField(1) mimeType = _messages.StringField(2) timeSegmentEnd = _messages.StringField(3) timeSegmentStart = _messages.StringField(4) class GoogleCloudAiplatformV1beta1SchemaPredictParamsGroundingConfig(_messages.Message): r"""The configuration for grounding checking. Fields: disableAttribution: If set, skip finding claim attributions (i.e not generate grounding citation). sources: The sources for the grounding checking. """ disableAttribution = _messages.BooleanField(1) sources = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPredictParamsGroundingConfigSourceEntry', 2, repeated=True) class GoogleCloudAiplatformV1beta1SchemaPredictParamsGroundingConfigSourceEntry(_messages.Message): r"""Single source entry for the grounding checking. Enums: TypeValueValuesEnum: The type of the grounding checking source. Fields: enterpriseDatastore: The uri of the Vertex AI Search data source. Deprecated. Use vertex_ai_search_datastore instead. inlineContext: The grounding text passed inline with the Predict API. It can support up to 1 million bytes. type: The type of the grounding checking source. vertexAiSearchDatastore: The uri of the Vertex AI Search data source. """ class TypeValueValuesEnum(_messages.Enum): r"""The type of the grounding checking source. Values: UNSPECIFIED: WEB: Uses Web Search to check the grounding. ENTERPRISE: Uses Vertex AI Search to check the grounding. Deprecated. Use VERTEX_AI_SEARCH instead. VERTEX_AI_SEARCH: Uses Vertex AI Search to check the grounding INLINE: Uses inline context to check the grounding. """ UNSPECIFIED = 0 WEB = 1 ENTERPRISE = 2 VERTEX_AI_SEARCH = 3 INLINE = 4 enterpriseDatastore = _messages.StringField(1) inlineContext = _messages.StringField(2) type = _messages.EnumField('TypeValueValuesEnum', 3) vertexAiSearchDatastore = _messages.StringField(4) class GoogleCloudAiplatformV1beta1SchemaPredictParamsImageClassificationPredictionParams(_messages.Message): r"""Prediction model parameters for Image Classification. Fields: confidenceThreshold: The Model only returns predictions with at least this confidence score. Default value is 0.0 maxPredictions: The Model only returns up to that many top, by confidence score, predictions per instance. If this number is very high, the Model may return fewer predictions. Default value is 10. """ confidenceThreshold = _messages.FloatField(1, variant=_messages.Variant.FLOAT) maxPredictions = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SchemaPredictParamsImageObjectDetectionPredictionParams(_messages.Message): r"""Prediction model parameters for Image Object Detection. Fields: confidenceThreshold: The Model only returns predictions with at least this confidence score. Default value is 0.0 maxPredictions: The Model only returns up to that many top, by confidence score, predictions per instance. Note that number of returned predictions is also limited by metadata's predictionsLimit. Default value is 10. """ confidenceThreshold = _messages.FloatField(1, variant=_messages.Variant.FLOAT) maxPredictions = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SchemaPredictParamsImageSegmentationPredictionParams(_messages.Message): r"""Prediction model parameters for Image Segmentation. Fields: confidenceThreshold: When the model predicts category of pixels of the image, it will only provide predictions for pixels that it is at least this much confident about. All other pixels will be classified as background. Default value is 0.5. """ confidenceThreshold = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoActionRecognitionPredictionParams(_messages.Message): r"""Prediction model parameters for Video Action Recognition. Fields: confidenceThreshold: The Model only returns predictions with at least this confidence score. Default value is 0.0 maxPredictions: The model only returns up to that many top, by confidence score, predictions per frame of the video. If this number is very high, the Model may return fewer predictions per frame. Default value is 50. """ confidenceThreshold = _messages.FloatField(1, variant=_messages.Variant.FLOAT) maxPredictions = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoClassificationPredictionParams(_messages.Message): r"""Prediction model parameters for Video Classification. Fields: confidenceThreshold: The Model only returns predictions with at least this confidence score. Default value is 0.0 maxPredictions: The Model only returns up to that many top, by confidence score, predictions per instance. If this number is very high, the Model may return fewer predictions. Default value is 10,000. oneSecIntervalClassification: Set to true to request classification for a video at one-second intervals. Vertex AI returns labels and their confidence scores for each second of the entire time segment of the video that user specified in the input WARNING: Model evaluation is not done for this classification type, the quality of it depends on the training data, but there are no metrics provided to describe that quality. Default value is false segmentClassification: Set to true to request segment-level classification. Vertex AI returns labels and their confidence scores for the entire time segment of the video that user specified in the input instance. Default value is true shotClassification: Set to true to request shot-level classification. Vertex AI determines the boundaries for each camera shot in the entire time segment of the video that user specified in the input instance. Vertex AI then returns labels and their confidence scores for each detected shot, along with the start and end time of the shot. WARNING: Model evaluation is not done for this classification type, the quality of it depends on the training data, but there are no metrics provided to describe that quality. Default value is false """ confidenceThreshold = _messages.FloatField(1, variant=_messages.Variant.FLOAT) maxPredictions = _messages.IntegerField(2, variant=_messages.Variant.INT32) oneSecIntervalClassification = _messages.BooleanField(3) segmentClassification = _messages.BooleanField(4) shotClassification = _messages.BooleanField(5) class GoogleCloudAiplatformV1beta1SchemaPredictParamsVideoObjectTrackingPredictionParams(_messages.Message): r"""Prediction model parameters for Video Object Tracking. Fields: confidenceThreshold: The Model only returns predictions with at least this confidence score. Default value is 0.0 maxPredictions: The model only returns up to that many top, by confidence score, predictions per frame of the video. If this number is very high, the Model may return fewer predictions per frame. Default value is 50. minBoundingBoxSize: Only bounding boxes with shortest edge at least that long as a relative value of video frame size are returned. Default value is 0.0. """ confidenceThreshold = _messages.FloatField(1, variant=_messages.Variant.FLOAT) maxPredictions = _messages.IntegerField(2, variant=_messages.Variant.INT32) minBoundingBoxSize = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionClassificationPredictionResult(_messages.Message): r"""Prediction output format for Image and Text Classification. Fields: confidences: The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids. displayNames: The display names of the AnnotationSpecs that had been identified, order matches the IDs. ids: The resource IDs of the AnnotationSpecs that had been identified. """ confidences = _messages.FloatField(1, repeated=True, variant=_messages.Variant.FLOAT) displayNames = _messages.StringField(2, repeated=True) ids = _messages.IntegerField(3, repeated=True) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionImageObjectDetectionPredictionResult(_messages.Message): r"""Prediction output format for Image Object Detection. Messages: BboxesValueListEntry: Single entry in a BboxesValue. Fields: bboxes: Bounding boxes, i.e. the rectangles over the image, that pinpoint the found AnnotationSpecs. Given in order that matches the IDs. Each bounding box is an array of 4 numbers `xMin`, `xMax`, `yMin`, and `yMax`, which represent the extremal coordinates of the box. They are relative to the image size, and the point 0,0 is in the top left of the image. confidences: The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids. displayNames: The display names of the AnnotationSpecs that had been identified, order matches the IDs. ids: The resource IDs of the AnnotationSpecs that had been identified, ordered by the confidence score descendingly. """ class BboxesValueListEntry(_messages.Message): r"""Single entry in a BboxesValue. Fields: entry: A extra_types.JsonValue attribute. """ entry = _messages.MessageField('extra_types.JsonValue', 1, repeated=True) bboxes = _messages.MessageField('BboxesValueListEntry', 1, repeated=True) confidences = _messages.FloatField(2, repeated=True, variant=_messages.Variant.FLOAT) displayNames = _messages.StringField(3, repeated=True) ids = _messages.IntegerField(4, repeated=True) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionImageSegmentationPredictionResult(_messages.Message): r"""Prediction output format for Image Segmentation. Fields: categoryMask: A PNG image where each pixel in the mask represents the category in which the pixel in the original image was predicted to belong to. The size of this image will be the same as the original image. The mapping between the AnntoationSpec and the color can be found in model's metadata. The model will choose the most likely category and if none of the categories reach the confidence threshold, the pixel will be marked as background. confidenceMask: A one channel image which is encoded as an 8bit lossless PNG. The size of the image will be the same as the original image. For a specific pixel, darker color means less confidence in correctness of the cateogry in the categoryMask for the corresponding pixel. Black means no confidence and white means complete confidence. """ categoryMask = _messages.StringField(1) confidenceMask = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionTabularClassificationPredictionResult(_messages.Message): r"""Prediction output format for Tabular Classification. Fields: classes: The name of the classes being classified, contains all possible values of the target column. scores: The model's confidence in each class being correct, higher value means higher confidence. The N-th score corresponds to the N-th class in classes. """ classes = _messages.StringField(1, repeated=True) scores = _messages.FloatField(2, repeated=True, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionTabularRegressionPredictionResult(_messages.Message): r"""Prediction output format for Tabular Regression. Fields: lowerBound: The lower bound of the prediction interval. quantilePredictions: Quantile predictions, in 1-1 correspondence with quantile_values. quantileValues: Quantile values. upperBound: The upper bound of the prediction interval. value: The regression value. """ lowerBound = _messages.FloatField(1, variant=_messages.Variant.FLOAT) quantilePredictions = _messages.FloatField(2, repeated=True, variant=_messages.Variant.FLOAT) quantileValues = _messages.FloatField(3, repeated=True, variant=_messages.Variant.FLOAT) upperBound = _messages.FloatField(4, variant=_messages.Variant.FLOAT) value = _messages.FloatField(5, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionTextExtractionPredictionResult(_messages.Message): r"""Prediction output format for Text Extraction. Fields: confidences: The Model's confidences in correctness of the predicted IDs, higher value means higher confidence. Order matches the Ids. displayNames: The display names of the AnnotationSpecs that had been identified, order matches the IDs. ids: The resource IDs of the AnnotationSpecs that had been identified, ordered by the confidence score descendingly. textSegmentEndOffsets: The end offsets, inclusive, of the text segment in which the AnnotationSpec has been identified. Expressed as a zero-based number of characters as measured from the start of the text snippet. textSegmentStartOffsets: The start offsets, inclusive, of the text segment in which the AnnotationSpec has been identified. Expressed as a zero- based number of characters as measured from the start of the text snippet. """ confidences = _messages.FloatField(1, repeated=True, variant=_messages.Variant.FLOAT) displayNames = _messages.StringField(2, repeated=True) ids = _messages.IntegerField(3, repeated=True) textSegmentEndOffsets = _messages.IntegerField(4, repeated=True) textSegmentStartOffsets = _messages.IntegerField(5, repeated=True) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionTextSentimentPredictionResult(_messages.Message): r"""Prediction output format for Text Sentiment Fields: sentiment: The integer sentiment labels between 0 (inclusive) and sentimentMax label (inclusive), while 0 maps to the least positive sentiment and sentimentMax maps to the most positive one. The higher the score is, the more positive the sentiment in the text snippet is. Note: sentimentMax is an integer value between 1 (inclusive) and 10 (inclusive). """ sentiment = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionTftFeatureImportance(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaPredictPredictionTftFeatureImportance object. Fields: attributeColumns: A string attribute. attributeWeights: A number attribute. contextColumns: A string attribute. contextWeights: TFT feature importance values. Each pair for {context/horizon/attribute} should have the same shape since the weight corresponds to the column names. horizonColumns: A string attribute. horizonWeights: A number attribute. """ attributeColumns = _messages.StringField(1, repeated=True) attributeWeights = _messages.FloatField(2, repeated=True, variant=_messages.Variant.FLOAT) contextColumns = _messages.StringField(3, repeated=True) contextWeights = _messages.FloatField(4, repeated=True, variant=_messages.Variant.FLOAT) horizonColumns = _messages.StringField(5, repeated=True) horizonWeights = _messages.FloatField(6, repeated=True, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionTimeSeriesForecastingPredictionResult(_messages.Message): r"""Prediction output format for Time Series Forecasting. Fields: quantilePredictions: Quantile predictions, in 1-1 correspondence with quantile_values. quantileValues: Quantile values. tftFeatureImportance: Only use these if TFt is enabled. value: The regression value. """ quantilePredictions = _messages.FloatField(1, repeated=True, variant=_messages.Variant.FLOAT) quantileValues = _messages.FloatField(2, repeated=True, variant=_messages.Variant.FLOAT) tftFeatureImportance = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPredictPredictionTftFeatureImportance', 3) value = _messages.FloatField(4, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoActionRecognitionPredictionResult(_messages.Message): r"""Prediction output format for Video Action Recognition. Fields: confidence: The Model's confidence in correction of this prediction, higher value means higher confidence. displayName: The display name of the AnnotationSpec that had been identified. id: The resource ID of the AnnotationSpec that had been identified. timeSegmentEnd: The end, exclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with "s" appended at the end. timeSegmentStart: The beginning, inclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with "s" appended at the end. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) displayName = _messages.StringField(2) id = _messages.StringField(3) timeSegmentEnd = _messages.StringField(4) timeSegmentStart = _messages.StringField(5) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoClassificationPredictionResult(_messages.Message): r"""Prediction output format for Video Classification. Fields: confidence: The Model's confidence in correction of this prediction, higher value means higher confidence. displayName: The display name of the AnnotationSpec that had been identified. id: The resource ID of the AnnotationSpec that had been identified. timeSegmentEnd: The end, exclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with "s" appended at the end. Note that for 'segment-classification' prediction type, this equals the original 'timeSegmentEnd' from the input instance, for other types it is the end of a shot or a 1 second interval respectively. timeSegmentStart: The beginning, inclusive, of the video's time segment in which the AnnotationSpec has been identified. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with "s" appended at the end. Note that for 'segment-classification' prediction type, this equals the original 'timeSegmentStart' from the input instance, for other types it is the start of a shot or a 1 second interval respectively. type: The type of the prediction. The requested types can be configured via parameters. This will be one of - segment-classification - shot- classification - one-sec-interval-classification """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) displayName = _messages.StringField(2) id = _messages.StringField(3) timeSegmentEnd = _messages.StringField(4) timeSegmentStart = _messages.StringField(5) type = _messages.StringField(6) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResult(_messages.Message): r"""Prediction output format for Video Object Tracking. Fields: confidence: The Model's confidence in correction of this prediction, higher value means higher confidence. displayName: The display name of the AnnotationSpec that had been identified. frames: All of the frames of the video in which a single object instance has been detected. The bounding boxes in the frames identify the same object. id: The resource ID of the AnnotationSpec that had been identified. timeSegmentEnd: The end, inclusive, of the video's time segment in which the object instance has been detected. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with "s" appended at the end. timeSegmentStart: The beginning, inclusive, of the video's time segment in which the object instance has been detected. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with "s" appended at the end. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) displayName = _messages.StringField(2) frames = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame', 3, repeated=True) id = _messages.StringField(4) timeSegmentEnd = _messages.StringField(5) timeSegmentStart = _messages.StringField(6) class GoogleCloudAiplatformV1beta1SchemaPredictPredictionVideoObjectTrackingPredictionResultFrame(_messages.Message): r"""The fields `xMin`, `xMax`, `yMin`, and `yMax` refer to a bounding box, i.e. the rectangle over the video frame pinpointing the found AnnotationSpec. The coordinates are relative to the frame size, and the point 0,0 is in the top left of the frame. Fields: timeOffset: A time (frame) of a video in which the object has been detected. Expressed as a number of seconds as measured from the start of the video, with fractions up to a microsecond precision, and with "s" appended at the end. xMax: The rightmost coordinate of the bounding box. xMin: The leftmost coordinate of the bounding box. yMax: The bottommost coordinate of the bounding box. yMin: The topmost coordinate of the bounding box. """ timeOffset = _messages.StringField(1) xMax = _messages.FloatField(2, variant=_messages.Variant.FLOAT) xMin = _messages.FloatField(3, variant=_messages.Variant.FLOAT) yMax = _messages.FloatField(4, variant=_messages.Variant.FLOAT) yMin = _messages.FloatField(5, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaPredictionResult(_messages.Message): r"""Represents a line of JSONL in the batch prediction output file. Messages: InstanceValue: User's input instance. Struct is used here instead of Any so that JsonFormat does not append an extra "@type" field when we convert the proto to JSON. Fields: error: The error result. Do not set prediction if this is set. instance: User's input instance. Struct is used here instead of Any so that JsonFormat does not append an extra "@type" field when we convert the proto to JSON. key: Optional user-provided key from the input instance. prediction: The prediction result. Value is used here instead of Any so that JsonFormat does not append an extra "@type" field when we convert the proto to JSON and so we can represent array of objects. Do not set error if this is set. """ @encoding.MapUnrecognizedFields('additionalProperties') class InstanceValue(_messages.Message): r"""User's input instance. Struct is used here instead of Any so that JsonFormat does not append an extra "@type" field when we convert the proto to JSON. Messages: AdditionalProperty: An additional property for a InstanceValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a InstanceValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) error = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPredictionResultError', 1) instance = _messages.MessageField('InstanceValue', 2) key = _messages.StringField(3) prediction = _messages.MessageField('extra_types.JsonValue', 4) class GoogleCloudAiplatformV1beta1SchemaPredictionResultError(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaPredictionResultError object. Enums: StatusValueValuesEnum: Error status. This will be serialized into the enum name e.g. "NOT_FOUND". Fields: message: Error message with additional details. status: Error status. This will be serialized into the enum name e.g. "NOT_FOUND". """ class StatusValueValuesEnum(_messages.Enum): r"""Error status. This will be serialized into the enum name e.g. "NOT_FOUND". Values: OK: Not an error; returned on success. HTTP Mapping: 200 OK CANCELLED: The operation was cancelled, typically by the caller. HTTP Mapping: 499 Client Closed Request UNKNOWN: Unknown error. For example, this error may be returned when a `Status` value received from another address space belongs to an error space that is not known in this address space. Also errors raised by APIs that do not return enough error information may be converted to this error. HTTP Mapping: 500 Internal Server Error INVALID_ARGUMENT: The client specified an invalid argument. Note that this differs from `FAILED_PRECONDITION`. `INVALID_ARGUMENT` indicates arguments that are problematic regardless of the state of the system (e.g., a malformed file name). HTTP Mapping: 400 Bad Request DEADLINE_EXCEEDED: The deadline expired before the operation could complete. For operations that change the state of the system, this error may be returned even if the operation has completed successfully. For example, a successful response from a server could have been delayed long enough for the deadline to expire. HTTP Mapping: 504 Gateway Timeout NOT_FOUND: Some requested entity (e.g., file or directory) was not found. Note to server developers: if a request is denied for an entire class of users, such as gradual feature rollout or undocumented allowlist, `NOT_FOUND` may be used. If a request is denied for some users within a class of users, such as user-based access control, `PERMISSION_DENIED` must be used. HTTP Mapping: 404 Not Found ALREADY_EXISTS: The entity that a client attempted to create (e.g., file or directory) already exists. HTTP Mapping: 409 Conflict PERMISSION_DENIED: The caller does not have permission to execute the specified operation. `PERMISSION_DENIED` must not be used for rejections caused by exhausting some resource (use `RESOURCE_EXHAUSTED` instead for those errors). `PERMISSION_DENIED` must not be used if the caller can not be identified (use `UNAUTHENTICATED` instead for those errors). This error code does not imply the request is valid or the requested entity exists or satisfies other pre-conditions. HTTP Mapping: 403 Forbidden UNAUTHENTICATED: The request does not have valid authentication credentials for the operation. HTTP Mapping: 401 Unauthorized RESOURCE_EXHAUSTED: Some resource has been exhausted, perhaps a per-user quota, or perhaps the entire file system is out of space. HTTP Mapping: 429 Too Many Requests FAILED_PRECONDITION: The operation was rejected because the system is not in a state required for the operation's execution. For example, the directory to be deleted is non-empty, an rmdir operation is applied to a non-directory, etc. Service implementors can use the following guidelines to decide between `FAILED_PRECONDITION`, `ABORTED`, and `UNAVAILABLE`: (a) Use `UNAVAILABLE` if the client can retry just the failing call. (b) Use `ABORTED` if the client should retry at a higher level. For example, when a client-specified test- and-set fails, indicating the client should restart a read-modify- write sequence. (c) Use `FAILED_PRECONDITION` if the client should not retry until the system state has been explicitly fixed. For example, if an "rmdir" fails because the directory is non-empty, `FAILED_PRECONDITION` should be returned since the client should not retry unless the files are deleted from the directory. HTTP Mapping: 400 Bad Request ABORTED: The operation was aborted, typically due to a concurrency issue such as a sequencer check failure or transaction abort. See the guidelines above for deciding between `FAILED_PRECONDITION`, `ABORTED`, and `UNAVAILABLE`. HTTP Mapping: 409 Conflict OUT_OF_RANGE: The operation was attempted past the valid range. E.g., seeking or reading past end-of-file. Unlike `INVALID_ARGUMENT`, this error indicates a problem that may be fixed if the system state changes. For example, a 32-bit file system will generate `INVALID_ARGUMENT` if asked to read at an offset that is not in the range [0,2^32-1], but it will generate `OUT_OF_RANGE` if asked to read from an offset past the current file size. There is a fair bit of overlap between `FAILED_PRECONDITION` and `OUT_OF_RANGE`. We recommend using `OUT_OF_RANGE` (the more specific error) when it applies so that callers who are iterating through a space can easily look for an `OUT_OF_RANGE` error to detect when they are done. HTTP Mapping: 400 Bad Request UNIMPLEMENTED: The operation is not implemented or is not supported/enabled in this service. HTTP Mapping: 501 Not Implemented INTERNAL: Internal errors. This means that some invariants expected by the underlying system have been broken. This error code is reserved for serious errors. HTTP Mapping: 500 Internal Server Error UNAVAILABLE: The service is currently unavailable. This is most likely a transient condition, which can be corrected by retrying with a backoff. Note that it is not always safe to retry non-idempotent operations. See the guidelines above for deciding between `FAILED_PRECONDITION`, `ABORTED`, and `UNAVAILABLE`. HTTP Mapping: 503 Service Unavailable DATA_LOSS: Unrecoverable data loss or corruption. HTTP Mapping: 500 Internal Server Error """ OK = 0 CANCELLED = 1 UNKNOWN = 2 INVALID_ARGUMENT = 3 DEADLINE_EXCEEDED = 4 NOT_FOUND = 5 ALREADY_EXISTS = 6 PERMISSION_DENIED = 7 UNAUTHENTICATED = 8 RESOURCE_EXHAUSTED = 9 FAILED_PRECONDITION = 10 ABORTED = 11 OUT_OF_RANGE = 12 UNIMPLEMENTED = 13 INTERNAL = 14 UNAVAILABLE = 15 DATA_LOSS = 16 message = _messages.StringField(1) status = _messages.EnumField('StatusValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1SchemaPromptApiSchema(_messages.Message): r"""The A2 schema of a prompt. Fields: apiSchemaVersion: The Schema version that represents changes to the API behavior. executions: A list of execution instances for constructing a ready-to-use prompt. multimodalPrompt: Multimodal prompt which embeds preambles to prompt string. structuredPrompt: The prompt variation that stores preambles in separate fields. translationPrompt: The prompt variation for Translation use case. """ apiSchemaVersion = _messages.StringField(1) executions = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptInstancePromptExecution', 2, repeated=True) multimodalPrompt = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecMultimodalPrompt', 3) structuredPrompt = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecStructuredPrompt', 4) translationPrompt = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationPrompt', 5) class GoogleCloudAiplatformV1beta1SchemaPromptInstancePromptExecution(_messages.Message): r"""A prompt instance's parameters set that contains a set of variable values. Messages: ArgumentsValue: Maps variable names to their value. Fields: arguments: Maps variable names to their value. """ @encoding.MapUnrecognizedFields('additionalProperties') class ArgumentsValue(_messages.Message): r"""Maps variable names to their value. Messages: AdditionalProperty: An additional property for a ArgumentsValue object. Fields: additionalProperties: Additional properties of type ArgumentsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a ArgumentsValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1SchemaPromptInstanceVariableValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptInstanceVariableValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) arguments = _messages.MessageField('ArgumentsValue', 1) class GoogleCloudAiplatformV1beta1SchemaPromptInstanceVariableValue(_messages.Message): r"""The value of a variable in prompt. Fields: partList: The parts of the variable value. """ partList = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecPartList', 1) class GoogleCloudAiplatformV1beta1SchemaPromptSpecMultimodalPrompt(_messages.Message): r"""Prompt variation that embeds preambles to prompt string. Fields: promptMessage: The prompt message. """ promptMessage = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecPromptMessage', 1) class GoogleCloudAiplatformV1beta1SchemaPromptSpecPartList(_messages.Message): r"""A list of elements and information that make up a portion of prompt. Fields: parts: A list of elements that can be part of a prompt. """ parts = _messages.MessageField('GoogleCloudAiplatformV1beta1Part', 1, repeated=True) class GoogleCloudAiplatformV1beta1SchemaPromptSpecPromptMessage(_messages.Message): r"""The prompt message that aligns with the prompt message in google.cloud.aiplatform.master.GenerateContentRequest. Fields: contents: The content of the current conversation with the model. For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request. generationConfig: Generation config. model: The model name. safetySettings: Per request settings for blocking unsafe content. Enforced on GenerateContentResponse.candidates. systemInstruction: The user provided system instructions for the model. Note: only text should be used in parts and content in each part will be in a separate paragraph. toolConfig: Tool config. This config is shared for all tools provided in the request. tools: A list of `Tools` the model may use to generate the next response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. """ contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1, repeated=True) generationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1GenerationConfig', 2) model = _messages.StringField(3) safetySettings = _messages.MessageField('GoogleCloudAiplatformV1beta1SafetySetting', 4, repeated=True) systemInstruction = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 5) toolConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolConfig', 6) tools = _messages.MessageField('GoogleCloudAiplatformV1beta1Tool', 7, repeated=True) class GoogleCloudAiplatformV1beta1SchemaPromptSpecReferenceSentencePair(_messages.Message): r"""A pair of sentences used as reference in source and target languages. Fields: sourceSentence: Source sentence in the sentence pair. targetSentence: Target sentence in the sentence pair. """ sourceSentence = _messages.StringField(1) targetSentence = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaPromptSpecReferenceSentencePairList(_messages.Message): r"""A list of reference sentence pairs. Fields: referenceSentencePairs: Reference sentence pairs. """ referenceSentencePairs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecReferenceSentencePair', 1, repeated=True) class GoogleCloudAiplatformV1beta1SchemaPromptSpecStructuredPrompt(_messages.Message): r"""Prompt variation that stores preambles in separate fields. Fields: context: Preamble: The context of the prompt. examples: Preamble: A set of examples for expected model response. infillPrefix: Preamble: For infill prompt, the prefix before expected model response. infillSuffix: Preamble: For infill prompt, the suffix after expected model response. inputPrefixes: Preamble: The input prefixes before each example input. outputPrefixes: Preamble: The output prefixes before each example output. predictionInputs: Preamble: The input test data for prediction. Each PartList in this field represents one text-only input set for a single model request. promptMessage: The prompt message. """ context = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1) examples = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecPartList', 2, repeated=True) infillPrefix = _messages.StringField(3) infillSuffix = _messages.StringField(4) inputPrefixes = _messages.StringField(5, repeated=True) outputPrefixes = _messages.StringField(6, repeated=True) predictionInputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecPartList', 7, repeated=True) promptMessage = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecPromptMessage', 8) class GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationExample(_messages.Message): r"""The translation example that contains reference sentences from various sources. Fields: referenceSentencePairLists: The reference sentences from inline text. referenceSentencesFileInputs: The reference sentences from file. """ referenceSentencePairLists = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecReferenceSentencePairList', 1, repeated=True) referenceSentencesFileInputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationSentenceFileInput', 2, repeated=True) class GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationFileInputSource(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationFileInputSource object. Fields: content: The file's contents. displayName: The file's display name. mimeType: The file's mime type. """ content = _messages.StringField(1) displayName = _messages.StringField(2) mimeType = _messages.StringField(3) class GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationGcsInputSource(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationGcsInputSource object. Fields: inputUri: Source data URI. For example, `gs://my_bucket/my_object`. """ inputUri = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationOption(_messages.Message): r"""Optional settings for translation prompt. Fields: numberOfShots: How many shots to use. """ numberOfShots = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationPrompt(_messages.Message): r"""Prompt variation for Translation use case. Fields: example: The translation example. option: The translation option. promptMessage: The prompt message. sourceLanguageCode: The source language code. targetLanguageCode: The target language code. """ example = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationExample', 1) option = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationOption', 2) promptMessage = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecPromptMessage', 3) sourceLanguageCode = _messages.StringField(4) targetLanguageCode = _messages.StringField(5) class GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationSentenceFileInput(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationSentenceFileInput object. Fields: fileInputSource: Inlined file source. gcsInputSource: Cloud Storage file source. """ fileInputSource = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationFileInputSource', 1) gcsInputSource = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptSpecTranslationGcsInputSource', 2) class GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadata(_messages.Message): r"""The metadata of Datasets that contain tables data. Fields: inputConfig: A GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataInputConfig attribute. """ inputConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataInputConfig', 1) class GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataBigQuerySource(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataBigQuerySource object. Fields: uri: The URI of a BigQuery table. e.g. bq://projectId.bqDatasetId.bqTableId """ uri = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataGcsSource(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataGcsSource object. Fields: uri: Cloud Storage URI of one or more files. Only CSV files are supported. The first line of the CSV file is used as the header. If there are multiple files, the header is the first line of the lexicographically first file, the other files must either contain the exact same header or omit the header. """ uri = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataInputConfig(_messages.Message): r"""The tables Dataset's data source. The Dataset doesn't store the data directly, but only pointer(s) to its data. Fields: bigquerySource: A GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataBigQuerySource attribute. gcsSource: A GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataGcsSource attribute. """ bigquerySource = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataBigQuerySource', 1) gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTablesDatasetMetadataGcsSource', 2) class GoogleCloudAiplatformV1beta1SchemaTextClassificationAnnotation(_messages.Message): r"""Annotation details specific to text classification. Fields: annotationSpecId: The resource Id of the AnnotationSpec that this Annotation pertains to. displayName: The display name of the AnnotationSpec that this Annotation pertains to. """ annotationSpecId = _messages.StringField(1) displayName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaTextDataItem(_messages.Message): r"""Payload of Text DataItem. Fields: gcsUri: Output only. Google Cloud Storage URI points to a copy of the original text in the Vertex-managed bucket in the user's project. The text file is up to 10MB in size. """ gcsUri = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTextDatasetMetadata(_messages.Message): r"""The metadata of Datasets that contain Text DataItems. Fields: dataItemSchemaUri: Points to a YAML file stored on Google Cloud Storage describing payload of the Text DataItems that belong to this Dataset. gcsBucket: Google Cloud Storage Bucket name that contains the blob data of this Dataset. """ dataItemSchemaUri = _messages.StringField(1) gcsBucket = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaTextExtractionAnnotation(_messages.Message): r"""Annotation details specific to text extraction. Fields: annotationSpecId: The resource Id of the AnnotationSpec that this Annotation pertains to. displayName: The display name of the AnnotationSpec that this Annotation pertains to. textSegment: The segment of the text content. """ annotationSpecId = _messages.StringField(1) displayName = _messages.StringField(2) textSegment = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTextSegment', 3) class GoogleCloudAiplatformV1beta1SchemaTextPromptDatasetMetadata(_messages.Message): r"""The metadata of Datasets that contain Text Prompt data. Fields: candidateCount: Number of candidates. gcsUri: The Google Cloud Storage URI that stores the prompt data. groundingConfig: Grounding checking configuration. hasPromptVariable: Whether the prompt dataset has prompt variable. logprobs: Whether or not the user has enabled logit probabilities in the model parameters. maxOutputTokens: Value of the maximum number of tokens generated set when the dataset was saved. note: User-created prompt note. Note size limit is 2KB. promptApiSchema: The API schema of the prompt to support both UI and SDK usages. promptType: Type of the prompt dataset. seedEnabled: Seeding enables model to return a deterministic response on a best effort basis. Determinism isn't guaranteed. This field determines whether or not seeding is enabled. seedValue: The actual value of the seed. stopSequences: Customized stop sequences. systemInstruction: The content of the prompt dataset system instruction. systemInstructionGcsUri: The Google Cloud Storage URI that stores the system instruction, starting with gs://. temperature: Temperature value used for sampling set when the dataset was saved. This value is used to tune the degree of randomness. text: The content of the prompt dataset. topK: Top K value set when the dataset was saved. This value determines how many candidates with highest probability from the vocab would be selected for each decoding step. topP: Top P value set when the dataset was saved. Given topK tokens for decoding, top candidates will be selected until the sum of their probabilities is topP. """ candidateCount = _messages.IntegerField(1) gcsUri = _messages.StringField(2) groundingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPredictParamsGroundingConfig', 3) hasPromptVariable = _messages.BooleanField(4) logprobs = _messages.BooleanField(5) maxOutputTokens = _messages.IntegerField(6) note = _messages.StringField(7) promptApiSchema = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaPromptApiSchema', 8) promptType = _messages.StringField(9) seedEnabled = _messages.BooleanField(10) seedValue = _messages.IntegerField(11) stopSequences = _messages.StringField(12, repeated=True) systemInstruction = _messages.StringField(13) systemInstructionGcsUri = _messages.StringField(14) temperature = _messages.FloatField(15, variant=_messages.Variant.FLOAT) text = _messages.StringField(16) topK = _messages.IntegerField(17) topP = _messages.FloatField(18, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SchemaTextSegment(_messages.Message): r"""The text segment inside of DataItem. Fields: content: The text content in the segment for output only. endOffset: Zero-based character index of the first character past the end of the text segment (counting character from the beginning of the text). The character at the end_offset is NOT included in the text segment. startOffset: Zero-based character index of the first character of the text segment (counting characters from the beginning of the text). """ content = _messages.StringField(1) endOffset = _messages.IntegerField(2, variant=_messages.Variant.UINT64) startOffset = _messages.IntegerField(3, variant=_messages.Variant.UINT64) class GoogleCloudAiplatformV1beta1SchemaTextSentimentAnnotation(_messages.Message): r"""Annotation details specific to text sentiment. Fields: annotationSpecId: The resource Id of the AnnotationSpec that this Annotation pertains to. displayName: The display name of the AnnotationSpec that this Annotation pertains to. sentiment: The sentiment score for text. sentimentMax: The sentiment max score for text. """ annotationSpecId = _messages.StringField(1) displayName = _messages.StringField(2) sentiment = _messages.IntegerField(3, variant=_messages.Variant.INT32) sentimentMax = _messages.IntegerField(4, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SchemaTextSentimentSavedQueryMetadata(_messages.Message): r"""The metadata of SavedQuery contains TextSentiment Annotations. Fields: sentimentMax: The maximum sentiment of sentiment Anntoation in this SavedQuery. """ sentimentMax = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SchemaTimeSegment(_messages.Message): r"""A time period inside of a DataItem that has a time dimension (e.g. video). Fields: endTimeOffset: End of the time segment (exclusive), represented as the duration since the start of the DataItem. startTimeOffset: Start of the time segment (inclusive), represented as the duration since the start of the DataItem. """ endTimeOffset = _messages.StringField(1) startTimeOffset = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadata(_messages.Message): r"""The metadata of Datasets that contain time series data. Fields: inputConfig: A GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataInputConfig attribute. timeColumn: The column name of the time column that identifies time order in the time series. timeSeriesIdentifierColumn: The column name of the time series identifier column that identifies the time series. """ inputConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataInputConfig', 1) timeColumn = _messages.StringField(2) timeSeriesIdentifierColumn = _messages.StringField(3) class GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataBigQuerySource(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataBigQuerySource object. Fields: uri: The URI of a BigQuery table. """ uri = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataGcsSource(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataGcsSource object. Fields: uri: Cloud Storage URI of one or more files. Only CSV files are supported. The first line of the CSV file is used as the header. If there are multiple files, the header is the first line of the lexicographically first file, the other files must either contain the exact same header or omit the header. """ uri = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataInputConfig(_messages.Message): r"""The time series Dataset's data source. The Dataset doesn't store the data directly, but only pointer(s) to its data. Fields: bigquerySource: A GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataBigQuerySourc e attribute. gcsSource: A GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataGcsSource attribute. """ bigquerySource = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataBigQuerySource', 1) gcsSource = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTimeSeriesDatasetMetadataGcsSource', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecasting(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Forecasting Model. Fields: inputs: The input parameters of this TrainingJob. metadata: The metadata information. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputs', 1) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingMetadata', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecasti ngInputs object. Fields: additionalExperiments: Additional experiment flags for the time series forcasting training. availableAtForecastColumns: Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day. contextWindow: The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field. dataGranularity: Expected difference in time granularity between rows in the data. enableProbabilisticInference: If probabilistic inference is enabled, the model will fit a distribution that captures the uncertainty of a prediction. At inference time, the predictive distribution is used to make a point prediction that minimizes the optimization objective. For example, the mean of a predictive distribution is the point prediction that minimizes RMSE loss. If quantiles are specified, then the quantiles of the distribution are also returned. The optimization objective cannot be minimize-quantile-loss. exportEvaluatedDataItemsConfig: Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed. forecastHorizon: The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field. hierarchyConfig: Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies. holidayRegions: The geographical region based on which the holiday effect is applied in modeling by adding holiday categorical array feature that include all holidays matching the date. This option only allowed when data_granularity is day. By default, holiday effect modeling is disabled. To turn it on, specify the holiday region using this option. optimizationObjective: Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * "minimize-rmse" (default) - Minimize root-mean-squared error (RMSE). * "minimize-mae" - Minimize mean-absolute error (MAE). * "minimize-rmsle" - Minimize root-mean-squared log error (RMSLE). * "minimize-rmspe" - Minimize root-mean-squared percentage error (RMSPE). * "minimize-wape-mae" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * "minimize- quantile-loss" - Minimize the quantile loss at the quantiles defined in `quantiles`. * "minimize-mape" - Minimize the mean absolute percentage error. quantiles: Quantiles to use for minimize-quantile-loss `optimization_objective`, or for probabilistic inference. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique. targetColumn: The name of the column that the Model is to predict values for. This column must be unavailable at forecast. timeColumn: The name of the column that identifies time order in the time series. This column must be available at forecast. timeSeriesAttributeColumns: Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color. timeSeriesIdentifierColumn: The name of the column that identifies the time series. trainBudgetMilliNodeHours: Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive. transformations: Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using "." as the delimiter. unavailableAtForecastColumns: Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day. validationOptions: Validation options for the data validation component. The available options are: * "fail-pipeline" - default, will validate against the validation and fail the pipeline if it fails. * "ignore- validation" - ignore the results of the validation and continue weightColumn: Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1. windowConfig: Config containing strategy for generating sliding windows. """ additionalExperiments = _messages.StringField(1, repeated=True) availableAtForecastColumns = _messages.StringField(2, repeated=True) contextWindow = _messages.IntegerField(3) dataGranularity = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity', 4) enableProbabilisticInference = _messages.BooleanField(5) exportEvaluatedDataItemsConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig', 6) forecastHorizon = _messages.IntegerField(7) hierarchyConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig', 8) holidayRegions = _messages.StringField(9, repeated=True) optimizationObjective = _messages.StringField(10) quantiles = _messages.FloatField(11, repeated=True) targetColumn = _messages.StringField(12) timeColumn = _messages.StringField(13) timeSeriesAttributeColumns = _messages.StringField(14, repeated=True) timeSeriesIdentifierColumn = _messages.StringField(15) trainBudgetMilliNodeHours = _messages.IntegerField(16) transformations = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation', 17, repeated=True) unavailableAtForecastColumns = _messages.StringField(18, repeated=True) validationOptions = _messages.StringField(19) weightColumn = _messages.StringField(20) windowConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig', 21) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsGranularity(_messages.Message): r"""A duration of time expressed in time granularity units. Fields: quantity: The number of granularity_units between data points in the training data. If `granularity_unit` is `minute`, can be 1, 5, 10, 15, or 30. For all other values of `granularity_unit`, must be 1. unit: The time granularity unit of this time period. The supported units are: * "minute" * "hour" * "day" * "week" * "month" * "year" """ quantity = _messages.IntegerField(1) unit = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformation(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecasti ngInputsTransformation object. Fields: auto: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForec astingInputsTransformationAutoTransformation attribute. categorical: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAuto MlForecastingInputsTransformationCategoricalTransformation attribute. numeric: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlFo recastingInputsTransformationNumericTransformation attribute. text: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForec astingInputsTransformationTextTransformation attribute. timestamp: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMl ForecastingInputsTransformationTimestampTransformation attribute. """ auto = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation', 1) categorical = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation', 2) numeric = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation', 3) text = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation', 4) timestamp = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation', 5) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationAutoTransformation(_messages.Message): r"""Training pipeline will infer the proper transformation based on the statistic of dataset. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationCategoricalTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the "unknown" category. The "unknown" category gets its own special lookup index and resulting embedding. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationNumericTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * A boolean value that indicates whether the value is valid. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTextTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingInputsTransformationTimestampTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed. Fields: columnName: A string attribute. timeFormat: The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix- milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `"Z"` (e.g. 1985-04-12T23:20:50.52Z) """ columnName = _messages.StringField(1) timeFormat = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlForecastingMetadata(_messages.Message): r"""Model metadata specific to AutoML Forecasting. Fields: evaluatedDataItemsBigqueryUri: BigQuery destination uri for exported evaluated examples. trainCostMilliNodeHours: Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget. """ evaluatedDataItemsBigqueryUri = _messages.StringField(1) trainCostMilliNodeHours = _messages.IntegerField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassification(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Image Classification Model. Fields: inputs: The input parameters of this TrainingJob. metadata: The metadata information. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs', 1) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClas sificationInputs object. Enums: ModelTypeValueValuesEnum: Fields: baseModelId: The ID of the `base` model. If it is specified, the new model will be trained based on the `base` model. Otherwise, the new model will be trained from scratch. The `base` model must be in the same Project and Location as the new Model to train, and have the same modelType. budgetMilliNodeHours: The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be `model-converged`. Note, node_hour = actual_hour * number_of_nodes_involved. For modelType `cloud`(default), the budget must be between 8,000 and 800,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time, considering 8 nodes are used. For model types `mobile- tf-low-latency-1`, `mobile-tf-versatile-1`, `mobile-tf-high-accuracy-1`, the training budget must be between 1,000 and 100,000 milli node hours, inclusive. The default value is 24,000 which represents one day in wall time on a single node that is used. disableEarlyStopping: Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Classification might stop training before the entire training budget has been used. modelType: A ModelTypeValueValuesEnum attribute. multiLabel: If false, a single-label (multi-class) Model will be trained (i.e. assuming that for each image just up to one annotation may be applicable). If true, a multi-label Model will be trained (i.e. assuming that for each image multiple annotations may be applicable). tunableParameter: Trainer type for Vision TrainRequest. uptrainBaseModelId: The ID of `base` model for upTraining. If it is specified, the new model will be upTrained based on the `base` model for upTraining. Otherwise, the new model will be trained from scratch. The `base` model for upTraining must be in the same Project and Location as the new Model to train, and have the same modelType. """ class ModelTypeValueValuesEnum(_messages.Enum): r"""ModelTypeValueValuesEnum enum type. Values: MODEL_TYPE_UNSPECIFIED: Should not be set. CLOUD: A Model best tailored to be used within Google Cloud, and which cannot be exported. Default. CLOUD_1: A model type best tailored to be used within Google Cloud, which cannot be exported externally. Compared to the CLOUD model above, it is expected to have higher prediction accuracy. MOBILE_TF_LOW_LATENCY_1: A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow or Core ML model and used on a mobile or edge device afterwards. Expected to have low latency, but may have lower prediction quality than other mobile models. MOBILE_TF_VERSATILE_1: A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow or Core ML model and used on a mobile or edge device with afterwards. MOBILE_TF_HIGH_ACCURACY_1: A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow or Core ML model and used on a mobile or edge device afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other mobile models. EFFICIENTNET: EfficientNet model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally. MAXVIT: MaxViT model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally. VIT: ViT model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally. COCA: CoCa model for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally. """ MODEL_TYPE_UNSPECIFIED = 0 CLOUD = 1 CLOUD_1 = 2 MOBILE_TF_LOW_LATENCY_1 = 3 MOBILE_TF_VERSATILE_1 = 4 MOBILE_TF_HIGH_ACCURACY_1 = 5 EFFICIENTNET = 6 MAXVIT = 7 VIT = 8 COCA = 9 baseModelId = _messages.StringField(1) budgetMilliNodeHours = _messages.IntegerField(2) disableEarlyStopping = _messages.BooleanField(3) modelType = _messages.EnumField('ModelTypeValueValuesEnum', 4) multiLabel = _messages.BooleanField(5) tunableParameter = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter', 6) uptrainBaseModelId = _messages.StringField(7) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClassificationMetadata(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageClas sificationMetadata object. Enums: SuccessfulStopReasonValueValuesEnum: For successful job completions, this is the reason why the job has finished. Fields: costMilliNodeHours: The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours. successfulStopReason: For successful job completions, this is the reason why the job has finished. """ class SuccessfulStopReasonValueValuesEnum(_messages.Enum): r"""For successful job completions, this is the reason why the job has finished. Values: SUCCESSFUL_STOP_REASON_UNSPECIFIED: Should not be set. BUDGET_REACHED: The inputs.budgetMilliNodeHours had been reached. MODEL_CONVERGED: Further training of the Model ceased to increase its quality, since it already has converged. """ SUCCESSFUL_STOP_REASON_UNSPECIFIED = 0 BUDGET_REACHED = 1 MODEL_CONVERGED = 2 costMilliNodeHours = _messages.IntegerField(1) successfulStopReason = _messages.EnumField('SuccessfulStopReasonValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetection(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Image Object Detection Model. Fields: inputs: The input parameters of this TrainingJob. metadata: The metadata information """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs', 1) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObje ctDetectionInputs object. Enums: ModelTypeValueValuesEnum: Fields: budgetMilliNodeHours: The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be `model-converged`. Note, node_hour = actual_hour * number_of_nodes_involved. For modelType `cloud`(default), the budget must be between 20,000 and 900,000 milli node hours, inclusive. The default value is 216,000 which represents one day in wall time, considering 9 nodes are used. For model types `mobile- tf-low-latency-1`, `mobile-tf-versatile-1`, `mobile-tf-high-accuracy-1` the training budget must be between 1,000 and 100,000 milli node hours, inclusive. The default value is 24,000 which represents one day in wall time on a single node that is used. disableEarlyStopping: Use the entire training budget. This disables the early stopping feature. When false the early stopping feature is enabled, which means that AutoML Image Object Detection might stop training before the entire training budget has been used. modelType: A ModelTypeValueValuesEnum attribute. tunableParameter: Trainer type for Vision TrainRequest. uptrainBaseModelId: The ID of `base` model for upTraining. If it is specified, the new model will be upTrained based on the `base` model for upTraining. Otherwise, the new model will be trained from scratch. The `base` model for upTraining must be in the same Project and Location as the new Model to train, and have the same modelType. """ class ModelTypeValueValuesEnum(_messages.Enum): r"""ModelTypeValueValuesEnum enum type. Values: MODEL_TYPE_UNSPECIFIED: Should not be set. CLOUD_HIGH_ACCURACY_1: A model best tailored to be used within Google Cloud, and which cannot be exported. Expected to have a higher latency, but should also have a higher prediction quality than other cloud models. CLOUD_LOW_LATENCY_1: A model best tailored to be used within Google Cloud, and which cannot be exported. Expected to have a low latency, but may have lower prediction quality than other cloud models. CLOUD_1: A model best tailored to be used within Google Cloud, and which cannot be exported. Compared to the CLOUD_HIGH_ACCURACY_1 and CLOUD_LOW_LATENCY_1 models above, it is expected to have higher prediction quality and lower latency. MOBILE_TF_LOW_LATENCY_1: A model that, in addition to being available within Google Cloud can also be exported (see ModelService.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have low latency, but may have lower prediction quality than other mobile models. MOBILE_TF_VERSATILE_1: A model that, in addition to being available within Google Cloud can also be exported (see ModelService.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. MOBILE_TF_HIGH_ACCURACY_1: A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) and used on a mobile or edge device with TensorFlow afterwards. Expected to have a higher latency, but should also have a higher prediction quality than other mobile models. CLOUD_STREAMING_1: A model best tailored to be used within Google Cloud, and which cannot be exported. Expected to best support predictions in streaming with lower latency and lower prediction quality than other cloud models. SPINENET: SpineNet for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally. YOLO: YOLO for Model Garden training with customizable hyperparameters. Best tailored to be used within Google Cloud, and cannot be exported externally. """ MODEL_TYPE_UNSPECIFIED = 0 CLOUD_HIGH_ACCURACY_1 = 1 CLOUD_LOW_LATENCY_1 = 2 CLOUD_1 = 3 MOBILE_TF_LOW_LATENCY_1 = 4 MOBILE_TF_VERSATILE_1 = 5 MOBILE_TF_HIGH_ACCURACY_1 = 6 CLOUD_STREAMING_1 = 7 SPINENET = 8 YOLO = 9 budgetMilliNodeHours = _messages.IntegerField(1) disableEarlyStopping = _messages.BooleanField(2) modelType = _messages.EnumField('ModelTypeValueValuesEnum', 3) tunableParameter = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter', 4) uptrainBaseModelId = _messages.StringField(5) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObjectDetectionMetadata(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageObje ctDetectionMetadata object. Enums: SuccessfulStopReasonValueValuesEnum: For successful job completions, this is the reason why the job has finished. Fields: costMilliNodeHours: The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours. successfulStopReason: For successful job completions, this is the reason why the job has finished. """ class SuccessfulStopReasonValueValuesEnum(_messages.Enum): r"""For successful job completions, this is the reason why the job has finished. Values: SUCCESSFUL_STOP_REASON_UNSPECIFIED: Should not be set. BUDGET_REACHED: The inputs.budgetMilliNodeHours had been reached. MODEL_CONVERGED: Further training of the Model ceased to increase its quality, since it already has converged. """ SUCCESSFUL_STOP_REASON_UNSPECIFIED = 0 BUDGET_REACHED = 1 MODEL_CONVERGED = 2 costMilliNodeHours = _messages.IntegerField(1) successfulStopReason = _messages.EnumField('SuccessfulStopReasonValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentation(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Image Segmentation Model. Fields: inputs: The input parameters of this TrainingJob. metadata: The metadata information. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs', 1) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegm entationInputs object. Enums: ModelTypeValueValuesEnum: Fields: baseModelId: The ID of the `base` model. If it is specified, the new model will be trained based on the `base` model. Otherwise, the new model will be trained from scratch. The `base` model must be in the same Project and Location as the new Model to train, and have the same modelType. budgetMilliNodeHours: The training budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The actual metadata.costMilliNodeHours will be equal or less than this value. If further model training ceases to provide any improvements, it will stop without using the full budget and the metadata.successfulStopReason will be `model-converged`. Note, node_hour = actual_hour * number_of_nodes_involved. Or actual_wall_clock_hours = train_budget_milli_node_hours / (number_of_nodes_involved * 1000) For modelType `cloud-high-accuracy-1`(default), the budget must be between 20,000 and 2,000,000 milli node hours, inclusive. The default value is 192,000 which represents one day in wall time (1000 milli * 24 hours * 8 nodes). modelType: A ModelTypeValueValuesEnum attribute. """ class ModelTypeValueValuesEnum(_messages.Enum): r"""ModelTypeValueValuesEnum enum type. Values: MODEL_TYPE_UNSPECIFIED: Should not be set. CLOUD_HIGH_ACCURACY_1: A model to be used via prediction calls to uCAIP API. Expected to have a higher latency, but should also have a higher prediction quality than other models. CLOUD_LOW_ACCURACY_1: A model to be used via prediction calls to uCAIP API. Expected to have a lower latency but relatively lower prediction quality. MOBILE_TF_LOW_LATENCY_1: A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as TensorFlow model and used on a mobile or edge device afterwards. Expected to have low latency, but may have lower prediction quality than other mobile models. """ MODEL_TYPE_UNSPECIFIED = 0 CLOUD_HIGH_ACCURACY_1 = 1 CLOUD_LOW_ACCURACY_1 = 2 MOBILE_TF_LOW_LATENCY_1 = 3 baseModelId = _messages.StringField(1) budgetMilliNodeHours = _messages.IntegerField(2) modelType = _messages.EnumField('ModelTypeValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegmentationMetadata(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlImageSegm entationMetadata object. Enums: SuccessfulStopReasonValueValuesEnum: For successful job completions, this is the reason why the job has finished. Fields: costMilliNodeHours: The actual training cost of creating this model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed inputs.budgetMilliNodeHours. successfulStopReason: For successful job completions, this is the reason why the job has finished. """ class SuccessfulStopReasonValueValuesEnum(_messages.Enum): r"""For successful job completions, this is the reason why the job has finished. Values: SUCCESSFUL_STOP_REASON_UNSPECIFIED: Should not be set. BUDGET_REACHED: The inputs.budgetMilliNodeHours had been reached. MODEL_CONVERGED: Further training of the Model ceased to increase its quality, since it already has converged. """ SUCCESSFUL_STOP_REASON_UNSPECIFIED = 0 BUDGET_REACHED = 1 MODEL_CONVERGED = 2 costMilliNodeHours = _messages.IntegerField(1) successfulStopReason = _messages.EnumField('SuccessfulStopReasonValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTables(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Tables Model. Fields: inputs: The input parameters of this TrainingJob. metadata: The metadata information. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputs', 1) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesMetadata', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputs object. Fields: additionalExperiments: Additional experiment flags for the Tables training pipeline. disableEarlyStopping: Use the entire training budget. This disables the early stopping feature. By default, the early stopping feature is enabled, which means that AutoML Tables might stop training before the entire training budget has been used. exportEvaluatedDataItemsConfig: Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed. optimizationObjective: Objective function the model is optimizing towards. The training process creates a model that maximizes/minimizes the value of the objective function over the validation set. The supported optimization objectives depend on the prediction type. If the field is not set, a default objective function is used. classification (binary): "maximize-au-roc" (default) - Maximize the area under the receiver operating characteristic (ROC) curve. "minimize-log-loss" - Minimize log loss. "maximize-au-prc" - Maximize the area under the precision-recall curve. "maximize-precision-at-recall" - Maximize precision for a specified recall value. "maximize-recall-at-precision" - Maximize recall for a specified precision value. classification (multi-class): "minimize-log-loss" (default) - Minimize log loss. regression: "minimize-rmse" (default) - Minimize root-mean-squared error (RMSE). "minimize-mae" - Minimize mean-absolute error (MAE). "minimize-rmsle" - Minimize root-mean-squared log error (RMSLE). optimizationObjectivePrecisionValue: Required when optimization_objective is "maximize-recall-at-precision". Must be between 0 and 1, inclusive. optimizationObjectiveRecallValue: Required when optimization_objective is "maximize-precision-at-recall". Must be between 0 and 1, inclusive. predictionType: The type of prediction the Model is to produce. "classification" - Predict one out of multiple target values is picked for each row. "regression" - Predict a value based on its relation to other values. This type is available only to columns that contain semantically numeric values, i.e. integers or floating point number, even if stored as e.g. strings. targetColumn: The column name of the target column that the model is to predict. trainBudgetMilliNodeHours: Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive. transformations: Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using "." as the delimiter. weightColumnName: Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1. """ additionalExperiments = _messages.StringField(1, repeated=True) disableEarlyStopping = _messages.BooleanField(2) exportEvaluatedDataItemsConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig', 3) optimizationObjective = _messages.StringField(4) optimizationObjectivePrecisionValue = _messages.FloatField(5, variant=_messages.Variant.FLOAT) optimizationObjectiveRecallValue = _messages.FloatField(6, variant=_messages.Variant.FLOAT) predictionType = _messages.StringField(7) targetColumn = _messages.StringField(8) trainBudgetMilliNodeHours = _messages.IntegerField(9) transformations = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation', 10, repeated=True) weightColumnName = _messages.StringField(11) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformation(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInp utsTransformation object. Fields: auto: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTable sInputsTransformationAutoTransformation attribute. categorical: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAuto MlTablesInputsTransformationCategoricalTransformation attribute. numeric: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTa blesInputsTransformationNumericTransformation attribute. repeatedCategorical: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefini tionAutoMlTablesInputsTransformationCategoricalArrayTransformation attribute. repeatedNumeric: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinition AutoMlTablesInputsTransformationNumericArrayTransformation attribute. repeatedText: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAut oMlTablesInputsTransformationTextArrayTransformation attribute. text: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTable sInputsTransformationTextTransformation attribute. timestamp: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMl TablesInputsTransformationTimestampTransformation attribute. """ auto = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation', 1) categorical = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation', 2) numeric = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation', 3) repeatedCategorical = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation', 4) repeatedNumeric = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation', 5) repeatedText = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation', 6) text = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation', 7) timestamp = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation', 8) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationAutoTransformation(_messages.Message): r"""Training pipeline will infer the proper transformation based on the statistic of dataset. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalArrayTransformation(_messages.Message): r"""Treats the column as categorical array and performs following transformation functions. * For each element in the array, convert the category name to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean. * Empty arrays treated as an embedding of zeroes. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationCategoricalTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the "unknown" category. The "unknown" category gets its own special lookup index and resulting embedding. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericArrayTransformation(_messages.Message): r"""Treats the column as numerical array and performs following transformation functions. * All transformations for Numerical types applied to the average of the all elements. * The average of empty arrays is treated as zero. Fields: columnName: A string attribute. invalidValuesAllowed: If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data. """ columnName = _messages.StringField(1) invalidValuesAllowed = _messages.BooleanField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationNumericTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * A boolean value that indicates whether the value is valid. Fields: columnName: A string attribute. invalidValuesAllowed: If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data. """ columnName = _messages.StringField(1) invalidValuesAllowed = _messages.BooleanField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextArrayTransformation(_messages.Message): r"""Treats the column as text array and performs following transformation functions. * Concatenate all text values in the array into a single text value using a space (" ") as a delimiter, and then treat the result as a single text value. Apply the transformations for Text columns. * Empty arrays treated as an empty text. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTextTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Tokenize text to words. Convert each words to a dictionary lookup index and generate an embedding for each index. Combine the embedding of all elements into a single embedding using the mean. * Tokenization is based on unicode script boundaries. * Missing values get their own lookup index and resulting embedding. * Stop-words receive no special treatment and are not removed. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesInputsTransformationTimestampTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the * timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed. Fields: columnName: A string attribute. invalidValuesAllowed: If invalid values is allowed, the training pipeline will create a boolean feature that indicated whether the value is valid. Otherwise, the training pipeline will discard the input row from trainining data. timeFormat: The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix- milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `"Z"` (e.g. 1985-04-12T23:20:50.52Z) """ columnName = _messages.StringField(1) invalidValuesAllowed = _messages.BooleanField(2) timeFormat = _messages.StringField(3) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTablesMetadata(_messages.Message): r"""Model metadata specific to AutoML Tables. Fields: evaluatedDataItemsBigqueryUri: BigQuery destination uri for exported evaluated examples. trainCostMilliNodeHours: Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget. """ evaluatedDataItemsBigqueryUri = _messages.StringField(1) trainCostMilliNodeHours = _messages.IntegerField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassification(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Text Classification Model. Fields: inputs: The input parameters of this TrainingJob. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs', 1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClassificationInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextClass ificationInputs object. Fields: multiLabel: A boolean attribute. """ multiLabel = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtraction(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Text Extraction Model. Fields: inputs: The input parameters of this TrainingJob. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs', 1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtractionInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextExtra ctionInputs object. """ class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentiment(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Text Sentiment Model. Fields: inputs: The input parameters of this TrainingJob. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs', 1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSentimentInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlTextSenti mentInputs object. Fields: sentimentMax: A sentiment is expressed as an integer ordinal, where higher value means a more positive sentiment. The range of sentiments that will be used is between 0 and sentimentMax (inclusive on both ends), and all the values in the range must be represented in the dataset before a model can be created. Only the Annotations with this sentimentMax will be used for training. sentimentMax value must be between 1 and 10 (inclusive). """ sentimentMax = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognition(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Video Action Recognition Model. Fields: inputs: The input parameters of this TrainingJob. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs', 1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActionRecognitionInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoActi onRecognitionInputs object. Enums: ModelTypeValueValuesEnum: Fields: modelType: A ModelTypeValueValuesEnum attribute. """ class ModelTypeValueValuesEnum(_messages.Enum): r"""ModelTypeValueValuesEnum enum type. Values: MODEL_TYPE_UNSPECIFIED: Should not be set. CLOUD: A model best tailored to be used within Google Cloud, and which c annot be exported. Default. MOBILE_VERSATILE_1: A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a mobile or edge device afterwards. MOBILE_JETSON_VERSATILE_1: A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) to a Jetson device afterwards. MOBILE_CORAL_VERSATILE_1: A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a Coral device afterwards. """ MODEL_TYPE_UNSPECIFIED = 0 CLOUD = 1 MOBILE_VERSATILE_1 = 2 MOBILE_JETSON_VERSATILE_1 = 3 MOBILE_CORAL_VERSATILE_1 = 4 modelType = _messages.EnumField('ModelTypeValueValuesEnum', 1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassification(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Video Classification Model. Fields: inputs: The input parameters of this TrainingJob. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs', 1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClassificationInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoClas sificationInputs object. Enums: ModelTypeValueValuesEnum: Fields: modelType: A ModelTypeValueValuesEnum attribute. """ class ModelTypeValueValuesEnum(_messages.Enum): r"""ModelTypeValueValuesEnum enum type. Values: MODEL_TYPE_UNSPECIFIED: Should not be set. CLOUD: A model best tailored to be used within Google Cloud, and which cannot be exported. Default. MOBILE_VERSATILE_1: A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a mobile or edge device afterwards. MOBILE_JETSON_VERSATILE_1: A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) to a Jetson device afterwards. """ MODEL_TYPE_UNSPECIFIED = 0 CLOUD = 1 MOBILE_VERSATILE_1 = 2 MOBILE_JETSON_VERSATILE_1 = 3 modelType = _messages.EnumField('ModelTypeValueValuesEnum', 1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTracking(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Video ObjectTracking Model. Fields: inputs: The input parameters of this TrainingJob. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs', 1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObjectTrackingInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutoMlVideoObje ctTrackingInputs object. Enums: ModelTypeValueValuesEnum: Fields: modelType: A ModelTypeValueValuesEnum attribute. """ class ModelTypeValueValuesEnum(_messages.Enum): r"""ModelTypeValueValuesEnum enum type. Values: MODEL_TYPE_UNSPECIFIED: Should not be set. CLOUD: A model best tailored to be used within Google Cloud, and which c annot be exported. Default. MOBILE_VERSATILE_1: A model that, in addition to being available within Google Cloud, can also be exported (see ModelService.ExportModel) as a TensorFlow or TensorFlow Lite model and used on a mobile or edge device afterwards. MOBILE_CORAL_VERSATILE_1: A versatile model that is meant to be exported (see ModelService.ExportModel) and used on a Google Coral device. MOBILE_CORAL_LOW_LATENCY_1: A model that trades off quality for low latency, to be exported (see ModelService.ExportModel) and used on a Google Coral device. MOBILE_JETSON_VERSATILE_1: A versatile model that is meant to be exported (see ModelService.ExportModel) and used on an NVIDIA Jetson device. MOBILE_JETSON_LOW_LATENCY_1: A model that trades off quality for low latency, to be exported (see ModelService.ExportModel) and used on an NVIDIA Jetson device. """ MODEL_TYPE_UNSPECIFIED = 0 CLOUD = 1 MOBILE_VERSATILE_1 = 2 MOBILE_CORAL_VERSATILE_1 = 3 MOBILE_CORAL_LOW_LATENCY_1 = 4 MOBILE_JETSON_VERSATILE_1 = 5 MOBILE_JETSON_LOW_LATENCY_1 = 6 modelType = _messages.EnumField('ModelTypeValueValuesEnum', 1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionAutomlImageTrainingTunableParameter(_messages.Message): r"""A wrapper class which contains the tunable parameters in an AutoML Image training job. Enums: TrainerTypeValueValuesEnum: Messages: DatasetConfigValue: Customizable dataset settings, used in the `model_garden_trainer`. TrainerConfigValue: Customizable trainer settings, used in the `model_garden_trainer`. Fields: checkpointName: Optional. An unique name of pretrained model checkpoint provided in model garden, it will be mapped to a GCS location internally. datasetConfig: Customizable dataset settings, used in the `model_garden_trainer`. studySpec: Optioinal. StudySpec of hyperparameter tuning job. Required for `model_garden_trainer`. trainerConfig: Customizable trainer settings, used in the `model_garden_trainer`. trainerType: A TrainerTypeValueValuesEnum attribute. """ class TrainerTypeValueValuesEnum(_messages.Enum): r"""TrainerTypeValueValuesEnum enum type. Values: TRAINER_TYPE_UNSPECIFIED: Default value. AUTOML_TRAINER: MODEL_GARDEN_TRAINER: """ TRAINER_TYPE_UNSPECIFIED = 0 AUTOML_TRAINER = 1 MODEL_GARDEN_TRAINER = 2 @encoding.MapUnrecognizedFields('additionalProperties') class DatasetConfigValue(_messages.Message): r"""Customizable dataset settings, used in the `model_garden_trainer`. Messages: AdditionalProperty: An additional property for a DatasetConfigValue object. Fields: additionalProperties: Additional properties of type DatasetConfigValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a DatasetConfigValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class TrainerConfigValue(_messages.Message): r"""Customizable trainer settings, used in the `model_garden_trainer`. Messages: AdditionalProperty: An additional property for a TrainerConfigValue object. Fields: additionalProperties: Additional properties of type TrainerConfigValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a TrainerConfigValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) checkpointName = _messages.StringField(1) datasetConfig = _messages.MessageField('DatasetConfigValue', 2) studySpec = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpec', 3) trainerConfig = _messages.MessageField('TrainerConfigValue', 4) trainerType = _messages.EnumField('TrainerTypeValueValuesEnum', 5) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomJobMetadata(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomJobMetadata object. Fields: backingCustomJob: The resource name of the CustomJob that has been created to carry out this custom task. """ backingCustomJob = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomTask(_messages.Message): r"""A TrainingJob that trains a custom code Model. Fields: inputs: The input parameters of this CustomTask. metadata: The metadata information. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomJobSpec', 1) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionCustomJobMetadata', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig(_messages.Message): r"""Configuration for exporting test set predictions to a BigQuery table. Fields: destinationBigqueryUri: URI of desired destination BigQuery table. Expected format: `bq://{project_id}:{dataset_id}:{table}` If not specified, then results are exported to the following auto-created BigQuery table: `{project_id}:export_evaluated_examples_{model_name}_{yy yy_MM_dd'T'HH_mm_ss_SSS'Z'}.evaluated_examples` overrideExistingTable: If true and an export destination is specified, then the contents of the destination are overwritten. Otherwise, if the export destination already exists, then the export operation fails. """ destinationBigqueryUri = _messages.StringField(1) overrideExistingTable = _messages.BooleanField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig(_messages.Message): r"""Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies. Fields: groupColumns: A list of time series attribute column names that define the time series hierarchy. Only one level of hierarchy is supported, ex. 'region' for a hierarchy of stores or 'department' for a hierarchy of products. If multiple columns are specified, time series will be grouped by their combined values, ex. ('blue', 'large') for 'color' and 'size', up to 5 columns are accepted. If no group columns are specified, all time series are considered to be part of the same group. groupTemporalTotalWeight: The weight of the loss for predictions aggregated over both the horizon and time series in the same hierarchy group. groupTotalWeight: The weight of the loss for predictions aggregated over time series in the same group. temporalTotalWeight: The weight of the loss for predictions aggregated over the horizon for a single time series. """ groupColumns = _messages.StringField(1, repeated=True) groupTemporalTotalWeight = _messages.FloatField(2) groupTotalWeight = _messages.FloatField(3) temporalTotalWeight = _messages.FloatField(4) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterT uningJobMetadata object. Fields: backingHyperparameterTuningJob: The resource name of the HyperparameterTuningJob that has been created to carry out this HyperparameterTuning task. bestTrialBackingCustomJob: The resource name of the CustomJob that has been created to run the best Trial of this HyperparameterTuning task. """ backingHyperparameterTuningJob = _messages.StringField(1) bestTrialBackingCustomJob = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterT uningJobSpec object. Fields: maxFailedTrialCount: The number of failed Trials that need to be seen before failing the HyperparameterTuningJob. If set to 0, Vertex AI decides how many Trials must fail before the whole job fails. maxTrialCount: The desired total number of Trials. parallelTrialCount: The desired number of Trials to run in parallel. studySpec: Study configuration of the HyperparameterTuningJob. trialJobSpec: The spec of a trial job. The same spec applies to the CustomJobs created in all the trials. """ maxFailedTrialCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) maxTrialCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) parallelTrialCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) studySpec = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpec', 4) trialJobSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1CustomJobSpec', 5) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningTask(_messages.Message): r"""A TrainingJob that tunes Hypererparameters of a custom code Model. Fields: inputs: The input parameters of this HyperparameterTuningTask. metadata: The metadata information. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobSpec', 1) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHyperparameterTuningJobMetadata', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecasting(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Forecasting Model. Fields: inputs: The input parameters of this TrainingJob. metadata: The metadata information. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs', 1) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusFore castingInputs object. Fields: additionalExperiments: Additional experiment flags for the time series forcasting training. availableAtForecastColumns: Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day. contextWindow: The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field. dataGranularity: Expected difference in time granularity between rows in the data. exportEvaluatedDataItemsConfig: Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed. forecastHorizon: The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field. hierarchyConfig: Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies. holidayRegions: The geographical region based on which the holiday effect is applied in modeling by adding holiday categorical array feature that include all holidays matching the date. This option only allowed when data_granularity is day. By default, holiday effect modeling is disabled. To turn it on, specify the holiday region using this option. optimizationObjective: Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * "minimize-rmse" (default) - Minimize root-mean-squared error (RMSE). * "minimize-mae" - Minimize mean-absolute error (MAE). * "minimize-rmsle" - Minimize root-mean-squared log error (RMSLE). * "minimize-rmspe" - Minimize root-mean-squared percentage error (RMSPE). * "minimize-wape-mae" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * "minimize- quantile-loss" - Minimize the quantile loss at the quantiles defined in `quantiles`. * "minimize-mape" - Minimize the mean absolute percentage error. quantiles: Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique. targetColumn: The name of the column that the Model is to predict values for. This column must be unavailable at forecast. timeColumn: The name of the column that identifies time order in the time series. This column must be available at forecast. timeSeriesAttributeColumns: Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color. timeSeriesIdentifierColumn: The name of the column that identifies the time series. trainBudgetMilliNodeHours: Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive. transformations: Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using "." as the delimiter. unavailableAtForecastColumns: Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day. validationOptions: Validation options for the data validation component. The available options are: * "fail-pipeline" - default, will validate against the validation and fail the pipeline if it fails. * "ignore- validation" - ignore the results of the validation and continue weightColumn: Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1. This column must be available at forecast. windowConfig: Config containing strategy for generating sliding windows. """ additionalExperiments = _messages.StringField(1, repeated=True) availableAtForecastColumns = _messages.StringField(2, repeated=True) contextWindow = _messages.IntegerField(3) dataGranularity = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity', 4) exportEvaluatedDataItemsConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig', 5) forecastHorizon = _messages.IntegerField(6) hierarchyConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig', 7) holidayRegions = _messages.StringField(8, repeated=True) optimizationObjective = _messages.StringField(9) quantiles = _messages.FloatField(10, repeated=True) targetColumn = _messages.StringField(11) timeColumn = _messages.StringField(12) timeSeriesAttributeColumns = _messages.StringField(13, repeated=True) timeSeriesIdentifierColumn = _messages.StringField(14) trainBudgetMilliNodeHours = _messages.IntegerField(15) transformations = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation', 16, repeated=True) unavailableAtForecastColumns = _messages.StringField(17, repeated=True) validationOptions = _messages.StringField(18) weightColumn = _messages.StringField(19) windowConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig', 20) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsGranularity(_messages.Message): r"""A duration of time expressed in time granularity units. Fields: quantity: The number of granularity_units between data points in the training data. If `granularity_unit` is `minute`, can be 1, 5, 10, 15, or 30. For all other values of `granularity_unit`, must be 1. unit: The time granularity unit of this time period. The supported units are: * "minute" * "hour" * "day" * "week" * "month" * "year" """ quantity = _messages.IntegerField(1) unit = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformation(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusFore castingInputsTransformation object. Fields: auto: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlus ForecastingInputsTransformationAutoTransformation attribute. categorical: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2 SeqPlusForecastingInputsTransformationCategoricalTransformation attribute. numeric: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqP lusForecastingInputsTransformationNumericTransformation attribute. text: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlus ForecastingInputsTransformationTextTransformation attribute. timestamp: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2Se qPlusForecastingInputsTransformationTimestampTransformation attribute. """ auto = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation', 1) categorical = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation', 2) numeric = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation', 3) text = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation', 4) timestamp = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation', 5) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationAutoTransformation(_messages.Message): r"""Training pipeline will infer the proper transformation based on the statistic of dataset. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationCategoricalTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the "unknown" category. The "unknown" category gets its own special lookup index and resulting embedding. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationNumericTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTextTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingInputsTransformationTimestampTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed. Fields: columnName: A string attribute. timeFormat: The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix- milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `"Z"` (e.g. 1985-04-12T23:20:50.52Z) """ columnName = _messages.StringField(1) timeFormat = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionSeq2SeqPlusForecastingMetadata(_messages.Message): r"""Model metadata specific to Seq2Seq Plus Forecasting. Fields: evaluatedDataItemsBigqueryUri: BigQuery destination uri for exported evaluated examples. trainCostMilliNodeHours: Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget. """ evaluatedDataItemsBigqueryUri = _messages.StringField(1) trainCostMilliNodeHours = _messages.IntegerField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecasting(_messages.Message): r"""A TrainingJob that trains and uploads an AutoML Forecasting Model. Fields: inputs: The input parameters of this TrainingJob. metadata: The metadata information. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputs', 1) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingMetadata', 2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputs(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputs object. Fields: additionalExperiments: Additional experiment flags for the time series forcasting training. availableAtForecastColumns: Names of columns that are available and provided when a forecast is requested. These columns contain information for the given entity (identified by the time_series_identifier_column column) that is known at forecast. For example, predicted weather for a specific day. contextWindow: The amount of time into the past training and prediction data is used for model training and prediction respectively. Expressed in number of units defined by the `data_granularity` field. dataGranularity: Expected difference in time granularity between rows in the data. exportEvaluatedDataItemsConfig: Configuration for exporting test set predictions to a BigQuery table. If this configuration is absent, then the export is not performed. forecastHorizon: The amount of time into the future for which forecasted values for the target are returned. Expressed in number of units defined by the `data_granularity` field. hierarchyConfig: Configuration that defines the hierarchical relationship of time series and parameters for hierarchical forecasting strategies. holidayRegions: The geographical region based on which the holiday effect is applied in modeling by adding holiday categorical array feature that include all holidays matching the date. This option only allowed when data_granularity is day. By default, holiday effect modeling is disabled. To turn it on, specify the holiday region using this option. optimizationObjective: Objective function the model is optimizing towards. The training process creates a model that optimizes the value of the objective function over the validation set. The supported optimization objectives: * "minimize-rmse" (default) - Minimize root-mean-squared error (RMSE). * "minimize-mae" - Minimize mean-absolute error (MAE). * "minimize-rmsle" - Minimize root-mean-squared log error (RMSLE). * "minimize-rmspe" - Minimize root-mean-squared percentage error (RMSPE). * "minimize-wape-mae" - Minimize the combination of weighted absolute percentage error (WAPE) and mean-absolute-error (MAE). * "minimize- quantile-loss" - Minimize the quantile loss at the quantiles defined in `quantiles`. * "minimize-mape" - Minimize the mean absolute percentage error. quantiles: Quantiles to use for minimize-quantile-loss `optimization_objective`. Up to 5 quantiles are allowed of values between 0 and 1, exclusive. Required if the value of optimization_objective is minimize-quantile-loss. Represents the percent quantiles to use for that objective. Quantiles must be unique. targetColumn: The name of the column that the Model is to predict values for. This column must be unavailable at forecast. timeColumn: The name of the column that identifies time order in the time series. This column must be available at forecast. timeSeriesAttributeColumns: Column names that should be used as attribute columns. The value of these columns does not vary as a function of time. For example, store ID or item color. timeSeriesIdentifierColumn: The name of the column that identifies the time series. trainBudgetMilliNodeHours: Required. The train budget of creating this model, expressed in milli node hours i.e. 1,000 value in this field means 1 node hour. The training cost of the model will not exceed this budget. The final cost will be attempted to be close to the budget, though may end up being (even) noticeably smaller - at the backend's discretion. This especially may happen when further model training ceases to provide any improvements. If the budget is set to a value known to be insufficient to train a model for the given dataset, the training won't be attempted and will error. The train budget must be between 1,000 and 72,000 milli node hours, inclusive. transformations: Each transformation will apply transform function to given input column. And the result will be used for training. When creating transformation for BigQuery Struct column, the column should be flattened using "." as the delimiter. unavailableAtForecastColumns: Names of columns that are unavailable when a forecast is requested. This column contains information for the given entity (identified by the time_series_identifier_column) that is unknown before the forecast For example, actual weather on a given day. validationOptions: Validation options for the data validation component. The available options are: * "fail-pipeline" - default, will validate against the validation and fail the pipeline if it fails. * "ignore- validation" - ignore the results of the validation and continue weightColumn: Column name that should be used as the weight column. Higher values in this column give more importance to the row during model training. The column must have numeric values between 0 and 10000 inclusively; 0 means the row is ignored for training. If weight column field is not set, then all rows are assumed to have equal weight of 1. This column must be available at forecast. windowConfig: Config containing strategy for generating sliding windows. """ additionalExperiments = _messages.StringField(1, repeated=True) availableAtForecastColumns = _messages.StringField(2, repeated=True) contextWindow = _messages.IntegerField(3) dataGranularity = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsGranularity', 4) exportEvaluatedDataItemsConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionExportEvaluatedDataItemsConfig', 5) forecastHorizon = _messages.IntegerField(6) hierarchyConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionHierarchyConfig', 7) holidayRegions = _messages.StringField(8, repeated=True) optimizationObjective = _messages.StringField(9) quantiles = _messages.FloatField(10, repeated=True) targetColumn = _messages.StringField(11) timeColumn = _messages.StringField(12) timeSeriesAttributeColumns = _messages.StringField(13, repeated=True) timeSeriesIdentifierColumn = _messages.StringField(14) trainBudgetMilliNodeHours = _messages.IntegerField(15) transformations = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformation', 16, repeated=True) unavailableAtForecastColumns = _messages.StringField(17, repeated=True) validationOptions = _messages.StringField(18) weightColumn = _messages.StringField(19) windowConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig', 20) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsGranularity(_messages.Message): r"""A duration of time expressed in time granularity units. Fields: quantity: The number of granularity_units between data points in the training data. If `granularity_unit` is `minute`, can be 1, 5, 10, 15, or 30. For all other values of `granularity_unit`, must be 1. unit: The time granularity unit of this time period. The supported units are: * "minute" * "hour" * "day" * "week" * "month" * "year" """ quantity = _messages.IntegerField(1) unit = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformation(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingI nputsTransformation object. Fields: auto: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecast ingInputsTransformationAutoTransformation attribute. categorical: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftF orecastingInputsTransformationCategoricalTransformation attribute. numeric: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForec astingInputsTransformationNumericTransformation attribute. text: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecast ingInputsTransformationTextTransformation attribute. timestamp: A GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftFor ecastingInputsTransformationTimestampTransformation attribute. """ auto = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation', 1) categorical = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation', 2) numeric = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation', 3) text = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation', 4) timestamp = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation', 5) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationAutoTransformation(_messages.Message): r"""Training pipeline will infer the proper transformation based on the statistic of dataset. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationCategoricalTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * The categorical string as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. * Categories that appear less than 5 times in the training dataset are treated as the "unknown" category. The "unknown" category gets its own special lookup index and resulting embedding. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationNumericTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * The value converted to float32. * The z_score of the value. * log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. * z_score of log(value+1) when the value is greater than or equal to 0. Otherwise, this transformation is not applied and the value is considered a missing value. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTextTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * The text as is--no change to case, punctuation, spelling, tense, and so on. * Convert the category name to a dictionary lookup index and generate an embedding for each index. Fields: columnName: A string attribute. """ columnName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingInputsTransformationTimestampTransformation(_messages.Message): r"""Training pipeline will perform following transformation functions. * Apply the transformation functions for Numerical columns. * Determine the year, month, day,and weekday. Treat each value from the timestamp as a Categorical column. * Invalid numerical values (for example, values that fall outside of a typical timestamp range, or are extreme values) receive no special treatment and are not removed. Fields: columnName: A string attribute. timeFormat: The format in which that time field is expressed. The time_format must either be one of: * `unix-seconds` * `unix- milliseconds` * `unix-microseconds` * `unix-nanoseconds` (for respectively number of seconds, milliseconds, microseconds and nanoseconds since start of the Unix epoch); or be written in `strftime` syntax. If time_format is not set, then the default format is RFC 3339 `date-time` format, where `time-offset` = `"Z"` (e.g. 1985-04-12T23:20:50.52Z) """ columnName = _messages.StringField(1) timeFormat = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionTftForecastingMetadata(_messages.Message): r"""Model metadata specific to TFT Forecasting. Fields: evaluatedDataItemsBigqueryUri: BigQuery destination uri for exported evaluated examples. trainCostMilliNodeHours: Output only. The actual training cost of the model, expressed in milli node hours, i.e. 1,000 value in this field means 1 node hour. Guaranteed to not exceed the train budget. """ evaluatedDataItemsBigqueryUri = _messages.StringField(1) trainCostMilliNodeHours = _messages.IntegerField(2) class GoogleCloudAiplatformV1beta1SchemaTrainingjobDefinitionWindowConfig(_messages.Message): r"""Config that contains the strategy used to generate sliding windows in time series training. A window is a series of rows that comprise the context up to the time of prediction, and the horizon following. The corresponding row for each window marks the start of the forecast horizon. Each window is used as an input example for training/evaluation. Fields: column: Name of the column that should be used to generate sliding windows. The column should contain either booleans or string booleans; if the value of the row is True, generate a sliding window with the horizon starting at that row. The column will not be used as a feature in training. maxCount: Maximum number of windows that should be generated across all time series. strideLength: Stride length used to generate input examples. Within one time series, every {$STRIDE_LENGTH} rows will be used to generate a sliding window. """ column = _messages.StringField(1) maxCount = _messages.IntegerField(2) strideLength = _messages.IntegerField(3) class GoogleCloudAiplatformV1beta1SchemaVertex(_messages.Message): r"""A vertex represents a 2D point in the image. NOTE: the normalized vertex coordinates are relative to the original image and range from 0 to 1. Fields: x: X coordinate. y: Y coordinate. """ x = _messages.FloatField(1) y = _messages.FloatField(2) class GoogleCloudAiplatformV1beta1SchemaVideoActionRecognitionAnnotation(_messages.Message): r"""Annotation details specific to video action recognition. Fields: annotationSpecId: The resource Id of the AnnotationSpec that this Annotation pertains to. displayName: The display name of the AnnotationSpec that this Annotation pertains to. timeSegment: This Annotation applies to the time period represented by the TimeSegment. If it's not set, the Annotation applies to the whole video. """ annotationSpecId = _messages.StringField(1) displayName = _messages.StringField(2) timeSegment = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTimeSegment', 3) class GoogleCloudAiplatformV1beta1SchemaVideoClassificationAnnotation(_messages.Message): r"""Annotation details specific to video classification. Fields: annotationSpecId: The resource Id of the AnnotationSpec that this Annotation pertains to. displayName: The display name of the AnnotationSpec that this Annotation pertains to. timeSegment: This Annotation applies to the time period represented by the TimeSegment. If it's not set, the Annotation applies to the whole video. """ annotationSpecId = _messages.StringField(1) displayName = _messages.StringField(2) timeSegment = _messages.MessageField('GoogleCloudAiplatformV1beta1SchemaTimeSegment', 3) class GoogleCloudAiplatformV1beta1SchemaVideoDataItem(_messages.Message): r"""Payload of Video DataItem. Fields: gcsUri: Required. Google Cloud Storage URI points to the original video in user's bucket. The video is up to 50 GB in size and up to 3 hour in duration. mimeType: Output only. The mime type of the content of the video. Only the videos in below listed mime types are supported. Supported mime_type: - video/mp4 - video/avi - video/quicktime """ gcsUri = _messages.StringField(1) mimeType = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaVideoDatasetMetadata(_messages.Message): r"""The metadata of Datasets that contain Video DataItems. Fields: dataItemSchemaUri: Points to a YAML file stored on Google Cloud Storage describing payload of the Video DataItems that belong to this Dataset. gcsBucket: Google Cloud Storage Bucket name that contains the blob data of this Dataset. """ dataItemSchemaUri = _messages.StringField(1) gcsBucket = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SchemaVideoObjectTrackingAnnotation(_messages.Message): r"""Annotation details specific to video object tracking. Fields: annotationSpecId: The resource Id of the AnnotationSpec that this Annotation pertains to. displayName: The display name of the AnnotationSpec that this Annotation pertains to. instanceId: The instance of the object, expressed as a positive integer. Used to track the same object across different frames. timeOffset: A time (frame) of a video to which this annotation pertains. Represented as the duration since the video's start. xMax: The rightmost coordinate of the bounding box. xMin: The leftmost coordinate of the bounding box. yMax: The bottommost coordinate of the bounding box. yMin: The topmost coordinate of the bounding box. """ annotationSpecId = _messages.StringField(1) displayName = _messages.StringField(2) instanceId = _messages.IntegerField(3) timeOffset = _messages.StringField(4) xMax = _messages.FloatField(5) xMin = _messages.FloatField(6) yMax = _messages.FloatField(7) yMin = _messages.FloatField(8) class GoogleCloudAiplatformV1beta1SchemaVisualInspectionClassificationLabelSavedQueryMetadata(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaVisualInspectionClassificationLabelS avedQueryMetadata object. Fields: multiLabel: Whether or not the classification label is multi_label. """ multiLabel = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1SchemaVisualInspectionMaskSavedQueryMetadata(_messages.Message): r"""A GoogleCloudAiplatformV1beta1SchemaVisualInspectionMaskSavedQueryMetadata object. """ class GoogleCloudAiplatformV1beta1SearchDataItemsResponse(_messages.Message): r"""Response message for DatasetService.SearchDataItems. Fields: dataItemViews: The DataItemViews read. nextPageToken: A token to retrieve next page of results. Pass to SearchDataItemsRequest.page_token to obtain that page. """ dataItemViews = _messages.MessageField('GoogleCloudAiplatformV1beta1DataItemView', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SearchEntryPoint(_messages.Message): r"""An entry point for displaying Google Search results. A `SearchEntryPoint` is populated when the grounding source for a model's response is Google Search. It provides information that you can use to display the search results in your application. Fields: renderedContent: Optional. An HTML snippet that can be embedded in a web page or an application's webview. This snippet displays a search result, including the title, URL, and a brief description of the search result. sdkBlob: Optional. A base64-encoded JSON object that contains a list of search queries and their corresponding search URLs. This information can be used to build a custom search UI. """ renderedContent = _messages.StringField(1) sdkBlob = _messages.BytesField(2) class GoogleCloudAiplatformV1beta1SearchExamplesRequest(_messages.Message): r"""Request message for ExampleStoreService.SearchExamples. Fields: storedContentsExampleParameters: The parameters of StoredContentsExamples to be searched. topK: Optional. The number of similar examples to return. """ storedContentsExampleParameters = _messages.MessageField('GoogleCloudAiplatformV1beta1StoredContentsExampleParameters', 1) topK = _messages.IntegerField(2) class GoogleCloudAiplatformV1beta1SearchExamplesResponse(_messages.Message): r"""Response message for ExampleStoreService.SearchExamples. Fields: results: The results of searching for similar examples. """ results = _messages.MessageField('GoogleCloudAiplatformV1beta1SearchExamplesResponseSimilarExample', 1, repeated=True) class GoogleCloudAiplatformV1beta1SearchExamplesResponseSimilarExample(_messages.Message): r"""The result of the similar example. Fields: example: The example that is similar to the searched query. similarityScore: The similarity score of this example. """ example = _messages.MessageField('GoogleCloudAiplatformV1beta1Example', 1) similarityScore = _messages.FloatField(2, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SearchFeaturesResponse(_messages.Message): r"""Response message for FeaturestoreService.SearchFeatures. Fields: features: The Features matching the request. Fields returned: * `name` * `description` * `labels` * `create_time` * `update_time` nextPageToken: A token, which can be sent as SearchFeaturesRequest.page_token to retrieve the next page. If this field is omitted, there are no subsequent pages. """ features = _messages.MessageField('GoogleCloudAiplatformV1beta1Feature', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SearchMigratableResourcesRequest(_messages.Message): r"""Request message for MigrationService.SearchMigratableResources. Fields: filter: A filter for your search. You can use the following types of filters: * Resource type filters. The following strings filter for a specific type of MigratableResource: * `ml_engine_model_version:*` * `automl_model:*` * `automl_dataset:*` * `data_labeling_dataset:*` * "Migrated or not" filters. The following strings filter for resources that either have or have not already been migrated: * `last_migrate_time:*` filters for migrated resources. * `NOT last_migrate_time:*` filters for not yet migrated resources. pageSize: The standard page size. The default and maximum value is 100. pageToken: The standard page token. """ filter = _messages.StringField(1) pageSize = _messages.IntegerField(2, variant=_messages.Variant.INT32) pageToken = _messages.StringField(3) class GoogleCloudAiplatformV1beta1SearchMigratableResourcesResponse(_messages.Message): r"""Response message for MigrationService.SearchMigratableResources. Fields: migratableResources: All migratable resources that can be migrated to the location specified in the request. nextPageToken: The standard next-page token. The migratable_resources may not fill page_size in SearchMigratableResourcesRequest even when there are subsequent pages. """ migratableResources = _messages.MessageField('GoogleCloudAiplatformV1beta1MigratableResource', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequest(_messages.Message): r"""Request message for JobService.SearchModelDeploymentMonitoringStatsAnomalies. Fields: deployedModelId: Required. The DeployedModel ID of the [ModelDeploymentMonitoringObjectiveConfig.deployed_model_id]. endTime: The latest timestamp of stats being generated. If not set, indicates feching stats till the latest possible one. featureDisplayName: The feature display name. If specified, only return the stats belonging to this feature. Format: ModelMonitoringStatsAnomali es.FeatureHistoricStatsAnomalies.feature_display_name, example: "user_destination". objectives: Required. Objectives of the stats to retrieve. pageSize: The standard list page size. pageToken: A page token received from a previous JobService.SearchModelDeploymentMonitoringStatsAnomalies call. startTime: The earliest timestamp of stats being generated. If not set, indicates fetching stats till the earliest possible one. """ deployedModelId = _messages.StringField(1) endTime = _messages.StringField(2) featureDisplayName = _messages.StringField(3) objectives = _messages.MessageField('GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective', 4, repeated=True) pageSize = _messages.IntegerField(5, variant=_messages.Variant.INT32) pageToken = _messages.StringField(6) startTime = _messages.StringField(7) class GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesRequestStatsAnomaliesObjective(_messages.Message): r"""Stats requested for specific objective. Enums: TypeValueValuesEnum: Fields: topFeatureCount: If set, all attribution scores between SearchModelDeploymentMonitoringStatsAnomaliesRequest.start_time and SearchModelDeploymentMonitoringStatsAnomaliesRequest.end_time are fetched, and page token doesn't take effect in this case. Only used to retrieve attribution score for the top Features which has the highest attribution score in the latest monitoring run. type: A TypeValueValuesEnum attribute. """ class TypeValueValuesEnum(_messages.Enum): r"""TypeValueValuesEnum enum type. Values: MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_TYPE_UNSPECIFIED: Default value, should not be set. RAW_FEATURE_SKEW: Raw feature values' stats to detect skew between Training-Prediction datasets. RAW_FEATURE_DRIFT: Raw feature values' stats to detect drift between Serving-Prediction datasets. FEATURE_ATTRIBUTION_SKEW: Feature attribution scores to detect skew between Training-Prediction datasets. FEATURE_ATTRIBUTION_DRIFT: Feature attribution scores to detect skew between Prediction datasets collected within different time windows. """ MODEL_DEPLOYMENT_MONITORING_OBJECTIVE_TYPE_UNSPECIFIED = 0 RAW_FEATURE_SKEW = 1 RAW_FEATURE_DRIFT = 2 FEATURE_ATTRIBUTION_SKEW = 3 FEATURE_ATTRIBUTION_DRIFT = 4 topFeatureCount = _messages.IntegerField(1, variant=_messages.Variant.INT32) type = _messages.EnumField('TypeValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1SearchModelDeploymentMonitoringStatsAnomaliesResponse(_messages.Message): r"""Response message for JobService.SearchModelDeploymentMonitoringStatsAnomalies. Fields: monitoringStats: Stats retrieved for requested objectives. There are at most 1000 ModelMonitoringStatsAnomalies.FeatureHistoricStatsAnomalies.pr ediction_stats in the response. nextPageToken: The page token that can be used by the next JobService.SearchModelDeploymentMonitoringStatsAnomalies call. """ monitoringStats = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringStatsAnomalies', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsRequest(_messages.Message): r"""Request message for ModelMonitoringService.SearchModelMonitoringAlerts. Fields: alertTimeInterval: If non-empty, returns the alerts in this time interval. modelMonitoringJob: If non-empty, returns the alerts of this model monitoring job. objectiveType: If non-empty, returns the alerts of this objective type. Supported monitoring objectives: `raw-feature-drift` `prediction-output- drift` `feature-attribution` pageSize: The standard list page size. pageToken: A page token received from a previous ModelMonitoringService.SearchModelMonitoringAlerts call. statsName: If non-empty, returns the alerts of this stats_name. """ alertTimeInterval = _messages.MessageField('GoogleTypeInterval', 1) modelMonitoringJob = _messages.StringField(2) objectiveType = _messages.StringField(3) pageSize = _messages.IntegerField(4, variant=_messages.Variant.INT32) pageToken = _messages.StringField(5) statsName = _messages.StringField(6) class GoogleCloudAiplatformV1beta1SearchModelMonitoringAlertsResponse(_messages.Message): r"""Response message for ModelMonitoringService.SearchModelMonitoringAlerts. Fields: modelMonitoringAlerts: Alerts retrieved for the requested objectives. Sorted by alert time descendingly. nextPageToken: The page token that can be used by the next ModelMonitoringService.SearchModelMonitoringAlerts call. totalNumberAlerts: The total number of alerts retrieved by the requested objectives. """ modelMonitoringAlerts = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringAlert', 1, repeated=True) nextPageToken = _messages.StringField(2) totalNumberAlerts = _messages.IntegerField(3) class GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilter(_messages.Message): r"""Filter for searching ModelMonitoringStats. Fields: tabularStatsFilter: Tabular statistics filter. """ tabularStatsFilter = _messages.MessageField('GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilterTabularStatsFilter', 1) class GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilterTabularStatsFilter(_messages.Message): r"""Tabular statistics filter. Fields: algorithm: Specify the algorithm type used for distance calculation, eg: jensen_shannon_divergence, l_infinity. modelMonitoringJob: From a particular monitoring job. modelMonitoringSchedule: From a particular monitoring schedule. objectiveType: One of the supported monitoring objectives: `raw-feature- drift` `prediction-output-drift` `feature-attribution` statsName: If not specified, will return all the stats_names. """ algorithm = _messages.StringField(1) modelMonitoringJob = _messages.StringField(2) modelMonitoringSchedule = _messages.StringField(3) objectiveType = _messages.StringField(4) statsName = _messages.StringField(5) class GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsRequest(_messages.Message): r"""Request message for ModelMonitoringService.SearchModelMonitoringStats. Fields: pageSize: The standard list page size. pageToken: A page token received from a previous ModelMonitoringService.SearchModelMonitoringStats call. statsFilter: Filter for search different stats. timeInterval: The time interval for which results should be returned. """ pageSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) pageToken = _messages.StringField(2) statsFilter = _messages.MessageField('GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsFilter', 3) timeInterval = _messages.MessageField('GoogleTypeInterval', 4) class GoogleCloudAiplatformV1beta1SearchModelMonitoringStatsResponse(_messages.Message): r"""Response message for ModelMonitoringService.SearchModelMonitoringStats. Fields: monitoringStats: Stats retrieved for requested objectives. nextPageToken: The page token that can be used by the next ModelMonitoringService.SearchModelMonitoringStats call. """ monitoringStats = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelMonitoringStats', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SearchNearestEntitiesRequest(_messages.Message): r"""The request message for FeatureOnlineStoreService.SearchNearestEntities. Fields: query: Required. The query. returnFullEntity: Optional. If set to true, the full entities (including all vector values and metadata) of the nearest neighbors are returned; otherwise only entity id of the nearest neighbors will be returned. Note that returning full entities will significantly increase the latency and cost of the query. """ query = _messages.MessageField('GoogleCloudAiplatformV1beta1NearestNeighborQuery', 1) returnFullEntity = _messages.BooleanField(2) class GoogleCloudAiplatformV1beta1SearchNearestEntitiesResponse(_messages.Message): r"""Response message for FeatureOnlineStoreService.SearchNearestEntities Fields: nearestNeighbors: The nearest neighbors of the query entity. """ nearestNeighbors = _messages.MessageField('GoogleCloudAiplatformV1beta1NearestNeighbors', 1) class GoogleCloudAiplatformV1beta1SecretEnvVar(_messages.Message): r"""Represents an environment variable where the value is a secret in Cloud Secret Manager. Fields: name: Required. Name of the secret environment variable. secretRef: Required. Reference to a secret stored in the Cloud Secret Manager that will provide the value for this environment variable. """ name = _messages.StringField(1) secretRef = _messages.MessageField('GoogleCloudAiplatformV1beta1SecretRef', 2) class GoogleCloudAiplatformV1beta1SecretRef(_messages.Message): r"""Reference to a secret stored in the Cloud Secret Manager that will provide the value for this environment variable. Fields: secret: Required. The name of the secret in Cloud Secret Manager. Format: {secret_name}. version: The Cloud Secret Manager secret version. Can be 'latest' for the latest version, an integer for a specific version, or a version alias. """ secret = _messages.StringField(1) version = _messages.StringField(2) class GoogleCloudAiplatformV1beta1Segment(_messages.Message): r"""A segment of the content. Fields: endIndex: Output only. The end index of the segment in the `Part`, measured in bytes. This marks the end of the segment and is exclusive, meaning the segment includes content up to, but not including, the byte at this index. partIndex: Output only. The index of the `Part` object that this segment belongs to. This is useful for associating the segment with a specific part of the content. startIndex: Output only. The start index of the segment in the `Part`, measured in bytes. This marks the beginning of the segment and is inclusive, meaning the byte at this index is the first byte of the segment. text: Output only. The text of the segment. """ endIndex = _messages.IntegerField(1, variant=_messages.Variant.INT32) partIndex = _messages.IntegerField(2, variant=_messages.Variant.INT32) startIndex = _messages.IntegerField(3, variant=_messages.Variant.INT32) text = _messages.StringField(4) class GoogleCloudAiplatformV1beta1ServerlessRayJob(_messages.Message): r"""Represents a serverless Ray job resources. Messages: LabelsValue: Optional. The labels with user-defined metadata to organize ServerlessRayJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: description: Optional. The description of the ServerlessRayJob. displayName: Required. The display name of the ServerlessRayJob. The name can be up to 128 characters long and can be consist of any UTF-8 characters. error: Output only. Only populated when the serverless Ray job state is `FAILED`. jobSpec: Required. The spec of the ServerlessRayJob. labels: Optional. The labels with user-defined metadata to organize ServerlessRayJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. name: Output only. Identifier. Resource name of a ServerlessRayJob. Format: `projects/{project}/locations/{location}/serverlessRayJobs/{serv erless_ray_job_id}` stateInfo: Output only. The current state of the ServerlessRayJob. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize ServerlessRayJobs. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) description = _messages.StringField(1) displayName = _messages.StringField(2) error = _messages.MessageField('GoogleRpcStatus', 3) jobSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ServerlessRayJobSpec', 4) labels = _messages.MessageField('LabelsValue', 5) name = _messages.StringField(6) stateInfo = _messages.MessageField('GoogleCloudAiplatformV1beta1ServerlessRayJobStateInfo', 7) class GoogleCloudAiplatformV1beta1ServerlessRayJobSpec(_messages.Message): r"""Represents the spec of a ServerlessRayJob. Fields: archiveUris: Optional. The URIs of archives to be extracted into the working directory of each Ray node. Supported file types: `.tar`, `.tar.gz`, `.tgz`, and `.zip`. We only support Cloud Storage paths for this field. args: Optional. The arguments to pass to the Ray job script. mainPythonFileUri: Required. The URI of the main Python file to use as the Ray job. Must be a .py file. pscInterfaceConfig: Optional. The PSC interface config for the ServerlessRayJob. If unspecified, the ServerlessRayJob will not use PSC interface. resourceSpecs: Optional. The resource specs of the ServerlessRayJob. If unspecified, the default resource will be used. runtimeEnv: Optional. The runtime environment of the ServerlessRayJob. serviceAccount: Optional. Specifies the service account for workload run- as account. Users submitting jobs must have act-as permission on this run-as account. If unspecified, the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access- control#service-agents) for the ServerelessRayJob's project is used. """ archiveUris = _messages.StringField(1, repeated=True) args = _messages.StringField(2, repeated=True) mainPythonFileUri = _messages.StringField(3) pscInterfaceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PscInterfaceConfig', 4) resourceSpecs = _messages.MessageField('GoogleCloudAiplatformV1beta1ServerlessRayJobSpecResourceSpec', 5, repeated=True) runtimeEnv = _messages.MessageField('GoogleCloudAiplatformV1beta1ServerlessRayJobSpecRuntimeEnv', 6) serviceAccount = _messages.StringField(7) class GoogleCloudAiplatformV1beta1ServerlessRayJobSpecResourceSpec(_messages.Message): r"""Represents the resource spec of a worker node pool. Fields: disk: Optional. The disk spec for the node. By default, we use pd-standard disk with 100GB. maxNodeCount: Optional. The maximum number of nodes this job can occupy while running. Default is 2000. resourceUnit: Optional. Define the number of CPUs on one node. E.g. 1 resource_unit = 4 vCPUs. By default machine e2-standard series, resource_unit value can only be 1, 2, 4. Default value is 1. """ disk = _messages.MessageField('GoogleCloudAiplatformV1beta1ServerlessRayJobSpecResourceSpecDisk', 1) maxNodeCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) resourceUnit = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1ServerlessRayJobSpecResourceSpecDisk(_messages.Message): r"""Represents the disk spec. Fields: diskSizeGb: Optional. The size of the disk in GB. """ diskSizeGb = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1ServerlessRayJobSpecRuntimeEnv(_messages.Message): r"""Represents the runtime environment of a ServerlessRayJob. Fields: container: Optional. Docker container to run the Ray job in. """ container = _messages.MessageField('GoogleCloudAiplatformV1beta1ServerlessRayJobSpecRuntimeEnvContainer', 1) class GoogleCloudAiplatformV1beta1ServerlessRayJobSpecRuntimeEnvContainer(_messages.Message): r"""Require a given (Docker) image, and the worker process will run in a container with this image. Fields: imageUri: Optional. The URI of the Docker image. """ imageUri = _messages.StringField(1) class GoogleCloudAiplatformV1beta1ServerlessRayJobStateInfo(_messages.Message): r"""The state information of the ServerlessRayJob. Enums: StateValueValuesEnum: Output only. The state of the ServerlessRayJob. Fields: state: Output only. The state of the ServerlessRayJob. stateMessage: Output only. A message containing details about the current state of the ServerlessRayJob. stateTime: Output only. The time when the current state was entered. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The state of the ServerlessRayJob. Values: JOB_STATE_UNSPECIFIED: The job state is unspecified. JOB_STATE_QUEUED: The job has been just created or resumed and processing has not yet begun. JOB_STATE_PENDING: The service is preparing to run the job. JOB_STATE_RUNNING: The job is in progress. JOB_STATE_SUCCEEDED: The job completed successfully. JOB_STATE_FAILED: The job failed. JOB_STATE_CANCELLING: The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. JOB_STATE_CANCELLED: The job has been cancelled. JOB_STATE_PAUSED: The job has been stopped, and can be resumed. JOB_STATE_EXPIRED: The job has expired. JOB_STATE_UPDATING: The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state. JOB_STATE_PARTIALLY_SUCCEEDED: The job is partially succeeded, some results may be missing due to errors. """ JOB_STATE_UNSPECIFIED = 0 JOB_STATE_QUEUED = 1 JOB_STATE_PENDING = 2 JOB_STATE_RUNNING = 3 JOB_STATE_SUCCEEDED = 4 JOB_STATE_FAILED = 5 JOB_STATE_CANCELLING = 6 JOB_STATE_CANCELLED = 7 JOB_STATE_PAUSED = 8 JOB_STATE_EXPIRED = 9 JOB_STATE_UPDATING = 10 JOB_STATE_PARTIALLY_SUCCEEDED = 11 state = _messages.EnumField('StateValueValuesEnum', 1) stateMessage = _messages.StringField(2) stateTime = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ServiceAccountSpec(_messages.Message): r"""Configuration for the use of custom service account to run the workloads. Fields: enableCustomServiceAccount: Required. If true, custom user-managed service account is enforced to run any workloads (for example, Vertex Jobs) on the resource. Otherwise, uses the [Vertex AI Custom Code Service Agent](https://cloud.google.com/vertex-ai/docs/general/access- control#service-agents). serviceAccount: Optional. Required when all below conditions are met * `enable_custom_service_account` is true; * any runtime is specified via `ResourceRuntimeSpec` on creation time, for example, Ray The users must have `iam.serviceAccounts.actAs` permission on this service account and then the specified runtime containers will run as it. Do not set this field if you want to submit jobs using custom service account to this PersistentResource after creation, but only specify the `service_account` inside the job. """ enableCustomServiceAccount = _messages.BooleanField(1) serviceAccount = _messages.StringField(2) class GoogleCloudAiplatformV1beta1Session(_messages.Message): r"""A session contains a set of actions between users and Vertex agents. Messages: LabelsValue: The labels with user-defined metadata to organize your Sessions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. SessionStateValue: Optional. Session specific memory which stores key conversation points. Fields: createTime: Output only. Timestamp when the session was created. displayName: Optional. The display name of the session. expireTime: Optional. Timestamp of when this session is considered expired. This is *always* provided on output, regardless of what was sent on input. labels: The labels with user-defined metadata to organize your Sessions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. name: Identifier. The resource name of the session. Format: 'projects/{pro ject}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/ {session}'. sessionState: Optional. Session specific memory which stores key conversation points. ttl: Optional. Input only. The TTL for this session. updateTime: Output only. Timestamp when the session was updated. userId: Required. Immutable. String id provided by the user """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your Sessions. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class SessionStateValue(_messages.Message): r"""Optional. Session specific memory which stores key conversation points. Messages: AdditionalProperty: An additional property for a SessionStateValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a SessionStateValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) displayName = _messages.StringField(2) expireTime = _messages.StringField(3) labels = _messages.MessageField('LabelsValue', 4) name = _messages.StringField(5) sessionState = _messages.MessageField('SessionStateValue', 6) ttl = _messages.StringField(7) updateTime = _messages.StringField(8) userId = _messages.StringField(9) class GoogleCloudAiplatformV1beta1SessionEvent(_messages.Message): r"""An event represents a message from either the user or agent. Fields: actions: Optional. Actions executed by the agent. author: Required. The name of the agent that sent the event, or user. content: Optional. Content of the event provided by the author. errorCode: Optional. Error code if the response is an error. Code varies by model. errorMessage: Optional. Error message if the response is an error. eventMetadata: Optional. Metadata relating to this event. invocationId: Required. The invocation id of the event, multiple events can have the same invocation id. name: Identifier. The resource name of the event. Format:`projects/{projec t}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{se ssion}/events/{event}`. timestamp: Required. Timestamp when the event was created on client side. """ actions = _messages.MessageField('GoogleCloudAiplatformV1beta1EventActions', 1) author = _messages.StringField(2) content = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 3) errorCode = _messages.StringField(4) errorMessage = _messages.StringField(5) eventMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1EventMetadata', 6) invocationId = _messages.StringField(7) name = _messages.StringField(8) timestamp = _messages.StringField(9) class GoogleCloudAiplatformV1beta1SetPublisherModelConfigRequest(_messages.Message): r"""Request message for EndpointService.SetPublisherModelConfig. Fields: publisherModelConfig: Required. The publisher model config. """ publisherModelConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PublisherModelConfig', 1) class GoogleCloudAiplatformV1beta1SharePointSources(_messages.Message): r"""The SharePointSources to pass to ImportRagFiles. Fields: sharePointSources: The SharePoint sources. """ sharePointSources = _messages.MessageField('GoogleCloudAiplatformV1beta1SharePointSourcesSharePointSource', 1, repeated=True) class GoogleCloudAiplatformV1beta1SharePointSourcesSharePointSource(_messages.Message): r"""An individual SharePointSource. Fields: clientId: The Application ID for the app registered in Microsoft Azure Portal. The application must also be configured with MS Graph permissions "Files.ReadAll", "Sites.ReadAll" and BrowserSiteLists.Read.All. clientSecret: The application secret for the app registered in Azure. driveId: The ID of the drive to download from. driveName: The name of the drive to download from. fileId: Output only. The SharePoint file id. Output only. sharepointFolderId: The ID of the SharePoint folder to download from. sharepointFolderPath: The path of the SharePoint folder to download from. sharepointSiteName: The name of the SharePoint site to download from. This can be the site name or the site id. tenantId: Unique identifier of the Azure Active Directory Instance. """ clientId = _messages.StringField(1) clientSecret = _messages.MessageField('GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig', 2) driveId = _messages.StringField(3) driveName = _messages.StringField(4) fileId = _messages.StringField(5) sharepointFolderId = _messages.StringField(6) sharepointFolderPath = _messages.StringField(7) sharepointSiteName = _messages.StringField(8) tenantId = _messages.StringField(9) class GoogleCloudAiplatformV1beta1ShieldedVmConfig(_messages.Message): r"""A set of Shielded Instance options. See [Images using supported Shielded VM features](https://cloud.google.com/compute/docs/instances/modifying- shielded-vm). Fields: enableSecureBoot: Defines whether the instance has [Secure Boot](https://cloud.google.com/compute/shielded-vm/docs/shielded- vm#secure-boot) enabled. Secure Boot helps ensure that the system only runs authentic software by verifying the digital signature of all boot components, and halting the boot process if signature verification fails. """ enableSecureBoot = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1SlackSource(_messages.Message): r"""The Slack source for the ImportRagFilesRequest. Fields: channels: Required. The Slack channels. """ channels = _messages.MessageField('GoogleCloudAiplatformV1beta1SlackSourceSlackChannels', 1, repeated=True) class GoogleCloudAiplatformV1beta1SlackSourceSlackChannels(_messages.Message): r"""SlackChannels contains the Slack channels and corresponding access token. Fields: apiKeyConfig: Required. The SecretManager secret version resource name (e.g. projects/{project}/secrets/{secret}/versions/{version}) storing the Slack channel access token that has access to the slack channel IDs. See: https://api.slack.com/tutorials/tracks/getting-a-token. channels: Required. The Slack channel IDs. """ apiKeyConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1ApiAuthApiKeyConfig', 1) channels = _messages.MessageField('GoogleCloudAiplatformV1beta1SlackSourceSlackChannelsSlackChannel', 2, repeated=True) class GoogleCloudAiplatformV1beta1SlackSourceSlackChannelsSlackChannel(_messages.Message): r"""SlackChannel contains the Slack channel ID and the time range to import. Fields: channelId: Required. The Slack channel ID. endTime: Optional. The ending timestamp for messages to import. startTime: Optional. The starting timestamp for messages to import. """ channelId = _messages.StringField(1) endTime = _messages.StringField(2) startTime = _messages.StringField(3) class GoogleCloudAiplatformV1beta1SmoothGradConfig(_messages.Message): r"""Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf Fields: featureNoiseSigma: This is similar to noise_sigma, but provides additional flexibility. A separate noise sigma can be provided for each feature, which is useful if their distributions are different. No noise is added to features that are not set. If this field is unset, noise_sigma will be used for all features. noiseSigma: This is a single float value and will be used to add noise to all the features. Use this field when all features are normalized to have the same distribution: scale to range [0, 1], [-1, 1] or z-scoring, where features are normalized to have 0-mean and 1-variance. Learn more about [normalization](https://developers.google.com/machine- learning/data-prep/transform/normalization). For best results the recommended value is about 10% - 20% of the standard deviation of the input feature. Refer to section 3.2 of the SmoothGrad paper: https://arxiv.org/pdf/1706.03825.pdf. Defaults to 0.1. If the distribution is different per feature, set feature_noise_sigma instead for each feature. noisySampleCount: The number of gradient samples to use for approximation. The higher this number, the more accurate the gradient is, but the runtime complexity increases by this factor as well. Valid range of its value is [1, 50]. Defaults to 3. """ featureNoiseSigma = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureNoiseSigma', 1) noiseSigma = _messages.FloatField(2, variant=_messages.Variant.FLOAT) noisySampleCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SpeakerVoiceConfig(_messages.Message): r"""Configuration for a single speaker in a multi-speaker setup. Fields: speaker: Required. The name of the speaker. This should be the same as the speaker name used in the prompt. voiceConfig: Required. The configuration for the voice of this speaker. """ speaker = _messages.StringField(1) voiceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1VoiceConfig', 2) class GoogleCloudAiplatformV1beta1SpecialistPool(_messages.Message): r"""SpecialistPool represents customers' own workforce to work on their data labeling jobs. It includes a group of specialist managers and workers. Managers are responsible for managing the workers in this pool as well as customers' data labeling jobs associated with this pool. Customers create specialist pool as well as start data labeling jobs on Cloud, managers and workers handle the jobs using CrowdCompute console. Fields: displayName: Required. The user-defined name of the SpecialistPool. The name can be up to 128 characters long and can consist of any UTF-8 characters. This field should be unique on project-level. name: Required. The resource name of the SpecialistPool. pendingDataLabelingJobs: Output only. The resource name of the pending data labeling jobs. specialistManagerEmails: The email addresses of the managers in the SpecialistPool. specialistManagersCount: Output only. The number of managers in this SpecialistPool. specialistWorkerEmails: The email addresses of workers in the SpecialistPool. """ displayName = _messages.StringField(1) name = _messages.StringField(2) pendingDataLabelingJobs = _messages.StringField(3, repeated=True) specialistManagerEmails = _messages.StringField(4, repeated=True) specialistManagersCount = _messages.IntegerField(5, variant=_messages.Variant.INT32) specialistWorkerEmails = _messages.StringField(6, repeated=True) class GoogleCloudAiplatformV1beta1SpeculativeDecodingSpec(_messages.Message): r"""Configuration for Speculative Decoding. Fields: draftModelSpeculation: draft model speculation. ngramSpeculation: N-Gram speculation. speculativeTokenCount: The number of speculative tokens to generate at each step. """ draftModelSpeculation = _messages.MessageField('GoogleCloudAiplatformV1beta1SpeculativeDecodingSpecDraftModelSpeculation', 1) ngramSpeculation = _messages.MessageField('GoogleCloudAiplatformV1beta1SpeculativeDecodingSpecNgramSpeculation', 2) speculativeTokenCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SpeculativeDecodingSpecDraftModelSpeculation(_messages.Message): r"""Draft model speculation works by using the smaller model to generate candidate tokens for speculative decoding. Fields: draftModel: Required. The resource name of the draft model. """ draftModel = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SpeculativeDecodingSpecNgramSpeculation(_messages.Message): r"""N-Gram speculation works by trying to find matching tokens in the previous prompt sequence and use those as speculation for generating new tokens. Fields: ngramSize: The number of last N input tokens used as ngram to search/match against the previous prompt sequence. This is equal to the N in N-Gram. The default value is 3 if not specified. """ ngramSize = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SpeechConfig(_messages.Message): r"""Configuration for speech generation. Fields: languageCode: Optional. The language code (ISO 639-1) for the speech synthesis. multiSpeakerVoiceConfig: The configuration for a multi-speaker text-to- speech request. This field is mutually exclusive with `voice_config`. voiceConfig: The configuration for the voice to use. """ languageCode = _messages.StringField(1) multiSpeakerVoiceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1MultiSpeakerVoiceConfig', 2) voiceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1VoiceConfig', 3) class GoogleCloudAiplatformV1beta1StartNotebookRuntimeOperationMetadata(_messages.Message): r"""Metadata information for NotebookService.StartNotebookRuntime. Fields: genericMetadata: The operation generic information. progressMessage: A human-readable message that shows the intermediate progress details of NotebookRuntime. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) progressMessage = _messages.StringField(2) class GoogleCloudAiplatformV1beta1StartNotebookRuntimeRequest(_messages.Message): r"""Request message for NotebookService.StartNotebookRuntime.""" class GoogleCloudAiplatformV1beta1StopNotebookRuntimeRequest(_messages.Message): r"""Request message for NotebookService.StopNotebookRuntime.""" class GoogleCloudAiplatformV1beta1StopTrialRequest(_messages.Message): r"""Request message for VizierService.StopTrial.""" class GoogleCloudAiplatformV1beta1StoredContentsExample(_messages.Message): r"""A ContentsExample to be used with GenerateContent alongside information required for storage and retrieval with Example Store. Fields: contentsExample: Required. The example to be used with GenerateContent. searchKey: Optional. (Optional) the search key used for retrieval. If not provided at upload-time, the search key will be generated from `contents_example.contents` using the method provided by `search_key_generation_method`. The generated search key will be included in retrieved examples. searchKeyGenerationMethod: Optional. The method used to generate the search key from `contents_example.contents`. This is ignored when uploading an example if `search_key` is provided. """ contentsExample = _messages.MessageField('GoogleCloudAiplatformV1beta1ContentsExample', 1) searchKey = _messages.StringField(2) searchKeyGenerationMethod = _messages.MessageField('GoogleCloudAiplatformV1beta1StoredContentsExampleSearchKeyGenerationMethod', 3) class GoogleCloudAiplatformV1beta1StoredContentsExampleFilter(_messages.Message): r"""The metadata filters that will be used to remove or fetch StoredContentsExamples. If a field is unspecified, then no filtering for that field will be applied. Fields: functionNames: Optional. The function names for filtering. searchKeys: Optional. The search keys for filtering. Only examples with one of the specified search keys (StoredContentsExample.search_key) are eligible to be returned. """ functionNames = _messages.MessageField('GoogleCloudAiplatformV1beta1ExamplesArrayFilter', 1) searchKeys = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1StoredContentsExampleParameters(_messages.Message): r"""The metadata filters that will be used to search StoredContentsExamples. If a field is unspecified, then no filtering for that field will be applied Fields: contentSearchKey: The chat history to use to generate the search key for retrieval. functionNames: Optional. The function names for filtering. searchKey: The exact search key to use for retrieval. """ contentSearchKey = _messages.MessageField('GoogleCloudAiplatformV1beta1StoredContentsExampleParametersContentSearchKey', 1) functionNames = _messages.MessageField('GoogleCloudAiplatformV1beta1ExamplesArrayFilter', 2) searchKey = _messages.StringField(3) class GoogleCloudAiplatformV1beta1StoredContentsExampleParametersContentSearchKey(_messages.Message): r"""The chat history to use to generate the search key for retrieval. Fields: contents: Required. The conversation for generating a search key. searchKeyGenerationMethod: Required. The method of generating a search key. """ contents = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1, repeated=True) searchKeyGenerationMethod = _messages.MessageField('GoogleCloudAiplatformV1beta1StoredContentsExampleSearchKeyGenerationMethod', 2) class GoogleCloudAiplatformV1beta1StoredContentsExampleSearchKeyGenerationMethod(_messages.Message): r"""Options for generating the search key from the conversation history. Fields: lastEntry: Use only the last entry of the conversation history (`contents_example.contents`) as the search key. """ lastEntry = _messages.MessageField('GoogleCloudAiplatformV1beta1StoredContentsExampleSearchKeyGenerationMethodLastEntry', 1) class GoogleCloudAiplatformV1beta1StoredContentsExampleSearchKeyGenerationMethodLastEntry(_messages.Message): r"""Configuration for using only the last entry of the conversation history as the search key. """ class GoogleCloudAiplatformV1beta1StratifiedSplit(_messages.Message): r"""Assigns input data to the training, validation, and test sets so that the distribution of values found in the categorical column (as specified by the `key` field) is mirrored within each split. The fraction values determine the relative sizes of the splits. For example, if the specified column has three values, with 50% of the rows having value "A", 25% value "B", and 25% value "C", and the split fractions are specified as 80/10/10, then the training set will constitute 80% of the training data, with about 50% of the training set rows having the value "A" for the specified column, about 25% having the value "B", and about 25% having the value "C". Only the top 500 occurring values are used; any values not in the top 500 values are randomly assigned to a split. If less than three rows contain a specific value, those rows are randomly assigned. Supported only for tabular Datasets. Fields: key: Required. The key is a name of one of the Dataset's data columns. The key provided must be for a categorical column. testFraction: The fraction of the input data that is to be used to evaluate the Model. trainingFraction: The fraction of the input data that is to be used to train the Model. validationFraction: The fraction of the input data that is to be used to validate the Model. """ key = _messages.StringField(1) testFraction = _messages.FloatField(2) trainingFraction = _messages.FloatField(3) validationFraction = _messages.FloatField(4) class GoogleCloudAiplatformV1beta1StreamQueryReasoningEngineRequest(_messages.Message): r"""Request message for ReasoningEngineExecutionService.StreamQuery. Messages: InputValue: Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc. Fields: classMethod: Optional. Class method to be used for the stream query. It is optional and defaults to "stream_query" if unspecified. input: Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc. """ @encoding.MapUnrecognizedFields('additionalProperties') class InputValue(_messages.Message): r"""Optional. Input content provided by users in JSON object format. Examples include text query, function calling parameters, media bytes, etc. Messages: AdditionalProperty: An additional property for a InputValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a InputValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) classMethod = _messages.StringField(1) input = _messages.MessageField('InputValue', 2) class GoogleCloudAiplatformV1beta1StreamRawPredictRequest(_messages.Message): r"""Request message for PredictionService.StreamRawPredict. Fields: httpBody: The prediction input. Supports HTTP headers and arbitrary data payload. """ httpBody = _messages.MessageField('GoogleApiHttpBody', 1) class GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesRequest(_messages.Message): r"""Request message for FeatureOnlineStoreService.StreamingFetchFeatureValues. For the entities requested, all features under the requested feature view will be returned. Enums: DataFormatValueValuesEnum: Specify response data format. If not set, KeyValue format will be used. Fields: dataFormat: Specify response data format. If not set, KeyValue format will be used. dataKeys: A GoogleCloudAiplatformV1beta1FeatureViewDataKey attribute. """ class DataFormatValueValuesEnum(_messages.Enum): r"""Specify response data format. If not set, KeyValue format will be used. Values: FEATURE_VIEW_DATA_FORMAT_UNSPECIFIED: Not set. Will be treated as the KeyValue format. KEY_VALUE: Return response data in key-value format. PROTO_STRUCT: Return response data in proto Struct format. """ FEATURE_VIEW_DATA_FORMAT_UNSPECIFIED = 0 KEY_VALUE = 1 PROTO_STRUCT = 2 dataFormat = _messages.EnumField('DataFormatValueValuesEnum', 1) dataKeys = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewDataKey', 2, repeated=True) class GoogleCloudAiplatformV1beta1StreamingFetchFeatureValuesResponse(_messages.Message): r"""Response message for FeatureOnlineStoreService.StreamingFetchFeatureValues. Fields: data: A GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse attribute. dataKeysWithError: A GoogleCloudAiplatformV1beta1FeatureViewDataKey attribute. status: Response status. If OK, then StreamingFetchFeatureValuesResponse.data will be populated. Otherwise StreamingFetchFeatureValuesResponse.data_keys_with_error will be populated with the appropriate data keys. The error only applies to the listed data keys - the stream will remain open for further FeatureOnlineStoreService.StreamingFetchFeatureValuesRequest requests. """ data = _messages.MessageField('GoogleCloudAiplatformV1beta1FetchFeatureValuesResponse', 1, repeated=True) dataKeysWithError = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureViewDataKey', 2, repeated=True) status = _messages.MessageField('GoogleRpcStatus', 3) class GoogleCloudAiplatformV1beta1StreamingPredictRequest(_messages.Message): r"""Request message for PredictionService.StreamingPredict. The first message must contain endpoint field and optionally input. The subsequent messages must contain input. Fields: inputs: The prediction input. parameters: The parameters that govern the prediction. """ inputs = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensor', 1, repeated=True) parameters = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensor', 2) class GoogleCloudAiplatformV1beta1StreamingPredictResponse(_messages.Message): r"""Response message for PredictionService.StreamingPredict. Fields: outputs: The prediction output. parameters: The parameters that govern the prediction. """ outputs = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensor', 1, repeated=True) parameters = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensor', 2) class GoogleCloudAiplatformV1beta1StreamingReadFeatureValuesRequest(_messages.Message): r"""Request message for FeaturestoreOnlineServingService.StreamingReadFeatureValues. Fields: entityIds: Required. IDs of entities to read Feature values of. The maximum number of IDs is 100. For example, for a machine learning model predicting user clicks on a website, an entity ID could be `user_123`. featureSelector: Required. Selector choosing Features of the target EntityType. Feature IDs will be deduplicated. """ entityIds = _messages.StringField(1, repeated=True) featureSelector = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureSelector', 2) class GoogleCloudAiplatformV1beta1StringArray(_messages.Message): r"""A list of string values. Fields: values: A list of string values. """ values = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1StructFieldValue(_messages.Message): r"""One field of a Struct (or object) type feature value. Fields: name: Name of the field in the struct feature. value: The value for this field. """ name = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureValue', 2) class GoogleCloudAiplatformV1beta1StructValue(_messages.Message): r"""Struct (or object) type feature value. Fields: values: A list of field values. """ values = _messages.MessageField('GoogleCloudAiplatformV1beta1StructFieldValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1Study(_messages.Message): r"""A message representing a Study. Enums: StateValueValuesEnum: Output only. The detailed state of a Study. Fields: createTime: Output only. Time at which the study was created. displayName: Required. Describes the Study, default value is empty string. inactiveReason: Output only. A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED. name: Output only. The name of a study. The study's globally unique identifier. Format: `projects/{project}/locations/{location}/studies/{study}` state: Output only. The detailed state of a Study. studySpec: Required. Configuration of the Study. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of a Study. Values: STATE_UNSPECIFIED: The study state is unspecified. ACTIVE: The study is active. INACTIVE: The study is stopped due to an internal error. COMPLETED: The study is done when the service exhausts the parameter search space or max_trial_count is reached. """ STATE_UNSPECIFIED = 0 ACTIVE = 1 INACTIVE = 2 COMPLETED = 3 createTime = _messages.StringField(1) displayName = _messages.StringField(2) inactiveReason = _messages.StringField(3) name = _messages.StringField(4) state = _messages.EnumField('StateValueValuesEnum', 5) studySpec = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpec', 6) class GoogleCloudAiplatformV1beta1StudySpec(_messages.Message): r"""Represents specification of a Study. Enums: AlgorithmValueValuesEnum: The search algorithm specified for the Study. MeasurementSelectionTypeValueValuesEnum: Describe which measurement selection type will be used ObservationNoiseValueValuesEnum: The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline. Fields: algorithm: The search algorithm specified for the Study. convexAutomatedStoppingSpec: The automated early stopping spec using convex stopping rule. convexStopConfig: Deprecated. The automated early stopping using convex stopping rule. decayCurveStoppingSpec: The automated early stopping spec using decay curve rule. measurementSelectionType: Describe which measurement selection type will be used medianAutomatedStoppingSpec: The automated early stopping spec using median rule. metrics: Required. Metric specs for the Study. observationNoise: The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline. parameters: Required. The set of parameters to tune. studyStoppingConfig: Conditions for automated stopping of a Study. Enable automated stopping by configuring at least one condition. transferLearningConfig: The configuration info/options for transfer learning. Currently supported for Vertex AI Vizier service, not HyperParameterTuningJob """ class AlgorithmValueValuesEnum(_messages.Enum): r"""The search algorithm specified for the Study. Values: ALGORITHM_UNSPECIFIED: The default algorithm used by Vertex AI for [hyperparameter tuning](https://cloud.google.com/vertex- ai/docs/training/hyperparameter-tuning-overview) and [Vertex AI Vizier](https://cloud.google.com/vertex-ai/docs/vizier). GRID_SEARCH: Simple grid search within the feasible space. To use grid search, all parameters must be `INTEGER`, `CATEGORICAL`, or `DISCRETE`. RANDOM_SEARCH: Simple random search within the feasible space. """ ALGORITHM_UNSPECIFIED = 0 GRID_SEARCH = 1 RANDOM_SEARCH = 2 class MeasurementSelectionTypeValueValuesEnum(_messages.Enum): r"""Describe which measurement selection type will be used Values: MEASUREMENT_SELECTION_TYPE_UNSPECIFIED: Will be treated as LAST_MEASUREMENT. LAST_MEASUREMENT: Use the last measurement reported. BEST_MEASUREMENT: Use the best measurement reported. """ MEASUREMENT_SELECTION_TYPE_UNSPECIFIED = 0 LAST_MEASUREMENT = 1 BEST_MEASUREMENT = 2 class ObservationNoiseValueValuesEnum(_messages.Enum): r"""The observation noise level of the study. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline. Values: OBSERVATION_NOISE_UNSPECIFIED: The default noise level chosen by Vertex AI. LOW: Vertex AI assumes that the objective function is (nearly) perfectly reproducible, and will never repeat the same Trial parameters. HIGH: Vertex AI will estimate the amount of noise in metric evaluations, it may repeat the same Trial parameters more than once. """ OBSERVATION_NOISE_UNSPECIFIED = 0 LOW = 1 HIGH = 2 algorithm = _messages.EnumField('AlgorithmValueValuesEnum', 1) convexAutomatedStoppingSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecConvexAutomatedStoppingSpec', 2) convexStopConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecConvexStopConfig', 3) decayCurveStoppingSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecDecayCurveAutomatedStoppingSpec', 4) measurementSelectionType = _messages.EnumField('MeasurementSelectionTypeValueValuesEnum', 5) medianAutomatedStoppingSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecMedianAutomatedStoppingSpec', 6) metrics = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecMetricSpec', 7, repeated=True) observationNoise = _messages.EnumField('ObservationNoiseValueValuesEnum', 8) parameters = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecParameterSpec', 9, repeated=True) studyStoppingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecStudyStoppingConfig', 10) transferLearningConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecTransferLearningConfig', 11) class GoogleCloudAiplatformV1beta1StudySpecConvexAutomatedStoppingSpec(_messages.Message): r"""Configuration for ConvexAutomatedStoppingSpec. When there are enough completed trials (configured by min_measurement_count), for pending trials with enough measurements and steps, the policy first computes an overestimate of the objective value at max_num_steps according to the slope of the incomplete objective value curve. No prediction can be made if the curve is completely flat. If the overestimation is worse than the best objective value of the completed trials, this pending trial will be early- stopped, but a last measurement will be added to the pending trial with max_num_steps and predicted objective value from the autoregression model. Fields: learningRateParameterName: The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial. maxStepCount: Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. If not defined, it will learn it from the completed trials. When use_steps is false, this field is set to the maximum elapsed seconds. minMeasurementCount: The minimal number of measurements in a Trial. Early- stopping checks will not trigger if less than min_measurement_count+1 completed trials or pending trials with less than min_measurement_count measurements. If not defined, the default value is 5. minStepCount: Minimum number of steps for a trial to complete. Trials which do not have a measurement with step_count > min_step_count won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_step_count is set to be one-tenth of the max_step_count. When use_elapsed_duration is true, this field is set to the minimum elapsed seconds. updateAllStoppedTrials: ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model. When this flag is set to True, all stopped trials from the beginning are potentially updated in terms of their `final_measurement`. Also, note that the training logic of autoregressive models is different in this case. Enabling this option has shown better results and this may be the default option in the future. useElapsedDuration: This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_elapsed_duration==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_elapsed_duration==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds. """ learningRateParameterName = _messages.StringField(1) maxStepCount = _messages.IntegerField(2) minMeasurementCount = _messages.IntegerField(3) minStepCount = _messages.IntegerField(4) updateAllStoppedTrials = _messages.BooleanField(5) useElapsedDuration = _messages.BooleanField(6) class GoogleCloudAiplatformV1beta1StudySpecConvexStopConfig(_messages.Message): r"""Configuration for ConvexStopPolicy. Fields: autoregressiveOrder: The number of Trial measurements used in autoregressive model for value prediction. A trial won't be considered early stopping if has fewer measurement points. learningRateParameterName: The hyper-parameter name used in the tuning job that stands for learning rate. Leave it blank if learning rate is not in a parameter in tuning. The learning_rate is used to estimate the objective value of the ongoing trial. maxNumSteps: Steps used in predicting the final objective for early stopped trials. In general, it's set to be the same as the defined steps in training / tuning. When use_steps is false, this field is set to the maximum elapsed seconds. minNumSteps: Minimum number of steps for a trial to complete. Trials which do not have a measurement with num_steps > min_num_steps won't be considered for early stopping. It's ok to set it to 0, and a trial can be early stopped at any stage. By default, min_num_steps is set to be one-tenth of the max_num_steps. When use_steps is false, this field is set to the minimum elapsed seconds. useSeconds: This bool determines whether or not the rule is applied based on elapsed_secs or steps. If use_seconds==false, the early stopping decision is made according to the predicted objective values according to the target steps. If use_seconds==true, elapsed_secs is used instead of steps. Also, in this case, the parameters max_num_steps and min_num_steps are overloaded to contain max_elapsed_seconds and min_elapsed_seconds. """ autoregressiveOrder = _messages.IntegerField(1) learningRateParameterName = _messages.StringField(2) maxNumSteps = _messages.IntegerField(3) minNumSteps = _messages.IntegerField(4) useSeconds = _messages.BooleanField(5) class GoogleCloudAiplatformV1beta1StudySpecDecayCurveAutomatedStoppingSpec(_messages.Message): r"""The decay curve automated stopping rule builds a Gaussian Process Regressor to predict the final objective value of a Trial based on the already completed Trials and the intermediate measurements of the current Trial. Early stopping is requested for the current Trial if there is very low probability to exceed the optimal value found so far. Fields: useElapsedDuration: True if Measurement.elapsed_duration is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.step_count will be used as the x-axis. """ useElapsedDuration = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1StudySpecMedianAutomatedStoppingSpec(_messages.Message): r"""The median automated stopping rule stops a pending Trial if the Trial's best objective_value is strictly below the median 'performance' of all completed Trials reported up to the Trial's last measurement. Currently, 'performance' refers to the running average of the objective values reported by the Trial in each measurement. Fields: useElapsedDuration: True if median automated stopping rule applies on Measurement.elapsed_duration. It means that elapsed_duration field of latest measurement of current Trial is used to compute median objective value for each completed Trials. """ useElapsedDuration = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1StudySpecMetricSpec(_messages.Message): r"""Represents a metric to optimize. Enums: GoalValueValuesEnum: Required. The optimization goal of the metric. Fields: goal: Required. The optimization goal of the metric. metricId: Required. The ID of the metric. Must not contain whitespaces and must be unique amongst all MetricSpecs. safetyConfig: Used for safe search. In the case, the metric will be a safety metric. You must provide a separate metric for objective metric. """ class GoalValueValuesEnum(_messages.Enum): r"""Required. The optimization goal of the metric. Values: GOAL_TYPE_UNSPECIFIED: Goal Type will default to maximize. MAXIMIZE: Maximize the goal metric. MINIMIZE: Minimize the goal metric. """ GOAL_TYPE_UNSPECIFIED = 0 MAXIMIZE = 1 MINIMIZE = 2 goal = _messages.EnumField('GoalValueValuesEnum', 1) metricId = _messages.StringField(2) safetyConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecMetricSpecSafetyMetricConfig', 3) class GoogleCloudAiplatformV1beta1StudySpecMetricSpecSafetyMetricConfig(_messages.Message): r"""Used in safe optimization to specify threshold levels and risk tolerance. Fields: desiredMinSafeTrialsFraction: Desired minimum fraction of safe trials (over total number of trials) that should be targeted by the algorithm at any time during the study (best effort). This should be between 0.0 and 1.0 and a value of 0.0 means that there is no minimum and an algorithm proceeds without targeting any specific fraction. A value of 1.0 means that the algorithm attempts to only Suggest safe Trials. safetyThreshold: Safety threshold (boundary value between safe and unsafe). NOTE that if you leave SafetyMetricConfig unset, a default value of 0 will be used. """ desiredMinSafeTrialsFraction = _messages.FloatField(1) safetyThreshold = _messages.FloatField(2) class GoogleCloudAiplatformV1beta1StudySpecParameterSpec(_messages.Message): r"""Represents a single parameter to optimize. Enums: ScaleTypeValueValuesEnum: How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters. Fields: categoricalValueSpec: The value spec for a 'CATEGORICAL' parameter. conditionalParameterSpecs: A conditional parameter node is active if the parameter's value matches the conditional node's parent_value_condition. If two items in conditional_parameter_specs have the same name, they must have disjoint parent_value_condition. discreteValueSpec: The value spec for a 'DISCRETE' parameter. doubleValueSpec: The value spec for a 'DOUBLE' parameter. integerValueSpec: The value spec for an 'INTEGER' parameter. parameterId: Required. The ID of the parameter. Must not contain whitespaces and must be unique amongst all ParameterSpecs. scaleType: How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters. """ class ScaleTypeValueValuesEnum(_messages.Enum): r"""How the parameter should be scaled. Leave unset for `CATEGORICAL` parameters. Values: SCALE_TYPE_UNSPECIFIED: By default, no scaling is applied. UNIT_LINEAR_SCALE: Scales the feasible space to (0, 1) linearly. UNIT_LOG_SCALE: Scales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive. UNIT_REVERSE_LOG_SCALE: Scales the feasible space "reverse" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive. """ SCALE_TYPE_UNSPECIFIED = 0 UNIT_LINEAR_SCALE = 1 UNIT_LOG_SCALE = 2 UNIT_REVERSE_LOG_SCALE = 3 categoricalValueSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecParameterSpecCategoricalValueSpec', 1) conditionalParameterSpecs = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpec', 2, repeated=True) discreteValueSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecParameterSpecDiscreteValueSpec', 3) doubleValueSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecParameterSpecDoubleValueSpec', 4) integerValueSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecParameterSpecIntegerValueSpec', 5) parameterId = _messages.StringField(6) scaleType = _messages.EnumField('ScaleTypeValueValuesEnum', 7) class GoogleCloudAiplatformV1beta1StudySpecParameterSpecCategoricalValueSpec(_messages.Message): r"""Value specification for a parameter in `CATEGORICAL` type. Fields: defaultValue: A default value for a `CATEGORICAL` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline. values: Required. The list of possible categories. """ defaultValue = _messages.StringField(1) values = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpec(_messages.Message): r"""Represents a parameter spec with condition from its parent parameter. Fields: parameterSpec: Required. The spec for a conditional parameter. parentCategoricalValues: The spec for matching values from a parent parameter of `CATEGORICAL` type. parentDiscreteValues: The spec for matching values from a parent parameter of `DISCRETE` type. parentIntValues: The spec for matching values from a parent parameter of `INTEGER` type. """ parameterSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecParameterSpec', 1) parentCategoricalValues = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition', 2) parentDiscreteValues = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition', 3) parentIntValues = _messages.MessageField('GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecIntValueCondition', 4) class GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecCategoricalValueCondition(_messages.Message): r"""Represents the spec to match categorical values from parent parameter. Fields: values: Required. Matches values of the parent parameter of 'CATEGORICAL' type. All values must exist in `categorical_value_spec` of parent parameter. """ values = _messages.StringField(1, repeated=True) class GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecDiscreteValueCondition(_messages.Message): r"""Represents the spec to match discrete values from parent parameter. Fields: values: Required. Matches values of the parent parameter of 'DISCRETE' type. All values must exist in `discrete_value_spec` of parent parameter. The Epsilon of the value matching is 1e-10. """ values = _messages.FloatField(1, repeated=True) class GoogleCloudAiplatformV1beta1StudySpecParameterSpecConditionalParameterSpecIntValueCondition(_messages.Message): r"""Represents the spec to match integer values from parent parameter. Fields: values: Required. Matches values of the parent parameter of 'INTEGER' type. All values must lie in `integer_value_spec` of parent parameter. """ values = _messages.IntegerField(1, repeated=True) class GoogleCloudAiplatformV1beta1StudySpecParameterSpecDiscreteValueSpec(_messages.Message): r"""Value specification for a parameter in `DISCRETE` type. Fields: defaultValue: A default value for a `DISCRETE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. It automatically rounds to the nearest feasible discrete point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline. values: Required. A list of possible values. The list should be in increasing order and at least 1e-10 apart. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values. """ defaultValue = _messages.FloatField(1) values = _messages.FloatField(2, repeated=True) class GoogleCloudAiplatformV1beta1StudySpecParameterSpecDoubleValueSpec(_messages.Message): r"""Value specification for a parameter in `DOUBLE` type. Fields: defaultValue: A default value for a `DOUBLE` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline. maxValue: Required. Inclusive maximum value of the parameter. minValue: Required. Inclusive minimum value of the parameter. """ defaultValue = _messages.FloatField(1) maxValue = _messages.FloatField(2) minValue = _messages.FloatField(3) class GoogleCloudAiplatformV1beta1StudySpecParameterSpecIntegerValueSpec(_messages.Message): r"""Value specification for a parameter in `INTEGER` type. Fields: defaultValue: A default value for an `INTEGER` parameter that is assumed to be a relatively good starting point. Unset value signals that there is no offered starting point. Currently only supported by the Vertex AI Vizier service. Not supported by HyperparameterTuningJob or TrainingPipeline. maxValue: Required. Inclusive maximum value of the parameter. minValue: Required. Inclusive minimum value of the parameter. """ defaultValue = _messages.IntegerField(1) maxValue = _messages.IntegerField(2) minValue = _messages.IntegerField(3) class GoogleCloudAiplatformV1beta1StudySpecStudyStoppingConfig(_messages.Message): r"""The configuration (stopping conditions) for automated stopping of a Study. Conditions include trial budgets, time budgets, and convergence detection. Fields: maxDurationNoProgress: If the objective value has not improved for this much time, stop the study. WARNING: Effective only for single-objective studies. maxNumTrials: If there are more than this many trials, stop the study. maxNumTrialsNoProgress: If the objective value has not improved for this many consecutive trials, stop the study. WARNING: Effective only for single-objective studies. maximumRuntimeConstraint: If the specified time or duration has passed, stop the study. minNumTrials: If there are fewer than this many COMPLETED trials, do not stop the study. minimumRuntimeConstraint: Each "stopping rule" in this proto specifies an "if" condition. Before Vizier would generate a new suggestion, it first checks each specified stopping rule, from top to bottom in this list. Note that the first few rules (e.g. minimum_runtime_constraint, min_num_trials) will prevent other stopping rules from being evaluated until they are met. For example, setting `min_num_trials=5` and `always_stop_after= 1 hour` means that the Study will ONLY stop after it has 5 COMPLETED trials, even if more than an hour has passed since its creation. It follows the first applicable rule (whose "if" condition is satisfied) to make a stopping decision. If none of the specified rules are applicable, then Vizier decides that the study should not stop. If Vizier decides that the study should stop, the study enters STOPPING state (or STOPPING_ASAP if should_stop_asap = true). IMPORTANT: The automatic study state transition happens precisely as described above; that is, deleting trials or updating StudyConfig NEVER automatically moves the study state back to ACTIVE. If you want to _resume_ a Study that was stopped, 1) change the stopping conditions if necessary, 2) activate the study, and then 3) ask for suggestions. If the specified time or duration has not passed, do not stop the study. shouldStopAsap: If true, a Study enters STOPPING_ASAP whenever it would normally enters STOPPING state. The bottom line is: set to true if you want to interrupt on-going evaluations of Trials as soon as the study stopping condition is met. (Please see Study.State documentation for the source of truth). """ maxDurationNoProgress = _messages.StringField(1) maxNumTrials = _messages.IntegerField(2, variant=_messages.Variant.INT32) maxNumTrialsNoProgress = _messages.IntegerField(3, variant=_messages.Variant.INT32) maximumRuntimeConstraint = _messages.MessageField('GoogleCloudAiplatformV1beta1StudyTimeConstraint', 4) minNumTrials = _messages.IntegerField(5, variant=_messages.Variant.INT32) minimumRuntimeConstraint = _messages.MessageField('GoogleCloudAiplatformV1beta1StudyTimeConstraint', 6) shouldStopAsap = _messages.BooleanField(7) class GoogleCloudAiplatformV1beta1StudySpecTransferLearningConfig(_messages.Message): r"""This contains flag for manually disabling transfer learning for a study. The names of prior studies being used for transfer learning (if any) are also listed here. Fields: disableTransferLearning: Flag to to manually prevent vizier from using transfer learning on a new study. Otherwise, vizier will automatically determine whether or not to use transfer learning. priorStudyNames: Output only. Names of previously completed studies """ disableTransferLearning = _messages.BooleanField(1) priorStudyNames = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1StudyTimeConstraint(_messages.Message): r"""Time-based Constraint for Study Fields: endTime: Compares the wallclock time to this time. Must use UTC timezone. maxDuration: Counts the wallclock time passed since the creation of this Study. """ endTime = _messages.StringField(1) maxDuration = _messages.StringField(2) class GoogleCloudAiplatformV1beta1SuggestTrialsMetadata(_messages.Message): r"""Details of operations that perform Trials suggestion. Fields: clientId: The identifier of the client that is requesting the suggestion. If multiple SuggestTrialsRequests have the same `client_id`, the service will return the identical suggested Trial if the Trial is pending, and provide a new Trial if the last suggested Trial was completed. genericMetadata: Operation metadata for suggesting Trials. """ clientId = _messages.StringField(1) genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 2) class GoogleCloudAiplatformV1beta1SuggestTrialsRequest(_messages.Message): r"""Request message for VizierService.SuggestTrials. Fields: clientId: Required. The identifier of the client that is requesting the suggestion. If multiple SuggestTrialsRequests have the same `client_id`, the service will return the identical suggested Trial if the Trial is pending, and provide a new Trial if the last suggested Trial was completed. contexts: Optional. This allows you to specify the "context" for a Trial; a context is a slice (a subspace) of the search space. Typical uses for contexts: 1) You are using Vizier to tune a server for best performance, but there's a strong weekly cycle. The context specifies the day-of- week. This allows Tuesday to generalize from Wednesday without assuming that everything is identical. 2) Imagine you're optimizing some medical treatment for people. As they walk in the door, you know certain facts about them (e.g. sex, weight, height, blood-pressure). Put that information in the context, and Vizier will adapt its suggestions to the patient. 3) You want to do a fair A/B test efficiently. Specify the "A" and "B" conditions as contexts, and Vizier will generalize between "A" and "B" conditions. If they are similar, this will allow Vizier to converge to the optimum faster than if "A" and "B" were separate Studies. NOTE: You can also enter contexts as REQUESTED Trials, e.g. via the CreateTrial() RPC; that's the asynchronous option where you don't need a close association between contexts and suggestions. NOTE: All the Parameters you set in a context MUST be defined in the Study. NOTE: You must supply 0 or $suggestion_count contexts. If you don't supply any contexts, Vizier will make suggestions from the full search space specified in the StudySpec; if you supply a full set of context, each suggestion will match the corresponding context. NOTE: A Context with no features set matches anything, and allows suggestions from the full search space. NOTE: Contexts MUST lie within the search space specified in the StudySpec. It's an error if they don't. NOTE: Contexts preferentially match ACTIVE then REQUESTED trials before new suggestions are generated. NOTE: Generation of suggestions involves a match between a Context and (optionally) a REQUESTED trial; if that match is not fully specified, a suggestion will be geneated in the merged subspace. suggestionCount: Required. The number of suggestions requested. It must be positive. """ clientId = _messages.StringField(1) contexts = _messages.MessageField('GoogleCloudAiplatformV1beta1TrialContext', 2, repeated=True) suggestionCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SuggestTrialsResponse(_messages.Message): r"""Response message for VizierService.SuggestTrials. Enums: StudyStateValueValuesEnum: The state of the Study. Fields: endTime: The time at which operation processing completed. startTime: The time at which the operation was started. studyState: The state of the Study. trials: A list of Trials. """ class StudyStateValueValuesEnum(_messages.Enum): r"""The state of the Study. Values: STATE_UNSPECIFIED: The study state is unspecified. ACTIVE: The study is active. INACTIVE: The study is stopped due to an internal error. COMPLETED: The study is done when the service exhausts the parameter search space or max_trial_count is reached. """ STATE_UNSPECIFIED = 0 ACTIVE = 1 INACTIVE = 2 COMPLETED = 3 endTime = _messages.StringField(1) startTime = _messages.StringField(2) studyState = _messages.EnumField('StudyStateValueValuesEnum', 3) trials = _messages.MessageField('GoogleCloudAiplatformV1beta1Trial', 4, repeated=True) class GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInput(_messages.Message): r"""Input for summarization helpfulness metric. Fields: instance: Required. Summarization helpfulness instance. metricSpec: Required. Spec for summarization helpfulness score metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1SummarizationHelpfulnessSpec', 2) class GoogleCloudAiplatformV1beta1SummarizationHelpfulnessInstance(_messages.Message): r"""Spec for summarization helpfulness instance. Fields: context: Required. Text to be summarized. instruction: Optional. Summarization prompt for LLM. prediction: Required. Output of the evaluated model. reference: Optional. Ground truth used to compare against the prediction. """ context = _messages.StringField(1) instruction = _messages.StringField(2) prediction = _messages.StringField(3) reference = _messages.StringField(4) class GoogleCloudAiplatformV1beta1SummarizationHelpfulnessResult(_messages.Message): r"""Spec for summarization helpfulness result. Fields: confidence: Output only. Confidence for summarization helpfulness score. explanation: Output only. Explanation for summarization helpfulness score. score: Output only. Summarization Helpfulness score. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SummarizationHelpfulnessSpec(_messages.Message): r"""Spec for summarization helpfulness score metric. Fields: useReference: Optional. Whether to use instance.reference to compute summarization helpfulness. version: Optional. Which version to use for evaluation. """ useReference = _messages.BooleanField(1) version = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SummarizationQualityInput(_messages.Message): r"""Input for summarization quality metric. Fields: instance: Required. Summarization quality instance. metricSpec: Required. Spec for summarization quality score metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1SummarizationQualityInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1SummarizationQualitySpec', 2) class GoogleCloudAiplatformV1beta1SummarizationQualityInstance(_messages.Message): r"""Spec for summarization quality instance. Fields: context: Required. Text to be summarized. instruction: Required. Summarization prompt for LLM. prediction: Required. Output of the evaluated model. reference: Optional. Ground truth used to compare against the prediction. """ context = _messages.StringField(1) instruction = _messages.StringField(2) prediction = _messages.StringField(3) reference = _messages.StringField(4) class GoogleCloudAiplatformV1beta1SummarizationQualityResult(_messages.Message): r"""Spec for summarization quality result. Fields: confidence: Output only. Confidence for summarization quality score. explanation: Output only. Explanation for summarization quality score. score: Output only. Summarization Quality score. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SummarizationQualitySpec(_messages.Message): r"""Spec for summarization quality score metric. Fields: useReference: Optional. Whether to use instance.reference to compute summarization quality. version: Optional. Which version to use for evaluation. """ useReference = _messages.BooleanField(1) version = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SummarizationVerbosityInput(_messages.Message): r"""Input for summarization verbosity metric. Fields: instance: Required. Summarization verbosity instance. metricSpec: Required. Spec for summarization verbosity score metric. """ instance = _messages.MessageField('GoogleCloudAiplatformV1beta1SummarizationVerbosityInstance', 1) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1SummarizationVerbositySpec', 2) class GoogleCloudAiplatformV1beta1SummarizationVerbosityInstance(_messages.Message): r"""Spec for summarization verbosity instance. Fields: context: Required. Text to be summarized. instruction: Optional. Summarization prompt for LLM. prediction: Required. Output of the evaluated model. reference: Optional. Ground truth used to compare against the prediction. """ context = _messages.StringField(1) instruction = _messages.StringField(2) prediction = _messages.StringField(3) reference = _messages.StringField(4) class GoogleCloudAiplatformV1beta1SummarizationVerbosityResult(_messages.Message): r"""Spec for summarization verbosity result. Fields: confidence: Output only. Confidence for summarization verbosity score. explanation: Output only. Explanation for summarization verbosity score. score: Output only. Summarization Verbosity score. """ confidence = _messages.FloatField(1, variant=_messages.Variant.FLOAT) explanation = _messages.StringField(2) score = _messages.FloatField(3, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1SummarizationVerbositySpec(_messages.Message): r"""Spec for summarization verbosity score metric. Fields: useReference: Optional. Whether to use instance.reference to compute summarization verbosity. version: Optional. Which version to use for evaluation. """ useReference = _messages.BooleanField(1) version = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SummaryMetrics(_messages.Message): r"""The summary metrics for the evaluation run. Messages: MetricsValue: Optional. Map of metric name to metric value. Fields: failedItems: Optional. The number of items that failed to be evaluated. metrics: Optional. Map of metric name to metric value. totalItems: Optional. The total number of items that were evaluated. """ @encoding.MapUnrecognizedFields('additionalProperties') class MetricsValue(_messages.Message): r"""Optional. Map of metric name to metric value. Messages: AdditionalProperty: An additional property for a MetricsValue object. Fields: additionalProperties: Additional properties of type MetricsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a MetricsValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) failedItems = _messages.IntegerField(1, variant=_messages.Variant.INT32) metrics = _messages.MessageField('MetricsValue', 2) totalItems = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1SupervisedHyperParameters(_messages.Message): r"""Hyperparameters for SFT. Enums: AdapterSizeValueValuesEnum: Optional. Adapter size for tuning. Fields: adapterSize: Optional. Adapter size for tuning. batchSize: Optional. Batch size for tuning. This feature is only available for open source models. epochCount: Optional. Number of complete passes the model makes over the entire training dataset during training. learningRate: Optional. Learning rate for tuning. Mutually exclusive with `learning_rate_multiplier`. This feature is only available for open source models. learningRateMultiplier: Optional. Multiplier for adjusting the default learning rate. Mutually exclusive with `learning_rate`. This feature is only available for 1P models. """ class AdapterSizeValueValuesEnum(_messages.Enum): r"""Optional. Adapter size for tuning. Values: ADAPTER_SIZE_UNSPECIFIED: Adapter size is unspecified. ADAPTER_SIZE_ONE: Adapter size 1. ADAPTER_SIZE_TWO: Adapter size 2. ADAPTER_SIZE_FOUR: Adapter size 4. ADAPTER_SIZE_EIGHT: Adapter size 8. ADAPTER_SIZE_SIXTEEN: Adapter size 16. ADAPTER_SIZE_THIRTY_TWO: Adapter size 32. """ ADAPTER_SIZE_UNSPECIFIED = 0 ADAPTER_SIZE_ONE = 1 ADAPTER_SIZE_TWO = 2 ADAPTER_SIZE_FOUR = 3 ADAPTER_SIZE_EIGHT = 4 ADAPTER_SIZE_SIXTEEN = 5 ADAPTER_SIZE_THIRTY_TWO = 6 adapterSize = _messages.EnumField('AdapterSizeValueValuesEnum', 1) batchSize = _messages.IntegerField(2) epochCount = _messages.IntegerField(3) learningRate = _messages.FloatField(4) learningRateMultiplier = _messages.FloatField(5) class GoogleCloudAiplatformV1beta1SupervisedTuningDataStats(_messages.Message): r"""Tuning data statistics for Supervised Tuning. Fields: droppedExampleReasons: Output only. For each index in `truncated_example_indices`, the user-facing reason why the example was dropped. totalBillableCharacterCount: Output only. Number of billable characters in the tuning dataset. totalBillableTokenCount: Output only. Number of billable tokens in the tuning dataset. totalTruncatedExampleCount: Output only. The number of examples in the dataset that have been dropped. An example can be dropped for reasons including: too many tokens, contains an invalid image, contains too many images, etc. totalTuningCharacterCount: Output only. Number of tuning characters in the tuning dataset. truncatedExampleIndices: Output only. A partial sample of the indices (starting from 1) of the dropped examples. tuningDatasetExampleCount: Output only. Number of examples in the tuning dataset. tuningStepCount: Output only. Number of tuning steps for this Tuning Job. userDatasetExamples: Output only. Sample user messages in the training dataset uri. userInputTokenDistribution: Output only. Dataset distributions for the user input tokens. userMessagePerExampleDistribution: Output only. Dataset distributions for the messages per example. userOutputTokenDistribution: Output only. Dataset distributions for the user output tokens. """ droppedExampleReasons = _messages.StringField(1, repeated=True) totalBillableCharacterCount = _messages.IntegerField(2) totalBillableTokenCount = _messages.IntegerField(3) totalTruncatedExampleCount = _messages.IntegerField(4) totalTuningCharacterCount = _messages.IntegerField(5) truncatedExampleIndices = _messages.IntegerField(6, repeated=True) tuningDatasetExampleCount = _messages.IntegerField(7) tuningStepCount = _messages.IntegerField(8) userDatasetExamples = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 9, repeated=True) userInputTokenDistribution = _messages.MessageField('GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution', 10) userMessagePerExampleDistribution = _messages.MessageField('GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution', 11) userOutputTokenDistribution = _messages.MessageField('GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution', 12) class GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistribution(_messages.Message): r"""Dataset distribution for Supervised Tuning. Fields: billableSum: Output only. Sum of a given population of values that are billable. buckets: Output only. Defines the histogram bucket. max: Output only. The maximum of the population values. mean: Output only. The arithmetic mean of the values in the population. median: Output only. The median of the values in the population. min: Output only. The minimum of the population values. p5: Output only. The 5th percentile of the values in the population. p95: Output only. The 95th percentile of the values in the population. sum: Output only. Sum of a given population of values. """ billableSum = _messages.IntegerField(1) buckets = _messages.MessageField('GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistributionDatasetBucket', 2, repeated=True) max = _messages.FloatField(3) mean = _messages.FloatField(4) median = _messages.FloatField(5) min = _messages.FloatField(6) p5 = _messages.FloatField(7) p95 = _messages.FloatField(8) sum = _messages.IntegerField(9) class GoogleCloudAiplatformV1beta1SupervisedTuningDatasetDistributionDatasetBucket(_messages.Message): r"""Dataset bucket used to create a histogram for the distribution given a population of values. Fields: count: Output only. Number of values in the bucket. left: Output only. Left bound of the bucket. right: Output only. Right bound of the bucket. """ count = _messages.FloatField(1) left = _messages.FloatField(2) right = _messages.FloatField(3) class GoogleCloudAiplatformV1beta1SupervisedTuningSpec(_messages.Message): r"""Tuning Spec for Supervised Tuning for first party models. Enums: TuningModeValueValuesEnum: Tuning mode. Fields: evaluationConfig: Optional. Evaluation Config for Tuning Job. exportLastCheckpointOnly: Optional. If set to true, disable intermediate checkpoints for SFT and only the last checkpoint will be exported. Otherwise, enable intermediate checkpoints for SFT. Default is false. hyperParameters: Optional. Hyperparameters for SFT. trainingDatasetUri: Required. Training dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset. tuningMode: Tuning mode. validationDatasetUri: Optional. Validation dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset. """ class TuningModeValueValuesEnum(_messages.Enum): r"""Tuning mode. Values: TUNING_MODE_UNSPECIFIED: Tuning mode is unspecified. TUNING_MODE_FULL: Full fine-tuning mode. TUNING_MODE_PEFT_ADAPTER: PEFT adapter tuning mode. """ TUNING_MODE_UNSPECIFIED = 0 TUNING_MODE_FULL = 1 TUNING_MODE_PEFT_ADAPTER = 2 evaluationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluationConfig', 1) exportLastCheckpointOnly = _messages.BooleanField(2) hyperParameters = _messages.MessageField('GoogleCloudAiplatformV1beta1SupervisedHyperParameters', 3) trainingDatasetUri = _messages.StringField(4) tuningMode = _messages.EnumField('TuningModeValueValuesEnum', 5) validationDatasetUri = _messages.StringField(6) class GoogleCloudAiplatformV1beta1SyncFeatureViewRequest(_messages.Message): r"""Request message for FeatureOnlineStoreAdminService.SyncFeatureView.""" class GoogleCloudAiplatformV1beta1SyncFeatureViewResponse(_messages.Message): r"""Response message for FeatureOnlineStoreAdminService.SyncFeatureView. Fields: featureViewSync: Format: `projects/{project}/locations/{location}/featureO nlineStores/{feature_online_store}/featureViews/{feature_view}/featureVi ewSyncs/{feature_view_sync}` """ featureViewSync = _messages.StringField(1) class GoogleCloudAiplatformV1beta1SyntheticExample(_messages.Message): r"""Represents a single synthetic example, composed of multiple fields. Used for providing few-shot examples in the request and for returning generated examples in the response. Fields: fields: Required. A list of fields that constitute an example. """ fields = _messages.MessageField('GoogleCloudAiplatformV1beta1SyntheticField', 1, repeated=True) class GoogleCloudAiplatformV1beta1SyntheticField(_messages.Message): r"""Represents a single named field within a SyntheticExample. Fields: content: Required. The content of the field. fieldName: Optional. The name of the field. """ content = _messages.MessageField('GoogleCloudAiplatformV1beta1Content', 1) fieldName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1TFRecordDestination(_messages.Message): r"""The storage details for TFRecord output content. Fields: gcsDestination: Required. Google Cloud Storage location. """ gcsDestination = _messages.MessageField('GoogleCloudAiplatformV1beta1GcsDestination', 1) class GoogleCloudAiplatformV1beta1TaskDescriptionStrategy(_messages.Message): r"""Defines a generation strategy based on a high-level task description. Fields: taskDescription: Required. A high-level description of the synthetic data to be generated. """ taskDescription = _messages.StringField(1) class GoogleCloudAiplatformV1beta1Tensor(_messages.Message): r"""A tensor value type. Enums: DtypeValueValuesEnum: The data type of tensor. Messages: StructValValue: A map of string to tensor. Fields: boolVal: Type specific representations that make it easy to create tensor protos in all languages. Only the representation corresponding to "dtype" can be set. The values hold the flattened representation of the tensor in row major order. BOOL bytesVal: STRING doubleVal: DOUBLE dtype: The data type of tensor. floatVal: FLOAT int64Val: INT64 intVal: INT_8 INT_16 INT_32 listVal: A list of tensor values. shape: Shape of the tensor. stringVal: STRING structVal: A map of string to tensor. tensorVal: Serialized raw tensor content. uint64Val: UINT64 uintVal: UINT8 UINT16 UINT32 """ class DtypeValueValuesEnum(_messages.Enum): r"""The data type of tensor. Values: DATA_TYPE_UNSPECIFIED: Not a legal value for DataType. Used to indicate a DataType field has not been set. BOOL: Data types that all computation devices are expected to be capable to support. STRING: FLOAT: DOUBLE: INT8: INT16: INT32: INT64: UINT8: UINT16: UINT32: UINT64: """ DATA_TYPE_UNSPECIFIED = 0 BOOL = 1 STRING = 2 FLOAT = 3 DOUBLE = 4 INT8 = 5 INT16 = 6 INT32 = 7 INT64 = 8 UINT8 = 9 UINT16 = 10 UINT32 = 11 UINT64 = 12 @encoding.MapUnrecognizedFields('additionalProperties') class StructValValue(_messages.Message): r"""A map of string to tensor. Messages: AdditionalProperty: An additional property for a StructValValue object. Fields: additionalProperties: Additional properties of type StructValValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a StructValValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1Tensor attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensor', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) boolVal = _messages.BooleanField(1, repeated=True) bytesVal = _messages.BytesField(2, repeated=True) doubleVal = _messages.FloatField(3, repeated=True) dtype = _messages.EnumField('DtypeValueValuesEnum', 4) floatVal = _messages.FloatField(5, repeated=True, variant=_messages.Variant.FLOAT) int64Val = _messages.IntegerField(6, repeated=True) intVal = _messages.IntegerField(7, repeated=True, variant=_messages.Variant.INT32) listVal = _messages.MessageField('GoogleCloudAiplatformV1beta1Tensor', 8, repeated=True) shape = _messages.IntegerField(9, repeated=True) stringVal = _messages.StringField(10, repeated=True) structVal = _messages.MessageField('StructValValue', 11) tensorVal = _messages.BytesField(12) uint64Val = _messages.IntegerField(13, repeated=True, variant=_messages.Variant.UINT64) uintVal = _messages.IntegerField(14, repeated=True, variant=_messages.Variant.UINT32) class GoogleCloudAiplatformV1beta1Tensorboard(_messages.Message): r"""Tensorboard is a physical database that stores users' training metrics. A default Tensorboard is provided in each region of a Google Cloud project. If needed users can also create extra Tensorboards in their projects. Messages: LabelsValue: The labels with user-defined metadata to organize your Tensorboards. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Tensorboard (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: blobStoragePathPrefix: Output only. Consumer project Cloud Storage path prefix used to store blob data, which can either be a bucket or directory. Does not end with a '/'. createTime: Output only. Timestamp when this Tensorboard was created. description: Description of this Tensorboard. displayName: Required. User provided name of this Tensorboard. encryptionSpec: Customer-managed encryption key spec for a Tensorboard. If set, this Tensorboard and all sub-resources of this Tensorboard will be secured by this key. etag: Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens. isDefault: Used to indicate if the TensorBoard instance is the default one. Each project & region can have at most one default TensorBoard instance. Creation of a default TensorBoard instance and updating an existing TensorBoard instance to be default will mark all other TensorBoard instances (if any) as non default. labels: The labels with user-defined metadata to organize your Tensorboards. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Tensorboard (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. name: Output only. Name of the Tensorboard. Format: `projects/{project}/locations/{location}/tensorboards/{tensorboard}` runCount: Output only. The number of Runs stored in this Tensorboard. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. updateTime: Output only. Timestamp when this Tensorboard was last updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your Tensorboards. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Tensorboard (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) blobStoragePathPrefix = _messages.StringField(1) createTime = _messages.StringField(2) description = _messages.StringField(3) displayName = _messages.StringField(4) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 5) etag = _messages.StringField(6) isDefault = _messages.BooleanField(7) labels = _messages.MessageField('LabelsValue', 8) name = _messages.StringField(9) runCount = _messages.IntegerField(10, variant=_messages.Variant.INT32) satisfiesPzi = _messages.BooleanField(11) satisfiesPzs = _messages.BooleanField(12) updateTime = _messages.StringField(13) class GoogleCloudAiplatformV1beta1TensorboardBlob(_messages.Message): r"""One blob (e.g, image, graph) viewable on a blob metric plot. Fields: data: Optional. The bytes of the blob is not present unless it's returned by the ReadTensorboardBlobData endpoint. id: Output only. A URI safe key uniquely identifying a blob. Can be used to locate the blob stored in the Cloud Storage bucket of the consumer project. """ data = _messages.BytesField(1) id = _messages.StringField(2) class GoogleCloudAiplatformV1beta1TensorboardBlobSequence(_messages.Message): r"""One point viewable on a blob metric plot, but mostly just a wrapper message to work around repeated fields can't be used directly within `oneof` fields. Fields: values: List of blobs contained within the sequence. """ values = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardBlob', 1, repeated=True) class GoogleCloudAiplatformV1beta1TensorboardExperiment(_messages.Message): r"""A TensorboardExperiment is a group of TensorboardRuns, that are typically the results of a training job run, in a Tensorboard. Messages: LabelsValue: The labels with user-defined metadata to organize your TensorboardExperiment. Label keys and values cannot be longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with `aiplatform.googleapis.com/` and are immutable. The following system labels exist for each Dataset: * `aiplatform.googleapis.com/dataset_metadata_schema`: output only. Its value is the metadata_schema's title. Fields: createTime: Output only. Timestamp when this TensorboardExperiment was created. description: Description of this TensorboardExperiment. displayName: User provided name of this TensorboardExperiment. etag: Used to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: The labels with user-defined metadata to organize your TensorboardExperiment. Label keys and values cannot be longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with `aiplatform.googleapis.com/` and are immutable. The following system labels exist for each Dataset: * `aiplatform.googleapis.com/dataset_metadata_schema`: output only. Its value is the metadata_schema's title. name: Output only. Name of the TensorboardExperiment. Format: `projects/{p roject}/locations/{location}/tensorboards/{tensorboard}/experiments/{exp eriment}` source: Immutable. Source of the TensorboardExperiment. Example: a custom training job. updateTime: Output only. Timestamp when this TensorboardExperiment was last updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your TensorboardExperiment. Label keys and values cannot be longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one Dataset (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with `aiplatform.googleapis.com/` and are immutable. The following system labels exist for each Dataset: * `aiplatform.googleapis.com/dataset_metadata_schema`: output only. Its value is the metadata_schema's title. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) description = _messages.StringField(2) displayName = _messages.StringField(3) etag = _messages.StringField(4) labels = _messages.MessageField('LabelsValue', 5) name = _messages.StringField(6) source = _messages.StringField(7) updateTime = _messages.StringField(8) class GoogleCloudAiplatformV1beta1TensorboardRun(_messages.Message): r"""TensorboardRun maps to a specific execution of a training job with a given set of hyperparameter values, model definition, dataset, etc Messages: LabelsValue: The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Fields: createTime: Output only. Timestamp when this TensorboardRun was created. description: Description of this TensorboardRun. displayName: Required. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment. etag: Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens. labels: The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. name: Output only. Name of the TensorboardRun. Format: `projects/{project} /locations/{location}/tensorboards/{tensorboard}/experiments/{experiment }/runs/{run}` updateTime: Output only. Timestamp when this TensorboardRun was last updated. """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize your TensorboardRuns. This field will be used to filter and visualize Runs in the Tensorboard UI. For example, a Vertex AI training job can set a label aiplatform.googleapis.com/training_job_id=xxxxx to all the runs created within that job. An end user can set a label experiment_id=xxxxx for all the runs produced in a Jupyter notebook. These runs can be grouped by a label value and visualized together in the Tensorboard UI. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. No more than 64 user labels can be associated with one TensorboardRun (System labels are excluded). See https://goo.gl/xmQnxf for more information and examples of labels. System reserved label keys are prefixed with "aiplatform.googleapis.com/" and are immutable. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) description = _messages.StringField(2) displayName = _messages.StringField(3) etag = _messages.StringField(4) labels = _messages.MessageField('LabelsValue', 5) name = _messages.StringField(6) updateTime = _messages.StringField(7) class GoogleCloudAiplatformV1beta1TensorboardTensor(_messages.Message): r"""One point viewable on a tensor metric plot. Fields: value: Required. Serialized form of https://github.com/tensorflow/tensorfl ow/blob/master/tensorflow/core/framework/tensor.proto versionNumber: Optional. Version number of TensorProto used to serialize value. """ value = _messages.BytesField(1) versionNumber = _messages.IntegerField(2, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1TensorboardTimeSeries(_messages.Message): r"""TensorboardTimeSeries maps to times series produced in training runs Enums: ValueTypeValueValuesEnum: Required. Immutable. Type of TensorboardTimeSeries value. Fields: createTime: Output only. Timestamp when this TensorboardTimeSeries was created. description: Description of this TensorboardTimeSeries. displayName: Required. User provided name of this TensorboardTimeSeries. This value should be unique among all TensorboardTimeSeries resources belonging to the same TensorboardRun resource (parent resource). etag: Used to perform a consistent read-modify-write updates. If not set, a blind "overwrite" update happens. metadata: Output only. Scalar, Tensor, or Blob metadata for this TensorboardTimeSeries. name: Output only. Name of the TensorboardTimeSeries. pluginData: Data of the current plugin, with the size limited to 65KB. pluginName: Immutable. Name of the plugin this time series pertain to. Such as Scalar, Tensor, Blob updateTime: Output only. Timestamp when this TensorboardTimeSeries was last updated. valueType: Required. Immutable. Type of TensorboardTimeSeries value. """ class ValueTypeValueValuesEnum(_messages.Enum): r"""Required. Immutable. Type of TensorboardTimeSeries value. Values: VALUE_TYPE_UNSPECIFIED: The value type is unspecified. SCALAR: Used for TensorboardTimeSeries that is a list of scalars. E.g. accuracy of a model over epochs/time. TENSOR: Used for TensorboardTimeSeries that is a list of tensors. E.g. histograms of weights of layer in a model over epoch/time. BLOB_SEQUENCE: Used for TensorboardTimeSeries that is a list of blob sequences. E.g. set of sample images with labels over epochs/time. """ VALUE_TYPE_UNSPECIFIED = 0 SCALAR = 1 TENSOR = 2 BLOB_SEQUENCE = 3 createTime = _messages.StringField(1) description = _messages.StringField(2) displayName = _messages.StringField(3) etag = _messages.StringField(4) metadata = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardTimeSeriesMetadata', 5) name = _messages.StringField(6) pluginData = _messages.BytesField(7) pluginName = _messages.StringField(8) updateTime = _messages.StringField(9) valueType = _messages.EnumField('ValueTypeValueValuesEnum', 10) class GoogleCloudAiplatformV1beta1TensorboardTimeSeriesMetadata(_messages.Message): r"""Describes metadata for a TensorboardTimeSeries. Fields: maxBlobSequenceLength: Output only. The largest blob sequence length (number of blobs) of all data points in this time series, if its ValueType is BLOB_SEQUENCE. maxStep: Output only. Max step index of all data points within a TensorboardTimeSeries. maxWallTime: Output only. Max wall clock timestamp of all data points within a TensorboardTimeSeries. """ maxBlobSequenceLength = _messages.IntegerField(1) maxStep = _messages.IntegerField(2) maxWallTime = _messages.StringField(3) class GoogleCloudAiplatformV1beta1ThresholdConfig(_messages.Message): r"""The config for feature monitoring threshold. Fields: value: Specify a threshold value that can trigger the alert. If this threshold config is for feature distribution distance: 1. For categorical feature, the distribution distance is calculated by L-inifinity norm. 2. For numerical feature, the distribution distance is calculated by Jensen\u2013Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature. """ value = _messages.FloatField(1) class GoogleCloudAiplatformV1beta1TimeSeriesData(_messages.Message): r"""All the data stored in a TensorboardTimeSeries. Enums: ValueTypeValueValuesEnum: Required. Immutable. The value type of this time series. All the values in this time series data must match this value type. Fields: tensorboardTimeSeriesId: Required. The ID of the TensorboardTimeSeries, which will become the final component of the TensorboardTimeSeries' resource name valueType: Required. Immutable. The value type of this time series. All the values in this time series data must match this value type. values: Required. Data points in this time series. """ class ValueTypeValueValuesEnum(_messages.Enum): r"""Required. Immutable. The value type of this time series. All the values in this time series data must match this value type. Values: VALUE_TYPE_UNSPECIFIED: The value type is unspecified. SCALAR: Used for TensorboardTimeSeries that is a list of scalars. E.g. accuracy of a model over epochs/time. TENSOR: Used for TensorboardTimeSeries that is a list of tensors. E.g. histograms of weights of layer in a model over epoch/time. BLOB_SEQUENCE: Used for TensorboardTimeSeries that is a list of blob sequences. E.g. set of sample images with labels over epochs/time. """ VALUE_TYPE_UNSPECIFIED = 0 SCALAR = 1 TENSOR = 2 BLOB_SEQUENCE = 3 tensorboardTimeSeriesId = _messages.StringField(1) valueType = _messages.EnumField('ValueTypeValueValuesEnum', 2) values = _messages.MessageField('GoogleCloudAiplatformV1beta1TimeSeriesDataPoint', 3, repeated=True) class GoogleCloudAiplatformV1beta1TimeSeriesDataPoint(_messages.Message): r"""A TensorboardTimeSeries data point. Fields: blobs: A blob sequence value. scalar: A scalar value. step: Step index of this data point within the run. tensor: A tensor value. wallTime: Wall clock timestamp when this data point is generated by the end user. """ blobs = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardBlobSequence', 1) scalar = _messages.MessageField('GoogleCloudAiplatformV1beta1Scalar', 2) step = _messages.IntegerField(3) tensor = _messages.MessageField('GoogleCloudAiplatformV1beta1TensorboardTensor', 4) wallTime = _messages.StringField(5) class GoogleCloudAiplatformV1beta1TimestampSplit(_messages.Message): r"""Assigns input data to training, validation, and test sets based on a provided timestamps. The youngest data pieces are assigned to training set, next to validation set, and the oldest to the test set. Supported only for tabular Datasets. Fields: key: Required. The key is a name of one of the Dataset's data columns. The values of the key (the values in the column) must be in RFC 3339 `date- time` format, where `time-offset` = `"Z"` (e.g. 1985-04-12T23:20:50.52Z). If for a piece of data the key is not present or has an invalid value, that piece is ignored by the pipeline. testFraction: The fraction of the input data that is to be used to evaluate the Model. trainingFraction: The fraction of the input data that is to be used to train the Model. validationFraction: The fraction of the input data that is to be used to validate the Model. """ key = _messages.StringField(1) testFraction = _messages.FloatField(2) trainingFraction = _messages.FloatField(3) validationFraction = _messages.FloatField(4) class GoogleCloudAiplatformV1beta1TokensInfo(_messages.Message): r"""Tokens info with a list of tokens and the corresponding list of token ids. Fields: role: Optional. Optional fields for the role from the corresponding Content. tokenIds: A list of token ids from the input. tokens: A list of tokens from the input. """ role = _messages.StringField(1) tokenIds = _messages.IntegerField(2, repeated=True) tokens = _messages.BytesField(3, repeated=True) class GoogleCloudAiplatformV1beta1Tool(_messages.Message): r"""Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval). Fields: codeExecution: Optional. CodeExecution tool type. Enables the model to execute code as part of generation. computerUse: Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations. enterpriseWebSearch: Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance. functionDeclarations: Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided. googleMaps: Optional. GoogleMaps tool type. Tool to support Google Maps in Model. googleSearch: Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. googleSearchRetrieval: Optional. Specialized retrieval tool that is powered by Google Search. retrieval: Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation. urlContext: Optional. Tool to support URL context retrieval. """ codeExecution = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolCodeExecution', 1) computerUse = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolComputerUse', 2) enterpriseWebSearch = _messages.MessageField('GoogleCloudAiplatformV1beta1EnterpriseWebSearch', 3) functionDeclarations = _messages.MessageField('GoogleCloudAiplatformV1beta1FunctionDeclaration', 4, repeated=True) googleMaps = _messages.MessageField('GoogleCloudAiplatformV1beta1GoogleMaps', 5) googleSearch = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolGoogleSearch', 6) googleSearchRetrieval = _messages.MessageField('GoogleCloudAiplatformV1beta1GoogleSearchRetrieval', 7) retrieval = _messages.MessageField('GoogleCloudAiplatformV1beta1Retrieval', 8) urlContext = _messages.MessageField('GoogleCloudAiplatformV1beta1UrlContext', 9) class GoogleCloudAiplatformV1beta1ToolCall(_messages.Message): r"""Spec for tool call. Fields: toolInput: Optional. Spec for tool input toolName: Required. Spec for tool name """ toolInput = _messages.StringField(1) toolName = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ToolCallValidInput(_messages.Message): r"""Input for tool call valid metric. Fields: instances: Required. Repeated tool call valid instances. metricSpec: Required. Spec for tool call valid metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolCallValidInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolCallValidSpec', 2) class GoogleCloudAiplatformV1beta1ToolCallValidInstance(_messages.Message): r"""Spec for tool call valid instance. Fields: prediction: Required. Output of the evaluated model. reference: Required. Ground truth used to compare against the prediction. """ prediction = _messages.StringField(1) reference = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ToolCallValidMetricValue(_messages.Message): r"""Tool call valid metric value for an instance. Fields: score: Output only. Tool call valid score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1ToolCallValidResults(_messages.Message): r"""Results for tool call valid metric. Fields: toolCallValidMetricValues: Output only. Tool call valid metric values. """ toolCallValidMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolCallValidMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1ToolCallValidSpec(_messages.Message): r"""Spec for tool call valid metric.""" class GoogleCloudAiplatformV1beta1ToolCodeExecution(_messages.Message): r"""Tool that executes code generated by the model, and automatically returns the result to the model. See also [ExecutableCode]and [CodeExecutionResult] which are input and output to this tool. """ class GoogleCloudAiplatformV1beta1ToolComputerUse(_messages.Message): r"""Tool to support computer use. Enums: EnvironmentValueValuesEnum: Required. The environment being operated. Fields: environment: Required. The environment being operated. excludedPredefinedFunctions: Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative- ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions. """ class EnvironmentValueValuesEnum(_messages.Enum): r"""Required. The environment being operated. Values: ENVIRONMENT_UNSPECIFIED: Defaults to browser. ENVIRONMENT_BROWSER: Operates in a web browser. """ ENVIRONMENT_UNSPECIFIED = 0 ENVIRONMENT_BROWSER = 1 environment = _messages.EnumField('EnvironmentValueValuesEnum', 1) excludedPredefinedFunctions = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1ToolConfig(_messages.Message): r"""Tool config. This config is shared for all tools provided in the request. Fields: functionCallingConfig: Optional. Function calling config. retrievalConfig: Optional. Retrieval config. """ functionCallingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1FunctionCallingConfig', 1) retrievalConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RetrievalConfig', 2) class GoogleCloudAiplatformV1beta1ToolGoogleSearch(_messages.Message): r"""GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. Enums: BlockingConfidenceValueValuesEnum: Optional. Sites with confidence level chosen & above this value will be blocked from the search results. Fields: blockingConfidence: Optional. Sites with confidence level chosen & above this value will be blocked from the search results. excludeDomains: Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"]. """ class BlockingConfidenceValueValuesEnum(_messages.Enum): r"""Optional. Sites with confidence level chosen & above this value will be blocked from the search results. Values: PHISH_BLOCK_THRESHOLD_UNSPECIFIED: Defaults to unspecified. BLOCK_LOW_AND_ABOVE: Blocks Low and above confidence URL that is risky. BLOCK_MEDIUM_AND_ABOVE: Blocks Medium and above confidence URL that is risky. BLOCK_HIGH_AND_ABOVE: Blocks High and above confidence URL that is risky. BLOCK_HIGHER_AND_ABOVE: Blocks Higher and above confidence URL that is risky. BLOCK_VERY_HIGH_AND_ABOVE: Blocks Very high and above confidence URL that is risky. BLOCK_ONLY_EXTREMELY_HIGH: Blocks Extremely high confidence URL that is risky. """ PHISH_BLOCK_THRESHOLD_UNSPECIFIED = 0 BLOCK_LOW_AND_ABOVE = 1 BLOCK_MEDIUM_AND_ABOVE = 2 BLOCK_HIGH_AND_ABOVE = 3 BLOCK_HIGHER_AND_ABOVE = 4 BLOCK_VERY_HIGH_AND_ABOVE = 5 BLOCK_ONLY_EXTREMELY_HIGH = 6 blockingConfidence = _messages.EnumField('BlockingConfidenceValueValuesEnum', 1) excludeDomains = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1ToolNameMatchInput(_messages.Message): r"""Input for tool name match metric. Fields: instances: Required. Repeated tool name match instances. metricSpec: Required. Spec for tool name match metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolNameMatchInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolNameMatchSpec', 2) class GoogleCloudAiplatformV1beta1ToolNameMatchInstance(_messages.Message): r"""Spec for tool name match instance. Fields: prediction: Required. Output of the evaluated model. reference: Required. Ground truth used to compare against the prediction. """ prediction = _messages.StringField(1) reference = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ToolNameMatchMetricValue(_messages.Message): r"""Tool name match metric value for an instance. Fields: score: Output only. Tool name match score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1ToolNameMatchResults(_messages.Message): r"""Results for tool name match metric. Fields: toolNameMatchMetricValues: Output only. Tool name match metric values. """ toolNameMatchMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolNameMatchMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1ToolNameMatchSpec(_messages.Message): r"""Spec for tool name match metric.""" class GoogleCloudAiplatformV1beta1ToolParameterKVMatchInput(_messages.Message): r"""Input for tool parameter key value match metric. Fields: instances: Required. Repeated tool parameter key value match instances. metricSpec: Required. Spec for tool parameter key value match metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolParameterKVMatchInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolParameterKVMatchSpec', 2) class GoogleCloudAiplatformV1beta1ToolParameterKVMatchInstance(_messages.Message): r"""Spec for tool parameter key value match instance. Fields: prediction: Required. Output of the evaluated model. reference: Required. Ground truth used to compare against the prediction. """ prediction = _messages.StringField(1) reference = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ToolParameterKVMatchMetricValue(_messages.Message): r"""Tool parameter key value match metric value for an instance. Fields: score: Output only. Tool parameter key value match score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1ToolParameterKVMatchResults(_messages.Message): r"""Results for tool parameter key value match metric. Fields: toolParameterKvMatchMetricValues: Output only. Tool parameter key value match metric values. """ toolParameterKvMatchMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolParameterKVMatchMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1ToolParameterKVMatchSpec(_messages.Message): r"""Spec for tool parameter key value match metric. Fields: useStrictStringMatch: Optional. Whether to use STRICT string match on parameter values. """ useStrictStringMatch = _messages.BooleanField(1) class GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInput(_messages.Message): r"""Input for tool parameter key match metric. Fields: instances: Required. Repeated tool parameter key match instances. metricSpec: Required. Spec for tool parameter key match metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolParameterKeyMatchSpec', 2) class GoogleCloudAiplatformV1beta1ToolParameterKeyMatchInstance(_messages.Message): r"""Spec for tool parameter key match instance. Fields: prediction: Required. Output of the evaluated model. reference: Required. Ground truth used to compare against the prediction. """ prediction = _messages.StringField(1) reference = _messages.StringField(2) class GoogleCloudAiplatformV1beta1ToolParameterKeyMatchMetricValue(_messages.Message): r"""Tool parameter key match metric value for an instance. Fields: score: Output only. Tool parameter key match score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1ToolParameterKeyMatchResults(_messages.Message): r"""Results for tool parameter key match metric. Fields: toolParameterKeyMatchMetricValues: Output only. Tool parameter key match metric values. """ toolParameterKeyMatchMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolParameterKeyMatchMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1ToolParameterKeyMatchSpec(_messages.Message): r"""Spec for tool parameter key match metric.""" class GoogleCloudAiplatformV1beta1ToolUseExample(_messages.Message): r"""A single example of the tool usage. Messages: RequestParamsValue: Request parameters used for executing this tool. ResponseParamsValue: Response parameters generated by this tool. Fields: displayName: Required. The display name for example. extensionOperation: Extension operation to call. functionName: Function name to call. query: Required. Query that should be routed to this tool. requestParams: Request parameters used for executing this tool. responseParams: Response parameters generated by this tool. responseSummary: Summary of the tool response to the user query. """ @encoding.MapUnrecognizedFields('additionalProperties') class RequestParamsValue(_messages.Message): r"""Request parameters used for executing this tool. Messages: AdditionalProperty: An additional property for a RequestParamsValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a RequestParamsValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class ResponseParamsValue(_messages.Message): r"""Response parameters generated by this tool. Messages: AdditionalProperty: An additional property for a ResponseParamsValue object. Fields: additionalProperties: Properties of the object. """ class AdditionalProperty(_messages.Message): r"""An additional property for a ResponseParamsValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) displayName = _messages.StringField(1) extensionOperation = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolUseExampleExtensionOperation', 2) functionName = _messages.StringField(3) query = _messages.StringField(4) requestParams = _messages.MessageField('RequestParamsValue', 5) responseParams = _messages.MessageField('ResponseParamsValue', 6) responseSummary = _messages.StringField(7) class GoogleCloudAiplatformV1beta1ToolUseExampleExtensionOperation(_messages.Message): r"""Identifies one operation of the extension. Fields: extension: Resource name of the extension. operationId: Required. Operation ID of the extension. """ extension = _messages.StringField(1) operationId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1TrainingConfig(_messages.Message): r"""CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems. Fields: timeoutTrainingMilliHours: The timeout hours for the CMLE training job, expressed in milli hours i.e. 1,000 value in this field means 1 hour. """ timeoutTrainingMilliHours = _messages.IntegerField(1) class GoogleCloudAiplatformV1beta1TrainingPipeline(_messages.Message): r"""The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model. Enums: StateValueValuesEnum: Output only. The detailed state of the pipeline. Messages: LabelsValue: The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: createTime: Output only. Time when the TrainingPipeline was created. displayName: Required. The user-defined name of this TrainingPipeline. encryptionSpec: Customer-managed encryption key spec for a TrainingPipeline. If set, this TrainingPipeline will be secured by this key. Note: Model trained by this TrainingPipeline is also secured by this key if model_to_upload is not set separately. endTime: Output only. Time when the TrainingPipeline entered any of the following states: `PIPELINE_STATE_SUCCEEDED`, `PIPELINE_STATE_FAILED`, `PIPELINE_STATE_CANCELLED`. error: Output only. Only populated when the pipeline's state is `PIPELINE_STATE_FAILED` or `PIPELINE_STATE_CANCELLED`. inputDataConfig: Specifies Vertex AI owned input data that may be used for training the Model. The TrainingPipeline's training_task_definition should make clear whether this config is used and if there are any special requirements on how it should be filled. If nothing about this config is mentioned in the training_task_definition, then it should be assumed that the TrainingPipeline does not depend on this configuration. labels: The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. modelId: Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen. modelToUpload: Describes the Model that may be uploaded (via ModelService.UploadModel) by this TrainingPipeline. The TrainingPipeline's training_task_definition should make clear whether this Model description should be populated, and if there are any special requirements regarding how it should be filled. If nothing is mentioned in the training_task_definition, then it should be assumed that this field should not be filled and the training task either uploads the Model without a need of this information, or that training task does not support uploading a Model as part of the pipeline. When the Pipeline's state becomes `PIPELINE_STATE_SUCCEEDED` and the trained Model had been uploaded into Vertex AI, then the model_to_upload's resource name is populated. The Model is always uploaded into the Project and Location in which this pipeline is. name: Output only. Resource name of the TrainingPipeline. parentModel: Optional. When specify this field, the `model_to_upload` will not be uploaded as a new model, instead, it will become a new version of this `parent_model`. startTime: Output only. Time when the TrainingPipeline for the first time entered the `PIPELINE_STATE_RUNNING` state. state: Output only. The detailed state of the pipeline. trainingTaskDefinition: Required. A Google Cloud Storage path to the YAML file that defines the training task which is responsible for producing the model artifact, and may also include additional auxiliary work. The definition files that can be used here are found in gs://google-cloud- aiplatform/schema/trainingjob/definition/. Note: The URI given on output will be immutable and probably different, including the URI scheme, than the one given on input. The output URI will point to a location where the user only has a read access. trainingTaskInputs: Required. The training task's parameter(s), as specified in the training_task_definition's `inputs`. trainingTaskMetadata: Output only. The metadata information as specified in the training_task_definition's `metadata`. This metadata is an auxiliary runtime and final information about the training task. While the pipeline is running this information is populated only at a best effort basis. Only present if the pipeline's training_task_definition contains `metadata` object. updateTime: Output only. Time when the TrainingPipeline was most recently updated. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of the pipeline. Values: PIPELINE_STATE_UNSPECIFIED: The pipeline state is unspecified. PIPELINE_STATE_QUEUED: The pipeline has been created or resumed, and processing has not yet begun. PIPELINE_STATE_PENDING: The service is preparing to run the pipeline. PIPELINE_STATE_RUNNING: The pipeline is in progress. PIPELINE_STATE_SUCCEEDED: The pipeline completed successfully. PIPELINE_STATE_FAILED: The pipeline failed. PIPELINE_STATE_CANCELLING: The pipeline is being cancelled. From this state, the pipeline may only go to either PIPELINE_STATE_SUCCEEDED, PIPELINE_STATE_FAILED or PIPELINE_STATE_CANCELLED. PIPELINE_STATE_CANCELLED: The pipeline has been cancelled. PIPELINE_STATE_PAUSED: The pipeline has been stopped, and can be resumed. """ PIPELINE_STATE_UNSPECIFIED = 0 PIPELINE_STATE_QUEUED = 1 PIPELINE_STATE_PENDING = 2 PIPELINE_STATE_RUNNING = 3 PIPELINE_STATE_SUCCEEDED = 4 PIPELINE_STATE_FAILED = 5 PIPELINE_STATE_CANCELLING = 6 PIPELINE_STATE_CANCELLED = 7 PIPELINE_STATE_PAUSED = 8 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""The labels with user-defined metadata to organize TrainingPipelines. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) createTime = _messages.StringField(1) displayName = _messages.StringField(2) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 3) endTime = _messages.StringField(4) error = _messages.MessageField('GoogleRpcStatus', 5) inputDataConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1InputDataConfig', 6) labels = _messages.MessageField('LabelsValue', 7) modelId = _messages.StringField(8) modelToUpload = _messages.MessageField('GoogleCloudAiplatformV1beta1Model', 9) name = _messages.StringField(10) parentModel = _messages.StringField(11) startTime = _messages.StringField(12) state = _messages.EnumField('StateValueValuesEnum', 13) trainingTaskDefinition = _messages.StringField(14) trainingTaskInputs = _messages.MessageField('extra_types.JsonValue', 15) trainingTaskMetadata = _messages.MessageField('extra_types.JsonValue', 16) updateTime = _messages.StringField(17) class GoogleCloudAiplatformV1beta1Trajectory(_messages.Message): r"""Spec for trajectory. Fields: toolCalls: Required. Tool calls in the trajectory. """ toolCalls = _messages.MessageField('GoogleCloudAiplatformV1beta1ToolCall', 1, repeated=True) class GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchInput(_messages.Message): r"""Instances and metric spec for TrajectoryAnyOrderMatch metric. Fields: instances: Required. Repeated TrajectoryAnyOrderMatch instance. metricSpec: Required. Spec for TrajectoryAnyOrderMatch metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchSpec', 2) class GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchInstance(_messages.Message): r"""Spec for TrajectoryAnyOrderMatch instance. Fields: predictedTrajectory: Required. Spec for predicted tool call trajectory. referenceTrajectory: Required. Spec for reference tool call trajectory. """ predictedTrajectory = _messages.MessageField('GoogleCloudAiplatformV1beta1Trajectory', 1) referenceTrajectory = _messages.MessageField('GoogleCloudAiplatformV1beta1Trajectory', 2) class GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchMetricValue(_messages.Message): r"""TrajectoryAnyOrderMatch metric value for an instance. Fields: score: Output only. TrajectoryAnyOrderMatch score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchResults(_messages.Message): r"""Results for TrajectoryAnyOrderMatch metric. Fields: trajectoryAnyOrderMatchMetricValues: Output only. TrajectoryAnyOrderMatch metric values. """ trajectoryAnyOrderMatchMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1TrajectoryAnyOrderMatchSpec(_messages.Message): r"""Spec for TrajectoryAnyOrderMatch metric - returns 1 if all tool calls in the reference trajectory appear in the predicted trajectory in any order, else 0. """ class GoogleCloudAiplatformV1beta1TrajectoryExactMatchInput(_messages.Message): r"""Instances and metric spec for TrajectoryExactMatch metric. Fields: instances: Required. Repeated TrajectoryExactMatch instance. metricSpec: Required. Spec for TrajectoryExactMatch metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryExactMatchInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryExactMatchSpec', 2) class GoogleCloudAiplatformV1beta1TrajectoryExactMatchInstance(_messages.Message): r"""Spec for TrajectoryExactMatch instance. Fields: predictedTrajectory: Required. Spec for predicted tool call trajectory. referenceTrajectory: Required. Spec for reference tool call trajectory. """ predictedTrajectory = _messages.MessageField('GoogleCloudAiplatformV1beta1Trajectory', 1) referenceTrajectory = _messages.MessageField('GoogleCloudAiplatformV1beta1Trajectory', 2) class GoogleCloudAiplatformV1beta1TrajectoryExactMatchMetricValue(_messages.Message): r"""TrajectoryExactMatch metric value for an instance. Fields: score: Output only. TrajectoryExactMatch score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1TrajectoryExactMatchResults(_messages.Message): r"""Results for TrajectoryExactMatch metric. Fields: trajectoryExactMatchMetricValues: Output only. TrajectoryExactMatch metric values. """ trajectoryExactMatchMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryExactMatchMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1TrajectoryExactMatchSpec(_messages.Message): r"""Spec for TrajectoryExactMatch metric - returns 1 if tool calls in the reference trajectory exactly match the predicted trajectory, else 0. """ class GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchInput(_messages.Message): r"""Instances and metric spec for TrajectoryInOrderMatch metric. Fields: instances: Required. Repeated TrajectoryInOrderMatch instance. metricSpec: Required. Spec for TrajectoryInOrderMatch metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchSpec', 2) class GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchInstance(_messages.Message): r"""Spec for TrajectoryInOrderMatch instance. Fields: predictedTrajectory: Required. Spec for predicted tool call trajectory. referenceTrajectory: Required. Spec for reference tool call trajectory. """ predictedTrajectory = _messages.MessageField('GoogleCloudAiplatformV1beta1Trajectory', 1) referenceTrajectory = _messages.MessageField('GoogleCloudAiplatformV1beta1Trajectory', 2) class GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchMetricValue(_messages.Message): r"""TrajectoryInOrderMatch metric value for an instance. Fields: score: Output only. TrajectoryInOrderMatch score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchResults(_messages.Message): r"""Results for TrajectoryInOrderMatch metric. Fields: trajectoryInOrderMatchMetricValues: Output only. TrajectoryInOrderMatch metric values. """ trajectoryInOrderMatchMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1TrajectoryInOrderMatchSpec(_messages.Message): r"""Spec for TrajectoryInOrderMatch metric - returns 1 if tool calls in the reference trajectory appear in the predicted trajectory in the same order, else 0. """ class GoogleCloudAiplatformV1beta1TrajectoryPrecisionInput(_messages.Message): r"""Instances and metric spec for TrajectoryPrecision metric. Fields: instances: Required. Repeated TrajectoryPrecision instance. metricSpec: Required. Spec for TrajectoryPrecision metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryPrecisionInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryPrecisionSpec', 2) class GoogleCloudAiplatformV1beta1TrajectoryPrecisionInstance(_messages.Message): r"""Spec for TrajectoryPrecision instance. Fields: predictedTrajectory: Required. Spec for predicted tool call trajectory. referenceTrajectory: Required. Spec for reference tool call trajectory. """ predictedTrajectory = _messages.MessageField('GoogleCloudAiplatformV1beta1Trajectory', 1) referenceTrajectory = _messages.MessageField('GoogleCloudAiplatformV1beta1Trajectory', 2) class GoogleCloudAiplatformV1beta1TrajectoryPrecisionMetricValue(_messages.Message): r"""TrajectoryPrecision metric value for an instance. Fields: score: Output only. TrajectoryPrecision score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1TrajectoryPrecisionResults(_messages.Message): r"""Results for TrajectoryPrecision metric. Fields: trajectoryPrecisionMetricValues: Output only. TrajectoryPrecision metric values. """ trajectoryPrecisionMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryPrecisionMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1TrajectoryPrecisionSpec(_messages.Message): r"""Spec for TrajectoryPrecision metric - returns a float score based on average precision of individual tool calls. """ class GoogleCloudAiplatformV1beta1TrajectoryRecallInput(_messages.Message): r"""Instances and metric spec for TrajectoryRecall metric. Fields: instances: Required. Repeated TrajectoryRecall instance. metricSpec: Required. Spec for TrajectoryRecall metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryRecallInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryRecallSpec', 2) class GoogleCloudAiplatformV1beta1TrajectoryRecallInstance(_messages.Message): r"""Spec for TrajectoryRecall instance. Fields: predictedTrajectory: Required. Spec for predicted tool call trajectory. referenceTrajectory: Required. Spec for reference tool call trajectory. """ predictedTrajectory = _messages.MessageField('GoogleCloudAiplatformV1beta1Trajectory', 1) referenceTrajectory = _messages.MessageField('GoogleCloudAiplatformV1beta1Trajectory', 2) class GoogleCloudAiplatformV1beta1TrajectoryRecallMetricValue(_messages.Message): r"""TrajectoryRecall metric value for an instance. Fields: score: Output only. TrajectoryRecall score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1TrajectoryRecallResults(_messages.Message): r"""Results for TrajectoryRecall metric. Fields: trajectoryRecallMetricValues: Output only. TrajectoryRecall metric values. """ trajectoryRecallMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectoryRecallMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1TrajectoryRecallSpec(_messages.Message): r"""Spec for TrajectoryRecall metric - returns a float score based on average recall of individual tool calls. """ class GoogleCloudAiplatformV1beta1TrajectorySingleToolUseInput(_messages.Message): r"""Instances and metric spec for TrajectorySingleToolUse metric. Fields: instances: Required. Repeated TrajectorySingleToolUse instance. metricSpec: Required. Spec for TrajectorySingleToolUse metric. """ instances = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectorySingleToolUseInstance', 1, repeated=True) metricSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectorySingleToolUseSpec', 2) class GoogleCloudAiplatformV1beta1TrajectorySingleToolUseInstance(_messages.Message): r"""Spec for TrajectorySingleToolUse instance. Fields: predictedTrajectory: Required. Spec for predicted tool call trajectory. """ predictedTrajectory = _messages.MessageField('GoogleCloudAiplatformV1beta1Trajectory', 1) class GoogleCloudAiplatformV1beta1TrajectorySingleToolUseMetricValue(_messages.Message): r"""TrajectorySingleToolUse metric value for an instance. Fields: score: Output only. TrajectorySingleToolUse score. """ score = _messages.FloatField(1, variant=_messages.Variant.FLOAT) class GoogleCloudAiplatformV1beta1TrajectorySingleToolUseResults(_messages.Message): r"""Results for TrajectorySingleToolUse metric. Fields: trajectorySingleToolUseMetricValues: Output only. TrajectorySingleToolUse metric values. """ trajectorySingleToolUseMetricValues = _messages.MessageField('GoogleCloudAiplatformV1beta1TrajectorySingleToolUseMetricValue', 1, repeated=True) class GoogleCloudAiplatformV1beta1TrajectorySingleToolUseSpec(_messages.Message): r"""Spec for TrajectorySingleToolUse metric - returns 1 if tool is present in the predicted trajectory, else 0. Fields: toolName: Required. Spec for tool name to be checked for in the predicted trajectory. """ toolName = _messages.StringField(1) class GoogleCloudAiplatformV1beta1Trial(_messages.Message): r"""A message representing a Trial. A Trial contains a unique set of Parameters that has been or will be evaluated, along with the objective metrics got by running the Trial. Enums: StateValueValuesEnum: Output only. The detailed state of the Trial. Messages: WebAccessUrisValue: Output only. URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug- interactive-shell) (one URI for each training node). Only available if this trial is part of a HyperparameterTuningJob and the job's trial_job_spec.enable_web_access field is `true`. The keys are names of each node used for the trial; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell. Fields: clientId: Output only. The identifier of the client that originally requested this Trial. Each client is identified by a unique client_id. When a client asks for a suggestion, Vertex AI Vizier will assign it a Trial. The client should evaluate the Trial, complete it, and report back to Vertex AI Vizier. If suggestion is asked again by same client_id before the Trial is completed, the same Trial will be returned. Multiple clients with different client_ids can ask for suggestions simultaneously, each of them will get their own Trial. customJob: Output only. The CustomJob name linked to the Trial. It's set for a HyperparameterTuningJob's Trial. endTime: Output only. Time when the Trial's status changed to `SUCCEEDED` or `INFEASIBLE`. finalMeasurement: Output only. The final measurement containing the objective value. id: Output only. The identifier of the Trial assigned by the service. infeasibleReason: Output only. A human readable string describing why the Trial is infeasible. This is set only if Trial state is `INFEASIBLE`. measurements: Output only. A list of measurements that are strictly lexicographically ordered by their induced tuples (steps, elapsed_duration). These are used for early stopping computations. name: Output only. Resource name of the Trial assigned by the service. parameters: Output only. The parameters of the Trial. startTime: Output only. Time when the Trial was started. state: Output only. The detailed state of the Trial. webAccessUris: Output only. URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug- interactive-shell) (one URI for each training node). Only available if this trial is part of a HyperparameterTuningJob and the job's trial_job_spec.enable_web_access field is `true`. The keys are names of each node used for the trial; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of the Trial. Values: STATE_UNSPECIFIED: The Trial state is unspecified. REQUESTED: Indicates that a specific Trial has been requested, but it has not yet been suggested by the service. ACTIVE: Indicates that the Trial has been suggested. STOPPING: Indicates that the Trial should stop according to the service. SUCCEEDED: Indicates that the Trial is completed successfully. INFEASIBLE: Indicates that the Trial should not be attempted again. The service will set a Trial to INFEASIBLE when it's done but missing the final_measurement. """ STATE_UNSPECIFIED = 0 REQUESTED = 1 ACTIVE = 2 STOPPING = 3 SUCCEEDED = 4 INFEASIBLE = 5 @encoding.MapUnrecognizedFields('additionalProperties') class WebAccessUrisValue(_messages.Message): r"""Output only. URIs for accessing [interactive shells](https://cloud.google.com/vertex-ai/docs/training/monitor-debug- interactive-shell) (one URI for each training node). Only available if this trial is part of a HyperparameterTuningJob and the job's trial_job_spec.enable_web_access field is `true`. The keys are names of each node used for the trial; for example, `workerpool0-0` for the primary node, `workerpool1-0` for the first node in the second worker pool, and `workerpool1-1` for the second node in the second worker pool. The values are the URIs for each node's interactive shell. Messages: AdditionalProperty: An additional property for a WebAccessUrisValue object. Fields: additionalProperties: Additional properties of type WebAccessUrisValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a WebAccessUrisValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) clientId = _messages.StringField(1) customJob = _messages.StringField(2) endTime = _messages.StringField(3) finalMeasurement = _messages.MessageField('GoogleCloudAiplatformV1beta1Measurement', 4) id = _messages.StringField(5) infeasibleReason = _messages.StringField(6) measurements = _messages.MessageField('GoogleCloudAiplatformV1beta1Measurement', 7, repeated=True) name = _messages.StringField(8) parameters = _messages.MessageField('GoogleCloudAiplatformV1beta1TrialParameter', 9, repeated=True) startTime = _messages.StringField(10) state = _messages.EnumField('StateValueValuesEnum', 11) webAccessUris = _messages.MessageField('WebAccessUrisValue', 12) class GoogleCloudAiplatformV1beta1TrialContext(_messages.Message): r"""A GoogleCloudAiplatformV1beta1TrialContext object. Fields: description: A human-readable field which can store a description of this context. This will become part of the resulting Trial's description field. parameters: If/when a Trial is generated or selected from this Context, its Parameters will match any parameters specified here. (I.e. if this context specifies parameter name:'a' int_value:3, then a resulting Trial will have int_value:3 for its parameter named 'a'.) Note that we first attempt to match existing REQUESTED Trials with contexts, and if there are no matches, we generate suggestions in the subspace defined by the parameters specified here. NOTE: a Context without any Parameters matches the entire feasible search space. """ description = _messages.StringField(1) parameters = _messages.MessageField('GoogleCloudAiplatformV1beta1TrialParameter', 2, repeated=True) class GoogleCloudAiplatformV1beta1TrialParameter(_messages.Message): r"""A message representing a parameter to be tuned. Fields: parameterId: Output only. The ID of the parameter. The parameter should be defined in StudySpec's Parameters. value: Output only. The value of the parameter. `number_value` will be set if a parameter defined in StudySpec is in type 'INTEGER', 'DOUBLE' or 'DISCRETE'. `string_value` will be set if a parameter defined in StudySpec is in type 'CATEGORICAL'. """ parameterId = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) class GoogleCloudAiplatformV1beta1TunedModel(_messages.Message): r"""The Model Registry Model and Online Prediction Endpoint associated with this TuningJob. Fields: checkpoints: Output only. The checkpoints associated with this TunedModel. This field is only populated for tuning jobs that enable intermediate checkpoints. endpoint: Output only. A resource name of an Endpoint. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`. model: Output only. The resource name of the TunedModel. Format: `projects/{project}/locations/{location}/models/{model}@{version_id}` When tuning from a base model, the version ID will be 1. For continuous tuning, if the provided tuned_model_display_name is set and different from parent model's display name, the tuned model will have a new parent model with version 1. Otherwise the version id will be incremented by 1 from the last version ID in the parent model. E.g., `projects/{project}/locations/{location}/models/{model}@{last_version_id + 1}` """ checkpoints = _messages.MessageField('GoogleCloudAiplatformV1beta1TunedModelCheckpoint', 1, repeated=True) endpoint = _messages.StringField(2) model = _messages.StringField(3) class GoogleCloudAiplatformV1beta1TunedModelCheckpoint(_messages.Message): r"""TunedModelCheckpoint for the Tuned Model of a Tuning Job. Fields: checkpointId: The ID of the checkpoint. endpoint: The Endpoint resource name that the checkpoint is deployed to. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`. epoch: The epoch of the checkpoint. step: The step of the checkpoint. """ checkpointId = _messages.StringField(1) endpoint = _messages.StringField(2) epoch = _messages.IntegerField(3) step = _messages.IntegerField(4) class GoogleCloudAiplatformV1beta1TunedModelRef(_messages.Message): r"""TunedModel Reference for legacy model migration. Fields: pipelineJob: Support migration from tuning job list page, from bison model to gemini model. tunedModel: Support migration from model registry. tuningJob: Support migration from tuning job list page, from gemini-1.0-pro-002 to 1.5 and above. """ pipelineJob = _messages.StringField(1) tunedModel = _messages.StringField(2) tuningJob = _messages.StringField(3) class GoogleCloudAiplatformV1beta1TuningDataStats(_messages.Message): r"""The tuning data statistic values for TuningJob. Fields: distillationDataStats: Output only. Statistics for distillation. preferenceOptimizationDataStats: Output only. Statistics for preference optimization. supervisedTuningDataStats: The SFT Tuning data stats. """ distillationDataStats = _messages.MessageField('GoogleCloudAiplatformV1beta1DistillationDataStats', 1) preferenceOptimizationDataStats = _messages.MessageField('GoogleCloudAiplatformV1beta1PreferenceOptimizationDataStats', 2) supervisedTuningDataStats = _messages.MessageField('GoogleCloudAiplatformV1beta1SupervisedTuningDataStats', 3) class GoogleCloudAiplatformV1beta1TuningJob(_messages.Message): r"""Represents a TuningJob that runs with Google owned models. Enums: StateValueValuesEnum: Output only. The detailed state of the job. TuningJobStateValueValuesEnum: Output only. The detail state of the tuning job (while the overall `JobState` is running). Messages: LabelsValue: Optional. The labels with user-defined metadata to organize TuningJob and generated resources such as Model and Endpoint. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Fields: baseModel: The base model that is being tuned. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model- reference/tuning#supported_models). createTime: Output only. Time when the TuningJob was created. customBaseModel: Optional. The user-provided path to custom model weights. Set this field to tune a custom model. The path must be a Cloud Storage directory that contains the model weights in .safetensors format along with associated model metadata files. If this field is set, the base_model field must still be set to indicate which base model the custom model is derived from. This feature is only available for open source models. description: Optional. The description of the TuningJob. distillationSpec: Tuning Spec for Distillation. encryptionSpec: Customer-managed encryption key options for a TuningJob. If this is set, then all resources created by the TuningJob will be encrypted with the provided encryption key. endTime: Output only. Time when the TuningJob entered any of the following JobStates: `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED`, `JOB_STATE_CANCELLED`, `JOB_STATE_EXPIRED`. error: Output only. Only populated when job's state is `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. evaluateDatasetRuns: Output only. Evaluation runs for the Tuning Job. experiment: Output only. The Experiment associated with this TuningJob. fullFineTuningSpec: Tuning Spec for Full Fine Tuning. labels: Optional. The labels with user-defined metadata to organize TuningJob and generated resources such as Model and Endpoint. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. name: Output only. Identifier. Resource name of a TuningJob. Format: `projects/{project}/locations/{location}/tuningJobs/{tuning_job}` outputUri: Optional. Cloud Storage path to the directory where tuning job outputs are written to. This field is only available and required for open source models. partnerModelTuningSpec: Tuning Spec for open sourced and third party Partner models. pipelineJob: Output only. The resource name of the PipelineJob associated with the TuningJob. Format: `projects/{project}/locations/{location}/pipelineJobs/{pipeline_job}`. preTunedModel: The pre-tuned model for continuous tuning. preferenceOptimizationSpec: Tuning Spec for Preference Optimization. satisfiesPzi: Output only. Reserved for future use. satisfiesPzs: Output only. Reserved for future use. serviceAccount: The service account that the tuningJob workload runs as. If not specified, the Vertex AI Secure Fine-Tuned Service Agent in the project will be used. See https://cloud.google.com/iam/docs/service- agents#vertex-ai-secure-fine-tuning-service-agent Users starting the pipeline must have the `iam.serviceAccounts.actAs` permission on this service account. startTime: Output only. Time when the TuningJob for the first time entered the `JOB_STATE_RUNNING` state. state: Output only. The detailed state of the job. supervisedTuningSpec: Tuning Spec for Supervised Fine Tuning. tunedModel: Output only. The tuned model resources associated with this TuningJob. tunedModelDisplayName: Optional. The display name of the TunedModel. The name can be up to 128 characters long and can consist of any UTF-8 characters. For continuous tuning, tuned_model_display_name will by default use the same display name as the pre-tuned model. If a new display name is provided, the tuning job will create a new model instead of a new version. tuningDataStats: Output only. The tuning data statistics associated with this TuningJob. tuningJobState: Output only. The detail state of the tuning job (while the overall `JobState` is running). updateTime: Output only. Time when the TuningJob was most recently updated. veoTuningSpec: Tuning Spec for Veo Tuning. """ class StateValueValuesEnum(_messages.Enum): r"""Output only. The detailed state of the job. Values: JOB_STATE_UNSPECIFIED: The job state is unspecified. JOB_STATE_QUEUED: The job has been just created or resumed and processing has not yet begun. JOB_STATE_PENDING: The service is preparing to run the job. JOB_STATE_RUNNING: The job is in progress. JOB_STATE_SUCCEEDED: The job completed successfully. JOB_STATE_FAILED: The job failed. JOB_STATE_CANCELLING: The job is being cancelled. From this state the job may only go to either `JOB_STATE_SUCCEEDED`, `JOB_STATE_FAILED` or `JOB_STATE_CANCELLED`. JOB_STATE_CANCELLED: The job has been cancelled. JOB_STATE_PAUSED: The job has been stopped, and can be resumed. JOB_STATE_EXPIRED: The job has expired. JOB_STATE_UPDATING: The job is being updated. Only jobs in the `RUNNING` state can be updated. After updating, the job goes back to the `RUNNING` state. JOB_STATE_PARTIALLY_SUCCEEDED: The job is partially succeeded, some results may be missing due to errors. """ JOB_STATE_UNSPECIFIED = 0 JOB_STATE_QUEUED = 1 JOB_STATE_PENDING = 2 JOB_STATE_RUNNING = 3 JOB_STATE_SUCCEEDED = 4 JOB_STATE_FAILED = 5 JOB_STATE_CANCELLING = 6 JOB_STATE_CANCELLED = 7 JOB_STATE_PAUSED = 8 JOB_STATE_EXPIRED = 9 JOB_STATE_UPDATING = 10 JOB_STATE_PARTIALLY_SUCCEEDED = 11 class TuningJobStateValueValuesEnum(_messages.Enum): r"""Output only. The detail state of the tuning job (while the overall `JobState` is running). Values: TUNING_JOB_STATE_UNSPECIFIED: Default tuning job state. TUNING_JOB_STATE_WAITING_FOR_QUOTA: Tuning job is waiting for job quota. TUNING_JOB_STATE_PROCESSING_DATASET: Tuning job is validating the dataset. TUNING_JOB_STATE_WAITING_FOR_CAPACITY: Tuning job is waiting for hardware capacity. TUNING_JOB_STATE_TUNING: Tuning job is running. TUNING_JOB_STATE_POST_PROCESSING: Tuning job is doing some post processing steps. """ TUNING_JOB_STATE_UNSPECIFIED = 0 TUNING_JOB_STATE_WAITING_FOR_QUOTA = 1 TUNING_JOB_STATE_PROCESSING_DATASET = 2 TUNING_JOB_STATE_WAITING_FOR_CAPACITY = 3 TUNING_JOB_STATE_TUNING = 4 TUNING_JOB_STATE_POST_PROCESSING = 5 @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Optional. The labels with user-defined metadata to organize TuningJob and generated resources such as Model and Endpoint. Label keys and values can be no longer than 64 characters (Unicode codepoints), can only contain lowercase letters, numeric characters, underscores and dashes. International characters are allowed. See https://goo.gl/xmQnxf for more information and examples of labels. Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) baseModel = _messages.StringField(1) createTime = _messages.StringField(2) customBaseModel = _messages.StringField(3) description = _messages.StringField(4) distillationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1DistillationSpec', 5) encryptionSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1EncryptionSpec', 6) endTime = _messages.StringField(7) error = _messages.MessageField('GoogleRpcStatus', 8) evaluateDatasetRuns = _messages.MessageField('GoogleCloudAiplatformV1beta1EvaluateDatasetRun', 9, repeated=True) experiment = _messages.StringField(10) fullFineTuningSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1FullFineTuningSpec', 11) labels = _messages.MessageField('LabelsValue', 12) name = _messages.StringField(13) outputUri = _messages.StringField(14) partnerModelTuningSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PartnerModelTuningSpec', 15) pipelineJob = _messages.StringField(16) preTunedModel = _messages.MessageField('GoogleCloudAiplatformV1beta1PreTunedModel', 17) preferenceOptimizationSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PreferenceOptimizationSpec', 18) satisfiesPzi = _messages.BooleanField(19) satisfiesPzs = _messages.BooleanField(20) serviceAccount = _messages.StringField(21) startTime = _messages.StringField(22) state = _messages.EnumField('StateValueValuesEnum', 23) supervisedTuningSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1SupervisedTuningSpec', 24) tunedModel = _messages.MessageField('GoogleCloudAiplatformV1beta1TunedModel', 25) tunedModelDisplayName = _messages.StringField(26) tuningDataStats = _messages.MessageField('GoogleCloudAiplatformV1beta1TuningDataStats', 27) tuningJobState = _messages.EnumField('TuningJobStateValueValuesEnum', 28) updateTime = _messages.StringField(29) veoTuningSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1VeoTuningSpec', 30) class GoogleCloudAiplatformV1beta1UndeployIndexOperationMetadata(_messages.Message): r"""Runtime operation information for IndexEndpointService.UndeployIndex. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UndeployIndexRequest(_messages.Message): r"""Request message for IndexEndpointService.UndeployIndex. Fields: deployedIndexId: Required. The ID of the DeployedIndex to be undeployed from the IndexEndpoint. """ deployedIndexId = _messages.StringField(1) class GoogleCloudAiplatformV1beta1UndeployIndexResponse(_messages.Message): r"""Response message for IndexEndpointService.UndeployIndex.""" class GoogleCloudAiplatformV1beta1UndeployModelOperationMetadata(_messages.Message): r"""Runtime operation information for EndpointService.UndeployModel. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UndeployModelRequest(_messages.Message): r"""Request message for EndpointService.UndeployModel. Messages: TrafficSplitValue: If this field is provided, then the Endpoint's traffic_split will be overwritten with it. If last DeployedModel is being undeployed from the Endpoint, the [Endpoint.traffic_split] will always end up empty when this call returns. A DeployedModel will be successfully undeployed only if it doesn't have any traffic assigned to it when this method executes, or if this field unassigns any traffic to it. Fields: deployedModelId: Required. The ID of the DeployedModel to be undeployed from the Endpoint. trafficSplit: If this field is provided, then the Endpoint's traffic_split will be overwritten with it. If last DeployedModel is being undeployed from the Endpoint, the [Endpoint.traffic_split] will always end up empty when this call returns. A DeployedModel will be successfully undeployed only if it doesn't have any traffic assigned to it when this method executes, or if this field unassigns any traffic to it. """ @encoding.MapUnrecognizedFields('additionalProperties') class TrafficSplitValue(_messages.Message): r"""If this field is provided, then the Endpoint's traffic_split will be overwritten with it. If last DeployedModel is being undeployed from the Endpoint, the [Endpoint.traffic_split] will always end up empty when this call returns. A DeployedModel will be successfully undeployed only if it doesn't have any traffic assigned to it when this method executes, or if this field unassigns any traffic to it. Messages: AdditionalProperty: An additional property for a TrafficSplitValue object. Fields: additionalProperties: Additional properties of type TrafficSplitValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a TrafficSplitValue object. Fields: key: Name of the additional property. value: A integer attribute. """ key = _messages.StringField(1) value = _messages.IntegerField(2, variant=_messages.Variant.INT32) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) deployedModelId = _messages.StringField(1) trafficSplit = _messages.MessageField('TrafficSplitValue', 2) class GoogleCloudAiplatformV1beta1UndeployModelResponse(_messages.Message): r"""Response message for EndpointService.UndeployModel.""" class GoogleCloudAiplatformV1beta1UndeploySolverOperationMetadata(_messages.Message): r"""Runtime operation information for SolverService.UndeploySolver. Fields: genericMetadata: The generic operation information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UnmanagedContainerModel(_messages.Message): r"""Contains model information necessary to perform batch prediction without requiring a full model import. Fields: artifactUri: The path to the directory containing the Model artifact and any of its supporting files. containerSpec: Input only. The specification of the container that is to be used when deploying this Model. predictSchemata: Contains the schemata used in Model's predictions and explanations """ artifactUri = _messages.StringField(1) containerSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ModelContainerSpec', 2) predictSchemata = _messages.MessageField('GoogleCloudAiplatformV1beta1PredictSchemata', 3) class GoogleCloudAiplatformV1beta1UpdateDeploymentResourcePoolOperationMetadata(_messages.Message): r"""Runtime operation information for UpdateDeploymentResourcePool method. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UpdateEndpointLongRunningRequest(_messages.Message): r"""Request message for EndpointService.UpdateEndpointLongRunning. Fields: endpoint: Required. The Endpoint which replaces the resource on the server. Currently we only support updating the `client_connection_config` field, all the other fields' update will be blocked. """ endpoint = _messages.MessageField('GoogleCloudAiplatformV1beta1Endpoint', 1) class GoogleCloudAiplatformV1beta1UpdateExplanationDatasetOperationMetadata(_messages.Message): r"""Runtime operation information for ModelService.UpdateExplanationDataset. Fields: genericMetadata: The common part of the operation metadata. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UpdateExplanationDatasetRequest(_messages.Message): r"""Request message for ModelService.UpdateExplanationDataset. Fields: examples: The example config containing the location of the dataset. """ examples = _messages.MessageField('GoogleCloudAiplatformV1beta1Examples', 1) class GoogleCloudAiplatformV1beta1UpdateExplanationDatasetResponse(_messages.Message): r"""Response message of ModelService.UpdateExplanationDataset operation.""" class GoogleCloudAiplatformV1beta1UpdateFeatureGroupOperationMetadata(_messages.Message): r"""Details of operations that perform update FeatureGroup. Fields: genericMetadata: Operation metadata for FeatureGroup. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UpdateFeatureOnlineStoreOperationMetadata(_messages.Message): r"""Details of operations that perform update FeatureOnlineStore. Fields: genericMetadata: Operation metadata for FeatureOnlineStore. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UpdateFeatureOperationMetadata(_messages.Message): r"""Details of operations that perform update Feature. Fields: genericMetadata: Operation metadata for Feature Update. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UpdateFeatureViewOperationMetadata(_messages.Message): r"""Details of operations that perform update FeatureView. Fields: genericMetadata: Operation metadata for FeatureView Update. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UpdateFeaturestoreOperationMetadata(_messages.Message): r"""Details of operations that perform update Featurestore. Fields: genericMetadata: Operation metadata for Featurestore. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UpdateIndexOperationMetadata(_messages.Message): r"""Runtime operation information for IndexService.UpdateIndex. Fields: genericMetadata: The operation generic information. nearestNeighborSearchOperationMetadata: The operation metadata with regard to Matching Engine Index operation. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) nearestNeighborSearchOperationMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1NearestNeighborSearchOperationMetadata', 2) class GoogleCloudAiplatformV1beta1UpdateModelDeploymentMonitoringJobOperationMetadata(_messages.Message): r"""Runtime operation information for JobService.UpdateModelDeploymentMonitoringJob. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UpdateModelMonitorOperationMetadata(_messages.Message): r"""Runtime operation information for ModelMonitoringService.UpdateModelMonitor. Fields: genericMetadata: The operation generic information. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UpdatePersistentResourceOperationMetadata(_messages.Message): r"""Details of operations that perform update PersistentResource. Fields: genericMetadata: Operation metadata for PersistentResource. progressMessage: Progress Message for Update LRO """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) progressMessage = _messages.StringField(2) class GoogleCloudAiplatformV1beta1UpdateSpecialistPoolOperationMetadata(_messages.Message): r"""Runtime operation metadata for SpecialistPoolService.UpdateSpecialistPool. Fields: genericMetadata: The operation generic information. specialistPool: Output only. The name of the SpecialistPool to which the specialists are being added. Format: `projects/{project_id}/locations/{l ocation_id}/specialistPools/{specialist_pool}` """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) specialistPool = _messages.StringField(2) class GoogleCloudAiplatformV1beta1UpdateTensorboardOperationMetadata(_messages.Message): r"""Details of operations that perform update Tensorboard. Fields: genericMetadata: Operation metadata for Tensorboard. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeOperationMetadata(_messages.Message): r"""Metadata information for NotebookService.UpgradeNotebookRuntime. Fields: genericMetadata: The operation generic information. progressMessage: A human-readable message that shows the intermediate progress details of NotebookRuntime. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) progressMessage = _messages.StringField(2) class GoogleCloudAiplatformV1beta1UpgradeNotebookRuntimeRequest(_messages.Message): r"""Request message for NotebookService.UpgradeNotebookRuntime.""" class GoogleCloudAiplatformV1beta1UploadModelOperationMetadata(_messages.Message): r"""Details of ModelService.UploadModel operation. Fields: genericMetadata: The common part of the operation metadata. """ genericMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1GenericOperationMetadata', 1) class GoogleCloudAiplatformV1beta1UploadModelRequest(_messages.Message): r"""Request message for ModelService.UploadModel. Fields: model: Required. The Model to create. modelId: Optional. The ID to use for the uploaded Model, which will become the final component of the model resource name. This value may be up to 63 characters, and valid characters are `[a-z0-9_-]`. The first character cannot be a number or hyphen. parentModel: Optional. The resource name of the model into which to upload the version. Only specify this field when uploading a new version. serviceAccount: Optional. The user-provided custom service account to use to do the model upload. If empty, [Vertex AI Service Agent](https://cloud.google.com/vertex-ai/docs/general/access- control#service-agents) will be used to access resources needed to upload the model. This account must belong to the target project where the model is uploaded to, i.e., the project specified in the `parent` field of this request and have necessary read permissions (to Google Cloud Storage, Artifact Registry, etc.). """ model = _messages.MessageField('GoogleCloudAiplatformV1beta1Model', 1) modelId = _messages.StringField(2) parentModel = _messages.StringField(3) serviceAccount = _messages.StringField(4) class GoogleCloudAiplatformV1beta1UploadModelResponse(_messages.Message): r"""Response message of ModelService.UploadModel operation. Fields: model: The name of the uploaded Model resource. Format: `projects/{project}/locations/{location}/models/{model}` modelVersionId: Output only. The version ID of the model that is uploaded. """ model = _messages.StringField(1) modelVersionId = _messages.StringField(2) class GoogleCloudAiplatformV1beta1UploadRagFileConfig(_messages.Message): r"""Config for uploading RagFile. Fields: ragFileChunkingConfig: Specifies the size and overlap of chunks after uploading RagFile. ragFileMetadataConfig: Specifies the metadata config for RagFiles. Including paths for metadata schema and metadata. Alteratively, inline metadata schema and metadata can be provided. ragFileParsingConfig: Optional. Specifies the parsing config for RagFiles. RAG will use the default parser if this field is not set. ragFileTransformationConfig: Specifies the transformation config for RagFiles. """ ragFileChunkingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileChunkingConfig', 1) ragFileMetadataConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileMetadataConfig', 2) ragFileParsingConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileParsingConfig', 3) ragFileTransformationConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFileTransformationConfig', 4) class GoogleCloudAiplatformV1beta1UploadRagFileRequest(_messages.Message): r"""Request message for VertexRagDataService.UploadRagFile. Fields: ragFile: Required. The RagFile to upload. uploadRagFileConfig: Required. The config for the RagFiles to be uploaded into the RagCorpus. VertexRagDataService.UploadRagFile. """ ragFile = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFile', 1) uploadRagFileConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1UploadRagFileConfig', 2) class GoogleCloudAiplatformV1beta1UploadRagFileResponse(_messages.Message): r"""Response message for VertexRagDataService.UploadRagFile. Fields: error: The error that occurred while processing the RagFile. ragFile: The RagFile that had been uploaded into the RagCorpus. """ error = _messages.MessageField('GoogleRpcStatus', 1) ragFile = _messages.MessageField('GoogleCloudAiplatformV1beta1RagFile', 2) class GoogleCloudAiplatformV1beta1UpsertDatapointsRequest(_messages.Message): r"""Request message for IndexService.UpsertDatapoints Fields: datapoints: A list of datapoints to be created/updated. updateMask: Optional. Update mask is used to specify the fields to be overwritten in the datapoints by the update. The fields specified in the update_mask are relative to each IndexDatapoint inside datapoints, not the full request. Updatable fields: * Use `all_restricts` to update both restricts and numeric_restricts. """ datapoints = _messages.MessageField('GoogleCloudAiplatformV1beta1IndexDatapoint', 1, repeated=True) updateMask = _messages.StringField(2) class GoogleCloudAiplatformV1beta1UpsertDatapointsResponse(_messages.Message): r"""Response message for IndexService.UpsertDatapoints""" class GoogleCloudAiplatformV1beta1UpsertExamplesRequest(_messages.Message): r"""Request message for ExampleStoreService.UpsertExamples. Fields: examples: Required. A list of examples to be created/updated. overwrite: Optional. A flag indicating whether an example can be overwritten if it already exists. If False (default) and the example already exists, the example will not be updated. This does not affect behavior if the example does not exist already. """ examples = _messages.MessageField('GoogleCloudAiplatformV1beta1Example', 1, repeated=True) overwrite = _messages.BooleanField(2) class GoogleCloudAiplatformV1beta1UpsertExamplesResponse(_messages.Message): r"""Response message for ExampleStoreService.UpsertExamples. Fields: results: A list of results for creating/updating. It's either a successfully created/updated example or a status with an error message. """ results = _messages.MessageField('GoogleCloudAiplatformV1beta1UpsertExamplesResponseUpsertResult', 1, repeated=True) class GoogleCloudAiplatformV1beta1UpsertExamplesResponseUpsertResult(_messages.Message): r"""The result for creating/updating a single example. Fields: example: The example created/updated successfully. status: The error message of the example that was not created/updated successfully. """ example = _messages.MessageField('GoogleCloudAiplatformV1beta1Example', 1) status = _messages.MessageField('GoogleRpcStatus', 2) class GoogleCloudAiplatformV1beta1UrlContext(_messages.Message): r"""Tool to support URL context.""" class GoogleCloudAiplatformV1beta1UrlContextMetadata(_messages.Message): r"""Metadata returned when the model uses the `url_context` tool to get information from a user-provided URL. Fields: urlMetadata: Output only. A list of URL metadata, with one entry for each URL retrieved by the tool. """ urlMetadata = _messages.MessageField('GoogleCloudAiplatformV1beta1UrlMetadata', 1, repeated=True) class GoogleCloudAiplatformV1beta1UrlMetadata(_messages.Message): r"""The metadata for a single URL retrieval. Enums: UrlRetrievalStatusValueValuesEnum: The status of the URL retrieval. Fields: retrievedUrl: The URL retrieved by the tool. urlRetrievalStatus: The status of the URL retrieval. """ class UrlRetrievalStatusValueValuesEnum(_messages.Enum): r"""The status of the URL retrieval. Values: URL_RETRIEVAL_STATUS_UNSPECIFIED: Default value. This value is unused. URL_RETRIEVAL_STATUS_SUCCESS: The URL was retrieved successfully. URL_RETRIEVAL_STATUS_ERROR: The URL retrieval failed. """ URL_RETRIEVAL_STATUS_UNSPECIFIED = 0 URL_RETRIEVAL_STATUS_SUCCESS = 1 URL_RETRIEVAL_STATUS_ERROR = 2 retrievedUrl = _messages.StringField(1) urlRetrievalStatus = _messages.EnumField('UrlRetrievalStatusValueValuesEnum', 2) class GoogleCloudAiplatformV1beta1UsageMetadata(_messages.Message): r"""Usage metadata about the content generation request and response. This message provides a detailed breakdown of token usage and other relevant metrics. Enums: TrafficTypeValueValuesEnum: Output only. The traffic type for this request. Fields: cacheTokensDetails: Output only. A detailed breakdown of the token count for each modality in the cached content. cachedContentTokenCount: Output only. The number of tokens in the cached content that was used for this request. candidatesTokenCount: The total number of tokens in the generated candidates. candidatesTokensDetails: Output only. A detailed breakdown of the token count for each modality in the generated candidates. promptTokenCount: The total number of tokens in the prompt. This includes any text, images, or other media provided in the request. When `cached_content` is set, this also includes the number of tokens in the cached content. promptTokensDetails: Output only. A detailed breakdown of the token count for each modality in the prompt. thoughtsTokenCount: Output only. The number of tokens that were part of the model's generated "thoughts" output, if applicable. toolUsePromptTokenCount: Output only. The number of tokens in the results from tool executions, which are provided back to the model as input, if applicable. toolUsePromptTokensDetails: Output only. A detailed breakdown by modality of the token counts from the results of tool executions, which are provided back to the model as input. totalTokenCount: The total number of tokens for the entire request. This is the sum of `prompt_token_count`, `candidates_token_count`, `tool_use_prompt_token_count`, and `thoughts_token_count`. trafficType: Output only. The traffic type for this request. """ class TrafficTypeValueValuesEnum(_messages.Enum): r"""Output only. The traffic type for this request. Values: TRAFFIC_TYPE_UNSPECIFIED: Unspecified request traffic type. ON_DEMAND: Type for Pay-As-You-Go traffic. PROVISIONED_THROUGHPUT: Type for Provisioned Throughput traffic. """ TRAFFIC_TYPE_UNSPECIFIED = 0 ON_DEMAND = 1 PROVISIONED_THROUGHPUT = 2 cacheTokensDetails = _messages.MessageField('GoogleCloudAiplatformV1beta1ModalityTokenCount', 1, repeated=True) cachedContentTokenCount = _messages.IntegerField(2, variant=_messages.Variant.INT32) candidatesTokenCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) candidatesTokensDetails = _messages.MessageField('GoogleCloudAiplatformV1beta1ModalityTokenCount', 4, repeated=True) promptTokenCount = _messages.IntegerField(5, variant=_messages.Variant.INT32) promptTokensDetails = _messages.MessageField('GoogleCloudAiplatformV1beta1ModalityTokenCount', 6, repeated=True) thoughtsTokenCount = _messages.IntegerField(7, variant=_messages.Variant.INT32) toolUsePromptTokenCount = _messages.IntegerField(8, variant=_messages.Variant.INT32) toolUsePromptTokensDetails = _messages.MessageField('GoogleCloudAiplatformV1beta1ModalityTokenCount', 9, repeated=True) totalTokenCount = _messages.IntegerField(10, variant=_messages.Variant.INT32) trafficType = _messages.EnumField('TrafficTypeValueValuesEnum', 11) class GoogleCloudAiplatformV1beta1UserActionReference(_messages.Message): r"""References an API call. It contains more information about long running operation and Jobs that are triggered by the API call. Fields: dataLabelingJob: For API calls that start a LabelingJob. Resource name of the LabelingJob. Format: `projects/{project}/locations/{location}/dataLa belingJobs/{data_labeling_job}` method: The method name of the API RPC call. For example, "/google.cloud.aiplatform.{apiVersion}.DatasetService.CreateDataset" operation: For API calls that return a long running operation. Resource name of the long running operation. Format: `projects/{project}/locations/{location}/operations/{operation}` """ dataLabelingJob = _messages.StringField(1) method = _messages.StringField(2) operation = _messages.StringField(3) class GoogleCloudAiplatformV1beta1Value(_messages.Message): r"""Value is the value of the field. Fields: doubleValue: A double value. intValue: An integer value. stringValue: A string value. """ doubleValue = _messages.FloatField(1) intValue = _messages.IntegerField(2) stringValue = _messages.StringField(3) class GoogleCloudAiplatformV1beta1VeoHyperParameters(_messages.Message): r"""Hyperparameters for Veo. Enums: TuningTaskValueValuesEnum: Optional. The tuning task. Either I2V or T2V. Fields: epochCount: Optional. Number of complete passes the model makes over the entire training dataset during training. learningRateMultiplier: Optional. Multiplier for adjusting the default learning rate. tuningTask: Optional. The tuning task. Either I2V or T2V. """ class TuningTaskValueValuesEnum(_messages.Enum): r"""Optional. The tuning task. Either I2V or T2V. Values: TUNING_TASK_UNSPECIFIED: Default value. This value is unused. TUNING_TASK_I2V: Tuning task for image to video. TUNING_TASK_T2V: Tuning task for text to video. TUNING_TASK_R2V: Tuning task for reference to video. """ TUNING_TASK_UNSPECIFIED = 0 TUNING_TASK_I2V = 1 TUNING_TASK_T2V = 2 TUNING_TASK_R2V = 3 epochCount = _messages.IntegerField(1) learningRateMultiplier = _messages.FloatField(2) tuningTask = _messages.EnumField('TuningTaskValueValuesEnum', 3) class GoogleCloudAiplatformV1beta1VeoTuningSpec(_messages.Message): r"""Tuning Spec for Veo Model Tuning. Fields: hyperParameters: Optional. Hyperparameters for Veo. trainingDatasetUri: Required. Training dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset. validationDatasetUri: Optional. Validation dataset used for tuning. The dataset can be specified as either a Cloud Storage path to a JSONL file or as the resource name of a Vertex Multimodal Dataset. """ hyperParameters = _messages.MessageField('GoogleCloudAiplatformV1beta1VeoHyperParameters', 1) trainingDatasetUri = _messages.StringField(2) validationDatasetUri = _messages.StringField(3) class GoogleCloudAiplatformV1beta1VertexAISearch(_messages.Message): r"""Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder Fields: dataStoreSpecs: Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used. datastore: Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collec tion}/dataStores/{dataStore}` engine: Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection }/engines/{engine}` filter: Optional. Filter strings to be passed to the search API. maxResults: Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10. """ dataStoreSpecs = _messages.MessageField('GoogleCloudAiplatformV1beta1VertexAISearchDataStoreSpec', 1, repeated=True) datastore = _messages.StringField(2) engine = _messages.StringField(3) filter = _messages.StringField(4) maxResults = _messages.IntegerField(5, variant=_messages.Variant.INT32) class GoogleCloudAiplatformV1beta1VertexAISearchDataStoreSpec(_messages.Message): r"""Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app- builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec Fields: dataStore: Full resource name of DataStore, such as Format: `projects/{pro ject}/locations/{location}/collections/{collection}/dataStores/{dataStor e}` filter: Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app- builder/docs/filter-search-metadata) """ dataStore = _messages.StringField(1) filter = _messages.StringField(2) class GoogleCloudAiplatformV1beta1VertexAiSearchConfig(_messages.Message): r"""Config for the Vertex AI Search. Fields: servingConfig: Vertex AI Search Serving Config resource full name. For example, `projects/{project}/locations/{location}/collections/{collectio n}/engines/{engine}/servingConfigs/{serving_config}` or `projects/{proje ct}/locations/{location}/collections/{collection}/dataStores/{data_store }/servingConfigs/{serving_config}`. """ servingConfig = _messages.StringField(1) class GoogleCloudAiplatformV1beta1VertexRagStore(_messages.Message): r"""Retrieve from Vertex RAG Store for grounding. Fields: ragCorpora: Optional. Deprecated. Please use rag_resources instead. ragResources: Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support. ragRetrievalConfig: Optional. The retrieval config for the Rag query. similarityTopK: Optional. Number of top k results to return from the selected corpora. storeContext: Optional. Currently only supported for Gemini Multimodal Live API. In Gemini Multimodal Live API, if `store_context` bool is specified, Gemini will leverage it to automatically memorize the interactions between the client and Gemini, and retrieve context when needed to augment the response generation for users' ongoing and future interactions. vectorDistanceThreshold: Optional. Only return results with vector distance smaller than the threshold. """ ragCorpora = _messages.StringField(1, repeated=True) ragResources = _messages.MessageField('GoogleCloudAiplatformV1beta1VertexRagStoreRagResource', 2, repeated=True) ragRetrievalConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1RagRetrievalConfig', 3) similarityTopK = _messages.IntegerField(4, variant=_messages.Variant.INT32) storeContext = _messages.BooleanField(5) vectorDistanceThreshold = _messages.FloatField(6) class GoogleCloudAiplatformV1beta1VertexRagStoreRagResource(_messages.Message): r"""The definition of the Rag resource. Fields: ragCorpus: Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}` ragFileIds: Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field. """ ragCorpus = _messages.StringField(1) ragFileIds = _messages.StringField(2, repeated=True) class GoogleCloudAiplatformV1beta1VideoMetadata(_messages.Message): r"""Provides metadata for a video, including the start and end offsets for clipping and the frame rate. Fields: endOffset: Optional. The end offset of the video. fps: Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0]. startOffset: Optional. The start offset of the video. """ endOffset = _messages.StringField(1) fps = _messages.FloatField(2) startOffset = _messages.StringField(3) class GoogleCloudAiplatformV1beta1VoiceConfig(_messages.Message): r"""Configuration for a voice. Fields: prebuiltVoiceConfig: The configuration for a prebuilt voice. """ prebuiltVoiceConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1PrebuiltVoiceConfig', 1) class GoogleCloudAiplatformV1beta1WorkerPoolSpec(_messages.Message): r"""Represents the spec of a worker pool in a job. Fields: containerSpec: The custom container task. diskSpec: Disk spec. lustreMounts: Optional. List of Lustre mounts. machineSpec: Optional. Immutable. The specification of a single machine. nfsMounts: Optional. List of NFS mount spec. pythonPackageSpec: The Python packaged task. replicaCount: Optional. The number of worker replicas to use for this worker pool. """ containerSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1ContainerSpec', 1) diskSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1DiskSpec', 2) lustreMounts = _messages.MessageField('GoogleCloudAiplatformV1beta1LustreMount', 3, repeated=True) machineSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1MachineSpec', 4) nfsMounts = _messages.MessageField('GoogleCloudAiplatformV1beta1NfsMount', 5, repeated=True) pythonPackageSpec = _messages.MessageField('GoogleCloudAiplatformV1beta1PythonPackageSpec', 6) replicaCount = _messages.IntegerField(7) class GoogleCloudAiplatformV1beta1WriteFeatureValuesPayload(_messages.Message): r"""Contains Feature values to be written for a specific entity. Messages: FeatureValuesValue: Required. Feature values to be written, mapping from Feature ID to value. Up to 100,000 `feature_values` entries may be written across all payloads. The feature generation time, aligned by days, must be no older than five years (1825 days) and no later than one year (366 days) in the future. Fields: entityId: Required. The ID of the entity. featureValues: Required. Feature values to be written, mapping from Feature ID to value. Up to 100,000 `feature_values` entries may be written across all payloads. The feature generation time, aligned by days, must be no older than five years (1825 days) and no later than one year (366 days) in the future. """ @encoding.MapUnrecognizedFields('additionalProperties') class FeatureValuesValue(_messages.Message): r"""Required. Feature values to be written, mapping from Feature ID to value. Up to 100,000 `feature_values` entries may be written across all payloads. The feature generation time, aligned by days, must be no older than five years (1825 days) and no later than one year (366 days) in the future. Messages: AdditionalProperty: An additional property for a FeatureValuesValue object. Fields: additionalProperties: Additional properties of type FeatureValuesValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a FeatureValuesValue object. Fields: key: Name of the additional property. value: A GoogleCloudAiplatformV1beta1FeatureValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('GoogleCloudAiplatformV1beta1FeatureValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) entityId = _messages.StringField(1) featureValues = _messages.MessageField('FeatureValuesValue', 2) class GoogleCloudAiplatformV1beta1WriteFeatureValuesRequest(_messages.Message): r"""Request message for FeaturestoreOnlineServingService.WriteFeatureValues. Fields: payloads: Required. The entities to be written. Up to 100,000 feature values can be written across all `payloads`. """ payloads = _messages.MessageField('GoogleCloudAiplatformV1beta1WriteFeatureValuesPayload', 1, repeated=True) class GoogleCloudAiplatformV1beta1WriteFeatureValuesResponse(_messages.Message): r"""Response message for FeaturestoreOnlineServingService.WriteFeatureValues. """ class GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataRequest(_messages.Message): r"""Request message for TensorboardService.WriteTensorboardExperimentData. Fields: writeRunDataRequests: Required. Requests containing per-run TensorboardTimeSeries data to write. """ writeRunDataRequests = _messages.MessageField('GoogleCloudAiplatformV1beta1WriteTensorboardRunDataRequest', 1, repeated=True) class GoogleCloudAiplatformV1beta1WriteTensorboardExperimentDataResponse(_messages.Message): r"""Response message for TensorboardService.WriteTensorboardExperimentData. """ class GoogleCloudAiplatformV1beta1WriteTensorboardRunDataRequest(_messages.Message): r"""Request message for TensorboardService.WriteTensorboardRunData. Fields: tensorboardRun: Required. The resource name of the TensorboardRun to write data to. Format: `projects/{project}/locations/{location}/tensorboards/{ tensorboard}/experiments/{experiment}/runs/{run}` timeSeriesData: Required. The TensorboardTimeSeries data to write. Values with in a time series are indexed by their step value. Repeated writes to the same step will overwrite the existing value for that step. The upper limit of data points per write request is 5000. """ tensorboardRun = _messages.StringField(1) timeSeriesData = _messages.MessageField('GoogleCloudAiplatformV1beta1TimeSeriesData', 2, repeated=True) class GoogleCloudAiplatformV1beta1WriteTensorboardRunDataResponse(_messages.Message): r"""Response message for TensorboardService.WriteTensorboardRunData.""" class GoogleCloudAiplatformV1beta1XraiAttribution(_messages.Message): r"""An explanation method that redistributes Integrated Gradients attributions to segmented regions, taking advantage of the model's fully differentiable structure. Refer to this paper for more details: https://arxiv.org/abs/1906.02825 Supported only by image Models. Fields: blurBaselineConfig: Config for XRAI with blur baseline. When enabled, a linear path from the maximally blurred image to the input image is created. Using a blurred baseline instead of zero (black image) is motivated by the BlurIG approach explained here: https://arxiv.org/abs/2004.03383 smoothGradConfig: Config for SmoothGrad approximation of gradients. When enabled, the gradients are approximated by averaging the gradients from noisy samples in the vicinity of the inputs. Adding noise can help improve the computed gradients. Refer to this paper for more details: https://arxiv.org/pdf/1706.03825.pdf stepCount: Required. The number of steps for approximating the path integral. A good value to start is 50 and gradually increase until the sum to diff property is met within the desired error range. Valid range of its value is [1, 100], inclusively. """ blurBaselineConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1BlurBaselineConfig', 1) smoothGradConfig = _messages.MessageField('GoogleCloudAiplatformV1beta1SmoothGradConfig', 2) stepCount = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleCloudLocationListLocationsResponse(_messages.Message): r"""The response message for Locations.ListLocations. Fields: locations: A list of locations that matches the specified filter in the request. nextPageToken: The standard List next-page token. """ locations = _messages.MessageField('GoogleCloudLocationLocation', 1, repeated=True) nextPageToken = _messages.StringField(2) class GoogleCloudLocationLocation(_messages.Message): r"""A resource that represents a Google Cloud location. Messages: LabelsValue: Cross-service attributes for the location. For example {"cloud.googleapis.com/region": "us-east1"} MetadataValue: Service-specific metadata. For example the available capacity at the given location. Fields: displayName: The friendly name for this location, typically a nearby city name. For example, "Tokyo". labels: Cross-service attributes for the location. For example {"cloud.googleapis.com/region": "us-east1"} locationId: The canonical id for this location. For example: `"us-east1"`. metadata: Service-specific metadata. For example the available capacity at the given location. name: Resource name for the location, which may vary between implementations. For example: `"projects/example-project/locations/us- east1"` """ @encoding.MapUnrecognizedFields('additionalProperties') class LabelsValue(_messages.Message): r"""Cross-service attributes for the location. For example {"cloud.googleapis.com/region": "us-east1"} Messages: AdditionalProperty: An additional property for a LabelsValue object. Fields: additionalProperties: Additional properties of type LabelsValue """ class AdditionalProperty(_messages.Message): r"""An additional property for a LabelsValue object. Fields: key: Name of the additional property. value: A string attribute. """ key = _messages.StringField(1) value = _messages.StringField(2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class MetadataValue(_messages.Message): r"""Service-specific metadata. For example the available capacity at the given location. Messages: AdditionalProperty: An additional property for a MetadataValue object. Fields: additionalProperties: Properties of the object. Contains field @type with type URL. """ class AdditionalProperty(_messages.Message): r"""An additional property for a MetadataValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) displayName = _messages.StringField(1) labels = _messages.MessageField('LabelsValue', 2) locationId = _messages.StringField(3) metadata = _messages.MessageField('MetadataValue', 4) name = _messages.StringField(5) class GoogleIamV1Binding(_messages.Message): r"""Associates `members`, or principals, with a `role`. Fields: condition: The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). members: Specifies the principals requesting access for a Google Cloud resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. Does not include identities that come from external identity providers (IdPs) through identity federation. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a Google service account. For example, `my-other- app@appspot.gserviceaccount.com`. * `serviceAccount:{projectid}.svc.id.goog[{namespace}/{kubernetes-sa}]`: An identifier for a [Kubernetes service account](https://cloud.google.com/kubernetes-engine/docs/how- to/kubernetes-service-accounts). For example, `my- project.svc.id.goog[my-namespace/my-kubernetes-sa]`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`. * `principal://iam.googleapis.com/locatio ns/global/workforcePools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workforce identity pool. * `principalSet://iam.goog leapis.com/locations/global/workforcePools/{pool_id}/group/{group_id}`: All workforce identities in a group. * `principalSet://iam.googleapis.co m/locations/global/workforcePools/{pool_id}/attribute.{attribute_name}/{ attribute_value}`: All workforce identities with a specific attribute value. * `principalSet://iam.googleapis.com/locations/global/workforcePo ols/{pool_id}/*`: All identities in a workforce identity pool. * `princi pal://iam.googleapis.com/projects/{project_number}/locations/global/work loadIdentityPools/{pool_id}/subject/{subject_attribute_value}`: A single identity in a workload identity pool. * `principalSet://iam.googleapis.c om/projects/{project_number}/locations/global/workloadIdentityPools/{poo l_id}/group/{group_id}`: A workload identity pool group. * `principalSet ://iam.googleapis.com/projects/{project_number}/locations/global/workloa dIdentityPools/{pool_id}/attribute.{attribute_name}/{attribute_value}`: All identities in a workload identity pool with a certain attribute. * ` principalSet://iam.googleapis.com/projects/{project_number}/locations/gl obal/workloadIdentityPools/{pool_id}/*`: All identities in a workload identity pool. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other- app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `deleted:principal://iam.google apis.com/locations/global/workforcePools/{pool_id}/subject/{subject_attr ibute_value}`: Deleted single identity in a workforce identity pool. For example, `deleted:principal://iam.googleapis.com/locations/global/workfo rcePools/my-pool-id/subject/my-subject-attribute-value`. role: Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`. For an overview of the IAM roles and permissions, see the [IAM documentation](https://cloud.google.com/iam/docs/roles-overview). For a list of the available pre-defined roles, see [here](https://cloud.google.com/iam/docs/understanding-roles). """ condition = _messages.MessageField('GoogleTypeExpr', 1) members = _messages.StringField(2, repeated=True) role = _messages.StringField(3) class GoogleIamV1GetIamPolicyRequest(_messages.Message): r"""Request message for `GetIamPolicy` method. Fields: options: OPTIONAL: A `GetPolicyOptions` object for specifying options to `GetIamPolicy`. """ options = _messages.MessageField('GoogleIamV1GetPolicyOptions', 1) class GoogleIamV1GetPolicyOptions(_messages.Message): r"""Encapsulates settings provided to GetIamPolicy. Fields: requestedPolicyVersion: Optional. The maximum policy version that will be used to format the policy. Valid values are 0, 1, and 3. Requests specifying an invalid value will be rejected. Requests for policies with any conditional role bindings must specify version 3. Policies with no conditional role bindings may specify any valid value or leave the field unset. The policy in the response might use the policy version that you specified, or it might use a lower policy version. For example, if you specify version 3, but the policy has no conditional role bindings, the response uses version 1. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). """ requestedPolicyVersion = _messages.IntegerField(1, variant=_messages.Variant.INT32) class GoogleIamV1Policy(_messages.Message): r"""An Identity and Access Management (IAM) policy, which specifies access controls for Google Cloud resources. A `Policy` is a collection of `bindings`. A `binding` binds one or more `members`, or principals, to a single `role`. Principals can be user accounts, service accounts, Google groups, and domains (such as G Suite). A `role` is a named list of permissions; each `role` can be an IAM predefined role or a user-created custom role. For some types of Google Cloud resources, a `binding` can also specify a `condition`, which is a logical expression that allows access to a resource only if the expression evaluates to `true`. A condition can add constraints based on attributes of the request, the resource, or both. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). **JSON example:** ``` { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": [ "user:eve@example.com" ], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01T00:00:00.000Z')", } } ], "etag": "BwWWja0YfJA=", "version": 3 } ``` **YAML example:** ``` bindings: - members: - user:mike@example.com - group:admins@example.com - domain:google.com - serviceAccount:my-project-id@appspot.gserviceaccount.com role: roles/resourcemanager.organizationAdmin - members: - user:eve@example.com role: roles/resourcemanager.organizationViewer condition: title: expirable access description: Does not grant access after Sep 2020 expression: request.time < timestamp('2020-10-01T00:00:00.000Z') etag: BwWWja0YfJA= version: 3 ``` For a description of IAM and its features, see the [IAM documentation](https://cloud.google.com/iam/docs/). Fields: bindings: Associates a list of `members`, or principals, with a `role`. Optionally, may specify a `condition` that determines how and when the `bindings` are applied. Each of the `bindings` must contain at least one principal. The `bindings` in a `Policy` can refer to up to 1,500 principals; up to 250 of these principals can be Google groups. Each occurrence of a principal counts towards these limits. For example, if the `bindings` grant 50 different roles to `user:alice@example.com`, and not to any other principal, then you can add another 1,450 principals to the `bindings` in the `Policy`. etag: `etag` is used for optimistic concurrency control as a way to help prevent simultaneous updates of a policy from overwriting each other. It is strongly suggested that systems make use of the `etag` in the read- modify-write cycle to perform policy updates in order to avoid race conditions: An `etag` is returned in the response to `getIamPolicy`, and systems are expected to put that etag in the request to `setIamPolicy` to ensure that their change will be applied to the same version of the policy. **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. version: Specifies the format of the policy. Valid values are `0`, `1`, and `3`. Requests that specify an invalid value are rejected. Any operation that affects conditional role bindings must specify version `3`. This requirement applies to the following operations: * Getting a policy that includes a conditional role binding * Adding a conditional role binding to a policy * Changing a conditional role binding in a policy * Removing any role binding, with or without a condition, from a policy that includes conditions **Important:** If you use IAM Conditions, you must include the `etag` field whenever you call `setIamPolicy`. If you omit this field, then IAM allows you to overwrite a version `3` policy with a version `1` policy, and all of the conditions in the version `3` policy are lost. If a policy does not include any conditions, operations on that policy may specify any valid version or leave the field unset. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource- policies). """ bindings = _messages.MessageField('GoogleIamV1Binding', 1, repeated=True) etag = _messages.BytesField(2) version = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleIamV1SetIamPolicyRequest(_messages.Message): r"""Request message for `SetIamPolicy` method. Fields: policy: REQUIRED: The complete policy to be applied to the `resource`. The size of the policy is limited to a few 10s of KB. An empty policy is a valid policy but certain Google Cloud services (such as Projects) might reject them. """ policy = _messages.MessageField('GoogleIamV1Policy', 1) class GoogleIamV1TestIamPermissionsRequest(_messages.Message): r"""Request message for `TestIamPermissions` method. Fields: permissions: The set of permissions to check for the `resource`. Permissions with wildcards (such as `*` or `storage.*`) are not allowed. For more information see [IAM Overview](https://cloud.google.com/iam/docs/overview#permissions). """ permissions = _messages.StringField(1, repeated=True) class GoogleIamV1TestIamPermissionsResponse(_messages.Message): r"""Response message for `TestIamPermissions` method. Fields: permissions: A subset of `TestPermissionsRequest.permissions` that the caller is allowed. """ permissions = _messages.StringField(1, repeated=True) class GoogleLongrunningListOperationsResponse(_messages.Message): r"""The response message for Operations.ListOperations. Fields: nextPageToken: The standard List next-page token. operations: A list of operations that matches the specified filter in the request. unreachable: Unordered list. Unreachable resources. Populated when the request sets `ListOperationsRequest.return_partial_success` and reads across collections e.g. when attempting to list all resources across all supported locations. """ nextPageToken = _messages.StringField(1) operations = _messages.MessageField('GoogleLongrunningOperation', 2, repeated=True) unreachable = _messages.StringField(3, repeated=True) class GoogleLongrunningOperation(_messages.Message): r"""This resource represents a long-running operation that is the result of a network API call. Messages: MetadataValue: Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any. ResponseValue: The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`. Fields: done: If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available. error: The error result of the operation in case of failure or cancellation. metadata: Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any. name: The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`. response: The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`. """ @encoding.MapUnrecognizedFields('additionalProperties') class MetadataValue(_messages.Message): r"""Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any. Messages: AdditionalProperty: An additional property for a MetadataValue object. Fields: additionalProperties: Properties of the object. Contains field @type with type URL. """ class AdditionalProperty(_messages.Message): r"""An additional property for a MetadataValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) @encoding.MapUnrecognizedFields('additionalProperties') class ResponseValue(_messages.Message): r"""The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`. Messages: AdditionalProperty: An additional property for a ResponseValue object. Fields: additionalProperties: Properties of the object. Contains field @type with type URL. """ class AdditionalProperty(_messages.Message): r"""An additional property for a ResponseValue object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) done = _messages.BooleanField(1) error = _messages.MessageField('GoogleRpcStatus', 2) metadata = _messages.MessageField('MetadataValue', 3) name = _messages.StringField(4) response = _messages.MessageField('ResponseValue', 5) class GoogleProtobufEmpty(_messages.Message): r"""A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } """ class GoogleRpcStatus(_messages.Message): r"""The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). Messages: DetailsValueListEntry: A DetailsValueListEntry object. Fields: code: The status code, which should be an enum value of google.rpc.Code. details: A list of messages that carry the error details. There is a common set of message types for APIs to use. message: A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client. """ @encoding.MapUnrecognizedFields('additionalProperties') class DetailsValueListEntry(_messages.Message): r"""A DetailsValueListEntry object. Messages: AdditionalProperty: An additional property for a DetailsValueListEntry object. Fields: additionalProperties: Properties of the object. Contains field @type with type URL. """ class AdditionalProperty(_messages.Message): r"""An additional property for a DetailsValueListEntry object. Fields: key: Name of the additional property. value: A extra_types.JsonValue attribute. """ key = _messages.StringField(1) value = _messages.MessageField('extra_types.JsonValue', 2) additionalProperties = _messages.MessageField('AdditionalProperty', 1, repeated=True) code = _messages.IntegerField(1, variant=_messages.Variant.INT32) details = _messages.MessageField('DetailsValueListEntry', 2, repeated=True) message = _messages.StringField(3) class GoogleTypeColor(_messages.Message): r"""Represents a color in the RGBA color space. This representation is designed for simplicity of conversion to and from color representations in various languages over compactness. For example, the fields of this representation can be trivially provided to the constructor of `java.awt.Color` in Java; it can also be trivially provided to UIColor's `+colorWithRed:green:blue:alpha` method in iOS; and, with just a little work, it can be easily formatted into a CSS `rgba()` string in JavaScript. This reference page doesn't have information about the absolute color space that should be used to interpret the RGB value-for example, sRGB, Adobe RGB, DCI-P3, and BT.2020. By default, applications should assume the sRGB color space. When color equality needs to be decided, implementations, unless documented otherwise, treat two colors as equal if all their red, green, blue, and alpha values each differ by at most `1e-5`. Example (Java): import com.google.type.Color; // ... public static java.awt.Color fromProto(Color protocolor) { float alpha = protocolor.hasAlpha() ? protocolor.getAlpha().getValue() : 1.0; return new java.awt.Color( protocolor.getRed(), protocolor.getGreen(), protocolor.getBlue(), alpha); } public static Color toProto(java.awt.Color color) { float red = (float) color.getRed(); float green = (float) color.getGreen(); float blue = (float) color.getBlue(); float denominator = 255.0; Color.Builder resultBuilder = Color .newBuilder() .setRed(red / denominator) .setGreen(green / denominator) .setBlue(blue / denominator); int alpha = color.getAlpha(); if (alpha != 255) { result.setAlpha( FloatValue .newBuilder() .setValue(((float) alpha) / denominator) .build()); } return resultBuilder.build(); } // ... Example (iOS / Obj-C): // ... static UIColor* fromProto(Color* protocolor) { float red = [protocolor red]; float green = [protocolor green]; float blue = [protocolor blue]; FloatValue* alpha_wrapper = [protocolor alpha]; float alpha = 1.0; if (alpha_wrapper != nil) { alpha = [alpha_wrapper value]; } return [UIColor colorWithRed:red green:green blue:blue alpha:alpha]; } static Color* toProto(UIColor* color) { CGFloat red, green, blue, alpha; if (![color getRed:&red green:&green blue:&blue alpha:&alpha]) { return nil; } Color* result = [[Color alloc] init]; [result setRed:red]; [result setGreen:green]; [result setBlue:blue]; if (alpha <= 0.9999) { [result setAlpha:floatWrapperWithValue(alpha)]; } [result autorelease]; return result; } // ... Example (JavaScript): // ... var protoToCssColor = function(rgb_color) { var redFrac = rgb_color.red || 0.0; var greenFrac = rgb_color.green || 0.0; var blueFrac = rgb_color.blue || 0.0; var red = Math.floor(redFrac * 255); var green = Math.floor(greenFrac * 255); var blue = Math.floor(blueFrac * 255); if (!('alpha' in rgb_color)) { return rgbToCssColor(red, green, blue); } var alphaFrac = rgb_color.alpha.value || 0.0; var rgbParams = [red, green, blue].join(','); return ['rgba(', rgbParams, ',', alphaFrac, ')'].join(''); }; var rgbToCssColor = function(red, green, blue) { var rgbNumber = new Number((red << 16) | (green << 8) | blue); var hexString = rgbNumber.toString(16); var missingZeros = 6 - hexString.length; var resultBuilder = ['#']; for (var i = 0; i < missingZeros; i++) { resultBuilder.push('0'); } resultBuilder.push(hexString); return resultBuilder.join(''); }; // ... Fields: alpha: The fraction of this color that should be applied to the pixel. That is, the final pixel color is defined by the equation: `pixel color = alpha * (this color) + (1.0 - alpha) * (background color)` This means that a value of 1.0 corresponds to a solid color, whereas a value of 0.0 corresponds to a completely transparent color. This uses a wrapper message rather than a simple float scalar so that it is possible to distinguish between a default value and the value being unset. If omitted, this color object is rendered as a solid color (as if the alpha value had been explicitly given a value of 1.0). blue: The amount of blue in the color as a value in the interval [0, 1]. green: The amount of green in the color as a value in the interval [0, 1]. red: The amount of red in the color as a value in the interval [0, 1]. """ alpha = _messages.FloatField(1, variant=_messages.Variant.FLOAT) blue = _messages.FloatField(2, variant=_messages.Variant.FLOAT) green = _messages.FloatField(3, variant=_messages.Variant.FLOAT) red = _messages.FloatField(4, variant=_messages.Variant.FLOAT) class GoogleTypeDate(_messages.Message): r"""Represents a whole or partial calendar date, such as a birthday. The time of day and time zone are either specified elsewhere or are insignificant. The date is relative to the Gregorian Calendar. This can represent one of the following: * A full date, with non-zero year, month, and day values. * A month and day, with a zero year (for example, an anniversary). * A year on its own, with a zero month and a zero day. * A year and month, with a zero day (for example, a credit card expiration date). Related types: * google.type.TimeOfDay * google.type.DateTime * google.protobuf.Timestamp Fields: day: Day of a month. Must be from 1 to 31 and valid for the year and month, or 0 to specify a year by itself or a year and month where the day isn't significant. month: Month of a year. Must be from 1 to 12, or 0 to specify a year without a month and day. year: Year of the date. Must be from 1 to 9999, or 0 to specify a date without a year. """ day = _messages.IntegerField(1, variant=_messages.Variant.INT32) month = _messages.IntegerField(2, variant=_messages.Variant.INT32) year = _messages.IntegerField(3, variant=_messages.Variant.INT32) class GoogleTypeExpr(_messages.Message): r"""Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information. Fields: description: Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI. expression: Textual representation of an expression in Common Expression Language syntax. location: Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file. title: Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression. """ description = _messages.StringField(1) expression = _messages.StringField(2) location = _messages.StringField(3) title = _messages.StringField(4) class GoogleTypeInterval(_messages.Message): r"""Represents a time interval, encoded as a Timestamp start (inclusive) and a Timestamp end (exclusive). The start must be less than or equal to the end. When the start equals the end, the interval is empty (matches no time). When both start and end are unspecified, the interval matches any time. Fields: endTime: Optional. Exclusive end of the interval. If specified, a Timestamp matching this interval will have to be before the end. startTime: Optional. Inclusive start of the interval. If specified, a Timestamp matching this interval will have to be the same or after the start. """ endTime = _messages.StringField(1) startTime = _messages.StringField(2) class GoogleTypeLatLng(_messages.Message): r"""An object that represents a latitude/longitude pair. This is expressed as a pair of doubles to represent degrees latitude and degrees longitude. Unless specified otherwise, this object must conform to the WGS84 standard. Values must be within normalized ranges. Fields: latitude: The latitude in degrees. It must be in the range [-90.0, +90.0]. longitude: The longitude in degrees. It must be in the range [-180.0, +180.0]. """ latitude = _messages.FloatField(1) longitude = _messages.FloatField(2) class GoogleTypeMoney(_messages.Message): r"""Represents an amount of money with its currency type. Fields: currencyCode: The three-letter currency code defined in ISO 4217. nanos: Number of nano (10^-9) units of the amount. The value must be between -999,999,999 and +999,999,999 inclusive. If `units` is positive, `nanos` must be positive or zero. If `units` is zero, `nanos` can be positive, zero, or negative. If `units` is negative, `nanos` must be negative or zero. For example $-1.75 is represented as `units`=-1 and `nanos`=-750,000,000. units: The whole units of the amount. For example if `currencyCode` is `"USD"`, then 1 unit is one US dollar. """ currencyCode = _messages.StringField(1) nanos = _messages.IntegerField(2, variant=_messages.Variant.INT32) units = _messages.IntegerField(3) class StandardQueryParameters(_messages.Message): r"""Query parameters accepted by all methods. Enums: FXgafvValueValuesEnum: V1 error format. AltValueValuesEnum: Data format for response. Fields: f__xgafv: V1 error format. access_token: OAuth access token. alt: Data format for response. callback: JSONP fields: Selector specifying which fields to include in a partial response. key: API key. Your API key identifies your project and provides you with API access, quota, and reports. Required unless you provide an OAuth 2.0 token. oauth_token: OAuth 2.0 token for the current user. prettyPrint: Returns response with indentations and line breaks. quotaUser: Available to use for quota purposes for server-side applications. Can be any arbitrary string assigned to a user, but should not exceed 40 characters. trace: A tracing token of the form "token:" to include in api requests. uploadType: Legacy upload protocol for media (e.g. "media", "multipart"). upload_protocol: Upload protocol for media (e.g. "raw", "multipart"). """ class AltValueValuesEnum(_messages.Enum): r"""Data format for response. Values: json: Responses with Content-Type of application/json media: Media download with context-dependent Content-Type proto: Responses with Content-Type of application/x-protobuf """ json = 0 media = 1 proto = 2 class FXgafvValueValuesEnum(_messages.Enum): r"""V1 error format. Values: _1: v1 error format _2: v2 error format """ _1 = 0 _2 = 1 f__xgafv = _messages.EnumField('FXgafvValueValuesEnum', 1) access_token = _messages.StringField(2) alt = _messages.EnumField('AltValueValuesEnum', 3, default='json') callback = _messages.StringField(4) fields = _messages.StringField(5) key = _messages.StringField(6) oauth_token = _messages.StringField(7) prettyPrint = _messages.BooleanField(8, default=True) quotaUser = _messages.StringField(9) trace = _messages.StringField(10) uploadType = _messages.StringField(11) upload_protocol = _messages.StringField(12) encoding.AddCustomJsonFieldMapping( GoogleCloudAiplatformV1beta1Probe, 'exec_', 'exec') encoding.AddCustomJsonFieldMapping( StandardQueryParameters, 'f__xgafv', '$.xgafv') encoding.AddCustomJsonEnumMapping( StandardQueryParameters.FXgafvValueValuesEnum, '_1', '1') encoding.AddCustomJsonEnumMapping( StandardQueryParameters.FXgafvValueValuesEnum, '_2', '2') encoding.AddCustomJsonFieldMapping( AiplatformProjectLocationsDatasetsGetIamPolicyRequest, 'options_requestedPolicyVersion', 'options.requestedPolicyVersion') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsDatasetsSearchDataItemsRequest, 'orderByAnnotation_orderBy', 'orderByAnnotation.orderBy') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsDatasetsSearchDataItemsRequest, 'orderByAnnotation_savedQuery', 'orderByAnnotation.savedQuery') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsEndpointsGetIamPolicyRequest, 'options_requestedPolicyVersion', 'options.requestedPolicyVersion') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsExampleStoresCreateRequest, 'exampleStore_createTime', 'exampleStore.createTime') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsExampleStoresCreateRequest, 'exampleStore_description', 'exampleStore.description') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsExampleStoresCreateRequest, 'exampleStore_displayName', 'exampleStore.displayName') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsExampleStoresCreateRequest, 'exampleStore_exampleStoreConfig_vertexEmbeddingModel', 'exampleStore.exampleStoreConfig.vertexEmbeddingModel') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsExampleStoresCreateRequest, 'exampleStore_name', 'exampleStore.name') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsExampleStoresCreateRequest, 'exampleStore_updateTime', 'exampleStore.updateTime') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsFeatureGroupsGetIamPolicyRequest, 'options_requestedPolicyVersion', 'options.requestedPolicyVersion') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsFeatureGroupsFeaturesGetRequest, 'featureStatsAndAnomalySpec_latestStatsCount', 'featureStatsAndAnomalySpec.latestStatsCount') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsFeatureGroupsFeaturesGetRequest, 'featureStatsAndAnomalySpec_statsTimeRange_endTime', 'featureStatsAndAnomalySpec.statsTimeRange.endTime') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsFeatureGroupsFeaturesGetRequest, 'featureStatsAndAnomalySpec_statsTimeRange_startTime', 'featureStatsAndAnomalySpec.statsTimeRange.startTime') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsFeatureOnlineStoresGetIamPolicyRequest, 'options_requestedPolicyVersion', 'options.requestedPolicyVersion') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsFeatureOnlineStoresFeatureViewsGetIamPolicyRequest, 'options_requestedPolicyVersion', 'options.requestedPolicyVersion') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsFeaturestoresEntityTypesGetIamPolicyRequest, 'options_requestedPolicyVersion', 'options.requestedPolicyVersion') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesGetRequest, 'featureStatsAndAnomalySpec_latestStatsCount', 'featureStatsAndAnomalySpec.latestStatsCount') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesGetRequest, 'featureStatsAndAnomalySpec_statsTimeRange_endTime', 'featureStatsAndAnomalySpec.statsTimeRange.endTime') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsFeaturestoresEntityTypesFeaturesGetRequest, 'featureStatsAndAnomalySpec_statsTimeRange_startTime', 'featureStatsAndAnomalySpec.statsTimeRange.startTime') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsModelsGetIamPolicyRequest, 'options_requestedPolicyVersion', 'options.requestedPolicyVersion') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsNotebookRuntimeTemplatesGetIamPolicyRequest, 'options_requestedPolicyVersion', 'options.requestedPolicyVersion') encoding.AddCustomJsonFieldMapping( AiplatformProjectsLocationsPublishersModelsGetIamPolicyRequest, 'options_requestedPolicyVersion', 'options.requestedPolicyVersion')