f:VSrSSKJr SSKJr SSKJr "SS\R5r g)z7Generated client library for gkerecommender version v1.)absolute_import)base_api)gkerecommender_v1_messagesc^\rSrSrSr\rSrSrSr S/r Sr Sr S r S rSrSrS rS U4S jjr"S S\R(5r"SS\R(5r"SS\R(5r"SS\R(5r"SS\R(5r"SS\R(5r"SS\R(5r"SS\R(5r"SS\R(5rSrU=r$)!GkerecommenderV1 z?Generated client library for service gkerecommender version v1.z&https://gkerecommender.googleapis.com/z+https://gkerecommender.mtls.googleapis.com/gkerecommenderz.https://www.googleapis.com/auth/cloud-platformv1 CLIENT_ID CLIENT_SECRETzgoogle-cloud-sdkNc >U=(d URn[[U]XX4UXgUU U U S9 UR U5UlUR U5UlURU5Ul URU5Ul URU5Ul URU5UlUR!U5UlUR%U5UlUR)U5Ulg)z#Create a new gkerecommender handle.) credentialsget_credentialshttpmodel log_request log_responsecredentials_argsdefault_global_paramsadditional_http_headersresponse_encodingN)BASE_URLsuperr__init__BenchmarkingDataServicebenchmarkingDataModelServerVersionsServicemodelServerVersionsModelServersService modelServers ModelsServicemodelsOptimizedManifestServiceoptimizedManifestProfilesServiceprofilesServingStackVersionsServiceservingStackVersionsServingStacksService servingStacksUseCasesServiceuseCases) selfurlrrrrrrrrrr __class__s Wlib/googlecloudsdk/generated_clients/apis/gkerecommender/v1/gkerecommender_v1_client.pyrGkerecommenderV1.__init__s  C D* '%)3 7++-!88>D#>>tDD006D$$T*DK!::4@D((.DM $ @ @ FD2248D((.DMcJ^\rSrSrSrSrU4SjrSSjrS\lSr U=r $) (GkerecommenderV1.BenchmarkingDataService4z0Service class for the benchmarkingData resource.rcN>[[RU]U5 0UlgN)rrrr_upload_configsr-clientr/s r0r1GkerecommenderV1.BenchmarkingDataService.__init__9s#  4 4dDVL dr2cDURS5nURX1US9$)aFetches all of the benchmarking data available for a profile. Benchmarking data returns all of the performance metrics available for a given model server setup on a given instance type. Args: request: (FetchBenchmarkingDataRequest) input message global_params: (StandardQueryParameters, default: None) global arguments Returns: (FetchBenchmarkingDataResponse) The response message. Fetch global_paramsGetMethodConfig _RunMethodr-requestr?configs r0r=.GkerecommenderV1.BenchmarkingDataService.Fetch>/##G,f __ 88r2c <[R"SS///SSSSSS9 $) NPOSTz%gkerecommender.benchmarkingData.fetchzv1/benchmarkingData:fetch FetchBenchmarkingDataRequestFetchBenchmarkingDataResponseF http_method method_idordered_params path_params query_params relative_path request_fieldrequest_type_nameresponse_type_namesupports_downloadr ApiMethodInfor2r01GkerecommenderV1.BenchmarkingDataService.Ks-("8"891!8: #r2r8r7 __name__ __module__ __qualname____firstlineno____doc___NAMErr= method_config__static_attributes__ __classcell__r/s@r0rr44s": E 8 Er2rcJ^\rSrSrSrSrU4SjrSSjrS\lSr U=r $) +GkerecommenderV1.ModelServerVersionsServiceXz3Service class for the modelServerVersions resource.rcN>[[RU]U5 0Ulgr7)rrrrr8r9s r0r4GkerecommenderV1.ModelServerVersionsService.__init__]s#  7 7GO dr2cDURS5nURX1US9$)aWFetches available model server versions. Open-source servers use their own versioning schemas (e.g., `vllm` uses semver like `v1.0.0`). Some model servers have different versioning schemas depending on the accelerator. For example, `vllm` uses semver on GPUs, but returns nightly build tags on TPUs. All available versions will be returned when different schemas are present. Args: request: (GkerecommenderModelServerVersionsFetchRequest) input message global_params: (StandardQueryParameters, default: None) global arguments Returns: (FetchModelServerVersionsResponse) The response message. r=r>r@rCs r0r=1GkerecommenderV1.ModelServerVersionsService.FetchbrGr2c @[R"SS///SQSSSSSS 9 $) NGETz(gkerecommender.modelServerVersions.fetchr modelServerpageSize pageTokenzv1/modelServerVersions:fetch-GkerecommenderModelServerVersionsFetchRequest FetchModelServerVersionsResponseFrMrXrZr2r0r[4GkerecommenderV1.ModelServerVersionsService.os-("8"8<F4I= #r2r]r7r^rhs@r0rrjXs"= !E 8 Er2rcJ^\rSrSrSrSrU4SjrSSjrS\lSr U=r $) $GkerecommenderV1.ModelServersService|z,Service class for the modelServers resource.r cN>[[RU]U5 0Ulgr7)rrrrr8r9s r0r-GkerecommenderV1.ModelServersService.__init__s#  0 0$@H dr2cDURS5nURX1US9$)a<Fetches available model servers. Open-source model servers use simplified, lowercase names (e.g., `vllm`). Args: request: (GkerecommenderModelServersFetchRequest) input message global_params: (StandardQueryParameters, default: None) global arguments Returns: (FetchModelServersResponse) The response message. r=r>r@rCs r0r=*GkerecommenderV1.ModelServersService.FetchrGr2c @[R"SS///SQSSSSSS 9 $) Nrqz!gkerecommender.modelServers.fetch)rrtruzv1/modelServers:fetchrv&GkerecommenderModelServersFetchRequestFetchModelServersResponseFrMrXrZr2r0r[-GkerecommenderV1.ModelServersService.s-("8"857-B6 #r2r]r7r^rhs@r0rr{|s"6 E 8 Er2rcJ^\rSrSrSrSrU4SjrSSjrS\lSr U=r $) GkerecommenderV1.ModelsServicez&Service class for the models resource.r"cN>[[RU]U5 0Ulgr7)rrr!rr8r9s r0r'GkerecommenderV1.ModelsService.__init__s#  * *D:6B dr2cDURS5nURX1US9$)a(Fetches available models. Open-source models follow the Huggingface Hub `owner/model_name` format. Args: request: (GkerecommenderModelsFetchRequest) input message global_params: (StandardQueryParameters, default: None) global arguments Returns: (FetchModelsResponse) The response message. r=r>r@rCs r0r=$GkerecommenderV1.ModelsService.FetchrGr2c @[R"SS//SS/SSSSS S 9 $) Nrqzgkerecommender.models.fetchrtruzv1/models:fetchrv GkerecommenderModelsFetchRequestFetchModelsResponseFrMrXrZr2r0r['GkerecommenderV1.ModelsService.s2("8"8/ +.'<0 #r2r]r7r^rhs@r0r!rs"0 E 8 Er2r!cJ^\rSrSrSrSrU4SjrSSjrS\lSr U=r $) )GkerecommenderV1.OptimizedManifestServicez1Service class for the optimizedManifest resource.r$cN>[[RU]U5 0Ulgr7)rrr#rr8r9s r0r2GkerecommenderV1.OptimizedManifestService.__init__s#  5 5tEfM dr2cDURS5nURX1US9$)a7Generates an optimized deployment manifest for a given model and model server, based on the specified accelerator, performance targets, and configurations. See [Run best practice inference with GKE Inference Quickstart recipes](https://cloud.google.com/kubernetes-engine/docs/how-to/machine-learning/inference/inference-quickstart) for deployment details. Args: request: (GenerateOptimizedManifestRequest) input message global_params: (StandardQueryParameters, default: None) global arguments Returns: (GenerateOptimizedManifestResponse) The response message. Generater>r@rCs r0r2GkerecommenderV1.OptimizedManifestService.Generates/##J/f __ 88r2c <[R"SS///SSSSSS9 $) NrIz)gkerecommender.optimizedManifest.generatezv1/optimizedManifest:generaterJ GenerateOptimizedManifestRequest!GenerateOptimizedManifestResponseFrMrXrZr2r0r[2GkerecommenderV1.OptimizedManifestService.s-X%;%;=5!<> &r2r]r7) r_r`rarbrcrdrrrerfrgrhs@r0r#rs"; E 8 Hr2r#cJ^\rSrSrSrSrU4SjrSSjrS\lSr U=r $) GkerecommenderV1.ProfilesServicez(Service class for the profiles resource.r&cN>[[RU]U5 0Ulgr7)rrr%rr8r9s r0r)GkerecommenderV1.ProfilesService.__init__#  , ,dr@rCs r0r=&GkerecommenderV1.ProfilesService.FetchrGr2c <[R"SS///SSSSSS9 $) NrIzgkerecommender.profiles.fetchzv1/profiles:fetchrJFetchProfilesRequestFetchProfilesResponseFrMrXrZr2r0r[)GkerecommenderV1.ProfilesService.-("8"81)!02 #r2r]r7r^rhs@r0r%r"2 E 8 Er2r%cJ^\rSrSrSrSrU4SjrSSjrS\lSr U=r $) ,GkerecommenderV1.ServingStackVersionsServicei z4Service class for the servingStackVersions resource.r(cN>[[RU]U5 0Ulgr7)rrr'rr8r9s r0r5GkerecommenderV1.ServingStackVersionsService.__init__s#  8 8$HP dr2cDURS5nURX1US9$)a Fetches available serving stack versions. Args: request: (GkerecommenderServingStackVersionsFetchRequest) input message global_params: (StandardQueryParameters, default: None) global arguments Returns: (FetchServingStackVersionsResponse) The response message. r=r>r@rCs r0r=2GkerecommenderV1.ServingStackVersionsService.FetchrGr2c @[R"SS///SQSSSSSS 9 $) Nrqz)gkerecommender.servingStackVersions.fetch)rrsrtru servingStackzv1/servingStackVersions:fetchrv.GkerecommenderServingStackVersionsFetchRequest!FetchServingStackVersionsResponseFrMrXrZr2r0r[5GkerecommenderV1.ServingStackVersionsService.#s-("8"8=V5J> #r2r]r7r^rhs@r0r'r s"> "E 8 Er2r'cJ^\rSrSrSrSrU4SjrSSjrS\lSr U=r $) %GkerecommenderV1.ServingStacksServicei0z-Service class for the servingStacks resource.r*cN>[[RU]U5 0Ulgr7)rrr)rr8r9s r0r.GkerecommenderV1.ServingStacksService.__init__5s#  1 14A&I dr2cDURS5nURX1US9$)zFetches available serving stacks. Args: request: (GkerecommenderServingStacksFetchRequest) input message global_params: (StandardQueryParameters, default: None) global arguments Returns: (FetchServingStacksResponse) The response message. r=r>r@rCs r0r=+GkerecommenderV1.ServingStacksService.Fetch:rGr2c @[R"SS///SQSSSSSS 9 $) Nrqz"gkerecommender.servingStacks.fetchrrzv1/servingStacks:fetchrv'GkerecommenderServingStacksFetchRequestFetchServingStacksResponseFrMrXrZr2r0r[.GkerecommenderV1.ServingStacksService.Gs-("8"86F.C7 #r2r]r7r^rhs@r0r)r0s"7 E 8 Er2r)cJ^\rSrSrSrSrU4SjrSSjrS\lSr U=r $) GkerecommenderV1.UseCasesServiceiTz(Service class for the useCases resource.r,cN>[[RU]U5 0Ulgr7)rrr+rr8r9s r0r)GkerecommenderV1.UseCasesService.__init__Yrr2cDURS5nURX1US9$)a Fetches all of the use cases available in the GKE Inference Quickstart database. Args: request: (FetchUseCasesRequest) input message global_params: (StandardQueryParameters, default: None) global arguments Returns: (FetchUseCasesResponse) The response message. r=r>r@rCs r0r=&GkerecommenderV1.UseCasesService.Fetch^rGr2c <[R"SS///SSSSSS9 $) NrIzgkerecommender.useCases.fetchzv1/useCases:fetchrJFetchUseCasesRequestFetchUseCasesResponseFrMrXrZr2r0r[)GkerecommenderV1.UseCasesService.krr2r]r7r^rhs@r0r+rTrr2r+) rrr r"r$r&r(r*r,) rvNTNNFFNNNN) r_r`rarbrcmessagesMESSAGES_MODULEr MTLS_BASE_URL_PACKAGE_SCOPES_VERSION _CLIENT_ID_CLIENT_SECRET _USER_AGENT_CLIENT_CLASS_NAME _URL_VERSION_API_KEYrrBaseApiServicerrrr!r#r%r'r)r+rfrgrhs@r0rr s G/ 5(?- ( = >' (*"."+), ()-6:/4<@?C /2" 7 7"H"8#:#:"H"H33"H"h--"H"!8!8"H"//"H"H$;$;"H"X44"H"//""r2rN) rc __future__rapitools.base.pyr7googlecloudsdk.generated_clients.apis.gkerecommender.v1rr BaseApiClientrrZr2r0rs'='%jlx--lr2