BSrSSKJr SSKJr SSKJr SSKrSSKJr SSK J r SSK J r SS KJr SS KJr SS KJr SSKJr SS KJr SS KJr SSKJr SSKJr SSKJr SSKJr SSKJr SSKJr \R>"\R@RB\R@RD\R@RF5\RH"SS\RJ555r&g)zModel Garden deploy command.)absolute_import)division)unicode_literalsN) exceptions) operations)client)apis) arg_parsers)base) constants) endpoint_util)flags)model_garden_utils) region_util) validation)_IsDefaultUniverse) propertiesc.\rSrSrSr\S5rSrSrg)Deploy*aCDeploy a model in Model Garden to a Vertex AI endpoint. ## EXAMPLES To deploy a Model Garden model `google/gemma2/gemma2-9b` under project `example` in region `us-central1`, run: $ gcloud ai model-garden models deploy --model=google/gemma2@gemma-2-9b --project=example --region=us-central1 To deploy a Hugging Face model `meta-llama/Meta-Llama-3-8B` under project `example` in region `us-central1`, run: $ gcloud ai model-garden models deploy --model=meta-llama/Meta-Llama-3-8B --hugging-face-access-token={hf_token} --project=example --region=us-central1 c [R"SSSS9RU5 [R"SSSS9RU5 [R"SSS S9RU5 [R"US [ R S 9 [R"S S SS9RU5 [R"SSSS9RU5 [R"SS[SS9RU5 [R"SSSSSS9RU5 [R"SSSSSS9RU5 [R"S[R"[[[R"5S.S/S9SS9RU5 [R"S SSSS!S"9RU5 [R"S#SSSS$S"9RU5 [R"S%SSSS&S"9RU5 [R"S'S(S)9RU5 URS*S+[R"5[RS,S-9 URS.[R"5S/[RS0S19 URS2S3[R"5S4S59 URS6S7[R"[R"S8S95S:9[RS;S-9 URSS?S)9 URS@SAS)9 URSB[SCS9 URSD[SES9 URSF[R"5SGSHSI9 URSJ[SKS9 URSL[SMS9 URSN[R"5SOSPSI9 URSQ[SRS9 URSS[STS9 g)UN--modelTaThe model to be deployed. If it is a Model Garden model, it should be in the format of `{publisher_name}/{model_name}@{model_version_name}, e.g. `google/gemma2@gemma-2-2b`. If it is a Hugging Face model, it should be in the convention of Hugging Face models, e.g. `meta-llama/Meta-Llama-3-8B`. If it is a Custom Weights model, it should be in the format of `gs://{gcs_bucket_uri}`, e.g. `gs://-model-garden-public-us/llama3.1/Meta-Llama-3.1-8B-Instruct`.)requiredhelpz--hugging-face-access-tokenFzThe access token from Hugging Face needed to read the model artifacts of gated models. It is only needed when the Hugging Face model to deploy is gated.z--endpoint-display-namez5Display name of the endpoint with the deployed model.zto deploy the model) prompt_funcz--machine-typezThe machine type to deploy the model to. It should be a supported machine type from the deployment configurations of the model. Use `gcloud ai model-garden models list-deployment-config` to check the supported machine types.)rrz--accelerator-typezThe accelerator type to serve the model. It should be a supported accelerator type from the verified deployment configurations of the model. Use `gcloud ai model-garden models list-deployment-config` to check the supported accelerator types.z--accelerator-countzSThe accelerator count to serve the model. Accelerator count should be non-negative.)rtyperz --accept-eulazNWhen set, the user accepts the End User License Agreement (EULA) of the model. store_true)ractiondefaultrz--asynchronouszaIf set to true, the command will terminate immediately and not keep polling the operation status.z--reservation-affinity)reservation-affinity-typekeyvaluesr )spec required_keyszA 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.)rrz--spotz5If true, schedule the deployment workload on Spot VM.)rrrrz--use-dedicated-endpointzIf true, the endpoint will be exposed through a dedicated DNS. Your request to the dedicated DNS will be isolated from other users' traffic and will have better performance and reliability.z--enable-fast-tryoutzIf True, model will be deployed using faster deployment path. Useful for quick experiments. Not for production workloads. Only available for most popular models with certain machine types.z--container-image-uriz{ URI of the Model serving container file in the Container Registry (e.g. gcr.io/myproject/server:latest). )rz--container-env-varsz KEY=VALUEz8List of key-value pairs to set as environment variables.)metavarrrrz--container-commandCOMMANDzm Entrypoint for the container image. If not specified, the container image's default entrypoint is run. )rr%rrz--container-argsARGz Comma-separated arguments passed to the command run by the container image. If not specified and no `--command` is provided, the container image's default command is used. )r%rrz--container-portsPORTi) element_typezd Container ports to receive http requests at. Must be a number between 1 and 65535, inclusive. z--container-grpc-portszd Container ports to receive grpc requests at. Must be a number between 1 and 65535, inclusive. z--container-predict-routez>HTTP path to send prediction requests to inside the container.z--container-health-routez8HTTP path to send health checks to inside the container.z&--container-deployment-timeout-secondszDeployment timeout in seconds.z!--container-shared-memory-size-mbz` The amount of the VM memory to reserve as the shared memory for the model in megabytes. z--container-startup-probe-execSTARTUP_PROBE_EXECz Exec specifies the action to take. Used by startup probe. An example of this argument would be ["cat", "/tmp/healthy"]. )rr%rz(--container-startup-probe-period-secondszh How often (in seconds) to perform the startup probe. Default to 10 seconds. Minimum value is 1. z)--container-startup-probe-timeout-secondszm Number of seconds after which the startup probe times out. Defaults to 1 second. Minimum value is 1. z--container-health-probe-execHEALTH_PROBE_EXECz Exec specifies the action to take. Used by health probe. An example of this argument would be ["cat", "/tmp/healthy"]. z'--container-health-probe-period-secondszg How often (in seconds) to perform the health probe. Default to 10 seconds. Minimum value is 1. z(--container-health-probe-timeout-secondszl Number of seconds after which the health probe times out. Defaults to 1 second. Minimum value is 1. )r Argument AddToParserrAddRegionResourceArgrPromptForOpRegionintr ArgDictstrArgList add_argument UpdateAction BoundedInt)parsers ,lib/surface/ai/model_garden/models/deploy.pyArgs Deploy.ArgsFsMM L k&MM% : k&MM! Dk& %;3P3P MM ,  k&MM Q  k&MM 'k&MM  k&MM 2 k&MM  -0%--/ 77   # k&MM D  k&MM" P k&MM M k&MM  k&   "'' G    "''     "     k.D.DQ.N O''      k.D.DQ.N O''   # M " G 0  -  +  (  "$  2  3  '  "#  1  2 c  URRS5nU(d[R"U5 [R"UR 5 UR RR5nUR5SUl[RnSUR;n[5(aSOSn[R"XFS9 U(Ga[UR 5[UR"5s=:Xa[UR$5:XdO [&R("SS5eSnUR (a[*R,"UUR UR"UR$S9 [.R0"[R2[R4U5nUR6R9UR UR6R8R;UR"5UR$S 9n[R"XARS9 S R=S [?[@R@"55RCS 5S S/5n [DRF"5n [HRJ"US9n UR (a UR OU n [*RL"UUU URU U 5 SSS5 GOM[DRF"5n U(a^URRO5RCS5upU RQSU SU3SS9nS R=XSS/5n U SU3nOrURRO5RCS5un nU RQSU SU35nS R=U URCS5SS/5n SU SU3n[*RX"X5n[*R,"UURZR\R^[?URZR\R`5URZR\RbS9 [dRfRhRjRmS5 [R"XARS9 [DRF"5n [HRJ"US9n UR (a UR OU n [*RL"UURZR\U UU U 5 SSS5 SSS5 g!,(df  N=f![RRTa% [&RV"SURS35ef=f![RRTa% [&RV"SURS35ef=f!,(df  N=f!,(df  g=f)Nzgs:// locationsId@z us-central1)regionz:--machine-type, --accelerator-type and --accelerator-countz Arguments for MachineType, AcceleratorType and AcceleratorCount must either all be provided or all be empty for custom weights model deployment.) machine_typeaccelerator_typeaccelerator_count) machineTypeacceleratorTypeacceleratorCount-zcustom-weights.rz mg-cli-deploy)version/z publishers/z/models/T) model_nameis_hugging_face_modelrzF is not a supported Hugging Face model for deployment in Model Garden.hfzF is not a supported Model Garden model for deployment in Model Garden.r))7model startswithrValidateModelGardenModelArgsValidateDisplayNameendpoint_display_nameCONCEPTSr@ParseAsDictr BETA_VERSIONrr AiplatformEndpointOverridesboolrArBrC c_exceptionsInvalidArgumentExceptionrCheckAcceleratorQuotar GetClientInstanceAI_PLATFORM_API_NAMEAI_PLATFORM_API_VERSIONMESSAGES_MODULE'GoogleCloudAiplatformV1beta1MachineSpecAcceleratorTypeValueValuesEnumjoinr3timesplit client_mgModelGardenClientrOperationsClientrlowerGetPublisherModelapitools_exceptionsHttpNotFoundErrorUnknownArgumentExceptionGetDeployConfigdedicatedResources machineSpecrDrErFrVALUESapi_endpoint_overrides aiplatformSet)selfargsis_custom_weights_model region_refrI is_hf_modelr@ machine_specrdefault_endpoint_name mg_clientoperation_client endpoint_namepublisher_namerKpublisher_model api_model_argmodel_and_version_name deploy_configs r9Run Deploy.RunJs\"jj33G< "--d3""4#=#=>%%++-J##%m4DK$$GTZZ'K022]F  2 27 J  "" #D))* ,D**+ ,55J#       2 2,,#44 $ 6 6  )),,//8 &  //WW++$44\\{{'' $55 X , 6 6 KK #&(($))+$$S)!,, #   113)'88I ++(((   # #jj  !  8//1 '+zz'7'7'9'?'?'D $. '99((8 M&*:O#&((4A# ,,Aj\:-48::3C3C3E3K3KC3P 0.0 '99n-X6L5MNO#&(($**3/2, #  N+84J3KL +::  00 &99EEQQ 00<<LL,>>JJ[[   00;;??E 6 6 KK  113)'88I ++(((   # #..::   C K JN  L%66 77::,99  &%66 77::,//  B  C K JsrE W%;B0U +AW%=UAW%V3DW%A8W:W% U W%9VW%9WW% W" W%% W3N) __name__ __module__ __qualname____firstlineno____doc__ staticmethodr:r__static_attributes__rr<r9rr*s$ .AAF^ r<r)'r __future__rrrrcapitools.base.pyrrjgooglecloudsdk.api_lib.air&googlecloudsdk.api_lib.ai.model_gardenrregooglecloudsdk.api_lib.utilr googlecloudsdk.callioper r rYgooglecloudsdk.command_lib.air r rrrr)googlecloudsdk.command_lib.ai.region_utilrgooglecloudsdk.corer ReleaseTracks ReleaseTrackALPHABETAGAUniverseCompatibleCommandrrr<r9rs#&' >0F,/(>37/<54+T..33T5F5F5I5Iz T\\z z r<