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@swamp/gcp/aiplatform

v2026.04.15.1

Google Cloud aiplatform infrastructure models

Platforms

linux-x86_64linux-aarch64darwin-x86_64darwin-aarch64

Labels

gcpgoogle-cloudaiplatformcloudinfrastructure

Contents

models

Install

$ swamp extension pull @swamp/gcp/aiplatform

Release Notes

  • Updated: evaluationruns, reasoningengines, reasoningengines_sandboxenvironmenttemplates, reasoningengines_sandboxenvironments, tuningjobs

tuningjobs.tsv2026.04.15.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
baseModel?stringThe base model that is being tuned. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/tuning#supported_models).
description?stringOptional. The description of the TuningJob.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
error?objectThe status code, which should be an enum value of google.rpc.Code.
labels?recordOptional. 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.
preTunedModel?objectOutput only. The name of the base model this PreTunedModel was tuned from.
preferenceOptimizationSpec?objectOptional. 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.
serviceAccount?stringThe 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.
supervisedTuningSpec?objectOptional. 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}`
tunedModel?objectThe ID of the checkpoint.
tunedModelDisplayName?stringOptional. 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?objectOutput only. A partial sample of the indices (starting from 1) of the dropped examples.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a tuningJobs
getGet a tuningJobs
ArgumentTypeDescription
identifierstringThe name of the tuningJobs
syncSync tuningJobs state from GCP
cancelcancel
rebase_tuned_modelrebase tuned model
ArgumentTypeDescription
artifactDestination?any
deployToSameEndpoint?any
tunedModelRef?any
tuningJob?any
datalabelingjobs.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
activeLearningConfig?objectMax number of human labeled DataItems.
annotationLabels?recordLabels 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.
currentSpend?objectThe three-letter currency code defined in ISO 4217.
datasets?arrayRequired. Dataset resource names. Right now we only support labeling from a single Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`
displayName?stringRequired. 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?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
error?objectThe status code, which should be an enum value of google.rpc.Code.
inputs?stringRequired. Input config parameters for the DataLabelingJob.
inputsSchemaUri?stringRequired. 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?stringRequired. 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?numberRequired. Number of labelers to work on each DataItem.
specialistPools?arrayThe SpecialistPools' resource names associated with this job.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a dataLabelingJobs
getGet a dataLabelingJobs
ArgumentTypeDescription
identifierstringThe name of the dataLabelingJobs
deleteDelete the dataLabelingJobs
ArgumentTypeDescription
identifierstringThe name of the dataLabelingJobs
syncSync dataLabelingJobs state from GCP
cancelcancel
notebookexecutionjobs.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
customEnvironmentSpec?objectThe number of accelerators to attach to the machine. For accelerator optimized machine types (https://cloud.google.com/compute/docs/accelerator-optimized-machines), One may set the accelerator_count from 1 to N for machine with N GPUs. If accelerator_count is less than or equal to N / 2, Vertex will co-schedule the replicas of the model into the same VM to save cost. For example, if the machine type is a3-highgpu-8g, which has 8 H100 GPUs, one can set accelerator_count to 1 to 8. If accelerator_count is 1, 2, 3, or 4, Vertex will co-schedule 8, 4, 2, or 2 replicas of the model into the same VM to save cost. When co-scheduling, CPU, memory and storage on the VM will be distributed to replicas on the VM. For example, one can expect a co-scheduled replica requesting 2 GPUs out of a 8-GPU VM will receive 25% of the CPU, memory and storage of the VM. Note that the feature is not compatible with multihost_gpu_node_count. When multihost_gpu_node_count is set, the co-scheduling will not be enabled.
dataformRepositorySource?objectThe commit SHA to read repository with. If unset, the file will be read at HEAD.
directNotebookSource?objectThe base64-encoded contents of the input notebook file.
displayName?stringThe display name of the NotebookExecutionJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
executionTimeout?stringMax running time of the execution job in seconds (default 86400s / 24 hrs).
executionUser?stringThe user email to run the execution as. Only supported by Colab runtimes.
gcsNotebookSource?objectThe 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.
gcsOutputUri?stringThe Cloud Storage location to upload the result to. Format: `gs://bucket-name`
kernelName?stringThe name of the kernel to use during notebook execution. If unset, the default kernel is used.
labels?recordThe 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.
notebookRuntimeTemplateResourceName?stringThe NotebookRuntimeTemplate to source compute configuration from.
scheduleResourceName?stringThe Schedule resource name if this job is triggered by one. Format: `projects/{project_id}/locations/{location}/schedules/{schedule_id}`
serviceAccount?stringThe service account to run the execution as.
status?objectThe status code, which should be an enum value of google.rpc.Code.
workbenchRuntime?objectConfiguration for a Workbench Instances-based environment.
notebookExecutionJobId?stringOptional. User specified ID for the NotebookExecutionJob.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a notebookExecutionJobs
getGet a notebookExecutionJobs
ArgumentTypeDescription
identifierstringThe name of the notebookExecutionJobs
deleteDelete the notebookExecutionJobs
ArgumentTypeDescription
identifierstringThe name of the notebookExecutionJobs
syncSync notebookExecutionJobs state from GCP
schedules.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
allowQueueing?booleanOptional. 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.
createNotebookExecutionJobRequest?objectOutput only. Timestamp when this NotebookExecutionJob was created.
createPipelineJobRequest?objectRequired. The resource name of the Location to create the PipelineJob in. Format: `projects/{project}/locations/{location}`
cron?stringCron 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?stringRequired. User provided name of the Schedule. The name can be up to 128 characters long and can consist of any UTF-8 characters.
endTime?stringOptional. 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.
lastScheduledRunResponse?objectThe response of the scheduled run.
maxConcurrentActiveRunCount?stringOptional. Specifies the maximum number of active runs that can be executed concurrently for this Schedule. This limits the number of runs that can be in a non-terminal state at the same time. Currently, this field is only supported for requests of type CreatePipelineJobRequest.
maxConcurrentRunCount?stringRequired. 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?stringOptional. 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?stringImmutable. The resource name of the Schedule.
startTime?stringOptional. Timestamp after which the first run can be scheduled. Default to Schedule create time if not specified.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a schedules
ArgumentTypeDescription
waitForReady?booleanWait for the resource to reach a ready state after creation (default: true)
getGet a schedules
ArgumentTypeDescription
identifierstringThe name of the schedules
updateUpdate schedules attributes
ArgumentTypeDescription
waitForReady?booleanWait for the resource to reach a ready state after update (default: true)
deleteDelete the schedules
ArgumentTypeDescription
identifierstringThe name of the schedules
syncSync schedules state from GCP
pausepause
resumeresume
ArgumentTypeDescription
catchUp?any
reasoningengines_memories_revisions.tsv2026.04.11.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a revisions
ArgumentTypeDescription
identifierstringThe name of the revisions
syncSync revisions state from GCP
nasjobs_nastrialdetails.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a nasTrialDetails
ArgumentTypeDescription
identifierstringThe name of the nasTrialDetails
syncSync nasTrialDetails state from GCP
reasoningengines_sandboxenvironmenttemplates.tsv2026.04.15.1

Global Arguments

ArgumentTypeDescription
customContainerEnvironment?objectRequired. The Artifact Registry Docker image URI (e.g., us-central1-docker.pkg.dev/my-project/my-repo/my-image:tag) of the container image that is to be run on each worker replica.
defaultContainerEnvironment?objectRequired. The category of the default container image.
displayName?stringRequired. The display name of the SandboxEnvironmentTemplate.
egressControlConfig?objectOptional. Whether to allow internet access.
name?stringIdentifier. The resource name of the SandboxEnvironmentTemplate. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentTemplates/{sandbox_environment_template}`
warmPoolConfig?objectOptional. The target number of pre-warmed instances to maintain.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a sandboxEnvironmentTemplates
ArgumentTypeDescription
waitForReady?booleanWait for the resource to reach a ready state after creation (default: true)
getGet a sandboxEnvironmentTemplates
ArgumentTypeDescription
identifierstringThe name of the sandboxEnvironmentTemplates
deleteDelete the sandboxEnvironmentTemplates
ArgumentTypeDescription
identifierstringThe name of the sandboxEnvironmentTemplates
syncSync sandboxEnvironmentTemplates state from GCP
endpoints.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
clientConnectionConfig?objectCustomizable online prediction request timeout.
dedicatedEndpointEnabled?booleanIf 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.
description?stringThe description of the Endpoint.
displayName?stringRequired. The display name of the Endpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
gdcConfig?objectGDC zone. A cluster will be designated for the Vertex AI workload in this zone.
genAiAdvancedFeaturesConfig?objectIf true, enable Retrieval Augmented Generation in ChatCompletion request. Once enabled, the endpoint will be identified as GenAI endpoint and Arthedain router will be used.
labels?recordThe 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.
name?stringIdentifier. The resource name of the Endpoint.
network?stringOptional. 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. [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.
predictRequestResponseLoggingConfig?objectRequired. 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`.
privateServiceConnectConfig?objectRequired. If true, expose the IndexEndpoint via private service connect.
trafficSplit?recordA 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.
endpoint?objectCustomizable online prediction request timeout.
endpointId?stringImmutable. 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a endpoints
getGet a endpoints
ArgumentTypeDescription
identifierstringThe name of the endpoints
updateUpdate endpoints attributes
deleteDelete the endpoints
ArgumentTypeDescription
identifierstringThe name of the endpoints
syncSync endpoints state from GCP
compute_tokenscompute tokens
ArgumentTypeDescription
contents?any
instances?any
model?any
count_tokenscount tokens
ArgumentTypeDescription
contents?any
generationConfig?any
instances?any
model?any
systemInstruction?any
tools?any
deploy_modeldeploy model
ArgumentTypeDescription
deployedModel?any
trafficSplit?any
direct_predictdirect predict
ArgumentTypeDescription
inputs?any
parameters?any
direct_raw_predictdirect raw predict
ArgumentTypeDescription
input?any
methodName?any
explainexplain
ArgumentTypeDescription
deployedModelId?any
explanationSpecOverride?any
instances?any
parameters?any
fetch_predict_operationfetch predict operation
ArgumentTypeDescription
operationName?any
generate_contentgenerate content
ArgumentTypeDescription
cachedContent?any
contents?any
generationConfig?any
labels?any
modelArmorConfig?any
safetySettings?any
systemInstruction?any
toolConfig?any
tools?any
mutate_deployed_modelmutate deployed model
ArgumentTypeDescription
deployedModel?any
updateMask?any
predictpredict
ArgumentTypeDescription
inputs?any
parameters?any
predict_long_runningpredict long running
ArgumentTypeDescription
instances?any
labels?any
parameters?any
raw_predictraw predict
ArgumentTypeDescription
input?any
methodName?any
server_streaming_predictserver streaming predict
ArgumentTypeDescription
inputs?any
parameters?any
stream_generate_contentstream generate content
ArgumentTypeDescription
cachedContent?any
contents?any
generationConfig?any
labels?any
modelArmorConfig?any
safetySettings?any
systemInstruction?any
toolConfig?any
tools?any
stream_raw_predictstream raw predict
ArgumentTypeDescription
httpBody?any
undeploy_modelundeploy model
ArgumentTypeDescription
deployedModelId?any
trafficSplit?any
ragcorpora.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
corpusStatus?objectOutput only. Only when the `state` field is ERROR.
description?stringOptional. The description of the RagCorpus.
displayName?stringRequired. The display name of the RagCorpus. The name can be up to 128 characters long and can consist of any UTF-8 characters.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
vectorDbConfig?objectRequired. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
vertexAiSearchConfig?objectVertex AI Search Serving Config resource full name. For example, `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}/servingConfigs/{serving_config}` or `projects/{project}/locations/{location}/collections/{collection}/dataStores/{data_store}/servingConfigs/{serving_config}`.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a ragCorpora
getGet a ragCorpora
ArgumentTypeDescription
identifierstringThe name of the ragCorpora
updateUpdate ragCorpora attributes
deleteDelete the ragCorpora
ArgumentTypeDescription
identifierstringThe name of the ragCorpora
syncSync ragCorpora state from GCP
pipelinejobs.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
displayName?stringThe display name of the Pipeline. The name can be up to 128 characters long and can consist of any UTF-8 characters.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
error?objectThe status code, which should be an enum value of google.rpc.Code.
jobDetail?objectOutput only. Timestamp when this Context was created.
labels?recordThe 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.
network?stringThe 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.
pipelineSpec?recordA compiled definition of a pipeline, represented as a `JSON` object. Defines the structure of the pipeline, including its components, tasks, and parameters. This specification is generated by compiling a pipeline function defined in `Python` using the `Kubeflow Pipelines SDK`.
preflightValidations?booleanOptional. Whether to do component level validations before job creation.
pscInterfaceConfig?objectRequired. The DNS name suffix of the zone being peered to, e.g., "my-internal-domain.corp.". Must end with a dot.
reservedIpRanges?arrayA 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?objectRepresents 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.
serviceAccount?stringThe 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.
templateMetadata?objectThe 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...".
templateUri?stringA 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.
pipelineJobId?stringThe 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-/`.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a pipelineJobs
getGet a pipelineJobs
ArgumentTypeDescription
identifierstringThe name of the pipelineJobs
deleteDelete the pipelineJobs
ArgumentTypeDescription
identifierstringThe name of the pipelineJobs
syncSync pipelineJobs state from GCP
batch_cancelbatch cancel
ArgumentTypeDescription
names?any
batch_deletebatch delete
ArgumentTypeDescription
names?any
cancelcancel
ArgumentTypeDescription
names?any
datasets_datasetversions.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
displayName?stringThe user-defined name of the DatasetVersion. The name can be up to 128 characters long and can consist of any UTF-8 characters.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a datasetVersions
getGet a datasetVersions
ArgumentTypeDescription
identifierstringThe name of the datasetVersions
updateUpdate datasetVersions attributes
deleteDelete the datasetVersions
ArgumentTypeDescription
identifierstringThe name of the datasetVersions
syncSync datasetVersions state from GCP
restorerestore
datasets_annotationspecs.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
getGet a annotationSpecs
ArgumentTypeDescription
identifierstringThe name of the annotationSpecs
syncSync annotationSpecs state from GCP
metadatastores.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
dataplexConfig?objectOptional. Whether or not Data Lineage synchronization is enabled for Vertex Pipelines.
description?stringDescription of the MetadataStore.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
state?objectThe disk utilization of the MetadataStore in bytes.
metadataStoreId?stringThe {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.)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a metadataStores
getGet a metadataStores
ArgumentTypeDescription
identifierstringThe name of the metadataStores
deleteDelete the metadataStores
ArgumentTypeDescription
identifierstringThe name of the metadataStores
syncSync metadataStores state from GCP
models_evaluations.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a evaluations
ArgumentTypeDescription
identifierstringThe name of the evaluations
syncSync evaluations state from GCP
importimport
ArgumentTypeDescription
modelEvaluation?any
studies.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
displayName?stringRequired. Describes the Study, default value is empty string.
studySpec?objectThe search algorithm specified for the Study.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a studies
ArgumentTypeDescription
waitForReady?booleanWait for the resource to reach a ready state after creation (default: true)
getGet a studies
ArgumentTypeDescription
identifierstringThe name of the studies
deleteDelete the studies
ArgumentTypeDescription
identifierstringThe name of the studies
syncSync studies state from GCP
lookuplookup
ArgumentTypeDescription
displayName?any
tensorboards.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
description?stringDescription of this Tensorboard.
displayName?stringRequired. User provided name of this Tensorboard.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
isDefault?booleanUsed 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?recordThe 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a tensorboards
getGet a tensorboards
ArgumentTypeDescription
identifierstringThe name of the tensorboards
updateUpdate tensorboards attributes
deleteDelete the tensorboards
ArgumentTypeDescription
identifierstringThe name of the tensorboards
syncSync tensorboards state from GCP
batch_readbatch read
read_sizeread size
read_usageread usage
locations.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
getGet a locations
ArgumentTypeDescription
identifierstringThe name of the locations
syncSync locations state from GCP
ask_contextsask contexts
ArgumentTypeDescription
query?any
tools?any
async_retrieve_contextsasync retrieve contexts
ArgumentTypeDescription
query?any
tools?any
augment_promptaugment prompt
ArgumentTypeDescription
contents?any
model?any
vertexRagStore?any
corroborate_contentcorroborate content
ArgumentTypeDescription
content?any
facts?any
parameters?any
deploydeploy
ArgumentTypeDescription
deployConfig?any
endpointConfig?any
huggingFaceModelId?any
modelConfig?any
publisherModelName?any
evaluate_datasetevaluate dataset
ArgumentTypeDescription
autoraterConfig?any
dataset?any
location?any
metrics?any
outputConfig?any
evaluate_instancesevaluate instances
ArgumentTypeDescription
autoraterConfig?any
bleuInput?any
coherenceInput?any
cometInput?any
exactMatchInput?any
fluencyInput?any
fulfillmentInput?any
groundednessInput?any
instance?any
location?any
metricSources?any
metrics?any
metricxInput?any
pairwiseMetricInput?any
pairwiseQuestionAnsweringQualityInput?any
pairwiseSummarizationQualityInput?any
pointwiseMetricInput?any
questionAnsweringCorrectnessInput?any
questionAnsweringHelpfulnessInput?any
questionAnsweringQualityInput?any
questionAnsweringRelevanceInput?any
rougeInput?any
rubricBasedInstructionFollowingInput?any
safetyInput?any
summarizationHelpfulnessInput?any
summarizationQualityInput?any
summarizationVerbosityInput?any
toolCallValidInput?any
toolNameMatchInput?any
toolParameterKeyMatchInput?any
toolParameterKvMatchInput?any
trajectoryAnyOrderMatchInput?any
trajectoryExactMatchInput?any
trajectoryInOrderMatchInput?any
trajectoryPrecisionInput?any
trajectoryRecallInput?any
trajectorySingleToolUseInput?any
generate_instance_rubricsgenerate instance rubrics
ArgumentTypeDescription
agentConfig?any
contents?any
location?any
metricResourceName?any
predefinedRubricGenerationSpec?any
rubricGenerationSpec?any
generate_synthetic_datagenerate synthetic data
ArgumentTypeDescription
count?any
examples?any
outputFieldSpecs?any
taskDescription?any
get_rag_engine_configget rag engine config
retrieve_contextsretrieve contexts
ArgumentTypeDescription
query?any
tools?any
update_rag_engine_configupdate rag engine config
ArgumentTypeDescription
name?any
ragManagedDbConfig?any
featureonlinestores_featureviews.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
bigQuerySource?objectRequired. Columns to construct entity_id / row keys.
bigtableMetadata?objectOutput only. The Bigtable App Profile to use for reading from Bigtable.
featureRegistrySource?objectRequired. Identifier of the feature group.
indexConfig?objectConfiguration options for using brute force search.
labels?recordOptional. 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?stringIdentifier. Name of the FeatureView. Format: `projects/{project}/locations/{location}/featureOnlineStores/{feature_online_store}/featureViews/{feature_view}`
optimizedConfig?objectImmutable. 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.
serviceAgentType?enumOptional. 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?objectOptional. If true, syncs the FeatureView in a continuous manner to Online Store.
vertexRagSource?objectOptional. The RAG corpus id corresponding to this FeatureView.
featureViewId?stringRequired. 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.
runSyncImmediately?stringImmutable. If set to true, one on demand sync will be run immediately, regardless whether the FeatureView.sync_config is configured or not.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a featureViews
getGet a featureViews
ArgumentTypeDescription
identifierstringThe name of the featureViews
updateUpdate featureViews attributes
deleteDelete the featureViews
ArgumentTypeDescription
identifierstringThe name of the featureViews
syncSync featureViews state from GCP
direct_writedirect write
ArgumentTypeDescription
dataKeyAndFeatureValues?any
fetch_feature_valuesfetch feature values
ArgumentTypeDescription
dataFormat?any
dataKey?any
generate_fetch_access_tokengenerate fetch access token
search_nearest_entitiessearch nearest entities
ArgumentTypeDescription
query?any
returnFullEntity?any
action_syncsync
reasoningengines_sessions_events.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a events
ArgumentTypeDescription
identifierstringThe name of the events
syncSync events state from GCP
featurestores.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
labels?recordOptional. 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.
onlineServingConfig?objectThe 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.
onlineStorageTtlDays?numberOptional. 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
featurestoreId?stringRequired. 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a featurestores
getGet a featurestores
ArgumentTypeDescription
identifierstringThe name of the featurestores
updateUpdate featurestores attributes
deleteDelete the featurestores
ArgumentTypeDescription
identifierstringThe name of the featurestores
syncSync featurestores state from GCP
batch_read_feature_valuesbatch read feature values
ArgumentTypeDescription
bigqueryReadInstances?any
csvReadInstances?any
destination?any
entityTypeSpecs?any
passThroughFields?any
startTime?any
search_featuressearch features
ragcorpora_ragfiles.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a ragFiles
ArgumentTypeDescription
identifierstringThe name of the ragFiles
deleteDelete the ragFiles
ArgumentTypeDescription
identifierstringThe name of the ragFiles
syncSync ragFiles state from GCP
importimport
ArgumentTypeDescription
importRagFilesConfig?any
indexendpoints.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
description?stringThe description of the IndexEndpoint.
displayName?stringRequired. The display name of the IndexEndpoint. The name can be up to 128 characters long and can consist of any UTF-8 characters.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
labels?recordThe 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.
network?stringOptional. 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?objectRequired. If true, expose the IndexEndpoint via private service connect.
publicEndpointEnabled?booleanOptional. If true, the deployed index will be accessible through public endpoint.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a indexEndpoints
getGet a indexEndpoints
ArgumentTypeDescription
identifierstringThe name of the indexEndpoints
updateUpdate indexEndpoints attributes
deleteDelete the indexEndpoints
ArgumentTypeDescription
identifierstringThe name of the indexEndpoints
syncSync indexEndpoints state from GCP
deploy_indexdeploy index
ArgumentTypeDescription
deployedIndex?any
find_neighborsfind neighbors
ArgumentTypeDescription
deployedIndexId?any
queries?any
returnFullDatapoint?any
mutate_deployed_indexmutate deployed index
ArgumentTypeDescription
automaticResources?any
createTime?any
dedicatedResources?any
deployedIndexAuthConfig?any
deploymentGroup?any
deploymentTier?any
displayName?any
enableAccessLogging?any
enableDatapointUpsertLogging?any
id?any
index?any
indexSyncTime?any
privateEndpoints?any
pscAutomationConfigs?any
reservedIpRanges?any
read_index_datapointsread index datapoints
ArgumentTypeDescription
deployedIndexId?any
ids?any
undeploy_indexundeploy index
ArgumentTypeDescription
deployedIndexId?any
metadatastores_artifacts.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
description?stringDescription of the Artifact
displayName?stringUser provided display name of the Artifact. May be up to 128 Unicode characters.
labels?recordThe 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?recordProperties of the Artifact. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
schemaTitle?stringThe 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?stringThe 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?enumThe 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.
uri?stringThe uniform resource identifier of the artifact file. May be empty if there is no actual artifact file.
artifactId?stringThe {artifact} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{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.)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a artifacts
getGet a artifacts
ArgumentTypeDescription
identifierstringThe name of the artifacts
updateUpdate artifacts attributes
deleteDelete the artifacts
ArgumentTypeDescription
identifierstringThe name of the artifacts
syncSync artifacts state from GCP
purgepurge
ArgumentTypeDescription
filter?any
force?any
query_artifact_lineage_subgraphquery artifact lineage subgraph
tensorboards_experiments_runs.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
description?stringDescription of this TensorboardRun.
displayName?stringRequired. User provided name of this TensorboardRun. This value must be unique among all TensorboardRuns belonging to the same parent TensorboardExperiment.
labels?recordThe 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.
tensorboardRunId?stringRequired. 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-/`.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a runs
getGet a runs
ArgumentTypeDescription
identifierstringThe name of the runs
updateUpdate runs attributes
deleteDelete the runs
ArgumentTypeDescription
identifierstringThe name of the runs
syncSync runs state from GCP
batch_createbatch create
ArgumentTypeDescription
requests?any
writewrite
ArgumentTypeDescription
tensorboardRun?any
timeSeriesData?any
studies_trials.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
finalMeasurement?objectOutput only. Time that the Trial has been running at the point of this Measurement.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a trials
ArgumentTypeDescription
waitForReady?booleanWait for the resource to reach a ready state after creation (default: true)
getGet a trials
ArgumentTypeDescription
identifierstringThe name of the trials
deleteDelete the trials
ArgumentTypeDescription
identifierstringThe name of the trials
syncSync trials state from GCP
add_trial_measurementadd trial measurement
ArgumentTypeDescription
measurement?any
check_trial_early_stopping_statecheck trial early stopping state
completecomplete
ArgumentTypeDescription
finalMeasurement?any
infeasibleReason?any
trialInfeasible?any
list_optimal_trialslist optimal trials
stopstop
suggestsuggest
ArgumentTypeDescription
clientId?any
contexts?any
suggestionCount?any
nasjobs.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
displayName?stringRequired. The display name of the NasJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
error?objectThe status code, which should be an enum value of google.rpc.Code.
labels?recordThe 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.
nasJobOutput?objectOutput only. Time when the NasTrial's status changed to `SUCCEEDED` or `INFEASIBLE`.
nasJobSpec?objectRequired. The optimization goal of the metric.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a nasJobs
getGet a nasJobs
ArgumentTypeDescription
identifierstringThe name of the nasJobs
deleteDelete the nasJobs
ArgumentTypeDescription
identifierstringThe name of the nasJobs
syncSync nasJobs state from GCP
cancelcancel
featureonlinestores.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
bigtable?objectOptional. 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%.
dedicatedServingEndpoint?objectRequired. If true, expose the IndexEndpoint via private service connect.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
labels?recordOptional. 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?stringIdentifier. Name of the FeatureOnlineStore. Format: `projects/{project}/locations/{location}/featureOnlineStores/{featureOnlineStore}`
optimized?objectOptimized storage type
featureOnlineStoreId?stringRequired. 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a featureOnlineStores
getGet a featureOnlineStores
ArgumentTypeDescription
identifierstringThe name of the featureOnlineStores
updateUpdate featureOnlineStores attributes
deleteDelete the featureOnlineStores
ArgumentTypeDescription
identifierstringThe name of the featureOnlineStores
syncSync featureOnlineStores state from GCP
models_evaluations_slices.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a slices
ArgumentTypeDescription
identifierstringThe name of the slices
syncSync slices state from GCP
batch_importbatch import
ArgumentTypeDescription
evaluatedAnnotations?any
featuregroups.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
bigQuery?objectRequired. BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.
description?stringOptional. Description of the FeatureGroup.
labels?recordOptional. 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?stringIdentifier. Name of the FeatureGroup. Format: `projects/{project}/locations/{location}/featureGroups/{featureGroup}`
serviceAgentType?enumOptional. 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.
featureGroupId?stringRequired. 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a featureGroups
getGet a featureGroups
ArgumentTypeDescription
identifierstringThe name of the featureGroups
updateUpdate featureGroups attributes
deleteDelete the featureGroups
ArgumentTypeDescription
identifierstringThe name of the featureGroups
syncSync featureGroups state from GCP
evaluationitems.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
displayName?stringRequired. The display name of the EvaluationItem.
error?objectThe status code, which should be an enum value of google.rpc.Code.
evaluationItemType?enumRequired. The type of the EvaluationItem.
evaluationRequest?objectRequired. The name of the candidate that produced the response.
evaluationResponse?objectOptional. Additional results for the metric.
gcsUri?stringThe Cloud Storage object where the request or response is stored.
labels?recordOptional. Labels for the EvaluationItem.
metadata?stringOptional. Metadata for the EvaluationItem.
name?stringIdentifier. The resource name of the EvaluationItem. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}`
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a evaluationItems
getGet a evaluationItems
ArgumentTypeDescription
identifierstringThe name of the evaluationItems
deleteDelete the evaluationItems
ArgumentTypeDescription
identifierstringThe name of the evaluationItems
syncSync evaluationItems state from GCP
metadatastores_contexts.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
description?stringDescription of the Context
displayName?stringUser provided display name of the Context. May be up to 128 Unicode characters.
labels?recordThe 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?recordProperties of the Context. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
name?stringImmutable. The resource name of the Context.
schemaTitle?stringThe 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?stringThe 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.
contextId?stringThe {context} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{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.)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a contexts
getGet a contexts
ArgumentTypeDescription
identifierstringThe name of the contexts
updateUpdate contexts attributes
deleteDelete the contexts
ArgumentTypeDescription
identifierstringThe name of the contexts
syncSync contexts state from GCP
add_context_artifacts_and_executionsadd context artifacts and executions
ArgumentTypeDescription
artifacts?any
executions?any
add_context_childrenadd context children
ArgumentTypeDescription
childContexts?any
purgepurge
ArgumentTypeDescription
filter?any
force?any
query_context_lineage_subgraphquery context lineage subgraph
datasets_savedqueries.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a savedQueries
ArgumentTypeDescription
identifierstringThe name of the savedQueries
deleteDelete the savedQueries
ArgumentTypeDescription
identifierstringThe name of the savedQueries
syncSync savedQueries state from GCP
tensorboards_experiments_runs_timeseries.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
description?stringDescription of this TensorboardTimeSeries.
displayName?stringRequired. User provided name of this TensorboardTimeSeries. This value should be unique among all TensorboardTimeSeries resources belonging to the same TensorboardRun resource (parent resource).
metadata?objectOutput only. The largest blob sequence length (number of blobs) of all data points in this time series, if its ValueType is BLOB_SEQUENCE.
pluginData?stringData of the current plugin, with the size limited to 65KB.
pluginName?stringImmutable. Name of the plugin this time series pertain to. Such as Scalar, Tensor, Blob
valueType?enumRequired. Immutable. Type of TensorboardTimeSeries value.
tensorboardTimeSeriesId?stringOptional. 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}"
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a timeSeries
getGet a timeSeries
ArgumentTypeDescription
identifierstringThe name of the timeSeries
updateUpdate timeSeries attributes
deleteDelete the timeSeries
ArgumentTypeDescription
identifierstringThe name of the timeSeries
syncSync timeSeries state from GCP
export_tensorboard_time_seriesexport tensorboard time series
ArgumentTypeDescription
filter?any
orderBy?any
pageSize?any
pageToken?any
readread
read_blob_dataread blob data
featurestores_entitytypes_features.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
description?stringDescription of the Feature.
disableMonitoring?booleanOptional. 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.
labels?recordOptional. 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.
name?stringImmutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{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?stringEntity responsible for maintaining this feature. Can be comma separated list of email addresses or URIs.
valueType?enumImmutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
versionColumnName?stringOnly 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.
featureId?stringRequired. 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a features
getGet a features
ArgumentTypeDescription
identifierstringThe name of the features
updateUpdate features attributes
deleteDelete the features
ArgumentTypeDescription
identifierstringThe name of the features
syncSync features state from GCP
batch_createbatch create
ArgumentTypeDescription
requests?any
persistentresources.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
displayName?stringOptional. The display name of the PersistentResource. The name can be up to 128 characters long and can consist of any UTF-8 characters.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
error?objectThe status code, which should be an enum value of google.rpc.Code.
labels?recordOptional. 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?stringImmutable. Resource name of a PersistentResource.
network?stringOptional. 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?objectRequired. The DNS name suffix of the zone being peered to, e.g., "my-internal-domain.corp.". Must end with a dot.
reservedIpRanges?arrayOptional. 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?arrayOptional. max replicas in the node pool, must be ≥ replica_count and > min_replica_count or will throw error
resourceRuntime?objectOutput 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" }
resourceRuntimeSpec?objectOptional. 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.
persistentResourceId?stringRequired. 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])?$/`.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a persistentResources
ArgumentTypeDescription
waitForReady?booleanWait for the resource to reach a ready state after creation (default: true)
getGet a persistentResources
ArgumentTypeDescription
identifierstringThe name of the persistentResources
updateUpdate persistentResources attributes
ArgumentTypeDescription
waitForReady?booleanWait for the resource to reach a ready state after update (default: true)
deleteDelete the persistentResources
ArgumentTypeDescription
identifierstringThe name of the persistentResources
syncSync persistentResources state from GCP
rebootreboot
notebookruntimetemplates.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
dataPersistentDiskSpec?objectSize in GB of the disk (default is 100GB).
description?stringThe description of the NotebookRuntimeTemplate.
displayName?stringRequired. The display name of the NotebookRuntimeTemplate. The name can be up to 128 characters long and can consist of any UTF-8 characters.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
eucConfig?objectOutput 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.
idleShutdownConfig?objectWhether Idle Shutdown is disabled in this NotebookRuntimeTemplate.
labels?recordThe 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?objectThe number of accelerators to attach to the machine. For accelerator optimized machine types (https://cloud.google.com/compute/docs/accelerator-optimized-machines), One may set the accelerator_count from 1 to N for machine with N GPUs. If accelerator_count is less than or equal to N / 2, Vertex will co-schedule the replicas of the model into the same VM to save cost. For example, if the machine type is a3-highgpu-8g, which has 8 H100 GPUs, one can set accelerator_count to 1 to 8. If accelerator_count is 1, 2, 3, or 4, Vertex will co-schedule 8, 4, 2, or 2 replicas of the model into the same VM to save cost. When co-scheduling, CPU, memory and storage on the VM will be distributed to replicas on the VM. For example, one can expect a co-scheduled replica requesting 2 GPUs out of a 8-GPU VM will receive 25% of the CPU, memory and storage of the VM. Note that the feature is not compatible with multihost_gpu_node_count. When multihost_gpu_node_count is set, the co-scheduling will not be enabled.
name?stringThe resource name of the NotebookRuntimeTemplate.
networkSpec?objectWhether to enable public internet access. Default false.
networkTags?arrayOptional. The Compute Engine tags to add to runtime (see [Tagging instances](https://cloud.google.com/vpc/docs/add-remove-network-tags)).
notebookRuntimeType?enumOptional. Immutable. The type of the notebook runtime template.
reservationAffinity?objectRequired. 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.
shieldedVmConfig?objectDefines 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.
softwareConfig?objectOutput only. A human-readable description of the specified colab image release, populated by the system. Example: "Python 3.10", "Latest - current Python 3.11"
notebookRuntimeTemplateId?stringOptional. User specified ID for the notebook runtime template.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a notebookRuntimeTemplates
getGet a notebookRuntimeTemplates
ArgumentTypeDescription
identifierstringThe name of the notebookRuntimeTemplates
updateUpdate notebookRuntimeTemplates attributes
deleteDelete the notebookRuntimeTemplates
ArgumentTypeDescription
identifierstringThe name of the notebookRuntimeTemplates
syncSync notebookRuntimeTemplates state from GCP
evaluationsets.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
displayName?stringRequired. The display name of the EvaluationSet.
evaluationItems?arrayRequired. The EvaluationItems that are part of this dataset.
metadata?stringOptional. Metadata for the EvaluationSet.
name?stringIdentifier. The resource name of the EvaluationSet. Format: `projects/{project}/locations/{location}/evaluationSets/{evaluation_set}`
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a evaluationSets
getGet a evaluationSets
ArgumentTypeDescription
identifierstringThe name of the evaluationSets
updateUpdate evaluationSets attributes
deleteDelete the evaluationSets
ArgumentTypeDescription
identifierstringThe name of the evaluationSets
syncSync evaluationSets state from GCP
batchpredictionjobs.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
completionStats?objectOutput only. The number of entities for which any error was encountered.
dedicatedResources?objectThe number of accelerators to attach to the machine. For accelerator optimized machine types (https://cloud.google.com/compute/docs/accelerator-optimized-machines), One may set the accelerator_count from 1 to N for machine with N GPUs. If accelerator_count is less than or equal to N / 2, Vertex will co-schedule the replicas of the model into the same VM to save cost. For example, if the machine type is a3-highgpu-8g, which has 8 H100 GPUs, one can set accelerator_count to 1 to 8. If accelerator_count is 1, 2, 3, or 4, Vertex will co-schedule 8, 4, 2, or 2 replicas of the model into the same VM to save cost. When co-scheduling, CPU, memory and storage on the VM will be distributed to replicas on the VM. For example, one can expect a co-scheduled replica requesting 2 GPUs out of a 8-GPU VM will receive 25% of the CPU, memory and storage of the VM. Note that the feature is not compatible with multihost_gpu_node_count. When multihost_gpu_node_count is set, the co-scheduling will not be enabled.
disableContainerLogging?booleanFor 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?stringRequired. The user-defined name of this BatchPredictionJob.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
error?objectThe status code, which should be an enum value of google.rpc.Code.
explanationSpec?objectPoints 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.
generateExplanation?booleanGenerate 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?objectRequired. BigQuery URI to a table, up to 2000 characters long. Accepted forms: * BigQuery path. For example: `bq://projectId.bqDatasetId.bqTableId`.
instanceConfig?objectFields 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.
labels?recordThe 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?objectImmutable. 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.
model?stringThe 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, unmanaged_container_model, or endpoint 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}`
modelParameters?stringThe parameters that govern the predictions. The schema of the parameters may be specified via the Model's PredictSchemata's parameters_schema_uri.
outputConfig?objectRequired. 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`.
outputInfo?objectOutput only. The path of the BigQuery dataset created, in `bq://projectId.bqDatasetId` format, into which the prediction output is written.
resourcesConsumed?objectOutput 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.
serviceAccount?stringThe 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.
unmanagedContainerModel?objectThe path to the directory containing the Model artifact and any of its supporting files.
parent?stringRequired. The resource name of the Location to create the BatchPredictionJob in. Format: `projects/{project}/locations/{location}`
createCreate a batchPredictionJobs
getGet a batchPredictionJobs
ArgumentTypeDescription
identifierstringThe name of the batchPredictionJobs
syncSync batchPredictionJobs state from GCP
reasoningengines_memories.tsv2026.04.11.1

Global Arguments

ArgumentTypeDescription
description?stringOptional. Represents the description of the Memory.
disableMemoryRevisions?booleanOptional. Input only. Indicates whether no revision will be created for this request.
displayName?stringOptional. Represents the display name of the Memory.
expireTime?stringOptional. Represents the 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?stringOptional. Represents semantic knowledge extracted from the source content.
metadata?recordRepresents a boolean value.
name?stringIdentifier. Represents the resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`
revisionExpireTime?stringOptional. Input only. Represents the timestamp of when the revision is considered expired. If not set, the memory revision will be kept until manually deleted.
revisionLabels?recordOptional. Input only. Represents the labels to apply to the Memory Revision created as a result of this request.
revisionTtl?stringOptional. Input only. Represents the TTL for the revision. The expiration time is computed: now + TTL.
scope?recordRequired. Immutable. Represents 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?arrayOptional. Represents the custom memory topic label.
ttl?stringOptional. Input only. Represents the TTL for this resource. The expiration time is computed: now + TTL.
memoryId?stringOptional. The user defined ID to use for memory, which will become the final component of the memory resource name. If not provided, Vertex AI will generate a value for this ID. This value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The first character must be a letter, and the last character must be a letter or number.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a memories
getGet a memories
ArgumentTypeDescription
identifierstringThe name of the memories
updateUpdate memories attributes
deleteDelete the memories
ArgumentTypeDescription
identifierstringThe name of the memories
syncSync memories state from GCP
generategenerate
ArgumentTypeDescription
allowedTopics?any
directContentsSource?any
directMemoriesSource?any
disableConsolidation?any
disableMemoryRevisions?any
metadata?any
metadataMergeStrategy?any
revisionExpireTime?any
revisionLabels?any
revisionTtl?any
scope?any
vertexSessionSource?any
purgepurge
ArgumentTypeDescription
filter?any
filterGroups?any
force?any
retrieveretrieve
ArgumentTypeDescription
filter?any
filterGroups?any
memoryTypes?any
scope?any
similaritySearchParams?any
simpleRetrievalParams?any
rollbackrollback
ArgumentTypeDescription
targetRevisionId?any
datasets_dataitems.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a dataItems
ArgumentTypeDescription
identifierstringThe name of the dataItems
syncSync dataItems state from GCP
reasoningengines_sessions.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
displayName?stringOptional. The display name of the session.
expireTime?stringOptional. Timestamp of when this session is considered expired. This is *always* provided on output, regardless of what was sent on input. The minimum value is 24 hours from the time of creation.
labels?recordThe 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?stringIdentifier. The resource name of the session. Format: 'projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sessions/{session}'.
sessionState?recordOptional. Session specific memory which stores key conversation points.
ttl?stringOptional. Input only. The TTL for this session. The minimum value is 24 hours.
userId?stringRequired. Immutable. String id provided by the user
sessionId?stringOptional. The user defined ID to use for session, which will become the final component of the session resource name. If not provided, Vertex AI will generate a value for this ID. This value may be up to 63 characters, and valid characters are `[a-z0-9-]`. The first and last characters must be a letter or number.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a sessions
getGet a sessions
ArgumentTypeDescription
identifierstringThe name of the sessions
updateUpdate sessions attributes
deleteDelete the sessions
ArgumentTypeDescription
identifierstringThe name of the sessions
syncSync sessions state from GCP
append_eventappend event
ArgumentTypeDescription
actions?any
author?any
content?any
errorCode?any
errorMessage?any
eventMetadata?any
invocationId?any
name?any
rawEvent?any
timestamp?any
reasoningengines.tsv2026.04.15.1

Global Arguments

ArgumentTypeDescription
contextSpec?objectOptional. Represents the maximum number of revisions to consider for each candidate memory. If not set, then the default value (1) will be used, which means that only the latest revision will be considered.
description?stringOptional. The description of the ReasoningEngine.
displayName?stringRequired. The display name of the ReasoningEngine.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
labels?recordLabels for the ReasoningEngine.
name?stringIdentifier. The resource name of the ReasoningEngine. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`
spec?objectOptional. The OSS agent framework used to develop the agent. Currently supported values: "google-adk", "langchain", "langgraph", "ag2", "llama-index", "custom".
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a reasoningEngines
getGet a reasoningEngines
ArgumentTypeDescription
identifierstringThe name of the reasoningEngines
updateUpdate reasoningEngines attributes
deleteDelete the reasoningEngines
ArgumentTypeDescription
identifierstringThe name of the reasoningEngines
syncSync reasoningEngines state from GCP
execute_codeexecute code
ArgumentTypeDescription
inputs?any
queryquery
ArgumentTypeDescription
classMethod?any
input?any
stream_querystream query
ArgumentTypeDescription
classMethod?any
input?any
deploymentresourcepools.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
deploymentResourcePool?objectOutput only. Timestamp when this DeploymentResourcePool was created.
deploymentResourcePoolId?stringRequired. 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])?$/`.
createTime?stringOutput only. Timestamp when this DeploymentResourcePool was created.
dedicatedResources?objectRequired. 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` * `prometheus.googleapis.com/vertex_dcgm_fi_dev_gpu_util` * `prometheus.googleapis.com/vertex_vllm_gpu_cache_usage_perc` * `prometheus.googleapis.com/vertex_vllm_num_requests_waiting`
disableContainerLogging?booleanIf 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?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
name?stringImmutable. The resource name of the DeploymentResourcePool. Format: `projects/{project}/locations/{location}/deploymentResourcePools/{deployment_resource_pool}`
satisfiesPzi?booleanOutput only. Reserved for future use.
satisfiesPzs?booleanOutput only. Reserved for future use.
serviceAccount?stringThe 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a deploymentResourcePools
getGet a deploymentResourcePools
ArgumentTypeDescription
identifierstringThe name of the deploymentResourcePools
updateUpdate deploymentResourcePools attributes
deleteDelete the deploymentResourcePools
ArgumentTypeDescription
identifierstringThe name of the deploymentResourcePools
syncSync deploymentResourcePools state from GCP
query_deployed_modelsquery deployed models
reasoningengines_sandboxenvironments.tsv2026.04.15.1

Global Arguments

ArgumentTypeDescription
connectionInfo?objectOutput only. The hostname of the load balancer.
displayName?stringRequired. The display name of the SandboxEnvironment.
expireTime?stringOptional. 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?stringIdentifier. The name of the SandboxEnvironment.
owner?stringOptional. Owner information for this sandbox environment. A Sandbox can only be restored from a snapshot that belongs to the same owner. If not set, sandbox will be created as the default owner.
sandboxEnvironmentSnapshot?stringOptional. The resource name of the SandboxEnvironmentSnapshot to use for creating this SandboxEnvironment. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/sandboxEnvironmentSnapshots/{sandbox_environment_snapshot}`
sandboxEnvironmentTemplate?stringOptional. The name of the SandboxEnvironmentTemplate specified in the parent Agent Engine resource that this SandboxEnvironment is created from. Only one of `sandbox_environment_template` and `spec` should be set.
spec?objectThe coding language supported in this environment.
ttl?stringOptional. Input only. The TTL for the sandbox environment. The expiration time is computed: now + TTL.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a sandboxEnvironments
getGet a sandboxEnvironments
ArgumentTypeDescription
identifierstringThe name of the sandboxEnvironments
deleteDelete the sandboxEnvironments
ArgumentTypeDescription
identifierstringThe name of the sandboxEnvironments
syncSync sandboxEnvironments state from GCP
executeexecute
ArgumentTypeDescription
identifierstringThe name of the sandboxEnvironments
snapshotsnapshot
ArgumentTypeDescription
createTime?any
displayName?any
expireTime?any
name?any
owner?any
parentSnapshot?any
postSnapshotAction?any
sizeBytes?any
sourceSandboxEnvironment?any
ttl?any
updateTime?any
featuregroups_features.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
description?stringDescription of the Feature.
disableMonitoring?booleanOptional. 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.
labels?recordOptional. 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.
name?stringImmutable. Name of the Feature. Format: `projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{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?stringEntity responsible for maintaining this feature. Can be comma separated list of email addresses or URIs.
valueType?enumImmutable. Only applicable for Vertex AI Feature Store (Legacy). Type of Feature value.
versionColumnName?stringOnly 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.
featureId?stringRequired. 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a features
getGet a features
ArgumentTypeDescription
identifierstringThe name of the features
updateUpdate features attributes
deleteDelete the features
ArgumentTypeDescription
identifierstringThe name of the features
syncSync features state from GCP
batch_createbatch create
ArgumentTypeDescription
requests?any
tensorboards_experiments.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
description?stringDescription of this TensorboardExperiment.
displayName?stringUser provided name of this TensorboardExperiment.
source?stringImmutable. Source of the TensorboardExperiment. Example: a custom training job.
tensorboardExperimentId?stringRequired. 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-/`.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a experiments
getGet a experiments
ArgumentTypeDescription
identifierstringThe name of the experiments
updateUpdate experiments attributes
deleteDelete the experiments
ArgumentTypeDescription
identifierstringThe name of the experiments
syncSync experiments state from GCP
batch_createbatch create
ArgumentTypeDescription
requests?any
writewrite
ArgumentTypeDescription
writeRunDataRequests?any
customjobs.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
displayName?stringRequired. The display name of the CustomJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
error?objectThe status code, which should be an enum value of google.rpc.Code.
jobSpec?objectRequired. 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.
labels?recordThe 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a customJobs
getGet a customJobs
ArgumentTypeDescription
identifierstringThe name of the customJobs
deleteDelete the customJobs
ArgumentTypeDescription
identifierstringThe name of the customJobs
syncSync customJobs state from GCP
cancelcancel
indexes.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
description?stringThe description of the Index.
displayName?stringRequired. The display name of the Index. The name can be up to 128 characters long and can consist of any UTF-8 characters.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
indexStats?objectOutput only. The number of shards in the Index.
indexUpdateMethod?enumImmutable. The update method to use with this Index. If not set, BATCH_UPDATE will be used by default.
labels?recordThe 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?stringAn additional information about the Index; the schema of the metadata can be found in metadata_schema.
metadataSchemaUri?stringImmutable. 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a indexes
getGet a indexes
ArgumentTypeDescription
identifierstringThe name of the indexes
updateUpdate indexes attributes
deleteDelete the indexes
ArgumentTypeDescription
identifierstringThe name of the indexes
syncSync indexes state from GCP
upsert_datapointsupsert datapoints
ArgumentTypeDescription
datapoints?any
updateMask?any
reasoningengines_sandboxenvironmentsnapshots.tsv2026.04.11.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a sandboxEnvironmentSnapshots
ArgumentTypeDescription
identifierstringThe name of the sandboxEnvironmentSnapshots
deleteDelete the sandboxEnvironmentSnapshots
ArgumentTypeDescription
identifierstringThe name of the sandboxEnvironmentSnapshots
syncSync sandboxEnvironmentSnapshots state from GCP
datasets.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
description?stringThe description of the Dataset.
displayName?stringRequired. 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?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
metadata?stringRequired. Additional information about the Dataset.
metadataSchemaUri?stringRequired. 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?stringOptional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
savedQueries?arrayOutput only. Filters on the Annotations in the dataset.
parent?stringRequired. The resource name of the Location to create the Dataset in. Format: `projects/{project}/locations/{location}`
createCreate a datasets
getGet a datasets
ArgumentTypeDescription
identifierstringThe name of the datasets
updateUpdate datasets attributes
deleteDelete the datasets
ArgumentTypeDescription
identifierstringThe name of the datasets
syncSync datasets state from GCP
trainingpipelines.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
displayName?stringRequired. The user-defined name of this TrainingPipeline.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
error?objectThe status code, which should be an enum value of google.rpc.Code.
inputDataConfig?objectApplicable 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.
labels?recordThe 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?stringOptional. 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?objectImmutable. The path to the directory containing the Model artifact and any of its supporting files. Not required for AutoML Models.
parentModel?stringOptional. 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`.
trainingTaskDefinition?stringRequired. 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?stringRequired. The training task's parameter(s), as specified in the training_task_definition's `inputs`.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a trainingPipelines
getGet a trainingPipelines
ArgumentTypeDescription
identifierstringThe name of the trainingPipelines
deleteDelete the trainingPipelines
ArgumentTypeDescription
identifierstringThe name of the trainingPipelines
syncSync trainingPipelines state from GCP
cancelcancel
modeldeploymentmonitoringjobs.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
analysisInstanceSchemaUri?stringYAML 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.
displayName?stringRequired. 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?booleanIf 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?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
endpoint?stringRequired. Endpoint resource name. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
error?objectThe status code, which should be an enum value of google.rpc.Code.
labels?recordThe 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?objectThe time that most recent monitoring pipelines that is related to this run.
logTtl?stringThe 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?objectSample rate (0, 1]
modelDeploymentMonitoringObjectiveConfigs?arrayThe DeployedModel ID of the objective config.
modelDeploymentMonitoringScheduleConfig?objectRequired. The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered.
modelMonitoringAlertConfig?objectThe email addresses to send the alert.
predictInstanceSchemaUri?stringYAML 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?stringSample 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.
statsAnomaliesBaseDirectory?objectRequired. 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a modelDeploymentMonitoringJobs
getGet a modelDeploymentMonitoringJobs
ArgumentTypeDescription
identifierstringThe name of the modelDeploymentMonitoringJobs
updateUpdate modelDeploymentMonitoringJobs attributes
deleteDelete the modelDeploymentMonitoringJobs
ArgumentTypeDescription
identifierstringThe name of the modelDeploymentMonitoringJobs
syncSync modelDeploymentMonitoringJobs state from GCP
pausepause
resumeresume
search_model_deployment_monitoring_stats_anomaliessearch model deployment monitoring stats anomalies
ArgumentTypeDescription
deployedModelId?any
endTime?any
featureDisplayName?any
objectives?any
pageSize?any
pageToken?any
startTime?any
metadatastores_metadataschemas.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
description?stringDescription of the Metadata Schema
schema?stringRequired. 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?enumThe type of the MetadataSchema. This is a property that identifies which metadata types will use the MetadataSchema.
schemaVersion?stringThe 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.
metadataSchemaId?stringThe {metadata_schema} portion of the resource name with the format: `projects/{project}/locations/{location}/metadataStores/{metadatastore}/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.)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a metadataSchemas
getGet a metadataSchemas
ArgumentTypeDescription
identifierstringThe name of the metadataSchemas
syncSync metadataSchemas state from GCP
metadatastores_executions.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
description?stringDescription of the Execution
displayName?stringUser provided display name of the Execution. May be up to 128 Unicode characters.
labels?recordThe 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?recordProperties of the Execution. Top level metadata keys' heading and trailing spaces will be trimmed. The size of this field should not exceed 200KB.
schemaTitle?stringThe 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?stringThe 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?enumThe 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.
executionId?stringThe {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.)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a executions
ArgumentTypeDescription
waitForReady?booleanWait for the resource to reach a ready state after creation (default: true)
getGet a executions
ArgumentTypeDescription
identifierstringThe name of the executions
updateUpdate executions attributes
ArgumentTypeDescription
waitForReady?booleanWait for the resource to reach a ready state after update (default: true)
deleteDelete the executions
ArgumentTypeDescription
identifierstringThe name of the executions
syncSync executions state from GCP
add_execution_eventsadd execution events
ArgumentTypeDescription
events?any
purgepurge
ArgumentTypeDescription
filter?any
force?any
query_execution_inputs_and_outputsquery execution inputs and outputs
featurestores_entitytypes.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
description?stringOptional. Description of the EntityType.
labels?recordOptional. 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?objectSpecify 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–Shannon divergence. Each feature must have a non-zero threshold if they need to be monitored. Otherwise no alert will be triggered for that feature.
name?stringImmutable. Name of the EntityType. Format: `projects/{project}/locations/{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?numberOptional. 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.
entityTypeId?stringRequired. 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a entityTypes
getGet a entityTypes
ArgumentTypeDescription
identifierstringThe name of the entityTypes
updateUpdate entityTypes attributes
deleteDelete the entityTypes
ArgumentTypeDescription
identifierstringThe name of the entityTypes
syncSync entityTypes state from GCP
export_feature_valuesexport feature values
ArgumentTypeDescription
destination?any
featureSelector?any
fullExport?any
settings?any
snapshotExport?any
import_feature_valuesimport feature values
ArgumentTypeDescription
avroSource?any
bigquerySource?any
csvSource?any
disableIngestionAnalysis?any
disableOnlineServing?any
entityIdField?any
featureSpecs?any
featureTime?any
featureTimeField?any
workerCount?any
read_feature_valuesread feature values
ArgumentTypeDescription
entityId?any
featureSelector?any
streaming_read_feature_valuesstreaming read feature values
ArgumentTypeDescription
entityIds?any
featureSelector?any
write_feature_valueswrite feature values
ArgumentTypeDescription
payloads?any
featureonlinestores_featureviews_featureviewsyncs.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a featureViewSyncs
ArgumentTypeDescription
identifierstringThe name of the featureViewSyncs
syncSync featureViewSyncs state from GCP
cachedcontents.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
contents?arrayRequired. Outcome of the code execution.
displayName?stringOptional. Immutable. The user-generated meaningful display name of the cached content.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
expireTime?stringTimestamp of when this resource is considered expired. This is *always* provided on output, regardless of what was sent on input.
model?stringImmutable. 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?stringImmutable. Identifier. The server-generated resource name of the cached content Format: projects/{project}/locations/{location}/cachedContents/{cached_content}
systemInstruction?objectRequired. Outcome of the code execution.
toolConfig?objectOptional. 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.
tools?arrayTool 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.
ttl?stringInput only. The TTL for this resource. The expiration time is computed: now + TTL.
usageMetadata?objectDuration of audio in seconds.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a cachedContents
getGet a cachedContents
ArgumentTypeDescription
identifierstringThe name of the cachedContents
updateUpdate cachedContents attributes
deleteDelete the cachedContents
ArgumentTypeDescription
identifierstringThe name of the cachedContents
syncSync cachedContents state from GCP
notebookruntimes.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a notebookRuntimes
ArgumentTypeDescription
identifierstringThe name of the notebookRuntimes
deleteDelete the notebookRuntimes
ArgumentTypeDescription
identifierstringThe name of the notebookRuntimes
syncSync notebookRuntimes state from GCP
assignassign
ArgumentTypeDescription
notebookRuntime?any
notebookRuntimeId?any
notebookRuntimeTemplate?any
startstart
stopstop
upgradeupgrade
datasets_dataitems_annotations.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a annotations
ArgumentTypeDescription
identifierstringThe name of the annotations
syncSync annotations state from GCP
evaluationruns.tsv2026.04.15.1

Global Arguments

ArgumentTypeDescription
dataSource?objectOptional. Map of candidate name to candidate response column name. The column will be in evaluation_item.CandidateResponse format.
displayName?stringRequired. The display name of the Evaluation Run.
error?objectThe status code, which should be an enum value of google.rpc.Code.
evaluationConfig?objectOptional. 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}`
evaluationResults?objectThe evaluation set where item level results are stored.
inferenceConfigs?recordOptional. The resource name of the Agent Engine. Format: projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine} For example: projects/123/locations/us-central1/reasoningEngines/456
labels?recordOptional. Labels for the evaluation run.
metadata?stringOptional. Metadata about the evaluation run, can be used by the caller to store additional tracking information about the evaluation run.
name?stringIdentifier. The resource name of the EvaluationRun. This is a unique identifier. Format: `projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}`
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a evaluationRuns
ArgumentTypeDescription
waitForReady?booleanWait for the resource to reach a ready state after creation (default: true)
getGet a evaluationRuns
ArgumentTypeDescription
identifierstringThe name of the evaluationRuns
deleteDelete the evaluationRuns
ArgumentTypeDescription
identifierstringThe name of the evaluationRuns
syncSync evaluationRuns state from GCP
cancelcancel
specialistpools.tsv2026.04.03.3

Global Arguments

ArgumentTypeDescription
displayName?stringRequired. 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?stringRequired. The resource name of the SpecialistPool.
specialistManagerEmails?arrayThe email addresses of the managers in the SpecialistPool.
specialistWorkerEmails?arrayThe email addresses of workers in the SpecialistPool.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a specialistPools
getGet a specialistPools
ArgumentTypeDescription
identifierstringThe name of the specialistPools
updateUpdate specialistPools attributes
deleteDelete the specialistPools
ArgumentTypeDescription
identifierstringThe name of the specialistPools
syncSync specialistPools state from GCP
models.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
artifactUri?stringImmutable. The path to the directory containing the Model artifact and any of its supporting files. Not required for AutoML Models.
baseModelSource?objectRequired. The public base model URI.
checkpoints?arrayThe ID of the checkpoint.
containerSpec?objectImmutable. 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).
createTime?stringOutput only. Timestamp when this Model was uploaded into Vertex AI.
dataStats?objectNumber of Annotations that are used for evaluating this Model. If the Model is evaluated multiple times, this will be the number of test Annotations used by the first evaluation. If the Model is not evaluated, the number is 0.
defaultCheckpointId?stringThe default checkpoint id of a model version.
deployedModels?arrayImmutable. The ID of the Checkpoint deployed in the DeployedModel.
description?stringThe description of the Model.
displayName?stringRequired. The display name of the Model. The name can be up to 128 characters long and can consist of any UTF-8 characters.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
etag?stringUsed to perform consistent read-modify-write updates. If not set, a blind "overwrite" update happens.
explanationSpec?objectPoints 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.
labels?recordThe 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?stringImmutable. 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?stringOutput 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?stringImmutable. 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?objectIf this Model is copy of another Model. If true then source_type pertains to the original.
name?stringIdentifier. The resource name of the Model.
originalModelInfo?objectOutput 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}`
pipelineJob?stringOptional. This field is populated if the model is produced by a pipeline job.
predictSchemata?objectImmutable. 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.
satisfiesPzi?booleanOutput only. Reserved for future use.
satisfiesPzs?booleanOutput only. Reserved for future use.
supportedDeploymentResourcesTypes?arrayOutput 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?arrayOutput only. The content of this Model that may be exported.
supportedInputStorageFormats?arrayOutput 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?arrayOutput 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?stringOutput only. The resource name of the TrainingPipeline that uploaded this Model, if any.
updateTime?stringOutput only. Timestamp when this Model was most recently updated.
versionAliases?arrayUser provided version aliases so that a model version can be referenced via alias (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_alias}` instead of auto-generated version id (i.e. `projects/{project}/locations/{location}/models/{model_id}@{version_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?stringOutput only. Timestamp when this version was created.
versionDescription?stringThe description of this version.
versionId?stringOutput 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?stringOutput only. Timestamp when this version was most recently updated.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
getGet a models
ArgumentTypeDescription
identifierstringThe name of the models
updateUpdate models attributes
deleteDelete the models
ArgumentTypeDescription
identifierstringThe name of the models
syncSync models state from GCP
copycopy
ArgumentTypeDescription
encryptionSpec?any
modelId?any
parentModel?any
sourceModel?any
exportexport
ArgumentTypeDescription
outputConfig?any
list_checkpointslist checkpoints
list_versionslist versions
merge_version_aliasesmerge version aliases
ArgumentTypeDescription
versionAliases?any
update_explanation_datasetupdate explanation dataset
ArgumentTypeDescription
examples?any
uploadupload
ArgumentTypeDescription
model?any
modelId?any
parentModel?any
serviceAccount?any
publishers_models.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
getGet a models
ArgumentTypeDescription
identifierstringThe name of the models
syncSync models state from GCP
compute_tokenscompute tokens
ArgumentTypeDescription
contents?any
instances?any
model?any
count_tokenscount tokens
ArgumentTypeDescription
contents?any
generationConfig?any
instances?any
model?any
systemInstruction?any
tools?any
fetch_predict_operationfetch predict operation
ArgumentTypeDescription
operationName?any
generate_contentgenerate content
ArgumentTypeDescription
cachedContent?any
contents?any
generationConfig?any
labels?any
modelArmorConfig?any
safetySettings?any
systemInstruction?any
toolConfig?any
tools?any
predictpredict
ArgumentTypeDescription
instances?any
labels?any
parameters?any
predict_long_runningpredict long running
ArgumentTypeDescription
instances?any
labels?any
parameters?any
stream_generate_contentstream generate content
ArgumentTypeDescription
cachedContent?any
contents?any
generationConfig?any
labels?any
modelArmorConfig?any
safetySettings?any
systemInstruction?any
toolConfig?any
tools?any
hyperparametertuningjobs.tsv2026.04.04.1

Global Arguments

ArgumentTypeDescription
namestringInstance name for this resource (used as the unique identifier in the factory pattern)
displayName?stringRequired. The display name of the HyperparameterTuningJob. The name can be up to 128 characters long and can consist of any UTF-8 characters.
encryptionSpec?objectRequired. Resource name of the Cloud KMS key used to protect the resource. The Cloud KMS key must be in the same region as the resource. It must have the format `projects/{project}/locations/{location}/keyRings/{key_ring}/cryptoKeys/{crypto_key}`.
error?objectThe status code, which should be an enum value of google.rpc.Code.
labels?recordThe 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?numberThe 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?numberRequired. The desired total number of Trials.
parallelTrialCount?numberRequired. The desired number of Trials to run in parallel.
studySpec?objectThe search algorithm specified for the Study.
trialJobSpec?objectRequired. 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.
location?stringThe location for this resource (e.g., 'us', 'us-central1', 'europe-west1')
createCreate a hyperparameterTuningJobs
getGet a hyperparameterTuningJobs
ArgumentTypeDescription
identifierstringThe name of the hyperparameterTuningJobs
deleteDelete the hyperparameterTuningJobs
ArgumentTypeDescription
identifierstringThe name of the hyperparameterTuningJobs
syncSync hyperparameterTuningJobs state from GCP
cancelcancel