Class EndpointServiceClient (1.9.0)

EndpointServiceClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.aiplatform_v1.services.endpoint_service.transports.base.EndpointServiceTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

A service for managing Vertex AI's Endpoints.

Inheritance

builtins.object > EndpointServiceClient

Properties

transport

Returns the transport used by the client instance.

Returns

Type	Description
EndpointServiceTransport	The transport used by the client instance.

Methods

EndpointServiceClient

EndpointServiceClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.aiplatform_v1.services.endpoint_service.transports.base.EndpointServiceTransport]] = None, client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Instantiates the endpoint service client.

Parameters

Name	Description
credentials	`Optional[google.auth.credentials.Credentials]` The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.
transport	`Union[str, EndpointServiceTransport]` The transport to use. If set to None, a transport is chosen automatically.
client_options	`google.api_core.client_options.ClientOptions` Custom options for the client. It won't take effect if a `transport` instance is provided. (1) The `api_endpoint` property can be used to override the default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT environment variable can also be used to override the endpoint: "always" (always use the default mTLS endpoint), "never" (always use the default regular endpoint) and "auto" (auto switch to the default mTLS endpoint if client certificate is present, this is the default value). However, the `api_endpoint` property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the `client_cert_source` property can be used to provide client certificate for mutual TLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not set, no client certificate will be used.
client_info	`google.api_core.gapic_v1.client_info.ClientInfo` The client info used to send a user-agent string along with API requests. If `None`, then default info will be used. Generally, you only need to set this if you're developing your own client library.

Exceptions

Type	Description
google.auth.exceptions.MutualTLSChannelError	If mutual TLS transport creation failed for any reason.

exit

__exit__(type, value, traceback)

Releases underlying transport's resources.

common_billing_account_path

common_billing_account_path(billing_account: str)

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str)

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str)

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str)

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str)

Returns a fully-qualified project string.

create_endpoint

create_endpoint(request: Optional[Union[google.cloud.aiplatform_v1.types.endpoint_service.CreateEndpointRequest, dict]] = None, *, parent: Optional[str] = None, endpoint: Optional[google.cloud.aiplatform_v1.types.endpoint.Endpoint] = None, endpoint_id: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Creates an Endpoint.

Parameters

Name	Description
request	`Union[google.cloud.aiplatform_v1.types.CreateEndpointRequest, dict]` The request object. Request message for EndpointService.CreateEndpoint.
parent	`str` Required. The resource name of the Location to create the Endpoint in. Format: `projects/{project}/locations/{location}` This corresponds to the `parent` field on the `request` instance; if `request` is provided, this should not be set.
endpoint	`google.cloud.aiplatform_v1.types.Endpoint` Required. The Endpoint to create. This corresponds to the `endpoint` field on the `request` instance; if `request` is provided, this should not be set.
endpoint_id	`str` Immutable. The ID to use for endpoint, which will become the final component of the endpoint resource name. If not provided, Vertex AI will generate a value for this ID. This value should be 1-10 characters, and valid characters are /[0-9]/. 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. This corresponds to the `endpoint_id` field on the `request` instance; if `request` is provided, this should not be set.
retry	`google.api_core.retry.Retry` Designation of what errors, if any, should be retried.
timeout	`float` The timeout for this request.
metadata	`Sequence[Tuple[str, str]]` Strings which should be sent along with the request as metadata.

Returns

Type	Description
google.api_core.operation.Operation	An object representing a long-running operation. The result type for the operation will be Endpoint Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.

delete_endpoint

delete_endpoint(request: Optional[Union[google.cloud.aiplatform_v1.types.endpoint_service.DeleteEndpointRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Deletes an Endpoint.

Parameters

Name	Description
request	`Union[google.cloud.aiplatform_v1.types.DeleteEndpointRequest, dict]` The request object. Request message for EndpointService.DeleteEndpoint.
name	`str` Required. The name of the Endpoint resource to be deleted. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` This corresponds to the `name` field on the `request` instance; if `request` is provided, this should not be set.
retry	`google.api_core.retry.Retry` Designation of what errors, if any, should be retried.
timeout	`float` The timeout for this request.
metadata	`Sequence[Tuple[str, str]]` Strings which should be sent along with the request as metadata.

Returns

Type

Description

google.api_core.operation.Operation

An object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

deploy_model

deploy_model(request: Optional[Union[google.cloud.aiplatform_v1.types.endpoint_service.DeployModelRequest, dict]] = None, *, endpoint: Optional[str] = None, deployed_model: Optional[google.cloud.aiplatform_v1.types.endpoint.DeployedModel] = None, traffic_split: Optional[Sequence[google.cloud.aiplatform_v1.types.endpoint_service.DeployModelRequest.TrafficSplitEntry]] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Deploys a Model into this Endpoint, creating a DeployedModel within it.

Parameters

Name	Description
request	`Union[google.cloud.aiplatform_v1.types.DeployModelRequest, dict]` The request object. Request message for EndpointService.DeployModel.
endpoint	`str` Required. The name of the Endpoint resource into which to deploy a Model. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` This corresponds to the `endpoint` field on the `request` instance; if `request` is provided, this should not be set.
deployed_model	`google.cloud.aiplatform_v1.types.DeployedModel` Required. The DeployedModel to be created within the Endpoint. Note that Endpoint.traffic_split must be updated for the DeployedModel to start receiving traffic, either as part of this call, or via EndpointService.UpdateEndpoint. This corresponds to the `deployed_model` field on the `request` instance; if `request` is provided, this should not be set.
traffic_split	`Sequence[google.cloud.aiplatform_v1.types.DeployModelRequest.TrafficSplitEntry]` A map from a DeployedModel's ID to the percentage of this Endpoint's traffic that should be forwarded to that DeployedModel. If this field is non-empty, then the Endpoint's traffic_split will be overwritten with it. To refer to the ID of the just being deployed Model, a "0" should be used, and the actual ID of the new DeployedModel will be filled in its place by this method. The traffic percentage values must add up to 100. If this field is empty, then the Endpoint's traffic_split is not updated. This corresponds to the `traffic_split` field on the `request` instance; if `request` is provided, this should not be set.
retry	`google.api_core.retry.Retry` Designation of what errors, if any, should be retried.
timeout	`float` The timeout for this request.
metadata	`Sequence[Tuple[str, str]]` Strings which should be sent along with the request as metadata.

Returns

Type	Description
google.api_core.operation.Operation	An object representing a long-running operation. The result type for the operation will be DeployModelResponse Response message for EndpointService.DeployModel.

endpoint_path

endpoint_path(project: str, location: str, endpoint: str)

Returns a fully-qualified endpoint string.

from_service_account_file

from_service_account_file(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter

Name	Description
filename	`str` The path to the service account private key json file.

Returns

Type	Description
EndpointServiceClient	The constructed client.

from_service_account_info

from_service_account_info(info: dict, *args, **kwargs)

Creates an instance of this client using the provided credentials info.

Parameter

Name	Description
info	`dict` The service account private key info.

Returns

Type	Description
EndpointServiceClient	The constructed client.

from_service_account_json

from_service_account_json(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter

Name	Description
filename	`str` The path to the service account private key json file.

Returns

Type	Description
EndpointServiceClient	The constructed client.

get_endpoint

get_endpoint(request: Optional[Union[google.cloud.aiplatform_v1.types.endpoint_service.GetEndpointRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets an Endpoint.

Parameters

Name	Description
request	`Union[google.cloud.aiplatform_v1.types.GetEndpointRequest, dict]` The request object. Request message for EndpointService.GetEndpoint
name	`str` Required. The name of the Endpoint resource. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` This corresponds to the `name` field on the `request` instance; if `request` is provided, this should not be set.
retry	`google.api_core.retry.Retry` Designation of what errors, if any, should be retried.
timeout	`float` The timeout for this request.
metadata	`Sequence[Tuple[str, str]]` Strings which should be sent along with the request as metadata.

Returns

Type	Description
google.cloud.aiplatform_v1.types.Endpoint	Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.

list_endpoints

list_endpoints(request: Optional[Union[google.cloud.aiplatform_v1.types.endpoint_service.ListEndpointsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists Endpoints in a Location.

Parameters

Name	Description
request	`Union[google.cloud.aiplatform_v1.types.ListEndpointsRequest, dict]` The request object. Request message for EndpointService.ListEndpoints.
parent	`str` Required. The resource name of the Location from which to list the Endpoints. Format: `projects/{project}/locations/{location}` This corresponds to the `parent` field on the `request` instance; if `request` is provided, this should not be set.
retry	`google.api_core.retry.Retry` Designation of what errors, if any, should be retried.
timeout	`float` The timeout for this request.
metadata	`Sequence[Tuple[str, str]]` Strings which should be sent along with the request as metadata.

Returns

Type	Description
google.cloud.aiplatform_v1.services.endpoint_service.pagers.ListEndpointsPager	Response message for EndpointService.ListEndpoints. Iterating over this object will yield results and resolve additional pages automatically.

model_deployment_monitoring_job_path

model_deployment_monitoring_job_path(
    project: str, location: str, model_deployment_monitoring_job: str
)

Returns a fully-qualified model_deployment_monitoring_job string.

model_path

model_path(project: str, location: str, model: str)

Returns a fully-qualified model string.

network_path

network_path(project: str, network: str)

Returns a fully-qualified network string.

parse_common_billing_account_path

parse_common_billing_account_path(path: str)

Parse a billing_account path into its component segments.

parse_common_folder_path

parse_common_folder_path(path: str)

Parse a folder path into its component segments.

parse_common_location_path

parse_common_location_path(path: str)

Parse a location path into its component segments.

parse_common_organization_path

parse_common_organization_path(path: str)

Parse a organization path into its component segments.

parse_common_project_path

parse_common_project_path(path: str)

Parse a project path into its component segments.

parse_endpoint_path

parse_endpoint_path(path: str)

Parses a endpoint path into its component segments.

parse_model_deployment_monitoring_job_path

parse_model_deployment_monitoring_job_path(path: str)

Parses a model_deployment_monitoring_job path into its component segments.

parse_model_path

parse_model_path(path: str)

Parses a model path into its component segments.

parse_network_path

parse_network_path(path: str)

Parses a network path into its component segments.

undeploy_model

undeploy_model(request: Optional[Union[google.cloud.aiplatform_v1.types.endpoint_service.UndeployModelRequest, dict]] = None, *, endpoint: Optional[str] = None, deployed_model_id: Optional[str] = None, traffic_split: Optional[Sequence[google.cloud.aiplatform_v1.types.endpoint_service.UndeployModelRequest.TrafficSplitEntry]] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Undeploys a Model from an Endpoint, removing a DeployedModel from it, and freeing all resources it's using.

Parameters

Name	Description
request	`Union[google.cloud.aiplatform_v1.types.UndeployModelRequest, dict]` The request object. Request message for EndpointService.UndeployModel.
endpoint	`str` Required. The name of the Endpoint resource from which to undeploy a Model. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}` This corresponds to the `endpoint` field on the `request` instance; if `request` is provided, this should not be set.
deployed_model_id	`str` Required. The ID of the DeployedModel to be undeployed from the Endpoint. This corresponds to the `deployed_model_id` field on the `request` instance; if `request` is provided, this should not be set.
traffic_split	`Sequence[google.cloud.aiplatform_v1.types.UndeployModelRequest.TrafficSplitEntry]` If this field is provided, then the Endpoint's traffic_split will be overwritten with it. If last DeployedModel is being undeployed from the Endpoint, the [Endpoint.traffic_split] will always end up empty when this call returns. A DeployedModel will be successfully undeployed only if it doesn't have any traffic assigned to it when this method executes, or if this field unassigns any traffic to it. This corresponds to the `traffic_split` field on the `request` instance; if `request` is provided, this should not be set.
retry	`google.api_core.retry.Retry` Designation of what errors, if any, should be retried.
timeout	`float` The timeout for this request.
metadata	`Sequence[Tuple[str, str]]` Strings which should be sent along with the request as metadata.

Returns

Type	Description
google.api_core.operation.Operation	An object representing a long-running operation. The result type for the operation will be UndeployModelResponse Response message for EndpointService.UndeployModel.

update_endpoint

update_endpoint(request: Optional[Union[google.cloud.aiplatform_v1.types.endpoint_service.UpdateEndpointRequest, dict]] = None, *, endpoint: Optional[google.cloud.aiplatform_v1.types.endpoint.Endpoint] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Updates an Endpoint.

Parameters

Name	Description
request	`Union[google.cloud.aiplatform_v1.types.UpdateEndpointRequest, dict]` The request object. Request message for EndpointService.UpdateEndpoint.
endpoint	`google.cloud.aiplatform_v1.types.Endpoint` Required. The Endpoint which replaces the resource on the server. This corresponds to the `endpoint` field on the `request` instance; if `request` is provided, this should not be set.
update_mask	`google.protobuf.field_mask_pb2.FieldMask` Required. The update mask applies to the resource. See `google.protobuf.FieldMask][google.protobuf.FieldMask]`. This corresponds to the `update_mask` field on the `request` instance; if `request` is provided, this should not be set.
retry	`google.api_core.retry.Retry` Designation of what errors, if any, should be retried.
timeout	`float` The timeout for this request.
metadata	`Sequence[Tuple[str, str]]` Strings which should be sent along with the request as metadata.

Returns

Type	Description
google.cloud.aiplatform_v1.types.Endpoint	Models are deployed into it, and afterwards Endpoint is called to obtain predictions and explanations.