Class EndpointServiceClient (1.31.0)

EndpointServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1.services.endpoint_service.transports.base.EndpointServiceTransport]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = 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.

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: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1.services.endpoint_service.transports.base.EndpointServiceTransport]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = 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`	`Optional[Union[google.api_core.client_options.ClientOptions, dict]]` 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.

cancel_operation

cancel_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.CancelOperationRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

Starts asynchronous cancellation on a long-running operation.

The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters
Name	Description
`request`	`.operations_pb2.CancelOperationRequest` The request object. Request message for `CancelOperation` method.
`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.

common_billing_account_path

common_billing_account_path(billing_account: str) -> str

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str) -> str

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str) -> str

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str) -> str

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str) -> str

Returns a fully-qualified project string.

create_endpoint

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

Creates an Endpoint.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_create_endpoint():
    # Create a client
    client = aiplatform_v1.EndpointServiceClient()

    # Initialize request argument(s)
    endpoint = aiplatform_v1.Endpoint()
    endpoint.display_name = "display_name_value"

    request = aiplatform_v1.CreateEndpointRequest(
        parent="parent_value",
        endpoint=endpoint,
    )

    # Make the request
    operation = client.create_endpoint(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

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

Deletes an Endpoint.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_delete_endpoint():
    # Create a client
    client = aiplatform_v1.EndpointServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeleteEndpointRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_endpoint(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

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); }

delete_operation

delete_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.DeleteOperationRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

Deletes a long-running operation.

This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters
Name	Description
`request`	`.operations_pb2.DeleteOperationRequest` The request object. Request message for `DeleteOperation` method.
`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.

deploy_model

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

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

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_deploy_model():
    # Create a client
    client = aiplatform_v1.EndpointServiceClient()

    # Initialize request argument(s)
    deployed_model = aiplatform_v1.DeployedModel()
    deployed_model.dedicated_resources.min_replica_count = 1803
    deployed_model.model = "model_value"

    request = aiplatform_v1.DeployModelRequest(
        endpoint="endpoint_value",
        deployed_model=deployed_model,
    )

    # Make the request
    operation = client.deploy_model(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

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`	`MutableMapping[str, int]` 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) -> 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: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.endpoint_service.GetEndpointRequest, dict
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.endpoint.Endpoint

Gets an Endpoint.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_get_endpoint():
    # Create a client
    client = aiplatform_v1.EndpointServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetEndpointRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_endpoint(request=request)

    # Handle the response
    print(response)

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.

get_iam_policy

get_iam_policy(
    request: typing.Optional[google.iam.v1.iam_policy_pb2.GetIamPolicyRequest] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy

Gets the IAM access control policy for a function.

Returns an empty policy if the function exists and does not have a policy set.

Parameters
Name	Description
`request`	`.iam_policy_pb2.GetIamPolicyRequest` The request object. Request message for `GetIamPolicy` method.
`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

.policy_pb2.Policy Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:eve@example.com"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:mike@example.com="" -="" group:admins@example.com="" -="" domain:google.com="" -="" serviceaccount:my-project-id@appspot.gserviceaccount.com="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:eve@example.com="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __.

get_location

get_location(
    request: typing.Optional[
        google.cloud.location.locations_pb2.GetLocationRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.Location

Gets information about a location.

Parameters
Name	Description
`request`	`.location_pb2.GetLocationRequest` The request object. Request message for `GetLocation` method.
`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
`.location_pb2.Location`	Location object.

get_mtls_endpoint_and_cert_source

get_mtls_endpoint_and_cert_source(
    client_options: typing.Optional[
        google.api_core.client_options.ClientOptions
    ] = None,
)

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variable is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Parameter
Name	Description
`client_options`	`google.api_core.client_options.ClientOptions` Custom options for the client. Only the `api_endpoint` and `client_cert_source` properties may be used in this method.

Exceptions
Type	Description
`google.auth.exceptions.MutualTLSChannelError`	If any errors happen.

Returns
Type	Description
`Tuple[str, Callable[[], Tuple[bytes, bytes]]]`	returns the API endpoint and the client cert source to use.

get_operation

get_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.GetOperationRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation

Gets the latest state of a long-running operation.

Parameters
Name	Description
`request`	`.operations_pb2.GetOperationRequest` The request object. Request message for `GetOperation` method.
`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
`.operations_pb2.Operation`	An `Operation` object.

list_endpoints

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

Lists Endpoints in a Location.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_list_endpoints():
    # Create a client
    client = aiplatform_v1.EndpointServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListEndpointsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_endpoints(request=request)

    # Handle the response
    for response in page_result:
        print(response)

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.

list_locations

list_locations(
    request: typing.Optional[
        google.cloud.location.locations_pb2.ListLocationsRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.ListLocationsResponse

Lists information about the supported locations for this service.

Parameters
Name	Description
`request`	`.location_pb2.ListLocationsRequest` The request object. Request message for `ListLocations` method.
`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
`.location_pb2.ListLocationsResponse`	Response message for `ListLocations` method.

list_operations

list_operations(
    request: typing.Optional[
        google.longrunning.operations_pb2.ListOperationsRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.ListOperationsResponse

Lists operations that match the specified filter in the request.

Parameters
Name	Description
`request`	`.operations_pb2.ListOperationsRequest` The request object. Request message for `ListOperations` method.
`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
`.operations_pb2.ListOperationsResponse`	Response message for `ListOperations` method.

model_deployment_monitoring_job_path

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

Returns a fully-qualified model_deployment_monitoring_job string.

model_path

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

Returns a fully-qualified model string.

mutate_deployed_model

mutate_deployed_model(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.endpoint_service.MutateDeployedModelRequest,
            dict,
        ]
    ] = None,
    *,
    endpoint: typing.Optional[str] = None,
    deployed_model: typing.Optional[
        google.cloud.aiplatform_v1.types.endpoint.DeployedModel
    ] = None,
    update_mask: typing.Optional[google.protobuf.field_mask_pb2.FieldMask] = None,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Updates an existing deployed model. Updatable fields include min_replica_count, max_replica_count, autoscaling_metric_specs, disable_container_logging (v1 only), and enable_container_logging (v1beta1 only).

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_mutate_deployed_model():
    # Create a client
    client = aiplatform_v1.EndpointServiceClient()

    # Initialize request argument(s)
    deployed_model = aiplatform_v1.DeployedModel()
    deployed_model.dedicated_resources.min_replica_count = 1803
    deployed_model.model = "model_value"

    request = aiplatform_v1.MutateDeployedModelRequest(
        endpoint="endpoint_value",
        deployed_model=deployed_model,
    )

    # Make the request
    operation = client.mutate_deployed_model(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

Parameters
Name	Description
`request`	`Union[google.cloud.aiplatform_v1.types.MutateDeployedModelRequest, dict]` The request object. Request message for EndpointService.MutateDeployedModel.
`endpoint`	`str` Required. The name of the Endpoint resource into which to mutate a DeployedModel. 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 mutated within the Endpoint. Only the following fields can be mutated: - `min_replica_count` in either DedicatedResources or AutomaticResources - `max_replica_count` in either DedicatedResources or AutomaticResources - autoscaling_metric_specs - `disable_container_logging` (v1 only) - `enable_container_logging` (v1beta1 only) This corresponds to the `deployed_model` 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.api_core.operation.Operation`	An object representing a long-running operation. The result type for the operation will be MutateDeployedModelResponse Response message for EndpointService.MutateDeployedModel.

network_path

network_path(project: str, network: str) -> str

Returns a fully-qualified network string.

parse_common_billing_account_path

parse_common_billing_account_path(path: str) -> typing.Dict[str, str]

Parse a billing_account path into its component segments.

parse_common_folder_path

parse_common_folder_path(path: str) -> typing.Dict[str, str]

Parse a folder path into its component segments.

parse_common_location_path

parse_common_location_path(path: str) -> typing.Dict[str, str]

Parse a location path into its component segments.

parse_common_organization_path

parse_common_organization_path(path: str) -> typing.Dict[str, str]

Parse a organization path into its component segments.

parse_common_project_path

parse_common_project_path(path: str) -> typing.Dict[str, str]

Parse a project path into its component segments.

parse_endpoint_path

parse_endpoint_path(path: str) -> typing.Dict[str, str]

Parses a endpoint path into its component segments.

parse_model_deployment_monitoring_job_path

parse_model_deployment_monitoring_job_path(path: str) -> typing.Dict[str, str]

Parses a model_deployment_monitoring_job path into its component segments.

parse_model_path

parse_model_path(path: str) -> typing.Dict[str, str]

Parses a model path into its component segments.

parse_network_path

parse_network_path(path: str) -> typing.Dict[str, str]

Parses a network path into its component segments.

set_iam_policy

set_iam_policy(
    request: typing.Optional[google.iam.v1.iam_policy_pb2.SetIamPolicyRequest] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy

Sets the IAM access control policy on the specified function.

Replaces any existing policy.

Parameters
Name	Description
`request`	`.iam_policy_pb2.SetIamPolicyRequest` The request object. Request message for `SetIamPolicy` method.
`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

test_iam_permissions

test_iam_permissions(
    request: typing.Optional[
        google.iam.v1.iam_policy_pb2.TestIamPermissionsRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.iam_policy_pb2.TestIamPermissionsResponse

Tests the specified IAM permissions against the IAM access control policy for a function.

If the function does not exist, this will return an empty set of permissions, not a NOT_FOUND error.

Parameters
Name	Description
`request`	`.iam_policy_pb2.TestIamPermissionsRequest` The request object. Request message for `TestIamPermissions` method.
`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
`.iam_policy_pb2.TestIamPermissionsResponse`	Response message for `TestIamPermissions` method.

undeploy_model

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

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

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_undeploy_model():
    # Create a client
    client = aiplatform_v1.EndpointServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.UndeployModelRequest(
        endpoint="endpoint_value",
        deployed_model_id="deployed_model_id_value",
    )

    # Make the request
    operation = client.undeploy_model(request=request)

    print("Waiting for operation to complete...")

    response = operation.result()

    # Handle the response
    print(response)

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

Updates an Endpoint.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_update_endpoint():
    # Create a client
    client = aiplatform_v1.EndpointServiceClient()

    # Initialize request argument(s)
    endpoint = aiplatform_v1.Endpoint()
    endpoint.display_name = "display_name_value"

    request = aiplatform_v1.UpdateEndpointRequest(
        endpoint=endpoint,
    )

    # Make the request
    response = client.update_endpoint(request=request)

    # Handle the response
    print(response)

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.

wait_operation

wait_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.WaitOperationRequest
    ] = None,
    *,
    retry: typing.Union[
        google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation

Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state.

If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters
Name	Description
`request`	`.operations_pb2.WaitOperationRequest` The request object. Request message for `WaitOperation` method.
`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
`.operations_pb2.Operation`	An `Operation` object.