- 1.71.0 (latest)
- 1.70.0
- 1.69.0
- 1.68.0
- 1.67.1
- 1.66.0
- 1.65.0
- 1.63.0
- 1.62.0
- 1.60.0
- 1.59.0
- 1.58.0
- 1.57.0
- 1.56.0
- 1.55.0
- 1.54.1
- 1.53.0
- 1.52.0
- 1.51.0
- 1.50.0
- 1.49.0
- 1.48.0
- 1.47.0
- 1.46.0
- 1.45.0
- 1.44.0
- 1.43.0
- 1.39.0
- 1.38.1
- 1.37.0
- 1.36.4
- 1.35.0
- 1.34.0
- 1.33.1
- 1.32.0
- 1.31.1
- 1.30.1
- 1.29.0
- 1.28.1
- 1.27.1
- 1.26.1
- 1.25.0
- 1.24.1
- 1.23.0
- 1.22.1
- 1.21.0
- 1.20.0
- 1.19.1
- 1.18.3
- 1.17.1
- 1.16.1
- 1.15.1
- 1.14.0
- 1.13.1
- 1.12.1
- 1.11.0
- 1.10.0
- 1.9.0
- 1.8.1
- 1.7.1
- 1.6.2
- 1.5.0
- 1.4.3
- 1.3.0
- 1.2.0
- 1.1.1
- 1.0.1
- 0.9.0
- 0.8.0
- 0.7.1
- 0.6.0
- 0.5.1
- 0.4.0
- 0.3.1
IndexEndpointServiceAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.aiplatform_v1.services.index_endpoint_service.transports.base.IndexEndpointServiceTransport] = 'grpc_asyncio', 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 IndexEndpoints.
Inheritance
builtins.object > IndexEndpointServiceAsyncClientProperties
transport
Returns the transport used by the client instance.
Type | Description |
IndexEndpointServiceTransport | The transport used by the client instance. |
Methods
IndexEndpointServiceAsyncClient
IndexEndpointServiceAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.aiplatform_v1.services.index_endpoint_service.transports.base.IndexEndpointServiceTransport] = 'grpc_asyncio', 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 index endpoint service client.
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, `.IndexEndpointServiceTransport`]
The transport to use. If set to None, a transport is chosen automatically. |
client_options |
ClientOptions
Custom options for the client. It won't take effect if a |
Type | Description |
google.auth.exceptions.MutualTlsChannelError | If mutual TLS transport creation failed for any reason. |
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_index_endpoint
create_index_endpoint(request: Optional[Union[google.cloud.aiplatform_v1.types.index_endpoint_service.CreateIndexEndpointRequest, dict]] = None, *, parent: Optional[str] = None, index_endpoint: Optional[google.cloud.aiplatform_v1.types.index_endpoint.IndexEndpoint] = 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 IndexEndpoint.
from google.cloud import aiplatform_v1
def sample_create_index_endpoint():
# Create a client
client = aiplatform_v1.IndexEndpointServiceClient()
# Initialize request argument(s)
index_endpoint = aiplatform_v1.IndexEndpoint()
index_endpoint.display_name = "display_name_value"
request = aiplatform_v1.CreateIndexEndpointRequest(
parent="parent_value",
index_endpoint=index_endpoint,
)
# Make the request
operation = client.create_index_endpoint(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.CreateIndexEndpointRequest, dict]
The request object. Request message for IndexEndpointService.CreateIndexEndpoint. |
parent |
`str`
Required. The resource name of the Location to create the IndexEndpoint in. Format: |
index_endpoint |
IndexEndpoint
Required. The IndexEndpoint to create. This corresponds to the |
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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be IndexEndpoint Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes. |
delete_index_endpoint
delete_index_endpoint(request: Optional[Union[google.cloud.aiplatform_v1.types.index_endpoint_service.DeleteIndexEndpointRequest, 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 IndexEndpoint.
from google.cloud import aiplatform_v1
def sample_delete_index_endpoint():
# Create a client
client = aiplatform_v1.IndexEndpointServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.DeleteIndexEndpointRequest(
name="name_value",
)
# Make the request
operation = client.delete_index_endpoint(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.DeleteIndexEndpointRequest, dict]
The request object. Request message for IndexEndpointService.DeleteIndexEndpoint. |
name |
`str`
Required. The name of the IndexEndpoint resource to be deleted. Format: |
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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | 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_index
deploy_index(request: Optional[Union[google.cloud.aiplatform_v1.types.index_endpoint_service.DeployIndexRequest, dict]] = None, *, index_endpoint: Optional[str] = None, deployed_index: Optional[google.cloud.aiplatform_v1.types.index_endpoint.DeployedIndex] = 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 an Index into this IndexEndpoint, creating a DeployedIndex within it. Only non-empty Indexes can be deployed.
from google.cloud import aiplatform_v1
def sample_deploy_index():
# Create a client
client = aiplatform_v1.IndexEndpointServiceClient()
# Initialize request argument(s)
deployed_index = aiplatform_v1.DeployedIndex()
deployed_index.id = "id_value"
deployed_index.index = "index_value"
request = aiplatform_v1.DeployIndexRequest(
index_endpoint="index_endpoint_value",
deployed_index=deployed_index,
)
# Make the request
operation = client.deploy_index(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.DeployIndexRequest, dict]
The request object. Request message for IndexEndpointService.DeployIndex. |
index_endpoint |
`str`
Required. The name of the IndexEndpoint resource into which to deploy an Index. Format: |
deployed_index |
DeployedIndex
Required. The DeployedIndex to be created within the IndexEndpoint. This corresponds to the |
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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be DeployIndexResponse Response message for IndexEndpointService.DeployIndex. |
from_service_account_file
from_service_account_file(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
IndexEndpointServiceAsyncClient | 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.
Name | Description |
info |
dict
The service account private key info. |
Type | Description |
IndexEndpointServiceAsyncClient | 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.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
IndexEndpointServiceAsyncClient | The constructed client. |
get_index_endpoint
get_index_endpoint(request: Optional[Union[google.cloud.aiplatform_v1.types.index_endpoint_service.GetIndexEndpointRequest, 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 IndexEndpoint.
from google.cloud import aiplatform_v1
def sample_get_index_endpoint():
# Create a client
client = aiplatform_v1.IndexEndpointServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.GetIndexEndpointRequest(
name="name_value",
)
# Make the request
response = client.get_index_endpoint(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.GetIndexEndpointRequest, dict]
The request object. Request message for IndexEndpointService.GetIndexEndpoint |
name |
`str`
Required. The name of the IndexEndpoint resource. Format: |
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. |
Type | Description |
google.cloud.aiplatform_v1.types.IndexEndpoint | Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes. |
get_mtls_endpoint_and_cert_source
get_mtls_endpoint_and_cert_source(
client_options: 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 variabel 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.
Name | Description |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. Only the |
Type | Description |
google.auth.exceptions.MutualTLSChannelError | If any errors happen. |
Type | Description |
Tuple[str, Callable[[], Tuple[bytes, bytes]]] | returns the API endpoint and the client cert source to use. |
get_transport_class
get_transport_class()
Returns an appropriate transport class.
index_endpoint_path
index_endpoint_path(project: str, location: str, index_endpoint: str)
Returns a fully-qualified index_endpoint string.
index_path
index_path(project: str, location: str, index: str)
Returns a fully-qualified index string.
list_index_endpoints
list_index_endpoints(request: Optional[Union[google.cloud.aiplatform_v1.types.index_endpoint_service.ListIndexEndpointsRequest, 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 IndexEndpoints in a Location.
from google.cloud import aiplatform_v1
def sample_list_index_endpoints():
# Create a client
client = aiplatform_v1.IndexEndpointServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.ListIndexEndpointsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_index_endpoints(request=request)
# Handle the response
for response in page_result:
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.ListIndexEndpointsRequest, dict]
The request object. Request message for IndexEndpointService.ListIndexEndpoints. |
parent |
`str`
Required. The resource name of the Location from which to list the IndexEndpoints. Format: |
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. |
Type | Description |
google.cloud.aiplatform_v1.services.index_endpoint_service.pagers.ListIndexEndpointsAsyncPager | Response message for IndexEndpointService.ListIndexEndpoints. Iterating over this object will yield results and resolve additional pages automatically. |
mutate_deployed_index
mutate_deployed_index(request: Optional[Union[google.cloud.aiplatform_v1.types.index_endpoint_service.MutateDeployedIndexRequest, dict]] = None, *, index_endpoint: Optional[str] = None, deployed_index: Optional[google.cloud.aiplatform_v1.types.index_endpoint.DeployedIndex] = 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]] = ())
Update an existing DeployedIndex under an IndexEndpoint.
from google.cloud import aiplatform_v1
def sample_mutate_deployed_index():
# Create a client
client = aiplatform_v1.IndexEndpointServiceClient()
# Initialize request argument(s)
deployed_index = aiplatform_v1.DeployedIndex()
deployed_index.id = "id_value"
deployed_index.index = "index_value"
request = aiplatform_v1.MutateDeployedIndexRequest(
index_endpoint="index_endpoint_value",
deployed_index=deployed_index,
)
# Make the request
operation = client.mutate_deployed_index(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.MutateDeployedIndexRequest, dict]
The request object. Request message for IndexEndpointService.MutateDeployedIndex. |
index_endpoint |
`str`
Required. The name of the IndexEndpoint resource into which to deploy an Index. Format: |
deployed_index |
DeployedIndex
Required. The DeployedIndex to be updated within the IndexEndpoint. Currently, the updatable fields are |
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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be MutateDeployedIndexResponse Response message for IndexEndpointService.MutateDeployedIndex. |
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_index_endpoint_path
parse_index_endpoint_path(path: str)
Parses a index_endpoint path into its component segments.
parse_index_path
parse_index_path(path: str)
Parses a index path into its component segments.
undeploy_index
undeploy_index(request: Optional[Union[google.cloud.aiplatform_v1.types.index_endpoint_service.UndeployIndexRequest, dict]] = None, *, index_endpoint: Optional[str] = None, deployed_index_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]] = ())
Undeploys an Index from an IndexEndpoint, removing a DeployedIndex from it, and freeing all resources it's using.
from google.cloud import aiplatform_v1
def sample_undeploy_index():
# Create a client
client = aiplatform_v1.IndexEndpointServiceClient()
# Initialize request argument(s)
request = aiplatform_v1.UndeployIndexRequest(
index_endpoint="index_endpoint_value",
deployed_index_id="deployed_index_id_value",
)
# Make the request
operation = client.undeploy_index(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.UndeployIndexRequest, dict]
The request object. Request message for IndexEndpointService.UndeployIndex. |
index_endpoint |
`str`
Required. The name of the IndexEndpoint resource from which to undeploy an Index. Format: |
deployed_index_id |
`str`
Required. The ID of the DeployedIndex to be undeployed from the IndexEndpoint. This corresponds to the |
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. |
Type | Description |
google.api_core.operation_async.AsyncOperation | An object representing a long-running operation. The result type for the operation will be UndeployIndexResponse Response message for IndexEndpointService.UndeployIndex. |
update_index_endpoint
update_index_endpoint(request: Optional[Union[google.cloud.aiplatform_v1.types.index_endpoint_service.UpdateIndexEndpointRequest, dict]] = None, *, index_endpoint: Optional[google.cloud.aiplatform_v1.types.index_endpoint.IndexEndpoint] = 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 IndexEndpoint.
from google.cloud import aiplatform_v1
def sample_update_index_endpoint():
# Create a client
client = aiplatform_v1.IndexEndpointServiceClient()
# Initialize request argument(s)
index_endpoint = aiplatform_v1.IndexEndpoint()
index_endpoint.display_name = "display_name_value"
request = aiplatform_v1.UpdateIndexEndpointRequest(
index_endpoint=index_endpoint,
)
# Make the request
response = client.update_index_endpoint(request=request)
# Handle the response
print(response)
Name | Description |
request |
Union[google.cloud.aiplatform_v1.types.UpdateIndexEndpointRequest, dict]
The request object. Request message for IndexEndpointService.UpdateIndexEndpoint. |
index_endpoint |
IndexEndpoint
Required. The IndexEndpoint which replaces the resource on the server. This corresponds to the |
update_mask |
`google.protobuf.field_mask_pb2.FieldMask`
Required. The update mask applies to the resource. See |
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. |
Type | Description |
google.cloud.aiplatform_v1.types.IndexEndpoint | Indexes are deployed into it. An IndexEndpoint can have multiple DeployedIndexes. |