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"""This module contains a Google Cloud Vertex AI hook."""
from __future__ import annotations
from typing import TYPE_CHECKING, Sequence
from google.api_core.client_options import ClientOptions
from google.api_core.gapic_v1.method import DEFAULT, _MethodDefault
from google.cloud.aiplatform_v1 import EndpointServiceClient
from airflow.exceptions import AirflowException
from airflow.providers.google.common.hooks.base_google import GoogleBaseHook
if TYPE_CHECKING:
from google.api_core.operation import Operation
from google.api_core.retry import Retry
from google.cloud.aiplatform_v1.services.endpoint_service.pagers import ListEndpointsPager
from google.cloud.aiplatform_v1.types import DeployedModel, Endpoint
from google.protobuf.field_mask_pb2 import FieldMask
[docs]class EndpointServiceHook(GoogleBaseHook):
"""Hook for Google Cloud Vertex AI Endpoint Service APIs."""
def __init__(self, **kwargs):
if kwargs.get("delegate_to") is not None:
raise RuntimeError(
"The `delegate_to` parameter has been deprecated before and finally removed in this version"
" of Google Provider. You MUST convert it to `impersonate_chain`"
)
super().__init__(**kwargs)
[docs] def get_endpoint_service_client(self, region: str | None = None) -> EndpointServiceClient:
"""Returns EndpointServiceClient."""
if region and region != "global":
client_options = ClientOptions(api_endpoint=f"{region}-aiplatform.googleapis.com:443")
else:
client_options = ClientOptions()
return EndpointServiceClient(
credentials=self.get_credentials(), client_info=self.client_info, client_options=client_options
)
[docs] def wait_for_operation(self, operation: Operation, timeout: float | None = None):
"""Waits for long-lasting operation to complete."""
try:
return operation.result(timeout=timeout)
except Exception:
error = operation.exception(timeout=timeout)
raise AirflowException(error)
@staticmethod
@staticmethod
@GoogleBaseHook.fallback_to_default_project_id
[docs] def create_endpoint(
self,
project_id: str,
region: str,
endpoint: Endpoint | dict,
endpoint_id: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""
Creates an Endpoint.
:param project_id: Required. The ID of the Google Cloud project that the service belongs to.
:param region: Required. The ID of the Google Cloud region that the service belongs to.
:param endpoint: Required. The Endpoint to create.
:param endpoint_id: The ID of Endpoint. This value should be 1-10 characters, and valid characters
are /[0-9]/. If not provided, Vertex AI will generate a value for this ID.
:param retry: Designation of what errors, if any, should be retried.
:param timeout: The timeout for this request.
:param metadata: Strings which should be sent along with the request as metadata.
"""
client = self.get_endpoint_service_client(region)
parent = client.common_location_path(project_id, region)
result = client.create_endpoint(
request={
"parent": parent,
"endpoint": endpoint,
"endpoint_id": endpoint_id,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def delete_endpoint(
self,
project_id: str,
region: str,
endpoint: str,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""
Deletes an Endpoint.
:param project_id: Required. The ID of the Google Cloud project that the service belongs to.
:param region: Required. The ID of the Google Cloud region that the service belongs to.
:param endpoint: Required. The Endpoint to delete.
:param retry: Designation of what errors, if any, should be retried.
:param timeout: The timeout for this request.
:param metadata: Strings which should be sent along with the request as metadata.
"""
client = self.get_endpoint_service_client(region)
name = client.endpoint_path(project_id, region, endpoint)
result = client.delete_endpoint(
request={
"name": name,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def deploy_model(
self,
project_id: str,
region: str,
endpoint: str,
deployed_model: DeployedModel | dict,
traffic_split: Sequence | dict | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""
Deploys a Model into this Endpoint, creating a DeployedModel within it.
:param project_id: Required. The ID of the Google Cloud project that the service belongs to.
:param region: Required. The ID of the Google Cloud region that the service belongs to.
:param endpoint: Required. The name of the Endpoint resource into which to deploy a Model. Format:
``projects/{project}/locations/{location}/endpoints/{endpoint}``
:param deployed_model: Required. The DeployedModel to be created within the Endpoint. Note that
[Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split] must be updated for
the DeployedModel to start receiving traffic, either as part of this call, or via
[EndpointService.UpdateEndpoint][google.cloud.aiplatform.v1.EndpointService.UpdateEndpoint].
:param traffic_split: 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][google.cloud.aiplatform.v1.Endpoint.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][google.cloud.aiplatform.v1.Endpoint.traffic_split] is not updated.
:param retry: Designation of what errors, if any, should be retried.
:param timeout: The timeout for this request.
:param metadata: Strings which should be sent along with the request as metadata.
"""
client = self.get_endpoint_service_client(region)
endpoint_path = client.endpoint_path(project_id, region, endpoint)
result = client.deploy_model(
request={
"endpoint": endpoint_path,
"deployed_model": deployed_model,
"traffic_split": traffic_split,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def get_endpoint(
self,
project_id: str,
region: str,
endpoint: str,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Endpoint:
"""
Gets an Endpoint.
:param project_id: Required. The ID of the Google Cloud project that the service belongs to.
:param region: Required. The ID of the Google Cloud region that the service belongs to.
:param endpoint: Required. The Endpoint to get.
:param retry: Designation of what errors, if any, should be retried.
:param timeout: The timeout for this request.
:param metadata: Strings which should be sent along with the request as metadata.
"""
client = self.get_endpoint_service_client(region)
name = client.endpoint_path(project_id, region, endpoint)
result = client.get_endpoint(
request={
"name": name,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def list_endpoints(
self,
project_id: str,
region: str,
filter: str | None = None,
page_size: int | None = None,
page_token: str | None = None,
read_mask: str | None = None,
order_by: str | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> ListEndpointsPager:
"""
Lists Endpoints in a Location.
:param project_id: Required. The ID of the Google Cloud project that the service belongs to.
:param region: Required. The ID of the Google Cloud region that the service belongs to.
:param filter: The standard list filter.
Supported fields:
- ``display_name`` supports = and !=.
- ``state`` supports = and !=.
- ``model_display_name`` supports = and !=
Some examples of using the filter are:
- ``state="JOB_STATE_SUCCEEDED" AND display_name="my_job"``
- ``state="JOB_STATE_RUNNING" OR display_name="my_job"``
- ``NOT display_name="my_job"``
- ``state="JOB_STATE_FAILED"``
:param page_size: The standard list page size.
:param page_token: The standard list page token.
:param read_mask: Mask specifying which fields to read.
:param order_by: A comma-separated list of fields to order by, sorted in
ascending order. Use "desc" after a field name for
descending. Supported fields:
- ``display_name``
- ``create_time``
- ``update_time``
Example: ``display_name, create_time desc``.
:param retry: Designation of what errors, if any, should be retried.
:param timeout: The timeout for this request.
:param metadata: Strings which should be sent along with the request as metadata.
"""
client = self.get_endpoint_service_client(region)
parent = client.common_location_path(project_id, region)
result = client.list_endpoints(
request={
"parent": parent,
"filter": filter,
"page_size": page_size,
"page_token": page_token,
"read_mask": read_mask,
"order_by": order_by,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def undeploy_model(
self,
project_id: str,
region: str,
endpoint: str,
deployed_model_id: str,
traffic_split: Sequence | dict | None = None,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""
Undeploys a Model from an Endpoint, removing a DeployedModel from it, and freeing all used resources.
:param project_id: Required. The ID of the Google Cloud project that the service belongs to.
:param region: Required. The ID of the Google Cloud region that the service belongs to.
:param endpoint: Required. The name of the Endpoint resource from which to undeploy a Model.
:param deployed_model_id: Required. The ID of the DeployedModel to be undeployed from the Endpoint.
:param traffic_split: If this field is provided, then the Endpoint's
[traffic_split][google.cloud.aiplatform.v1.Endpoint.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.
:param retry: Designation of what errors, if any, should be retried.
:param timeout: The timeout for this request.
:param metadata: Strings which should be sent along with the request as metadata.
"""
client = self.get_endpoint_service_client(region)
endpoint_path = client.endpoint_path(project_id, region, endpoint)
result = client.undeploy_model(
request={
"endpoint": endpoint_path,
"deployed_model_id": deployed_model_id,
"traffic_split": traffic_split,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def update_endpoint(
self,
project_id: str,
region: str,
endpoint_id: str,
endpoint: Endpoint | dict,
update_mask: FieldMask | dict,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Endpoint:
"""
Updates an Endpoint.
:param project_id: Required. The ID of the Google Cloud project that the service belongs to.
:param region: Required. The ID of the Google Cloud region that the service belongs to.
:param endpoint: Required. The Endpoint which replaces the resource on the server.
:param update_mask: Required. The update mask applies to the resource. See
[google.protobuf.FieldMask][google.protobuf.FieldMask].
:param retry: Designation of what errors, if any, should be retried.
:param timeout: The timeout for this request.
:param metadata: Strings which should be sent along with the request as metadata.
"""
client = self.get_endpoint_service_client(region)
endpoint["name"] = client.endpoint_path(project_id, region, endpoint_id)
result = client.update_endpoint(
request={
"endpoint": endpoint,
"update_mask": update_mask,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
