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"""This module contains a Google Cloud Vertex AI hook.
.. spelling:word-list::
aiplatform
camelCase
"""
from __future__ import annotations
from typing import Sequence
from google.api_core.client_options import ClientOptions
from google.api_core.gapic_v1.method import DEFAULT, _MethodDefault
from google.api_core.operation import Operation
from google.api_core.retry import Retry
from google.cloud.aiplatform_v1 import ModelServiceClient
from google.cloud.aiplatform_v1.services.model_service.pagers import ListModelsPager
from google.cloud.aiplatform_v1.types import Model, model_service
from airflow import AirflowException
from airflow.providers.google.common.hooks.base_google import GoogleBaseHook
[docs]class ModelServiceHook(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_model_service_client(self, region: str | None = None) -> ModelServiceClient:
"""Returns ModelServiceClient."""
if region and region != "global":
client_options = ClientOptions(api_endpoint=f"{region}-aiplatform.googleapis.com:443")
else:
client_options = ClientOptions()
return ModelServiceClient(
credentials=self.get_credentials(), client_info=self.client_info, client_options=client_options
)
@staticmethod
[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)
@GoogleBaseHook.fallback_to_default_project_id
[docs] def delete_model(
self,
project_id: str,
region: str,
model: str,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""
Deletes a Model.
: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 model: Required. The name of the Model resource to be deleted.
: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_model_service_client(region)
name = client.model_path(project_id, region, model)
result = client.delete_model(
request={
"name": name,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def export_model(
self,
project_id: str,
region: str,
model: str,
output_config: model_service.ExportModelRequest.OutputConfig | dict,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""
Exports a trained, exportable Model to a location specified by the user.
: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 model: Required. The resource name of the Model to export.
:param output_config: Required. The desired output location and configuration.
: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_model_service_client(region)
name = client.model_path(project_id, region, model)
result = client.export_model(
request={
"name": name,
"output_config": output_config,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
@GoogleBaseHook.fallback_to_default_project_id
[docs] def list_models(
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]] = (),
) -> ListModelsPager:
r"""
Lists Models 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: An expression for filtering the results of the request. For field names both
snake_case and camelCase are supported.
- ``model`` supports = and !=. ``model`` represents the Model ID, i.e. the last segment of the
Model's [resource name][google.cloud.aiplatform.v1.Model.name].
- ``display_name`` supports = and !=
- ``labels`` supports general map functions that is:
-- ``labels.key=value`` - key:value equality
-- \`labels.key:\* or labels:key - key existence
-- A key including a space must be quoted. ``labels."a key"``.
:param page_size: The standard list page size.
:param page_token: The standard list page token. Typically obtained via
[ListModelsResponse.next_page_token][google.cloud.aiplatform.v1.ListModelsResponse.next_page_token]
of the previous
[ModelService.ListModels][google.cloud.aiplatform.v1.ModelService.ListModels]
call.
: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.
: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_model_service_client(region)
parent = client.common_location_path(project_id, region)
result = client.list_models(
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 upload_model(
self,
project_id: str,
region: str,
model: Model | dict,
retry: Retry | _MethodDefault = DEFAULT,
timeout: float | None = None,
metadata: Sequence[tuple[str, str]] = (),
) -> Operation:
"""
Uploads a Model artifact into Vertex AI.
: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 model: Required. The Model to create.
: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_model_service_client(region)
parent = client.common_location_path(project_id, region)
result = client.upload_model(
request={
"parent": parent,
"model": model,
},
retry=retry,
timeout=timeout,
metadata=metadata,
)
return result
