Source code for airflow.providers.google.cloud.hooks.vertex_ai.model_service

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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 extract_model_id(obj: dict) -> str: """Returns unique id of the model.""" return obj["model"].rpartition("/")[-1]
[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

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