# -*- coding: utf-8 -*- # Copyright 2022 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from collections import OrderedDict import functools import re from typing import ( Dict, Mapping, MutableMapping, MutableSequence, Optional, Sequence, Tuple, Type, Union, ) from google.api_core import exceptions as core_exceptions from google.api_core import gapic_v1 from google.api_core import retry as retries from google.api_core.client_options import ClientOptions from google.auth import credentials as ga_credentials # type: ignore from google.oauth2 import service_account # type: ignore from google.ai.generativelanguage_v1beta2 import gapic_version as package_version try: OptionalRetry = Union[retries.Retry, gapic_v1.method._MethodDefault] except AttributeError: # pragma: NO COVER OptionalRetry = Union[retries.Retry, object] # type: ignore from google.ai.generativelanguage_v1beta2.services.model_service import pagers from google.ai.generativelanguage_v1beta2.types import model, model_service from .client import ModelServiceClient from .transports.base import DEFAULT_CLIENT_INFO, ModelServiceTransport from .transports.grpc_asyncio import ModelServiceGrpcAsyncIOTransport class ModelServiceAsyncClient: """Provides methods for getting metadata information about Generative Models. """ _client: ModelServiceClient DEFAULT_ENDPOINT = ModelServiceClient.DEFAULT_ENDPOINT DEFAULT_MTLS_ENDPOINT = ModelServiceClient.DEFAULT_MTLS_ENDPOINT model_path = staticmethod(ModelServiceClient.model_path) parse_model_path = staticmethod(ModelServiceClient.parse_model_path) common_billing_account_path = staticmethod( ModelServiceClient.common_billing_account_path ) parse_common_billing_account_path = staticmethod( ModelServiceClient.parse_common_billing_account_path ) common_folder_path = staticmethod(ModelServiceClient.common_folder_path) parse_common_folder_path = staticmethod(ModelServiceClient.parse_common_folder_path) common_organization_path = staticmethod(ModelServiceClient.common_organization_path) parse_common_organization_path = staticmethod( ModelServiceClient.parse_common_organization_path ) common_project_path = staticmethod(ModelServiceClient.common_project_path) parse_common_project_path = staticmethod( ModelServiceClient.parse_common_project_path ) common_location_path = staticmethod(ModelServiceClient.common_location_path) parse_common_location_path = staticmethod( ModelServiceClient.parse_common_location_path ) @classmethod def from_service_account_info(cls, info: dict, *args, **kwargs): """Creates an instance of this client using the provided credentials info. Args: info (dict): The service account private key info. args: Additional arguments to pass to the constructor. kwargs: Additional arguments to pass to the constructor. Returns: ModelServiceAsyncClient: The constructed client. """ return ModelServiceClient.from_service_account_info.__func__(ModelServiceAsyncClient, info, *args, **kwargs) # type: ignore @classmethod def from_service_account_file(cls, filename: str, *args, **kwargs): """Creates an instance of this client using the provided credentials file. Args: filename (str): The path to the service account private key json file. args: Additional arguments to pass to the constructor. kwargs: Additional arguments to pass to the constructor. Returns: ModelServiceAsyncClient: The constructed client. """ return ModelServiceClient.from_service_account_file.__func__(ModelServiceAsyncClient, filename, *args, **kwargs) # type: ignore from_service_account_json = from_service_account_file @classmethod def get_mtls_endpoint_and_cert_source( cls, client_options: Optional[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. Args: 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. Returns: Tuple[str, Callable[[], Tuple[bytes, bytes]]]: returns the API endpoint and the client cert source to use. Raises: google.auth.exceptions.MutualTLSChannelError: If any errors happen. """ return ModelServiceClient.get_mtls_endpoint_and_cert_source(client_options) # type: ignore @property def transport(self) -> ModelServiceTransport: """Returns the transport used by the client instance. Returns: ModelServiceTransport: The transport used by the client instance. """ return self._client.transport get_transport_class = functools.partial( type(ModelServiceClient).get_transport_class, type(ModelServiceClient) ) def __init__( self, *, credentials: Optional[ga_credentials.Credentials] = None, transport: Union[str, ModelServiceTransport] = "grpc_asyncio", client_options: Optional[ClientOptions] = None, client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, ) -> None: """Instantiates the model service client. Args: 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, ~.ModelServiceTransport]): 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 ``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. Raises: google.auth.exceptions.MutualTlsChannelError: If mutual TLS transport creation failed for any reason. """ self._client = ModelServiceClient( credentials=credentials, transport=transport, client_options=client_options, client_info=client_info, ) async def get_model( self, request: Optional[Union[model_service.GetModelRequest, dict]] = None, *, name: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, str]] = (), ) -> model.Model: r"""Gets information about a specific Model. .. code-block:: python # 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.ai import generativelanguage_v1beta2 async def sample_get_model(): # Create a client client = generativelanguage_v1beta2.ModelServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta2.GetModelRequest( name="name_value", ) # Make the request response = await client.get_model(request=request) # Handle the response print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta2.types.GetModelRequest, dict]]): The request object. Request for getting information about a specific Model. name (:class:`str`): Required. The resource name of the model. This name should match a model name returned by the ``ListModels`` method. Format: ``models/{model}`` 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: google.ai.generativelanguage_v1beta2.types.Model: Information about a Generative Language Model. """ # Create or coerce a protobuf request object. # Quick check: If we got a request object, we should *not* have # gotten any keyword arguments that map to the request. has_flattened_params = any([name]) if request is not None and has_flattened_params: raise ValueError( "If the `request` argument is set, then none of " "the individual field arguments should be set." ) request = model_service.GetModelRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if name is not None: request.name = name # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = gapic_v1.method_async.wrap_method( self._client._transport.get_model, default_timeout=None, client_info=DEFAULT_CLIENT_INFO, ) # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("name", request.name),)), ) # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response async def list_models( self, request: Optional[Union[model_service.ListModelsRequest, dict]] = None, *, page_size: Optional[int] = None, page_token: Optional[str] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, str]] = (), ) -> pagers.ListModelsAsyncPager: r"""Lists models available through the API. .. code-block:: python # 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.ai import generativelanguage_v1beta2 async def sample_list_models(): # Create a client client = generativelanguage_v1beta2.ModelServiceAsyncClient() # Initialize request argument(s) request = generativelanguage_v1beta2.ListModelsRequest( ) # Make the request page_result = client.list_models(request=request) # Handle the response async for response in page_result: print(response) Args: request (Optional[Union[google.ai.generativelanguage_v1beta2.types.ListModelsRequest, dict]]): The request object. Request for listing all Models. page_size (:class:`int`): The maximum number of ``Models`` to return (per page). The service may return fewer models. If unspecified, at most 50 models will be returned per page. This method returns at most 1000 models per page, even if you pass a larger page_size. This corresponds to the ``page_size`` field on the ``request`` instance; if ``request`` is provided, this should not be set. page_token (:class:`str`): A page token, received from a previous ``ListModels`` call. Provide the ``page_token`` returned by one request as an argument to the next request to retrieve the next page. When paginating, all other parameters provided to ``ListModels`` must match the call that provided the page token. This corresponds to the ``page_token`` 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: google.ai.generativelanguage_v1beta2.services.model_service.pagers.ListModelsAsyncPager: Response from ListModel containing a paginated list of Models. Iterating over this object will yield results and resolve additional pages automatically. """ # Create or coerce a protobuf request object. # Quick check: If we got a request object, we should *not* have # gotten any keyword arguments that map to the request. has_flattened_params = any([page_size, page_token]) if request is not None and has_flattened_params: raise ValueError( "If the `request` argument is set, then none of " "the individual field arguments should be set." ) request = model_service.ListModelsRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if page_size is not None: request.page_size = page_size if page_token is not None: request.page_token = page_token # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = gapic_v1.method_async.wrap_method( self._client._transport.list_models, default_timeout=None, client_info=DEFAULT_CLIENT_INFO, ) # Send the request. response = await rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # This method is paged; wrap the response in a pager, which provides # an `__aiter__` convenience method. response = pagers.ListModelsAsyncPager( method=rpc, request=request, response=response, metadata=metadata, ) # Done; return the response. return response async def __aenter__(self): return self async def __aexit__(self, exc_type, exc, tb): await self.transport.close() DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( gapic_version=package_version.__version__ ) __all__ = ("ModelServiceAsyncClient",)