# -*- 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 os import re from typing import ( Dict, Mapping, MutableMapping, MutableSequence, Optional, Sequence, Tuple, Type, Union, cast, ) from google.api_core import client_options as client_options_lib 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.auth import credentials as ga_credentials # type: ignore from google.auth.exceptions import MutualTLSChannelError # type: ignore from google.auth.transport import mtls # type: ignore from google.auth.transport.grpc import SslCredentials # 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.types import discuss_service from .transports.base import DEFAULT_CLIENT_INFO, DiscussServiceTransport from .transports.grpc import DiscussServiceGrpcTransport from .transports.grpc_asyncio import DiscussServiceGrpcAsyncIOTransport from .transports.rest import DiscussServiceRestTransport class DiscussServiceClientMeta(type): """Metaclass for the DiscussService client. This provides class-level methods for building and retrieving support objects (e.g. transport) without polluting the client instance objects. """ _transport_registry = ( OrderedDict() ) # type: Dict[str, Type[DiscussServiceTransport]] _transport_registry["grpc"] = DiscussServiceGrpcTransport _transport_registry["grpc_asyncio"] = DiscussServiceGrpcAsyncIOTransport _transport_registry["rest"] = DiscussServiceRestTransport def get_transport_class( cls, label: Optional[str] = None, ) -> Type[DiscussServiceTransport]: """Returns an appropriate transport class. Args: label: The name of the desired transport. If none is provided, then the first transport in the registry is used. Returns: The transport class to use. """ # If a specific transport is requested, return that one. if label: return cls._transport_registry[label] # No transport is requested; return the default (that is, the first one # in the dictionary). return next(iter(cls._transport_registry.values())) class DiscussServiceClient(metaclass=DiscussServiceClientMeta): """An API for using Generative Language Models (GLMs) in dialog applications. Also known as large language models (LLMs), this API provides models that are trained for multi-turn dialog. """ @staticmethod def _get_default_mtls_endpoint(api_endpoint): """Converts api endpoint to mTLS endpoint. Convert "*.sandbox.googleapis.com" and "*.googleapis.com" to "*.mtls.sandbox.googleapis.com" and "*.mtls.googleapis.com" respectively. Args: api_endpoint (Optional[str]): the api endpoint to convert. Returns: str: converted mTLS api endpoint. """ if not api_endpoint: return api_endpoint mtls_endpoint_re = re.compile( r"(?P[^.]+)(?P\.mtls)?(?P\.sandbox)?(?P\.googleapis\.com)?" ) m = mtls_endpoint_re.match(api_endpoint) name, mtls, sandbox, googledomain = m.groups() if mtls or not googledomain: return api_endpoint if sandbox: return api_endpoint.replace( "sandbox.googleapis.com", "mtls.sandbox.googleapis.com" ) return api_endpoint.replace(".googleapis.com", ".mtls.googleapis.com") DEFAULT_ENDPOINT = "generativelanguage.googleapis.com" DEFAULT_MTLS_ENDPOINT = _get_default_mtls_endpoint.__func__( # type: ignore DEFAULT_ENDPOINT ) @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: DiscussServiceClient: The constructed client. """ credentials = service_account.Credentials.from_service_account_info(info) kwargs["credentials"] = credentials return cls(*args, **kwargs) @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: DiscussServiceClient: The constructed client. """ credentials = service_account.Credentials.from_service_account_file(filename) kwargs["credentials"] = credentials return cls(*args, **kwargs) from_service_account_json = from_service_account_file @property def transport(self) -> DiscussServiceTransport: """Returns the transport used by the client instance. Returns: DiscussServiceTransport: The transport used by the client instance. """ return self._transport @staticmethod def model_path( model: str, ) -> str: """Returns a fully-qualified model string.""" return "models/{model}".format( model=model, ) @staticmethod def parse_model_path(path: str) -> Dict[str, str]: """Parses a model path into its component segments.""" m = re.match(r"^models/(?P.+?)$", path) return m.groupdict() if m else {} @staticmethod def common_billing_account_path( billing_account: str, ) -> str: """Returns a fully-qualified billing_account string.""" return "billingAccounts/{billing_account}".format( billing_account=billing_account, ) @staticmethod def parse_common_billing_account_path(path: str) -> Dict[str, str]: """Parse a billing_account path into its component segments.""" m = re.match(r"^billingAccounts/(?P.+?)$", path) return m.groupdict() if m else {} @staticmethod def common_folder_path( folder: str, ) -> str: """Returns a fully-qualified folder string.""" return "folders/{folder}".format( folder=folder, ) @staticmethod def parse_common_folder_path(path: str) -> Dict[str, str]: """Parse a folder path into its component segments.""" m = re.match(r"^folders/(?P.+?)$", path) return m.groupdict() if m else {} @staticmethod def common_organization_path( organization: str, ) -> str: """Returns a fully-qualified organization string.""" return "organizations/{organization}".format( organization=organization, ) @staticmethod def parse_common_organization_path(path: str) -> Dict[str, str]: """Parse a organization path into its component segments.""" m = re.match(r"^organizations/(?P.+?)$", path) return m.groupdict() if m else {} @staticmethod def common_project_path( project: str, ) -> str: """Returns a fully-qualified project string.""" return "projects/{project}".format( project=project, ) @staticmethod def parse_common_project_path(path: str) -> Dict[str, str]: """Parse a project path into its component segments.""" m = re.match(r"^projects/(?P.+?)$", path) return m.groupdict() if m else {} @staticmethod def common_location_path( project: str, location: str, ) -> str: """Returns a fully-qualified location string.""" return "projects/{project}/locations/{location}".format( project=project, location=location, ) @staticmethod def parse_common_location_path(path: str) -> Dict[str, str]: """Parse a location path into its component segments.""" m = re.match(r"^projects/(?P.+?)/locations/(?P.+?)$", path) return m.groupdict() if m else {} @classmethod def get_mtls_endpoint_and_cert_source( cls, client_options: Optional[client_options_lib.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. """ if client_options is None: client_options = client_options_lib.ClientOptions() use_client_cert = os.getenv("GOOGLE_API_USE_CLIENT_CERTIFICATE", "false") use_mtls_endpoint = os.getenv("GOOGLE_API_USE_MTLS_ENDPOINT", "auto") if use_client_cert not in ("true", "false"): raise ValueError( "Environment variable `GOOGLE_API_USE_CLIENT_CERTIFICATE` must be either `true` or `false`" ) if use_mtls_endpoint not in ("auto", "never", "always"): raise MutualTLSChannelError( "Environment variable `GOOGLE_API_USE_MTLS_ENDPOINT` must be `never`, `auto` or `always`" ) # Figure out the client cert source to use. client_cert_source = None if use_client_cert == "true": if client_options.client_cert_source: client_cert_source = client_options.client_cert_source elif mtls.has_default_client_cert_source(): client_cert_source = mtls.default_client_cert_source() # Figure out which api endpoint to use. if client_options.api_endpoint is not None: api_endpoint = client_options.api_endpoint elif use_mtls_endpoint == "always" or ( use_mtls_endpoint == "auto" and client_cert_source ): api_endpoint = cls.DEFAULT_MTLS_ENDPOINT else: api_endpoint = cls.DEFAULT_ENDPOINT return api_endpoint, client_cert_source def __init__( self, *, credentials: Optional[ga_credentials.Credentials] = None, transport: Optional[Union[str, DiscussServiceTransport]] = None, client_options: Optional[Union[client_options_lib.ClientOptions, dict]] = None, client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO, ) -> None: """Instantiates the discuss 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, DiscussServiceTransport]): The transport to use. If set to None, a transport is chosen automatically. client_options (Optional[Union[google.api_core.client_options.ClientOptions, dict]]): 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. client_info (google.api_core.gapic_v1.client_info.ClientInfo): The client info used to send a user-agent string along with API requests. If ``None``, then default info will be used. Generally, you only need to set this if you're developing your own client library. Raises: google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport creation failed for any reason. """ if isinstance(client_options, dict): client_options = client_options_lib.from_dict(client_options) if client_options is None: client_options = client_options_lib.ClientOptions() client_options = cast(client_options_lib.ClientOptions, client_options) api_endpoint, client_cert_source_func = self.get_mtls_endpoint_and_cert_source( client_options ) api_key_value = getattr(client_options, "api_key", None) if api_key_value and credentials: raise ValueError( "client_options.api_key and credentials are mutually exclusive" ) # Save or instantiate the transport. # Ordinarily, we provide the transport, but allowing a custom transport # instance provides an extensibility point for unusual situations. if isinstance(transport, DiscussServiceTransport): # transport is a DiscussServiceTransport instance. if credentials or client_options.credentials_file or api_key_value: raise ValueError( "When providing a transport instance, " "provide its credentials directly." ) if client_options.scopes: raise ValueError( "When providing a transport instance, provide its scopes " "directly." ) self._transport = transport else: import google.auth._default # type: ignore if api_key_value and hasattr( google.auth._default, "get_api_key_credentials" ): credentials = google.auth._default.get_api_key_credentials( api_key_value ) Transport = type(self).get_transport_class(transport) self._transport = Transport( credentials=credentials, credentials_file=client_options.credentials_file, host=api_endpoint, scopes=client_options.scopes, client_cert_source_for_mtls=client_cert_source_func, quota_project_id=client_options.quota_project_id, client_info=client_info, always_use_jwt_access=True, api_audience=client_options.api_audience, ) def generate_message( self, request: Optional[Union[discuss_service.GenerateMessageRequest, dict]] = None, *, model: Optional[str] = None, prompt: Optional[discuss_service.MessagePrompt] = None, temperature: Optional[float] = None, candidate_count: Optional[int] = None, top_p: Optional[float] = None, top_k: Optional[int] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, str]] = (), ) -> discuss_service.GenerateMessageResponse: r"""Generates a response from the model given an input ``MessagePrompt``. .. 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 def sample_generate_message(): # Create a client client = generativelanguage_v1beta2.DiscussServiceClient() # Initialize request argument(s) prompt = generativelanguage_v1beta2.MessagePrompt() prompt.messages.content = "content_value" request = generativelanguage_v1beta2.GenerateMessageRequest( model="model_value", prompt=prompt, ) # Make the request response = client.generate_message(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1beta2.types.GenerateMessageRequest, dict]): The request object. Request to generate a message response from the model. model (str): Required. The name of the model to use. Format: ``name=models/{model}``. This corresponds to the ``model`` field on the ``request`` instance; if ``request`` is provided, this should not be set. prompt (google.ai.generativelanguage_v1beta2.types.MessagePrompt): Required. The structured textual input given to the model as a prompt. Given a prompt, the model will return what it predicts is the next message in the discussion. This corresponds to the ``prompt`` field on the ``request`` instance; if ``request`` is provided, this should not be set. temperature (float): Optional. Controls the randomness of the output. Values can range over ``[0.0,1.0]``, inclusive. A value closer to ``1.0`` will produce responses that are more varied, while a value closer to ``0.0`` will typically result in less surprising responses from the model. This corresponds to the ``temperature`` field on the ``request`` instance; if ``request`` is provided, this should not be set. candidate_count (int): Optional. The number of generated response messages to return. This value must be between ``[1, 8]``, inclusive. If unset, this will default to ``1``. This corresponds to the ``candidate_count`` field on the ``request`` instance; if ``request`` is provided, this should not be set. top_p (float): Optional. The maximum cumulative probability of tokens to consider when sampling. The model uses combined Top-k and nucleus sampling. Nucleus sampling considers the smallest set of tokens whose probability sum is at least ``top_p``. This corresponds to the ``top_p`` field on the ``request`` instance; if ``request`` is provided, this should not be set. top_k (int): Optional. The maximum number of tokens to consider when sampling. The model uses combined Top-k and nucleus sampling. Top-k sampling considers the set of ``top_k`` most probable tokens. This corresponds to the ``top_k`` 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.GenerateMessageResponse: The response from the model. This includes candidate messages and conversation history in the form of chronologically-ordered messages. """ # 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( [model, prompt, temperature, candidate_count, top_p, top_k] ) 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." ) # Minor optimization to avoid making a copy if the user passes # in a discuss_service.GenerateMessageRequest. # There's no risk of modifying the input as we've already verified # there are no flattened fields. if not isinstance(request, discuss_service.GenerateMessageRequest): request = discuss_service.GenerateMessageRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if model is not None: request.model = model if prompt is not None: request.prompt = prompt if temperature is not None: request.temperature = temperature if candidate_count is not None: request.candidate_count = candidate_count if top_p is not None: request.top_p = top_p if top_k is not None: request.top_k = top_k # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[self._transport.generate_message] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("model", request.model),)), ) # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response def count_message_tokens( self, request: Optional[ Union[discuss_service.CountMessageTokensRequest, dict] ] = None, *, model: Optional[str] = None, prompt: Optional[discuss_service.MessagePrompt] = None, retry: OptionalRetry = gapic_v1.method.DEFAULT, timeout: Union[float, object] = gapic_v1.method.DEFAULT, metadata: Sequence[Tuple[str, str]] = (), ) -> discuss_service.CountMessageTokensResponse: r"""Runs a model's tokenizer on a string and returns the token count. .. 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 def sample_count_message_tokens(): # Create a client client = generativelanguage_v1beta2.DiscussServiceClient() # Initialize request argument(s) prompt = generativelanguage_v1beta2.MessagePrompt() prompt.messages.content = "content_value" request = generativelanguage_v1beta2.CountMessageTokensRequest( model="model_value", prompt=prompt, ) # Make the request response = client.count_message_tokens(request=request) # Handle the response print(response) Args: request (Union[google.ai.generativelanguage_v1beta2.types.CountMessageTokensRequest, dict]): The request object. Counts the number of tokens in the ``prompt`` sent to a model. Models may tokenize text differently, so each model may return a different ``token_count``. model (str): Required. The model's resource name. This serves as an ID for the Model to use. This name should match a model name returned by the ``ListModels`` method. Format: ``models/{model}`` This corresponds to the ``model`` field on the ``request`` instance; if ``request`` is provided, this should not be set. prompt (google.ai.generativelanguage_v1beta2.types.MessagePrompt): Required. The prompt, whose token count is to be returned. This corresponds to the ``prompt`` 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.CountMessageTokensResponse: A response from CountMessageTokens. It returns the model's token_count for the prompt. """ # 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([model, prompt]) 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." ) # Minor optimization to avoid making a copy if the user passes # in a discuss_service.CountMessageTokensRequest. # There's no risk of modifying the input as we've already verified # there are no flattened fields. if not isinstance(request, discuss_service.CountMessageTokensRequest): request = discuss_service.CountMessageTokensRequest(request) # If we have keyword arguments corresponding to fields on the # request, apply these. if model is not None: request.model = model if prompt is not None: request.prompt = prompt # Wrap the RPC method; this adds retry and timeout information, # and friendly error handling. rpc = self._transport._wrapped_methods[self._transport.count_message_tokens] # Certain fields should be provided within the metadata header; # add these here. metadata = tuple(metadata) + ( gapic_v1.routing_header.to_grpc_metadata((("model", request.model),)), ) # Send the request. response = rpc( request, retry=retry, timeout=timeout, metadata=metadata, ) # Done; return the response. return response def __enter__(self) -> "DiscussServiceClient": return self def __exit__(self, type, value, traceback): """Releases underlying transport's resources. .. warning:: ONLY use as a context manager if the transport is NOT shared with other clients! Exiting the with block will CLOSE the transport and may cause errors in other clients! """ self.transport.close() DEFAULT_CLIENT_INFO = gapic_v1.client_info.ClientInfo( gapic_version=package_version.__version__ ) __all__ = ("DiscussServiceClient",)