google.ai.generativelanguage.DiscussServiceAsyncClient

An API for using Generative Language Models (GLMs) in dialog applications.

google.ai.generativelanguage.DiscussServiceAsyncClient(
    *,
    credentials: Optional[ga_credentials.Credentials] = None,
    transport: Union[str, DiscussServiceTransport] = 'grpc_asyncio',
    client_options: Optional[ClientOptions] = None,
    client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO
) -> None

Also known as large language models (LLMs), this API provides models that are trained for multi-turn dialog.

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 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.

google.auth.exceptions.MutualTlsChannelError If mutual TLS transport creation failed for any reason.

transport Returns the transport used by the client instance.

Methods

count_message_tokens

View source

count_message_tokens(
    request=None,
    *,
    model=None,
    prompt=None,
    retry=<_MethodDefault._DEFAULT_VALUE: <object object>>,
    timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>,
    metadata=()
)

Runs a model's tokenizer on a string and returns the token count.

# 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:
#   <a href="https://googleapis.dev/python/google-api-core/latest/client_options.html">https://googleapis.dev/python/google-api-core/latest/client_options.html</a>
from google.ai import generativelanguage_v1beta

async def sample_count_message_tokens():
    # Create a client
    client = generativelanguage_v1beta.DiscussServiceAsyncClient()

    # Initialize request argument(s)
    prompt = generativelanguage_v1beta.MessagePrompt()
    prompt.messages.content = "content_value"

    request = generativelanguage_v1beta.CountMessageTokensRequest(
        model="model_value",
        prompt=prompt,
    )

    # Make the request
    response = await client.count_message_tokens(request=request)

    # Handle the response
    print(response)

Args
request Optional[Union[google.ai.generativelanguage.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 (:class: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 (:class:google.ai.generativelanguage.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_async.AsyncRetry

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.CountMessageTokensResponse A response from CountMessageTokens.

It returns the model's token_count for the prompt.

from_service_account_file

View source

@classmethod
from_service_account_file(
    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
DiscussServiceAsyncClient The constructed client.

from_service_account_info

View source

@classmethod
from_service_account_info(
    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
DiscussServiceAsyncClient The constructed client.

from_service_account_json

View source

@classmethod
from_service_account_json(
    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
DiscussServiceAsyncClient The constructed client.

generate_message

View source

generate_message(
    request=None,
    *,
    model=None,
    prompt=None,
    temperature=None,
    candidate_count=None,
    top_p=None,
    top_k=None,
    retry=<_MethodDefault._DEFAULT_VALUE: <object object>>,
    timeout=<_MethodDefault._DEFAULT_VALUE: <object object>>,
    metadata=()
)

Generates a response from the model given an input MessagePrompt.

# 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:
#   <a href="https://googleapis.dev/python/google-api-core/latest/client_options.html">https://googleapis.dev/python/google-api-core/latest/client_options.html</a>
from google.ai import generativelanguage_v1beta

async def sample_generate_message():
    # Create a client
    client = generativelanguage_v1beta.DiscussServiceAsyncClient()

    # Initialize request argument(s)
    prompt = generativelanguage_v1beta.MessagePrompt()
    prompt.messages.content = "content_value"

    request = generativelanguage_v1beta.GenerateMessageRequest(
        model="model_value",
        prompt=prompt,
    )

    # Make the request
    response = await client.generate_message(request=request)

    # Handle the response
    print(response)

Args
request Optional[Union[google.ai.generativelanguage.GenerateMessageRequest, dict]]

The request object. Request to generate a message
response from the model.

model (:class: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 (:class:google.ai.generativelanguage.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 (:class: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 (:class: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 (:class: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 (:class: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_async.AsyncRetry

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.GenerateMessageResponse The response from the model.

This includes candidate messages and conversation history in the form of chronologically-ordered messages.

get_mtls_endpoint_and_cert_source

View source

@classmethod
get_mtls_endpoint_and_cert_source(
    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.

get_transport_class

get_transport_class()

partial(func, *args, **keywords) - new function with partial application of the given arguments and keywords.

DEFAULT_ENDPOINT 'generativelanguage.googleapis.com'
DEFAULT_MTLS_ENDPOINT 'generativelanguage.mtls.googleapis.com'