google.ai.generativelanguage.DiscussServiceClient

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.

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.

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

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

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

    # 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 = client.count_message_tokens(request=request)

    # Handle the response
    print(response)

Args
request 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 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.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.CountMessageTokensResponse A response from CountMessageTokens.

It returns the model's token_count for the prompt.

from_service_account_file

View source

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.

from_service_account_info

View source

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.

from_service_account_json

View source

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.

generate_message

View source

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

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

    # 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 = client.generate_message(request=request)

    # Handle the response
    print(response)

Args
request Union[google.ai.generativelanguage.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.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.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

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.

__enter__

View source

__exit__

View source

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!

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