google.ai.generativelanguage.TextServiceAsyncClient

API for using Generative Language Models (GLMs) trained to generate text.

Also known as Large Language Models (LLM)s, these generate text given an input prompt from the user.

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, ~.TextServiceTransport]): 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

batch_embed_text

View source

Generates multiple embeddings from the model given input text in a synchronous call.

# 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_batch_embed_text():
    # Create a client
    client = generativelanguage_v1beta.TextServiceAsyncClient()

    # Initialize request argument(s)
    request = generativelanguage_v1beta.BatchEmbedTextRequest(
        model="model_value",
    )

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

    # Handle the response
    print(response)

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

The request object. Batch request to get a text embedding
from the model.

model (:class:str): Required. The name of the Model to use for generating the embedding. Examples: models/embedding-gecko-001

This corresponds to the ``model`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.

texts (:class:MutableSequence[str]): Optional. The free-form input texts that the model will turn into an embedding. The current limit is 100 texts, over which an error will be thrown.

This corresponds to the ``texts`` 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.BatchEmbedTextResponse The response to a EmbedTextRequest.

count_text_tokens

View source

Runs a model's tokenizer on a text 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_text_tokens():
    # Create a client
    client = generativelanguage_v1beta.TextServiceAsyncClient()

    # Initialize request argument(s)
    prompt = generativelanguage_v1beta.TextPrompt()
    prompt.text = "text_value"

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

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

    # Handle the response
    print(response)

Args
request Optional[Union[google.ai.generativelanguage.CountTextTokensRequest, 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.TextPrompt): Required. The free-form input text given to the model as a prompt.

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.CountTextTokensResponse A response from CountTextTokens.

It returns the model's token_count for the prompt.

embed_text

View source

Generates an embedding from the model given an input message.

# 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_embed_text():
    # Create a client
    client = generativelanguage_v1beta.TextServiceAsyncClient()

    # Initialize request argument(s)
    request = generativelanguage_v1beta.EmbedTextRequest(
        model="model_value",
    )

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

    # Handle the response
    print(response)

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

The request object. Request to get a text embedding from
the model.

model (:class:str): Required. The model name to use with the format model=models/{model}.

This corresponds to the ``model`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.

text (:class:str): Optional. The free-form input text that the model will turn into an embedding.

This corresponds to the <a href="https://www.tensorflow.org/text/api_docs/python/text"><code>text</code></a> 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.EmbedTextResponse The response to a EmbedTextRequest.

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
TextServiceAsyncClient 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
TextServiceAsyncClient 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
TextServiceAsyncClient The constructed client.

generate_text

View source

Generates a response from the model given an input message.

# 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_text():
    # Create a client
    client = generativelanguage_v1beta.TextServiceAsyncClient()

    # Initialize request argument(s)
    prompt = generativelanguage_v1beta.TextPrompt()
    prompt.text = "text_value"

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

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

    # Handle the response
    print(response)

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

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

model (:class:str): Required. The name of the Model or TunedModel to use for generating the completion. Examples: models/text-bison-001 tunedModels/sentence-translator-u3b7m

This corresponds to the ``model`` field
on the ``request`` instance; if ``request`` is provided, this
should not be set.

prompt (:class:google.ai.generativelanguage.TextPrompt): Required. The free-form input text given to the model as a prompt. Given a prompt, the model will generate a TextCompletion response it predicts as the completion of the input text.

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. Note: The default value varies by model, see the Model.temperature attribute of the Model returned the getModel function.

Values can range from [0.0,1.0], inclusive. A value
closer to 1.0 will produce responses that are more
varied and creative, while a value closer to 0.0 will
typically result in more straightforward 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. Number of generated responses 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.

max_output_tokens (:class:int): Optional. The maximum number of tokens to include in a candidate.

If unset, this will default to output_token_limit
specified in the ``Model`` specification.

This corresponds to the ``max_output_tokens`` 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.

Tokens are sorted based on their assigned probabilities
so that only the most likely tokens are considered.
Top-k sampling directly limits the maximum number of
tokens to consider, while Nucleus sampling limits number
of tokens based on the cumulative probability.

Note: The default value varies by model, see the
<a href="../../../google/ai/generativelanguage/Model#top_p"><code>Model.top_p</code></a> attribute of the ``Model`` returned the
``getModel`` function.

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. Defaults to 40.

Note: The default value varies by model, see the
<a href="../../../google/ai/generativelanguage/Model#top_k"><code>Model.top_k</code></a> attribute of the ``Model`` returned the
``getModel`` function.

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.GenerateTextResponse The response from the model, including candidate completions.

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.

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'