As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

TextService¶

class google.ai.generativelanguage_v1beta3.services.text_service.TextServiceAsyncClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.ai.generativelanguage_v1beta3.services.text_service.transports.base.TextServiceTransport, typing.Callable[[...], google.ai.generativelanguage_v1beta3.services.text_service.transports.base.TextServiceTransport]]] = 'grpc_asyncio', client_options: typing.Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)[source]¶

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.

Instantiates the text service async client.

Parameters

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 (Optional[Union[str,TextServiceTransport,Callable[..., TextServiceTransport]]]) – The transport to use, or a Callable that constructs and returns a new transport to use. If a Callable is given, it will be called with the same set of initialization arguments as used in the TextServiceTransport constructor. 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.

1. The api_endpoint property can be used to override the default endpoint provided by the client when transport is not explicitly provided. Only if this property is not set and transport was not explicitly provided, the endpoint is determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment variable, which have one of the following values: “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).

2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “true”, then the client_cert_source property can be used to provide a client certificate for mTLS 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.

3. The universe_domain property can be used to override the default “googleapis.com” universe. Note that api_endpoint property still takes precedence; and universe_domain is currently not supported for mTLS.
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.

property api_endpoint¶

Return the API endpoint used by the client instance.

Returns: The API endpoint used by the client instance.
Return type: str

async batch_embed_text(request: Optional[Union[google.ai.generativelanguage_v1beta3.types.text_service.BatchEmbedTextRequest, dict]] = None, *, model: Optional[str] = None, texts: Optional[MutableSequence[str]] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.ai.generativelanguage_v1beta3.types.text_service.BatchEmbedTextResponse[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:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta3

async def sample_batch_embed_text():
    # Create a client
    client = generativelanguage_v1beta3.TextServiceAsyncClient()

    # Initialize request argument(s)
    request = generativelanguage_v1beta3.BatchEmbedTextRequest(
        model="model_value",
        texts=['texts_value1', 'texts_value2'],
    )

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

    # Handle the response
    print(response)

Parameters

request (Optional[Union[google.ai.generativelanguage_v1beta3.types.BatchEmbedTextRequest, dict]]) – The request object. Batch request to get a text embedding from the model.
model (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 (MutableSequence[str]) –
Required. 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

The response to a EmbedTextRequest.

Return type

google.ai.generativelanguage_v1beta3.types.BatchEmbedTextResponse

static common_billing_account_path(billing_account: str) → str¶: Returns a fully-qualified billing_account string.

static common_folder_path(folder: str) → str¶: Returns a fully-qualified folder string.

static common_location_path(project: str, location: str) → str¶: Returns a fully-qualified location string.

static common_organization_path(organization: str) → str¶: Returns a fully-qualified organization string.

static common_project_path(project: str) → str¶: Returns a fully-qualified project string.

async count_text_tokens(request: Optional[Union[google.ai.generativelanguage_v1beta3.types.text_service.CountTextTokensRequest, dict]] = None, *, model: Optional[str] = None, prompt: Optional[google.ai.generativelanguage_v1beta3.types.text_service.TextPrompt] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.ai.generativelanguage_v1beta3.types.text_service.CountTextTokensResponse[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:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta3

async def sample_count_text_tokens():
    # Create a client
    client = generativelanguage_v1beta3.TextServiceAsyncClient()

    # Initialize request argument(s)
    prompt = generativelanguage_v1beta3.TextPrompt()
    prompt.text = "text_value"

    request = generativelanguage_v1beta3.CountTextTokensRequest(
        model="model_value",
        prompt=prompt,
    )

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

    # Handle the response
    print(response)

Parameters

request (Optional[Union[google.ai.generativelanguage_v1beta3.types.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 (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_v1beta3.types.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

A response from CountTextTokens.

It returns the model’s token_count for the prompt.

Return type

google.ai.generativelanguage_v1beta3.types.CountTextTokensResponse

async embed_text(request: Optional[Union[google.ai.generativelanguage_v1beta3.types.text_service.EmbedTextRequest, dict]] = None, *, model: Optional[str] = None, text: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.ai.generativelanguage_v1beta3.types.text_service.EmbedTextResponse[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:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta3

async def sample_embed_text():
    # Create a client
    client = generativelanguage_v1beta3.TextServiceAsyncClient()

    # Initialize request argument(s)
    request = generativelanguage_v1beta3.EmbedTextRequest(
        model="model_value",
        text="text_value",
    )

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

    # Handle the response
    print(response)

Parameters

request (Optional[Union[google.ai.generativelanguage_v1beta3.types.EmbedTextRequest, dict]]) – The request object. Request to get a text embedding from the model.
model (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 (str) –
Required. The free-form input text that the model will turn into an embedding.

This corresponds to the text 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

The response to a EmbedTextRequest.

Return type

google.ai.generativelanguage_v1beta3.types.EmbedTextResponse

classmethod from_service_account_file(filename: str, *args, **kwargs)[source]¶

Creates an instance of this client using the provided credentials: file.

Parameters

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

The constructed client.

Return type

TextServiceAsyncClient

classmethod from_service_account_info(info: dict, *args, **kwargs)[source]¶

Creates an instance of this client using the provided credentials: info.

Parameters

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

The constructed client.

Return type

TextServiceAsyncClient

classmethod from_service_account_json(filename: str, *args, **kwargs)¶

Creates an instance of this client using the provided credentials: file.

Parameters

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

The constructed client.

Return type

TextServiceAsyncClient

async generate_text(request: Optional[Union[google.ai.generativelanguage_v1beta3.types.text_service.GenerateTextRequest, dict]] = None, *, model: Optional[str] = None, prompt: Optional[google.ai.generativelanguage_v1beta3.types.text_service.TextPrompt] = None, temperature: Optional[float] = None, candidate_count: Optional[int] = None, max_output_tokens: Optional[int] = None, top_p: Optional[float] = None, top_k: Optional[int] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.ai.generativelanguage_v1beta3.types.text_service.GenerateTextResponse[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:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta3

async def sample_generate_text():
    # Create a client
    client = generativelanguage_v1beta3.TextServiceAsyncClient()

    # Initialize request argument(s)
    prompt = generativelanguage_v1beta3.TextPrompt()
    prompt.text = "text_value"

    request = generativelanguage_v1beta3.GenerateTextRequest(
        model="model_value",
        prompt=prompt,
    )

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

    # Handle the response
    print(response)

Parameters

request (Optional[Union[google.ai.generativelanguage_v1beta3.types.GenerateTextRequest, dict]]) – The request object. Request to generate a text completion response from the model.
model (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 (google.ai.generativelanguage_v1beta3.types.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 (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 (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 (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 (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 Model.top_p 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 (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 Model.top_k 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

The response from the model, including candidate completions.

Return type

google.ai.generativelanguage_v1beta3.types.GenerateTextResponse

classmethod get_mtls_endpoint_and_cert_source(client_options: Optional[google.api_core.client_options.ClientOptions] = None)[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.

Parameters

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

returns the API endpoint and the: client cert source to use.

Return type

Tuple[str, Callable[[], Tuple[bytes, bytes]]]

Raises

google.auth.exceptions.MutualTLSChannelError – If any errors happen.

classmethod get_transport_class(label: Optional[str] = None) → Type[google.ai.generativelanguage_v1beta3.services.text_service.transports.base.TextServiceTransport]¶

Returns an appropriate transport class.

Parameters: 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.

static model_path(model: str) → str¶: Returns a fully-qualified model string.

static parse_common_billing_account_path(path: str) → Dict[str, str]¶: Parse a billing_account path into its component segments.

static parse_common_folder_path(path: str) → Dict[str, str]¶: Parse a folder path into its component segments.

static parse_common_location_path(path: str) → Dict[str, str]¶: Parse a location path into its component segments.

static parse_common_organization_path(path: str) → Dict[str, str]¶: Parse a organization path into its component segments.

static parse_common_project_path(path: str) → Dict[str, str]¶: Parse a project path into its component segments.

static parse_model_path(path: str) → Dict[str, str]¶: Parses a model path into its component segments.

property transport: google.ai.generativelanguage_v1beta3.services.text_service.transports.base.TextServiceTransport¶

Returns the transport used by the client instance.

Returns: The transport used by the client instance.
Return type: TextServiceTransport

property universe_domain: str¶

Return the universe domain used by the client instance.

Returns

The universe domain used: by the client instance.

Return type

str

class google.ai.generativelanguage_v1beta3.services.text_service.TextServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.ai.generativelanguage_v1beta3.services.text_service.transports.base.TextServiceTransport, typing.Callable[[...], google.ai.generativelanguage_v1beta3.services.text_service.transports.base.TextServiceTransport]]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)[source]¶

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.

Instantiates the text service client.

Parameters

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 (Optional[Union[str,TextServiceTransport,Callable[..., TextServiceTransport]]]) – The transport to use, or a Callable that constructs and returns a new transport. If a Callable is given, it will be called with the same set of initialization arguments as used in the TextServiceTransport constructor. 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.

1. The api_endpoint property can be used to override the default endpoint provided by the client when transport is not explicitly provided. Only if this property is not set and transport was not explicitly provided, the endpoint is determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment variable, which have one of the following values: “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).

2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “true”, then the client_cert_source property can be used to provide a client certificate for mTLS 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.

3. The universe_domain property can be used to override the default “googleapis.com” universe. Note that the api_endpoint property still takes precedence; and universe_domain is currently not supported for mTLS.
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.

__exit__(type, value, traceback)[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!

property api_endpoint¶

Return the API endpoint used by the client instance.

Returns: The API endpoint used by the client instance.
Return type: str

batch_embed_text(request: Optional[Union[google.ai.generativelanguage_v1beta3.types.text_service.BatchEmbedTextRequest, dict]] = None, *, model: Optional[str] = None, texts: Optional[MutableSequence[str]] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.ai.generativelanguage_v1beta3.types.text_service.BatchEmbedTextResponse[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:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta3

def sample_batch_embed_text():
    # Create a client
    client = generativelanguage_v1beta3.TextServiceClient()

    # Initialize request argument(s)
    request = generativelanguage_v1beta3.BatchEmbedTextRequest(
        model="model_value",
        texts=['texts_value1', 'texts_value2'],
    )

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

    # Handle the response
    print(response)

Parameters

request (Union[google.ai.generativelanguage_v1beta3.types.BatchEmbedTextRequest, dict]) – The request object. Batch request to get a text embedding from the model.
model (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 (MutableSequence[str]) –
Required. 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.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

The response to a EmbedTextRequest.

Return type

google.ai.generativelanguage_v1beta3.types.BatchEmbedTextResponse

static common_billing_account_path(billing_account: str) → str[source]¶: Returns a fully-qualified billing_account string.

static common_folder_path(folder: str) → str[source]¶: Returns a fully-qualified folder string.

static common_location_path(project: str, location: str) → str[source]¶: Returns a fully-qualified location string.

static common_organization_path(organization: str) → str[source]¶: Returns a fully-qualified organization string.

static common_project_path(project: str) → str[source]¶: Returns a fully-qualified project string.

count_text_tokens(request: Optional[Union[google.ai.generativelanguage_v1beta3.types.text_service.CountTextTokensRequest, dict]] = None, *, model: Optional[str] = None, prompt: Optional[google.ai.generativelanguage_v1beta3.types.text_service.TextPrompt] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.ai.generativelanguage_v1beta3.types.text_service.CountTextTokensResponse[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:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta3

def sample_count_text_tokens():
    # Create a client
    client = generativelanguage_v1beta3.TextServiceClient()

    # Initialize request argument(s)
    prompt = generativelanguage_v1beta3.TextPrompt()
    prompt.text = "text_value"

    request = generativelanguage_v1beta3.CountTextTokensRequest(
        model="model_value",
        prompt=prompt,
    )

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

    # Handle the response
    print(response)

Parameters

request (Union[google.ai.generativelanguage_v1beta3.types.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 (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_v1beta3.types.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.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

A response from CountTextTokens.

It returns the model’s token_count for the prompt.

Return type

google.ai.generativelanguage_v1beta3.types.CountTextTokensResponse

embed_text(request: Optional[Union[google.ai.generativelanguage_v1beta3.types.text_service.EmbedTextRequest, dict]] = None, *, model: Optional[str] = None, text: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.ai.generativelanguage_v1beta3.types.text_service.EmbedTextResponse[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:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta3

def sample_embed_text():
    # Create a client
    client = generativelanguage_v1beta3.TextServiceClient()

    # Initialize request argument(s)
    request = generativelanguage_v1beta3.EmbedTextRequest(
        model="model_value",
        text="text_value",
    )

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

    # Handle the response
    print(response)

Parameters

request (Union[google.ai.generativelanguage_v1beta3.types.EmbedTextRequest, dict]) – The request object. Request to get a text embedding from the model.
model (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 (str) –
Required. The free-form input text that the model will turn into an embedding.

This corresponds to the text 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

The response to a EmbedTextRequest.

Return type

google.ai.generativelanguage_v1beta3.types.EmbedTextResponse

classmethod from_service_account_file(filename: str, *args, **kwargs)[source]¶

Creates an instance of this client using the provided credentials: file.

Parameters

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

The constructed client.

Return type

TextServiceClient

classmethod from_service_account_info(info: dict, *args, **kwargs)[source]¶

Creates an instance of this client using the provided credentials: info.

Parameters

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

The constructed client.

Return type

TextServiceClient

classmethod from_service_account_json(filename: str, *args, **kwargs)¶

Creates an instance of this client using the provided credentials: file.

Parameters

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

The constructed client.

Return type

TextServiceClient

generate_text(request: Optional[Union[google.ai.generativelanguage_v1beta3.types.text_service.GenerateTextRequest, dict]] = None, *, model: Optional[str] = None, prompt: Optional[google.ai.generativelanguage_v1beta3.types.text_service.TextPrompt] = None, temperature: Optional[float] = None, candidate_count: Optional[int] = None, max_output_tokens: Optional[int] = None, top_p: Optional[float] = None, top_k: Optional[int] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.ai.generativelanguage_v1beta3.types.text_service.GenerateTextResponse[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:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.ai import generativelanguage_v1beta3

def sample_generate_text():
    # Create a client
    client = generativelanguage_v1beta3.TextServiceClient()

    # Initialize request argument(s)
    prompt = generativelanguage_v1beta3.TextPrompt()
    prompt.text = "text_value"

    request = generativelanguage_v1beta3.GenerateTextRequest(
        model="model_value",
        prompt=prompt,
    )

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

    # Handle the response
    print(response)

Parameters

request (Union[google.ai.generativelanguage_v1beta3.types.GenerateTextRequest, dict]) – The request object. Request to generate a text completion response from the model.
model (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 (google.ai.generativelanguage_v1beta3.types.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 (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 (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 (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 (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 Model.top_p 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 (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 Model.top_k 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.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

The response from the model, including candidate completions.

Return type

google.ai.generativelanguage_v1beta3.types.GenerateTextResponse

classmethod get_mtls_endpoint_and_cert_source(client_options: Optional[google.api_core.client_options.ClientOptions] = None)[source]¶

Deprecated. 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.

Parameters

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

returns the API endpoint and the: client cert source to use.

Return type

Tuple[str, Callable[[], Tuple[bytes, bytes]]]

Raises

google.auth.exceptions.MutualTLSChannelError – If any errors happen.

static model_path(model: str) → str[source]¶: Returns a fully-qualified model string.

static parse_common_billing_account_path(path: str) → Dict[str, str][source]¶: Parse a billing_account path into its component segments.

static parse_common_folder_path(path: str) → Dict[str, str][source]¶: Parse a folder path into its component segments.

static parse_common_location_path(path: str) → Dict[str, str][source]¶: Parse a location path into its component segments.

static parse_common_organization_path(path: str) → Dict[str, str][source]¶: Parse a organization path into its component segments.

static parse_common_project_path(path: str) → Dict[str, str][source]¶: Parse a project path into its component segments.

static parse_model_path(path: str) → Dict[str, str][source]¶: Parses a model path into its component segments.

property transport: google.ai.generativelanguage_v1beta3.services.text_service.transports.base.TextServiceTransport¶

Returns the transport used by the client instance.

Returns

The transport used by the client: instance.

Return type

TextServiceTransport

property universe_domain: str¶

Return the universe domain used by the client instance.

Returns: The universe domain used by the client instance.
Return type: str

TextService¶

google-ai-generativelanguage

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