Class v1beta3.TextServiceClient (2.6.0)

Package

Constructors

(constructor)(opts, gaxInstance)

constructor(opts?: ClientOptions, gaxInstance?: typeof gax | typeof gax.fallback);

Properties

apiEndpoint

get apiEndpoint(): string;

apiEndpoint

static get apiEndpoint(): string;

auth

auth: gax.GoogleAuth;

descriptors

descriptors: Descriptors;

innerApiCalls

innerApiCalls: {
        [name: string]: Function;
    };

pathTemplates

pathTemplates: {
        [name: string]: gax.PathTemplate;
    };

port

static get port(): number;

scopes

static get scopes(): never[];

servicePath

static get servicePath(): string;

textServiceStub

textServiceStub?: Promise<{
        [name: string]: Function;
    }>;

universeDomain

get universeDomain(): string;

warn

warn: (code: string, message: string, warnType?: string) => void;

Methods

batchEmbedText(request, options)

batchEmbedText(request?: protos.google.ai.generativelanguage.v1beta3.IBatchEmbedTextRequest, options?: CallOptions): Promise<[
        protos.google.ai.generativelanguage.v1beta3.IBatchEmbedTextResponse,
        (protos.google.ai.generativelanguage.v1beta3.IBatchEmbedTextRequest | undefined),
        {} | undefined
    ]>;

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the `Model` to use for generating the embedding.
   *  Examples:
   *   models/embedding-gecko-001
   */
  // const model = 'abc123'
  /**
   *  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.
   */
  // const texts = ['abc','def']

  // Imports the Generativelanguage library
  const {TextServiceClient} = require('@google-ai/generativelanguage').v1beta3;

  // Instantiates a client
  const generativelanguageClient = new TextServiceClient();

  async function callBatchEmbedText() {
    // Construct request
    const request = {
      model,
      texts,
    };

    // Run request
    const response = await generativelanguageClient.batchEmbedText(request);
    console.log(response);
  }

  callBatchEmbedText();

batchEmbedText(request, options, callback)

batchEmbedText(request: protos.google.ai.generativelanguage.v1beta3.IBatchEmbedTextRequest, options: CallOptions, callback: Callback<protos.google.ai.generativelanguage.v1beta3.IBatchEmbedTextResponse, protos.google.ai.generativelanguage.v1beta3.IBatchEmbedTextRequest | null | undefined, {} | null | undefined>): void;

batchEmbedText(request, callback)

batchEmbedText(request: protos.google.ai.generativelanguage.v1beta3.IBatchEmbedTextRequest, callback: Callback<protos.google.ai.generativelanguage.v1beta3.IBatchEmbedTextResponse, protos.google.ai.generativelanguage.v1beta3.IBatchEmbedTextRequest | null | undefined, {} | null | undefined>): void;

close()

close(): Promise<void>;

countTextTokens(request, options)

countTextTokens(request?: protos.google.ai.generativelanguage.v1beta3.ICountTextTokensRequest, options?: CallOptions): Promise<[
        protos.google.ai.generativelanguage.v1beta3.ICountTextTokensResponse,
        (protos.google.ai.generativelanguage.v1beta3.ICountTextTokensRequest | undefined),
        {} | undefined
    ]>;

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  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}`
   */
  // const model = 'abc123'
  /**
   *  Required. The free-form input text given to the model as a prompt.
   */
  // const prompt = {}

  // Imports the Generativelanguage library
  const {TextServiceClient} = require('@google-ai/generativelanguage').v1beta3;

  // Instantiates a client
  const generativelanguageClient = new TextServiceClient();

  async function callCountTextTokens() {
    // Construct request
    const request = {
      model,
      prompt,
    };

    // Run request
    const response = await generativelanguageClient.countTextTokens(request);
    console.log(response);
  }

  callCountTextTokens();

countTextTokens(request, options, callback)

countTextTokens(request: protos.google.ai.generativelanguage.v1beta3.ICountTextTokensRequest, options: CallOptions, callback: Callback<protos.google.ai.generativelanguage.v1beta3.ICountTextTokensResponse, protos.google.ai.generativelanguage.v1beta3.ICountTextTokensRequest | null | undefined, {} | null | undefined>): void;

countTextTokens(request, callback)

countTextTokens(request: protos.google.ai.generativelanguage.v1beta3.ICountTextTokensRequest, callback: Callback<protos.google.ai.generativelanguage.v1beta3.ICountTextTokensResponse, protos.google.ai.generativelanguage.v1beta3.ICountTextTokensRequest | null | undefined, {} | null | undefined>): void;

embedText(request, options)

embedText(request?: protos.google.ai.generativelanguage.v1beta3.IEmbedTextRequest, options?: CallOptions): Promise<[
        protos.google.ai.generativelanguage.v1beta3.IEmbedTextResponse,
        protos.google.ai.generativelanguage.v1beta3.IEmbedTextRequest | undefined,
        {} | undefined
    ]>;

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The model name to use with the format model=models/{model}.
   */
  // const model = 'abc123'
  /**
   *  Required. The free-form input text that the model will turn into an
   *  embedding.
   */
  // const text = 'abc123'

  // Imports the Generativelanguage library
  const {TextServiceClient} = require('@google-ai/generativelanguage').v1beta3;

  // Instantiates a client
  const generativelanguageClient = new TextServiceClient();

  async function callEmbedText() {
    // Construct request
    const request = {
      model,
      text,
    };

    // Run request
    const response = await generativelanguageClient.embedText(request);
    console.log(response);
  }

  callEmbedText();

embedText(request, options, callback)

embedText(request: protos.google.ai.generativelanguage.v1beta3.IEmbedTextRequest, options: CallOptions, callback: Callback<protos.google.ai.generativelanguage.v1beta3.IEmbedTextResponse, protos.google.ai.generativelanguage.v1beta3.IEmbedTextRequest | null | undefined, {} | null | undefined>): void;

embedText(request, callback)

embedText(request: protos.google.ai.generativelanguage.v1beta3.IEmbedTextRequest, callback: Callback<protos.google.ai.generativelanguage.v1beta3.IEmbedTextResponse, protos.google.ai.generativelanguage.v1beta3.IEmbedTextRequest | null | undefined, {} | null | undefined>): void;

generateText(request, options)

generateText(request?: protos.google.ai.generativelanguage.v1beta3.IGenerateTextRequest, options?: CallOptions): Promise<[
        protos.google.ai.generativelanguage.v1beta3.IGenerateTextResponse,
        (protos.google.ai.generativelanguage.v1beta3.IGenerateTextRequest | undefined),
        {} | undefined
    ]>;

  /**
   * 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.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the `Model` or `TunedModel` to use for generating the
   *  completion.
   *  Examples:
   *   models/text-bison-001
   *   tunedModels/sentence-translator-u3b7m
   */
  // const model = 'abc123'
  /**
   *  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.
   */
  // const prompt = {}
  /**
   *  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.
   */
  // const temperature = 1234
  /**
   *  Optional. Number of generated responses to return.
   *  This value must be between 1, 8, inclusive. If unset, this will default
   *  to 1.
   */
  // const candidateCount = 1234
  /**
   *  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.
   */
  // const maxOutputTokens = 1234
  /**
   *  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.
   */
  // const topP = 1234
  /**
   *  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.
   */
  // const topK = 1234
  /**
   *  A list of unique `SafetySetting` instances for blocking unsafe content.
   *  that will be enforced on the `GenerateTextRequest.prompt` and
   *  `GenerateTextResponse.candidates`. There should not be more than one
   *  setting for each `SafetyCategory` type. The API will block any prompts and
   *  responses that fail to meet the thresholds set by these settings. This list
   *  overrides the default settings for each `SafetyCategory` specified in the
   *  safety_settings. If there is no `SafetySetting` for a given
   *  `SafetyCategory` provided in the list, the API will use the default safety
   *  setting for that category.
   */
  // const safetySettings = [1,2,3,4]
  /**
   *  The set of character sequences (up to 5) that will stop output generation.
   *  If specified, the API will stop at the first appearance of a stop
   *  sequence. The stop sequence will not be included as part of the response.
   */
  // const stopSequences = ['abc','def']

  // Imports the Generativelanguage library
  const {TextServiceClient} = require('@google-ai/generativelanguage').v1beta3;

  // Instantiates a client
  const generativelanguageClient = new TextServiceClient();

  async function callGenerateText() {
    // Construct request
    const request = {
      model,
      prompt,
    };

    // Run request
    const response = await generativelanguageClient.generateText(request);
    console.log(response);
  }

  callGenerateText();

generateText(request, options, callback)

generateText(request: protos.google.ai.generativelanguage.v1beta3.IGenerateTextRequest, options: CallOptions, callback: Callback<protos.google.ai.generativelanguage.v1beta3.IGenerateTextResponse, protos.google.ai.generativelanguage.v1beta3.IGenerateTextRequest | null | undefined, {} | null | undefined>): void;

generateText(request, callback)

generateText(request: protos.google.ai.generativelanguage.v1beta3.IGenerateTextRequest, callback: Callback<protos.google.ai.generativelanguage.v1beta3.IGenerateTextResponse, protos.google.ai.generativelanguage.v1beta3.IGenerateTextRequest | null | undefined, {} | null | undefined>): void;

getProjectId()

getProjectId(): Promise<string>;

getProjectId(callback)

getProjectId(callback: Callback<string, undefined, undefined>): void;

initialize()

initialize(): Promise<{
        [name: string]: Function;
    }>;

matchModelFromModelName(modelName)

matchModelFromModelName(modelName: string): string | number;

matchPermissionFromPermissionName(permissionName)

matchPermissionFromPermissionName(permissionName: string): string | number;

matchTunedModelFromPermissionName(permissionName)

matchTunedModelFromPermissionName(permissionName: string): string | number;

matchTunedModelFromTunedModelName(tunedModelName)

matchTunedModelFromTunedModelName(tunedModelName: string): string | number;

modelPath(model)

modelPath(model: string): string;

permissionPath(tunedModel, permission)

permissionPath(tunedModel: string, permission: string): string;

tunedModelPath(tunedModel)

tunedModelPath(tunedModel: string): string;