Class v1beta3.DiscussServiceClient (2.4.0)

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;

discussServiceStub

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

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;

universeDomain

get universeDomain(): string;

warn

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

Methods

close()

close(): Promise<void>;

countMessageTokens(request, options)

countMessageTokens(request?: protos.google.ai.generativelanguage.v1beta3.ICountMessageTokensRequest, options?: CallOptions): Promise<[
        protos.google.ai.generativelanguage.v1beta3.ICountMessageTokensResponse,
        (protos.google.ai.generativelanguage.v1beta3.ICountMessageTokensRequest | 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 prompt, whose token count is to be returned.
   */
  // const prompt = {}

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

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

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

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

  callCountMessageTokens();

countMessageTokens(request, options, callback)

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

countMessageTokens(request, callback)

countMessageTokens(request: protos.google.ai.generativelanguage.v1beta3.ICountMessageTokensRequest, callback: Callback<protos.google.ai.generativelanguage.v1beta3.ICountMessageTokensResponse, protos.google.ai.generativelanguage.v1beta3.ICountMessageTokensRequest | null | undefined, {} | null | undefined>): void;

generateMessage(request, options)

generateMessage(request?: protos.google.ai.generativelanguage.v1beta3.IGenerateMessageRequest, options?: CallOptions): Promise<[
        protos.google.ai.generativelanguage.v1beta3.IGenerateMessageResponse,
        (protos.google.ai.generativelanguage.v1beta3.IGenerateMessageRequest | 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.
   *  Format: `name=models/{model}`.
   */
  // const model = 'abc123'
  /**
   *  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.
   */
  // const prompt = {}
  /**
   *  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.
   */
  // const temperature = 1234
  /**
   *  Optional. The number of generated response messages to return.
   *  This value must be between
   *  `[1, 8]`, inclusive. If unset, this will default to `1`.
   */
  // const candidateCount = 1234
  /**
   *  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`.
   */
  // 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.
   */
  // const topK = 1234

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

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

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

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

  callGenerateMessage();

generateMessage(request, options, callback)

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

generateMessage(request, callback)

generateMessage(request: protos.google.ai.generativelanguage.v1beta3.IGenerateMessageRequest, callback: Callback<protos.google.ai.generativelanguage.v1beta3.IGenerateMessageResponse, protos.google.ai.generativelanguage.v1beta3.IGenerateMessageRequest | 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;