Class v1beta.GenerativeServiceClient (2.6.0)

  /**
   * 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. Embed requests for the batch. The model in each of these requests
   *  must match the model specified `BatchEmbedContentsRequest.model`.
   */
  // const requests = [1,2,3,4]

  // Imports the Generativelanguage library
  const {GenerativeServiceClient} = require('@google-ai/generativelanguage').v1beta;

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

  async function callBatchEmbedContents() {
    // Construct request
    const request = {
      model,
      requests,
    };

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

  callBatchEmbedContents();

  /**
   * 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'
  /**
   *  Optional. The input given to the model as a prompt. This field is ignored
   *  when `generate_content_request` is set.
   */
  // const contents = [1,2,3,4]
  /**
   *  Optional. The overall input given to the model. CountTokens will count
   *  prompt, function calling, etc.
   */
  // const generateContentRequest = {}

  // Imports the Generativelanguage library
  const {GenerativeServiceClient} = require('@google-ai/generativelanguage').v1beta;

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

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

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

  callCountTokens();

  /**
   * 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 content to embed. Only the `parts.text` fields will be
   *  counted.
   */
  // const content = {}
  /**
   *  Optional. Optional task type for which the embeddings will be used. Can
   *  only be set for `models/embedding-001`.
   */
  // const taskType = {}
  /**
   *  Optional. An optional title for the text. Only applicable when TaskType is
   *  `RETRIEVAL_DOCUMENT`.
   *  Note: Specifying a `title` for `RETRIEVAL_DOCUMENT` provides better quality
   *  embeddings for retrieval.
   */
  // const title = 'abc123'
  /**
   *  Optional. Optional reduced dimension for the output embedding. If set,
   *  excessive values in the output embedding are truncated from the end.
   *  Supported by newer models since 2024, and the earlier model
   *  (`models/embedding-001`) cannot specify this value.
   */
  // const outputDimensionality = 1234

  // Imports the Generativelanguage library
  const {GenerativeServiceClient} = require('@google-ai/generativelanguage').v1beta;

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

  async function callEmbedContent() {
    // Construct request
    const request = {
      model,
      content,
    };

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

  callEmbedContent();

  /**
   * 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.
   */
  /**
   *  Passages provided inline with the request.
   */
  // const inlinePassages = {}
  /**
   *  Content retrieved from resources created via the Semantic Retriever
   *  API.
   */
  // const semanticRetriever = {}
  /**
   *  Required. The name of the `Model` to use for generating the grounded
   *  response.
   *  Format: `model=models/{model}`.
   */
  // const model = 'abc123'
  /**
   *  Required. The content of the current conversation with the model. For
   *  single-turn queries, this is a single question to answer. For multi-turn
   *  queries, this is a repeated field that contains conversation history and
   *  the last `Content` in the list containing the question.
   *  Note: GenerateAnswer currently only supports queries in English.
   */
  // const contents = [1,2,3,4]
  /**
   *  Required. Style in which answers should be returned.
   */
  // const answerStyle = {}
  /**
   *  Optional. A list of unique `SafetySetting` instances for blocking unsafe
   *  content.
   *  This will be enforced on the `GenerateAnswerRequest.contents` and
   *  `GenerateAnswerResponse.candidate`. There should not be more than one
   *  setting for each `SafetyCategory` type. The API will block any contents 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. Harm categories HARM_CATEGORY_HATE_SPEECH,
   *  HARM_CATEGORY_SEXUALLY_EXPLICIT, HARM_CATEGORY_DANGEROUS_CONTENT,
   *  HARM_CATEGORY_HARASSMENT are supported.
   */
  // const safetySettings = [1,2,3,4]
  /**
   *  Optional. Controls the randomness of the output.
   *  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. A low temperature (~0.2) is usually recommended for
   *  Attributed-Question-Answering use cases.
   */
  // const temperature = 1234

  // Imports the Generativelanguage library
  const {GenerativeServiceClient} = require('@google-ai/generativelanguage').v1beta;

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

  async function callGenerateAnswer() {
    // Construct request
    const request = {
      model,
      contents,
      answerStyle,
    };

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

  callGenerateAnswer();

  /**
   * 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 completion.
   *  Format: `name=models/{model}`.
   */
  // const model = 'abc123'
  /**
   *  Optional. Developer set system instruction. Currently, text only.
   */
  // const systemInstruction = {}
  /**
   *  Required. The content of the current conversation with the model.
   *  For single-turn queries, this is a single instance. For multi-turn queries,
   *  this is a repeated field that contains conversation history + latest
   *  request.
   */
  // const contents = [1,2,3,4]
  /**
   *  Optional. A list of `Tools` the model may use to generate the next
   *  response.
   *  A `Tool` is a piece of code that enables the system to interact with
   *  external systems to perform an action, or set of actions, outside of
   *  knowledge and scope of the model. The only supported tool is currently
   *  `Function`.
   */
  // const tools = [1,2,3,4]
  /**
   *  Optional. Tool configuration for any `Tool` specified in the request.
   */
  // const toolConfig = {}
  /**
   *  Optional. A list of unique `SafetySetting` instances for blocking unsafe
   *  content.
   *  This will be enforced on the `GenerateContentRequest.contents` and
   *  `GenerateContentResponse.candidates`. There should not be more than one
   *  setting for each `SafetyCategory` type. The API will block any contents 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. Harm categories HARM_CATEGORY_HATE_SPEECH,
   *  HARM_CATEGORY_SEXUALLY_EXPLICIT, HARM_CATEGORY_DANGEROUS_CONTENT,
   *  HARM_CATEGORY_HARASSMENT are supported.
   */
  // const safetySettings = [1,2,3,4]
  /**
   *  Optional. Configuration options for model generation and outputs.
   */
  // const generationConfig = {}
  /**
   *  Optional. The name of the cached content used as context to serve the
   *  prediction. Note: only used in explicit caching, where users can have
   *  control over caching (e.g. what content to cache) and enjoy guaranteed cost
   *  savings. Format: `cachedContents/{cachedContent}`
   */
  // const cachedContent = 'abc123'

  // Imports the Generativelanguage library
  const {GenerativeServiceClient} = require('@google-ai/generativelanguage').v1beta;

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

  async function callGenerateContent() {
    // Construct request
    const request = {
      model,
      contents,
    };

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

  callGenerateContent();

  /**
   * 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 completion.
   *  Format: `name=models/{model}`.
   */
  // const model = 'abc123'
  /**
   *  Optional. Developer set system instruction. Currently, text only.
   */
  // const systemInstruction = {}
  /**
   *  Required. The content of the current conversation with the model.
   *  For single-turn queries, this is a single instance. For multi-turn queries,
   *  this is a repeated field that contains conversation history + latest
   *  request.
   */
  // const contents = [1,2,3,4]
  /**
   *  Optional. A list of `Tools` the model may use to generate the next
   *  response.
   *  A `Tool` is a piece of code that enables the system to interact with
   *  external systems to perform an action, or set of actions, outside of
   *  knowledge and scope of the model. The only supported tool is currently
   *  `Function`.
   */
  // const tools = [1,2,3,4]
  /**
   *  Optional. Tool configuration for any `Tool` specified in the request.
   */
  // const toolConfig = {}
  /**
   *  Optional. A list of unique `SafetySetting` instances for blocking unsafe
   *  content.
   *  This will be enforced on the `GenerateContentRequest.contents` and
   *  `GenerateContentResponse.candidates`. There should not be more than one
   *  setting for each `SafetyCategory` type. The API will block any contents 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. Harm categories HARM_CATEGORY_HATE_SPEECH,
   *  HARM_CATEGORY_SEXUALLY_EXPLICIT, HARM_CATEGORY_DANGEROUS_CONTENT,
   *  HARM_CATEGORY_HARASSMENT are supported.
   */
  // const safetySettings = [1,2,3,4]
  /**
   *  Optional. Configuration options for model generation and outputs.
   */
  // const generationConfig = {}
  /**
   *  Optional. The name of the cached content used as context to serve the
   *  prediction. Note: only used in explicit caching, where users can have
   *  control over caching (e.g. what content to cache) and enjoy guaranteed cost
   *  savings. Format: `cachedContents/{cachedContent}`
   */
  // const cachedContent = 'abc123'

  // Imports the Generativelanguage library
  const {GenerativeServiceClient} = require('@google-ai/generativelanguage').v1beta;

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

  async function callStreamGenerateContent() {
    // Construct request
    const request = {
      model,
      contents,
    };

    // Run request
    const stream = await generativelanguageClient.streamGenerateContent(request);
    stream.on('data', (response) => { console.log(response) });
    stream.on('error', (err) => { throw(err) });
    stream.on('end', () => { /* API call completed */ });
  }

  callStreamGenerateContent();