@langchain/community/dist/embeddings/togetherai.d.ts

Third-party integrations for LangChain.js

import { Embeddings, EmbeddingsParams } from "@langchain/core/embeddings";

//#region src/embeddings/togetherai.d.ts
/**
 * Interface for TogetherAIEmbeddingsParams parameters. Extends EmbeddingsParams and
 * defines additional parameters specific to the TogetherAIEmbeddings class.
 */
interface TogetherAIEmbeddingsParams extends EmbeddingsParams {
  /**
   * The API key to use for the TogetherAI API.
   * @default {process.env.TOGETHER_AI_API_KEY}
   */
  apiKey?: string;
  /**
   * Model name to use
   * Alias for `model`
   * @default {"togethercomputer/m2-bert-80M-8k-retrieval"}
   */
  modelName?: string;
  /**
   * Model name to use
   * @default {"togethercomputer/m2-bert-80M-8k-retrieval"}
   */
  model?: string;
  /**
   * Timeout to use when making requests to TogetherAI.
   * @default {undefined}
   */
  timeout?: number;
  /**
   * The maximum number of documents to embed in a single request.
   * @default {512}
   */
  batchSize?: number;
  /**
   * Whether to strip new lines from the input text. May not be suitable
   * for all use cases.
   * @default {false}
   */
  stripNewLines?: boolean;
}
/**
 * Class for generating embeddings using the TogetherAI API. Extends the
 * Embeddings class and implements TogetherAIEmbeddingsParams.
 * @example
 * ```typescript
 * const embeddings = new TogetherAIEmbeddings({
 *   apiKey: process.env.TOGETHER_AI_API_KEY, // Default value
 *   model: "togethercomputer/m2-bert-80M-8k-retrieval", // Default value
 * });
 * const res = await embeddings.embedQuery(
 *   "What would be a good company name a company that makes colorful socks?"
 * );
 * ```
 */
declare class TogetherAIEmbeddings extends Embeddings implements TogetherAIEmbeddingsParams {
  modelName: string;
  model: string;
  apiKey: string;
  batchSize: number;
  stripNewLines: boolean;
  timeout?: number;
  private embeddingsAPIUrl;
  constructor(fields?: Partial<TogetherAIEmbeddingsParams>);
  private constructHeaders;
  private constructBody;
  /**
   * Method to generate embeddings for an array of documents. Splits the
   * documents into batches and makes requests to the TogetherAI API to generate
   * embeddings.
   * @param texts Array of documents to generate embeddings for.
   * @returns Promise that resolves to a 2D array of embeddings for each document.
   */
  embedDocuments(texts: string[]): Promise<number[][]>;
  /**
   * Method to generate an embedding for a single document. Calls the
   * embeddingWithRetry method with the document as the input.
   * @param {string} text Document to generate an embedding for.
   * @returns {Promise<number[]>} Promise that resolves to an embedding for the document.
   */
  embedQuery(text: string): Promise<number[]>;
  private embeddingWithRetry;
}
//#endregion
export { TogetherAIEmbeddings, TogetherAIEmbeddingsParams };
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