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

//#region src/embeddings.d.ts
interface YandexGPTEmbeddingsParams extends EmbeddingsParams {
  /** Model name to use. */
  model?: string;
  /** Model version to use. */
  modelVersion?: string;
  /** Model version to use. */
  /** Model URI to use. */
  modelURI?: string;
  /** Yandex Cloud Folder ID. */
  folderID?: string;
  /**
   * Yandex Cloud Api Key for service account
   * with the `ai.languageModels.user` role.
   */
  apiKey?: string;
  /**
   * Yandex Cloud IAM token for service or user account
   * with the `ai.languageModels.user` role.
   */
  iamToken?: string;
}
/**
 * Class for generating embeddings using the YandexGPT Foundation models API. Extends the
 * Embeddings class and implements YandexGPTEmbeddings
 */
declare class YandexGPTEmbeddings extends Embeddings implements YandexGPTEmbeddingsParams {
  model: string;
  modelVersion: string;
  modelURI?: string;
  apiKey?: string;
  iamToken?: string;
  folderID?: string;
  constructor(fields?: YandexGPTEmbeddingsParams);
  get lc_secrets(): {
    [key: string]: string;
  } | undefined;
  /**
   * Method to generate embeddings for an array of documents.
   * @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
   * embedDocuments method with the document as the input.
   * @param text Document to generate an embedding for.
   * @returns Promise that resolves to an embedding for the document.
   */
  embedQuery(text: string): Promise<number[]>;
  private embeddingWithRetry;
}
//#endregion
export { YandexGPTEmbeddings, YandexGPTEmbeddingsParams };
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