libs/langchain-aws/src/embeddings.ts

import {
  BedrockRuntimeClient,
  InvokeModelCommand,
} from "@aws-sdk/client-bedrock-runtime";
import { Embeddings, EmbeddingsParams } from "@langchain/core/embeddings";
import { CredentialType } from "./types.js";

/**
 * Interface that extends EmbeddingsParams and defines additional
 * parameters specific to the BedrockEmbeddings class.
 */
export interface BedrockEmbeddingsParams extends EmbeddingsParams {
  /**
   * Model Name to use. Defaults to `amazon.titan-embed-text-v1` if not provided
   *
   */
  model?: string;

  /**
   * A client provided by the user that allows them to customze any
   * SDK configuration options.
   */
  client?: BedrockRuntimeClient;

  region?: string;

  credentials?: CredentialType;
}

/**
 * Class that extends the Embeddings class and provides methods for
 * generating embeddings using the Bedrock API.
 * @example
 * ```typescript
 * const embeddings = new BedrockEmbeddings({
 *   region: "your-aws-region",
 *   credentials: {
 *     accessKeyId: "your-access-key-id",
 *     secretAccessKey: "your-secret-access-key",
 *   },
 *   model: "amazon.titan-embed-text-v1",
 * });
 *
 * // Embed a query and log the result
 * const res = await embeddings.embedQuery(
 *   "What would be a good company name for a company that makes colorful socks?"
 * );
 * console.log({ res });
 * ```
 */
export class BedrockEmbeddings
  extends Embeddings
  implements BedrockEmbeddingsParams
{
  model: string;

  client: BedrockRuntimeClient;

  batchSize = 512;

  constructor(fields?: BedrockEmbeddingsParams) {
    super(fields ?? {});

    this.model = fields?.model ?? "amazon.titan-embed-text-v1";

    this.client =
      fields?.client ??
      new BedrockRuntimeClient({
        region: fields?.region,
        credentials: fields?.credentials,
      });
  }

  /**
   * Protected method to make a request to the Bedrock API to generate
   * embeddings. Handles the retry logic and returns the response from the
   * API.
   * @param request Request to send to the Bedrock API.
   * @returns Promise that resolves to the response from the API.
   */
  protected async _embedText(text: string): Promise<number[]> {
    return this.caller.call(async () => {
      try {
        // replace newlines, which can negatively affect performance.
        const cleanedText = text.replace(/\n/g, " ");

        const res = await this.client.send(
          new InvokeModelCommand({
            modelId: this.model,
            body: JSON.stringify({
              inputText: cleanedText,
            }),
            contentType: "application/json",
            accept: "application/json",
          })
        );

        const body = new TextDecoder().decode(res.body);
        return JSON.parse(body).embedding;
      } catch (e) {
        console.error({
          error: e,
        });
        // eslint-disable-next-line no-instanceof/no-instanceof
        if (e instanceof Error) {
          throw new Error(
            `An error occurred while embedding documents with Bedrock: ${e.message}`
          );
        }

        throw new Error(
          "An error occurred while embedding documents with Bedrock"
        );
      }
    });
  }

  /**
   * Method that takes a document as input and returns a promise that
   * resolves to an embedding for the document. It calls the _embedText
   * method with the document as the input.
   * @param document Document for which to generate an embedding.
   * @returns Promise that resolves to an embedding for the input document.
   */
  embedQuery(document: string): Promise<number[]> {
    return this.caller.callWithOptions(
      {},
      this._embedText.bind(this),
      document
    );
  }

  /**
   * Method to generate embeddings for an array of texts. Calls _embedText
   * method which batches and handles retry logic when calling the AWS Bedrock API.
   * @param documents Array of texts for which to generate embeddings.
   * @returns Promise that resolves to a 2D array of embeddings for each input document.
   */
  async embedDocuments(documents: string[]): Promise<number[][]> {
    return Promise.all(documents.map((document) => this._embedText(document)));
  }
}