"use strict"; Object.defineProperty(exports, "__esModule", { value: true }); exports.BedrockEmbeddings = void 0; const client_bedrock_runtime_1 = require("@aws-sdk/client-bedrock-runtime"); const embeddings_1 = require("@langchain/core/embeddings"); /** * @deprecated The BedrockEmbeddings integration has been moved to the `@langchain/aws` package. Import from `@langchain/aws` instead. * * 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 }); * ``` */ class BedrockEmbeddings extends embeddings_1.Embeddings { constructor(fields) { super(fields ?? {}); Object.defineProperty(this, "model", { enumerable: true, configurable: true, writable: true, value: void 0 }); Object.defineProperty(this, "client", { enumerable: true, configurable: true, writable: true, value: void 0 }); Object.defineProperty(this, "batchSize", { enumerable: true, configurable: true, writable: true, value: 512 }); this.model = fields?.model ?? "amazon.titan-embed-text-v1"; this.client = fields?.client ?? new client_bedrock_runtime_1.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. */ async _embedText(text) { 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 client_bedrock_runtime_1.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) { 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) { return Promise.all(documents.map((document) => this._embedText(document))); } } exports.BedrockEmbeddings = BedrockEmbeddings;