114 lines
4.4 KiB
JavaScript
114 lines
4.4 KiB
JavaScript
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"use strict";
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Object.defineProperty(exports, "__esModule", { value: true });
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exports.BedrockEmbeddings = void 0;
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const client_bedrock_runtime_1 = require("@aws-sdk/client-bedrock-runtime");
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const embeddings_1 = require("@langchain/core/embeddings");
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/**
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* @deprecated The BedrockEmbeddings integration has been moved to the `@langchain/aws` package. Import from `@langchain/aws` instead.
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*
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* Class that extends the Embeddings class and provides methods for
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* generating embeddings using the Bedrock API.
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* @example
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* ```typescript
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* const embeddings = new BedrockEmbeddings({
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* region: "your-aws-region",
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* credentials: {
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* accessKeyId: "your-access-key-id",
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* secretAccessKey: "your-secret-access-key",
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* },
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* model: "amazon.titan-embed-text-v1",
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* });
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*
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* // Embed a query and log the result
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* const res = await embeddings.embedQuery(
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* "What would be a good company name for a company that makes colorful socks?"
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* );
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* console.log({ res });
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* ```
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*/
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class BedrockEmbeddings extends embeddings_1.Embeddings {
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constructor(fields) {
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super(fields ?? {});
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Object.defineProperty(this, "model", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: void 0
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});
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Object.defineProperty(this, "client", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: void 0
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});
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Object.defineProperty(this, "batchSize", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: 512
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});
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this.model = fields?.model ?? "amazon.titan-embed-text-v1";
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this.client =
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fields?.client ??
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new client_bedrock_runtime_1.BedrockRuntimeClient({
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region: fields?.region,
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credentials: fields?.credentials,
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});
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}
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/**
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* Protected method to make a request to the Bedrock API to generate
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* embeddings. Handles the retry logic and returns the response from the
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* API.
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* @param request Request to send to the Bedrock API.
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* @returns Promise that resolves to the response from the API.
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*/
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async _embedText(text) {
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return this.caller.call(async () => {
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try {
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// replace newlines, which can negatively affect performance.
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const cleanedText = text.replace(/\n/g, " ");
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const res = await this.client.send(new client_bedrock_runtime_1.InvokeModelCommand({
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modelId: this.model,
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body: JSON.stringify({
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inputText: cleanedText,
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}),
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contentType: "application/json",
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accept: "application/json",
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}));
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const body = new TextDecoder().decode(res.body);
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return JSON.parse(body).embedding;
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}
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catch (e) {
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console.error({
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error: e,
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});
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// eslint-disable-next-line no-instanceof/no-instanceof
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if (e instanceof Error) {
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throw new Error(`An error occurred while embedding documents with Bedrock: ${e.message}`);
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}
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throw new Error("An error occurred while embedding documents with Bedrock");
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}
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});
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}
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/**
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* Method that takes a document as input and returns a promise that
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* resolves to an embedding for the document. It calls the _embedText
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* method with the document as the input.
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* @param document Document for which to generate an embedding.
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* @returns Promise that resolves to an embedding for the input document.
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*/
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embedQuery(document) {
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return this.caller.callWithOptions({}, this._embedText.bind(this), document);
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}
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/**
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* Method to generate embeddings for an array of texts. Calls _embedText
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* method which batches and handles retry logic when calling the AWS Bedrock API.
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* @param documents Array of texts for which to generate embeddings.
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* @returns Promise that resolves to a 2D array of embeddings for each input document.
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*/
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async embedDocuments(documents) {
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return Promise.all(documents.map((document) => this._embedText(document)));
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}
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}
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exports.BedrockEmbeddings = BedrockEmbeddings;
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