106 lines
4.2 KiB
JavaScript
106 lines
4.2 KiB
JavaScript
"use strict";
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Object.defineProperty(exports, "__esModule", { value: true });
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exports.TencentHunyuanEmbeddings = void 0;
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const env_1 = require("@langchain/core/utils/env");
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const embeddings_1 = require("@langchain/core/embeddings");
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/**
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* Class for generating embeddings using the Tencent Hunyuan API.
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*/
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class TencentHunyuanEmbeddings extends embeddings_1.Embeddings {
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constructor(fields) {
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super(fields ?? {});
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Object.defineProperty(this, "tencentSecretId", {
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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, "tencentSecretKey", {
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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, "host", {
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enumerable: true,
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configurable: true,
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writable: true,
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value: "hunyuan.tencentcloudapi.com"
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});
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Object.defineProperty(this, "sign", {
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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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this.tencentSecretId =
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fields?.tencentSecretId ?? (0, env_1.getEnvironmentVariable)("TENCENT_SECRET_ID");
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if (!this.tencentSecretId) {
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throw new Error("Tencent SecretID not found");
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}
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this.tencentSecretKey =
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fields?.tencentSecretKey ?? (0, env_1.getEnvironmentVariable)("TENCENT_SECRET_KEY");
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if (!this.tencentSecretKey) {
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throw new Error("Tencent SecretKey not found");
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}
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this.host = fields?.host ?? this.host;
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if (!fields?.sign) {
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throw new Error("Sign method undefined");
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}
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this.sign = fields?.sign;
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}
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/**
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* Private method to make a request to the TogetherAI API to generate
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* embeddings. Handles the retry logic and returns the response from the API.
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* @param {string} input The input text to embed.
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* @returns Promise that resolves to the response from the API.
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* @TODO Figure out return type and statically type it.
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*/
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async embeddingWithRetry(input) {
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const request = { Input: input };
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const timestamp = Math.trunc(Date.now() / 1000);
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const headers = {
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"Content-Type": "application/json",
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"X-TC-Action": "GetEmbedding",
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"X-TC-Version": "2023-09-01",
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"X-TC-Timestamp": timestamp.toString(),
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Authorization: "",
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};
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headers.Authorization = this.sign(this.host, request, timestamp, this.tencentSecretId ?? "", this.tencentSecretKey ?? "", headers);
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return this.caller.call(async () => {
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const response = await fetch(`https://${this.host}`, {
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headers,
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method: "POST",
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body: JSON.stringify(request),
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});
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if (response.ok) {
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return response.json();
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}
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throw new Error(`Error getting embeddings from Tencent Hunyuan. ${JSON.stringify(await response.json(), null, 2)}`);
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});
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}
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/**
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* Method to generate an embedding for a single document. Calls the
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* embeddingWithRetry method with the document as the input.
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* @param {string} text Document to generate an embedding for.
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* @returns {Promise<number[]>} Promise that resolves to an embedding for the document.
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*/
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async embedQuery(text) {
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const { Response } = await this.embeddingWithRetry(text);
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if (Response?.Error?.Message) {
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throw new Error(`[${Response.RequestId}] ${Response.Error.Message}`);
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}
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return Response.Data[0].Embedding;
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}
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/**
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* Method that takes an array of documents as input and returns a promise
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* that resolves to a 2D array of embeddings for each document. It calls
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* the embedQuery method for each document in the array.
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* @param documents Array of documents 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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embedDocuments(documents) {
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return Promise.all(documents.map((doc) => this.embedQuery(doc)));
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}
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}
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exports.TencentHunyuanEmbeddings = TencentHunyuanEmbeddings;
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