@langchain/community/dist/embeddings/tencent_hunyuan/base.js

Third-party integrations for LangChain.js

import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { Embeddings } from "@langchain/core/embeddings";
//#region src/embeddings/tencent_hunyuan/base.ts
/**
* Class for generating embeddings using the Tencent Hunyuan API.
*/
var TencentHunyuanEmbeddings = class extends Embeddings {
	tencentSecretId;
	tencentSecretKey;
	host = "hunyuan.tencentcloudapi.com";
	sign;
	constructor(fields) {
		super(fields ?? {});
		this.tencentSecretId = fields?.tencentSecretId ?? getEnvironmentVariable("TENCENT_SECRET_ID");
		if (!this.tencentSecretId) throw new Error("Tencent SecretID not found");
		this.tencentSecretKey = fields?.tencentSecretKey ?? getEnvironmentVariable("TENCENT_SECRET_KEY");
		if (!this.tencentSecretKey) throw new Error("Tencent SecretKey not found");
		this.host = fields?.host ?? this.host;
		if (!fields?.sign) throw new Error("Sign method undefined");
		this.sign = fields?.sign;
	}
	/**
	* Private method to make a request to the TogetherAI API to generate
	* embeddings. Handles the retry logic and returns the response from the API.
	* @param {string} input The input text to embed.
	* @returns Promise that resolves to the response from the API.
	* @TODO Figure out return type and statically type it.
	*/
	async embeddingWithRetry(input) {
		const request = { Input: input };
		const timestamp = Math.trunc(Date.now() / 1e3);
		const headers = {
			"Content-Type": "application/json",
			"X-TC-Action": "GetEmbedding",
			"X-TC-Version": "2023-09-01",
			"X-TC-Timestamp": timestamp.toString(),
			Authorization: ""
		};
		headers.Authorization = this.sign(this.host, request, timestamp, this.tencentSecretId ?? "", this.tencentSecretKey ?? "", headers);
		return this.caller.call(async () => {
			const response = await fetch(`https://${this.host}`, {
				headers,
				method: "POST",
				body: JSON.stringify(request)
			});
			if (response.ok) return response.json();
			throw new Error(`Error getting embeddings from Tencent Hunyuan. ${JSON.stringify(await response.json(), null, 2)}`);
		});
	}
	/**
	* Method to generate an embedding for a single document. Calls the
	* embeddingWithRetry method with the document as the input.
	* @param {string} text Document to generate an embedding for.
	* @returns {Promise<number[]>} Promise that resolves to an embedding for the document.
	*/
	async embedQuery(text) {
		const { Response } = await this.embeddingWithRetry(text);
		if (Response?.Error?.Message) throw new Error(`[${Response.RequestId}] ${Response.Error.Message}`);
		return Response.Data[0].Embedding;
	}
	/**
	* Method that takes an array of documents as input and returns a promise
	* that resolves to a 2D array of embeddings for each document. It calls
	* the embedQuery method for each document in the array.
	* @param documents Array of documents for which to generate embeddings.
	* @returns Promise that resolves to a 2D array of embeddings for each input document.
	*/
	embedDocuments(documents) {
		return Promise.all(documents.map((doc) => this.embedQuery(doc)));
	}
};
//#endregion
export { TencentHunyuanEmbeddings };

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