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Setup and Installation

info

Updating from <0.0.52? See this section for instructions.

Quickstart​

If you want to get started quickly on using LangChain in Node.js, clone this repository and follow the README instructions for a boilerplate project with those dependencies set up.

If you prefer to set things up yourself, or you want to run LangChain in other environments, read on for instructions.

Installation​

To get started, install LangChain with the following command:

npm install -S langchain

TypeScript​

LangChain is written in TypeScript and provides type definitions for all of its public APIs.

Loading the library​

ESM​

LangChain provides an ESM build targeting Node.js environments. You can import it using the following syntax:

import { OpenAI } from "langchain/llms/openai";

If you are using TypeScript in an ESM project we suggest updating your tsconfig.json to include the following:

tsconfig.json
{
  "compilerOptions": {
    ...
    "target": "ES2020", // or higher
    "module": "nodenext",
  }
}

CommonJS​

LangChain provides a CommonJS build targeting Node.js environments. You can import it using the following syntax:

const { OpenAI } = require("langchain/llms/openai");

Cloudflare Workers​

LangChain can be used in Cloudflare Workers. You can import it using the following syntax:

import { OpenAI } from "langchain/llms/openai";

Vercel / Next.js​

LangChain can be used in Vercel / Next.js. We support using LangChain in frontend components, in Serverless functions and in Edge functions. You can import it using the following syntax:

import { OpenAI } from "langchain/llms/openai";

If you want to use LangChain in frontend pages, you need to add the following to your next.config.js to enable support for WebAssembly modules (which is required by the tokenizer library @dqbd/tiktoken):

next.config.js
const nextConfig = {
  webpack(config) {
    config.experiments = {
      asyncWebAssembly: true,
      layers: true,
    };

    return config;
  },
};

Deno / Supabase Edge Functions​

LangChain can be used in Deno / Supabase Edge Functions. You can import it using the following syntax:

import { OpenAI } from "https://esm.sh/langchain/llms/openai";

We recommend looking at our Supabase Template for an example of how to use LangChain in Supabase Edge Functions.

Browser​

LangChain can be used in the browser. In our CI we test bundling LangChain with Webpack and Vite, but other bundlers should work too. You can import it using the following syntax:

import { OpenAI } from "langchain/llms/openai";

Create React App​

If you're using create-react-app by default it doesn't support WebAssembly modules, so the tokenizer library @dqbd/tiktoken will not work in the browser. You can follow the instructions here to enable support for WebAssembly modules.

Vite​

If you're using Vite, you need to add the following to your vite.config.js to enable support for WebAssembly modules (which is required by the tokenizer library @dqbd/tiktoken):

npm install -D vite-plugin-wasm vite-plugin-top-level-await
vite.config.js
import wasm from "vite-plugin-wasm";
import topLevelAwait from "vite-plugin-top-level-await";
import { defineConfig } from "vite";

export default defineConfig({
  plugins: [wasm(), topLevelAwait()],
});

Updating from <0.0.52​

If you are updating from a version of LangChain prior to 0.0.52, you will need to update your imports to use the new path structure.

For example, if you were previously doing

import { OpenAI } from "langchain/llms";

you will now need to do

import { OpenAI } from "langchain/llms/openai";

This applies to all imports from the following 6 modules, which have been split into submodules for each integration. The combined modules are deprecated, do not work outside of Node.js, and will be removed in a future version.

  • If you were using langchain/llms, see LLMs for updated import paths.
  • If you were using langchain/chat_models, see Chat Models for updated import paths.
  • If you were using langchain/embeddings, see Embeddings for updated import paths.
  • If you were using langchain/vectorstores, see Vector Stores for updated import paths.
  • If you were using langchain/document_loaders, see Document Loaders for updated import paths.
  • If you were using langchain/retrievers, see Retrievers for updated import paths.

Other modules are not affected by this change, and you can continue to import them from the same path.

Unsupported: Node.js 16​

We do not support Node.js 16, but if you still want to run LangChain on Node.js 16, you will need to follow the instructions in this section. We do not guarantee that these instructions will continue to work in the future.

You will have to make fetch available globally, either:

  • run your application with NODE_OPTIONS='--experimental-fetch' node ..., or
  • install node-fetch and follow the instructions here

Additionally you'll have to polyfill unstructuredClone, eg. by installing core-js and following the instructions here.

If you are running this on Node.js 18 or 19, you do not need to do anything.