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Installation

Supported Environments​

LangChain is written in TypeScript and can be used in:

  • Node.js (ESM and CommonJS) - 18.x, 19.x, 20.x
  • Cloudflare Workers
  • Vercel / Next.js (Browser, Serverless and Edge functions)
  • Supabase Edge Functions
  • Browser
  • Deno
  • Bun

However, note that individual integrations may not be supported in all environments.

Installation​

To install LangChain, run the following command:

npm install langchain

A lot of the value of LangChain comes when integrating it with various model providers, datastores, etc. By default, the dependencies needed to do that are NOT installed. You will need to install the dependencies for specific integrations separately.

@langchain/community​

The @langchain/community package contains a range of third-party integrations. Install with:

npm install @langchain/community

There are also more granular packages containing LangChain integrations for individual providers.

@langchain/core​

The @langchain/core package contains base abstractions that the rest of the LangChain ecosystem uses, along with the LangChain Expression Language. It is automatically installed along with langchain, but can also be used separately. Install with:

npm install @langchain/core

LangGraph​

langgraph is a library for building stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain. Install with:

npm install @langchain/langgraph

LangSmith SDK​

The LangSmith SDK is automatically installed by LangChain. If you're not using it with LangChain, install with:

npm install langsmith

Installing integration packages​

LangChain supports packages that contain module integrations with individual third-party providers. They can be as specific as @langchain/anthropic, which contains integrations just for Anthropic models, or as broad as @langchain/community, which contains broader variety of community contributed integrations.

These packages, as well as the main LangChain package, all depend on @langchain/core, which contains the base abstractions that these integration packages extend.

To ensure that all integrations and their types interact with each other properly, it is important that they all use the same version of @langchain/core. The best way to guarantee this is to add a "resolutions" or "overrides" field like the following in your project's package.json. The name will depend on your package manager:

tip

The resolutions or pnpm.overrides fields for yarn or pnpm must be set in the root package.json file.

If you are using yarn:

yarn package.json
{
"name": "your-project",
"version": "0.0.0",
"private": true,
"engines": {
"node": ">=18"
},
"dependencies": {
"@langchain/anthropic": "^0.0.2",
"langchain": "0.0.207"
},
"resolutions": {
"@langchain/core": "0.1.5"
}
}

Or for npm:

npm package.json
{
"name": "your-project",
"version": "0.0.0",
"private": true,
"engines": {
"node": ">=18"
},
"dependencies": {
"@langchain/anthropic": "^0.0.2",
"langchain": "0.0.207"
},
"overrides": {
"@langchain/core": "0.1.5"
}
}

Or for pnpm:

pnpm package.json
{
"name": "your-project",
"version": "0.0.0",
"private": true,
"engines": {
"node": ">=18"
},
"dependencies": {
"@langchain/anthropic": "^0.0.2",
"langchain": "0.0.207"
},
"pnpm": {
"overrides": {
"@langchain/core": "0.1.5"
}
}
}

Loading the library​

TypeScript​

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

ESM​

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

npm install @langchain/openai
import { OpenAI } from "@langchain/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/openai");

Cloudflare Workers​

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

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

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/openai";

or

import { OpenAI } from "npm:@langchain/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/openai";

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

You'll also need to polyfill ReadableStream by installing:

npm i web-streams-polyfill

And then adding it to the global namespace in your main entrypoint:

import "web-streams-polyfill/es6";

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

If you are running Node.js 18+, you do not need to do anything.


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