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Contribute Code

To contribute to this project, please follow the "fork and pull request" workflow. Please do not try to push directly to this repo unless you are a maintainer.

Please follow the checked-in pull request template when opening pull requests. Note related issues and tag relevant maintainers.

Pull requests cannot land without passing the formatting, linting, and testing checks first. See Testing and Formatting and Linting for how to run these checks locally.

It's essential that we maintain great documentation and testing. If you:

  • Fix a bug
    • Add a relevant unit or integration test when possible. These live in **/tests/*.test.ts and **/tests/*.int.test.ts/.
  • Make an improvement
    • Update any affected example notebooks and documentation. These live in docs.
    • Update unit and integration tests when relevant.
  • Add a feature
    • Add a demo notebook/MDX file in docs/core_docs/docs.
    • Add unit and integration tests.

We are a small, progress-oriented team. If there's something you'd like to add or change, opening a pull request is the best way to get our attention.

🚀 Quick Start

This quick start guide explains how to run the repository locally. For a development container, see the .devcontainer folder.

🏭 Release process

As of now, LangChain has an ad hoc release process: releases are cut with high frequency by a developer and published to npm.

LangChain follows the semver versioning standard. However, as pre-1.0 software, even patch releases may contain non-backwards-compatible changes.

If your contribution has made its way into a release, we will want to give you credit on Twitter (only if you want though)! If you have a Twitter account you would like us to mention, please let us know in the PR or in another manner.

Integration releases

The release script can be executed only while on a fresh main branch, with no un-committed changes, from the package root. If working from a fork of the repository, make sure to sync the forked main branch with the upstream main branch first.

You can invoke the script by calling yarn release. If new dependencies have been added to the integration package, install them first (i.e. run yarn, then yarn release).

There are three parameters which can be passed to this script, one required and two optional.

  • Required: <workspace name>. eg: @langchain/core The name of the package to release. Can be found in the name value of the package's package.json
  • Optional: --bump-deps eg --bump-deps Will find all packages in the repo which depend on this workspace and checkout a new branch, update the dep version, run yarn install, commit & push to new branch. Generally, this is not necessary.
  • Optional: --tag <tag> eg --tag beta Add a tag to the NPM release. Useful if you want to push a release candidate.

This script automatically bumps the package version, creates a new release branch with the changes, pushes the branch to GitHub, uses release-it to automatically release to NPM, and more depending on the flags passed.

Halfway through this script, you'll be prompted to enter an NPM OTP (typically from an authenticator app). This value is not stored anywhere and is only used to authenticate the NPM release.

Note Unless releasing langchain, no should be answered to all prompts following Publish @langchain/<package> to npm?. Then, the change should be manually committed with the following commit message: <package>[patch]: Release <new version>. E.g.: groq[patch]: Release 0.0.1.

Docker must be running if releasing one of langchain, @langchain/core or @langchain/community. These packages run LangChain's export tests, which run inside docker containers.

Full example: yarn release @langchain/core.

🛠️ Tooling

This project uses the following tools, which are worth getting familiar with if you plan to contribute:

  • yarn (v3.4.1) - dependency management
  • eslint - enforcing standard lint rules
  • prettier - enforcing standard code formatting
  • jest - testing code
  • TypeDoc - reference doc generation from comments
  • Docusaurus - static site generation for documentation

🚀 Quick Start

Clone this repo, then cd into it:

cd langchainjs

Next, try running the following common tasks:

✅ Common Tasks

Our goal is to make it as easy as possible for you to contribute to this project. All of the below commands should be run from within a workspace directory (e.g. langchain, libs/langchain-community) unless otherwise noted.

cd langchain

Or, if you are working on a community integration:

cd libs/langchain-community


Prerequisite: Node version 18+ is required. Please check node version node -v and update it if required.

To get started, you will need to install the dependencies for the project. To do so, run:


Then, you will need to switch directories into langchain-core and build core by running:

cd ../langchain-core
yarn build


We use eslint to enforce standard lint rules. To run the linter, run:

yarn lint


We use prettier to enforce code formatting style. To run the formatter, run:

yarn format

To just check for formatting differences, without fixing them, run:

yarn format:check


In general, tests should be added within a tests/ folder alongside the modules they are testing.

Unit tests cover modular logic that does not require calls to outside APIs.

If you add new logic, please add a unit test. Unit tests should be called *.test.ts.

To run only unit tests, run:

yarn test

Running a single test

To run a single test, run the following from within a workspace:

yarn test:single /path/to/yourtest.test.ts

This is useful for developing individual features.

Integration tests cover logic that requires making calls to outside APIs (often integration with other services).

If you add support for a new external API, please add a new integration test. Integration tests should be called *.int.test.ts.

Note that most integration tests require credentials or other setup. You will likely need to set up a langchain/.env or libs/langchain-community/.env file like the example here.

We generally recommend only running integration tests with yarn test:single, but if you want to run all integration tests, run:

yarn test:integration


To build the project, run:

yarn build

Adding an Entrypoint

LangChain exposes multiple subpaths the user can import from, e.g.

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

We call these subpaths "entrypoints". In general, you should create a new entrypoint if you are adding a new integration with a 3rd party library. If you're adding self-contained functionality without any external dependencies, you can add it to an existing entrypoint.

In order to declare a new entrypoint that users can import from, you should edit the langchain/langchain.config.js or libs/langchain-community/langchain.config.js file. To add an entrypoint tools that imports from tools/index.ts you'd add the following to the entrypoints key inside the config variable:

// ...
entrypoints: {
// ...
tools: "tools/index",
// ...

If you're adding a new integration which requires installing a third party dependency, you must add the entrypoint to the requiresOptionalDependency array, also located inside langchain/langchain.config.js or libs/langchain-community/langchain.config.js.

// ...
requiresOptionalDependency: [
// ...
// ...

This will make sure the entrypoint is included in the published package, and in generated documentation.


Contribute Documentation

Install dependencies

Note: you only need to follow these steps if you are building the docs site locally.
  1. Quarto - package that converts Jupyter notebooks (.ipynb files) into .mdx files for serving in Docusaurus.
  2. yarn build --filter=core_docs - It's as simple as that! (or you can simply run yarn build from docs/core_docs/)

All notebooks are converted to .md files and automatically gitignored. If you would like to create a non notebook doc, it must be a .mdx file.

Writing Notebooks

When adding new dependencies inside the notebook you must update the import map inside deno.json in the root of the LangChain repo.

This is required because the notebooks use the Deno runtime, and Deno formats imports differently than Node.js.


// Import in Node:
import { z } from "zod";
// Import in Deno:
import { z } from "npm:/zod";

See examples inside deno.json for more details.

Docs are largely autogenerated by TypeDoc from the code.

For that reason, we ask that you add good documentation to all classes and methods.

Similar to linting, we recognize documentation can be annoying. If you do not want to do it, please contact a project maintainer, and they can help you with it. We do not want this to be a blocker for good code getting contributed.

Documentation and the skeleton lives under the docs/ folder. Example code is imported from under the examples/ folder.

Running examples

If you add a new major piece of functionality, it is helpful to add an example to showcase how to use it. Most of our users find examples to be the most helpful kind of documentation.

Examples can be added in the examples/src directory, e.g. examples/src/path/to/example. This example can then be invoked with yarn example path/to/example at the top level of the repo.

To run examples that require an environment variable, you'll need to add a .env file under examples/.env.

Build Documentation Locally

To generate and view the documentation locally, change to the project root and run yarn to ensure dependencies get installed in both the docs/ and examples/ workspaces:

cd ..

Then run:

yarn docs


Environment tests test whether LangChain works across different JS environments, including Node.js (both ESM and CJS), Edge environments (eg. Cloudflare Workers), and browsers (using Webpack).

To run the environment tests with Docker, run the following command from the project root:

yarn test:exports:docker

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