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Contribute Integrations

To begin, make sure you have all the dependencies outlined in guide on Contributing Code.

There are a few different places you can contribute integrations for LangChain:

  • Community: For lighter-weight integrations that are primarily maintained by LangChain and the Open Source Community.
  • Partner Packages: For independent packages that are co-maintained by LangChain and a partner.

For the most part, new integrations should be added to the Community package. Partner packages require more maintenance as separate packages, so please confirm with the LangChain team before creating a new partner package.

In the following sections, we'll walk through how to contribute to each of these packages from a fake company, Parrot Link AI.

Community Package​

The langchain-community package is in libs/community and contains most integrations.

It is installed by users with pip install langchain-community, and exported members can be imported with code like 

from langchain_community.chat_models import ParrotLinkLLM
from langchain_community.llms import ChatParrotLink
from langchain_community.vectorstores import ParrotLinkVectorStore

The community package relies on manually-installed dependent packages, so you will see errors if you try to import a package that is not installed. In our fake example, if you tried to import ParrotLinkLLM without installing parrot-link-sdk, you will see an ImportError telling you to install it when trying to use it.

Let's say we wanted to implement a chat model for Parrot Link AI. We would create a new file in libs/community/langchain_community/chat_models/parrot_link.py with the following code:

from langchain_core.language_models.chat_models import BaseChatModel

class ChatParrotLink(BaseChatModel):
    """ChatParrotLink chat model.

    Example:
        .. code-block:: python

            from langchain_parrot_link import ChatParrotLink

            model = ChatParrotLink()
    """

    ...

And we would write tests in:

  • Unit tests: libs/community/tests/unit_tests/chat_models/test_parrot_link.py
  • Integration tests: libs/community/tests/integration_tests/chat_models/test_parrot_link.py

And add documentation to:

  • docs/docs/integrations/chat/parrot_link.ipynb

  • `docs/docs/

Partner Packages​

Partner packages are in libs/partners/* and are installed by users with pip install langchain-{partner}, and exported members can be imported with code like 

from langchain_{partner} import X

Set up a new package​

To set up a new partner package, use the latest version of the LangChain CLI. You can install or update it with:

pip install -U langchain-cli

Let's say you want to create a new partner package working for a company called Parrot Link AI.

Then, run the following command to create a new partner package:

cd libs/partners
langchain-cli integration new
> Name: parrot-link
> Name of integration in PascalCase [ParrotLink]: ParrotLink

This will create a new package in libs/partners/parrot-link with the following structure:

libs/partners/parrot-link/
  langchain_parrot_link/ # folder containing your package
    ...
  tests/
    ...
  docs/ # bootstrapped docs notebooks, must be moved to /docs in monorepo root
    ...
  scripts/ # scripts for CI
    ...
  LICENSE
  README.md # fill out with information about your package
  Makefile # default commands for CI
  pyproject.toml # package metadata, mostly managed by Poetry
  poetry.lock # package lockfile, managed by Poetry
  .gitignore

Implement your package​

First, add any dependencies your package needs, such as your company's SDK:

poetry add parrot-link-sdk

If you need separate dependencies for type checking, you can add them to the typing group with:

poetry add --group typing types-parrot-link-sdk

Then, implement your package in libs/partners/parrot-link/langchain_parrot_link.

By default, this will include stubs for a Chat Model, an LLM, and/or a Vector Store. You should delete any of the files you won't use and remove them from __init__.py.

Write Unit and Integration Tests​

Some basic tests are generated in the tests/ directory. You should add more tests to cover your package's functionality.

For information on running and implementing tests, see the Testing guide.

Write documentation​

Documentation is generated from Jupyter notebooks in the docs/ directory. You should move the generated notebooks to the relevant docs/docs/integrations directory in the monorepo root.

Additional steps​

Contributor steps:

  • Add secret names to manual integrations workflow in .github/workflows/_integration_test.yml
  • Add secrets to release workflow (for pre-release testing) in .github/workflows/_release.yml

Maintainer steps (Contributors should not do these):

  • set up pypi and test pypi projects
  • add credential secrets to Github Actions
  • add package to conda-forge