GitHubToolkit

Setup:

See detailed installation instructions here: https://python.langchain.com/docs/integrations/tools/github/#installation

You will need to install pygithub and set the following environment variables:

.. code-block:: bash

pip install -U pygithub
export GITHUB_APP_ID="your-app-id"
export GITHUB_APP_PRIVATE_KEY="path-to-private-key"
export GITHUB_REPOSITORY="your-github-repository"

Instantiate:

.. code-block:: python

from langchain_community.agent_toolkits.github.toolkit import GitHubToolkit from langchain_community.utilities.github import GitHubAPIWrapper

github = GitHubAPIWrapper() toolkit = GitHubToolkit.from_github_api_wrapper(github)

Tools:

.. code-block:: python

tools = toolkit.get_tools()
for tool in tools:
    print(tool.name)

.. code-block:: none

Get Issues
Get Issue
Comment on Issue
List open pull requests (PRs)
Get Pull Request
Overview of files included in PR
Create Pull Request
List Pull Requests' Files
Create File
Read File
Update File
Delete File
Overview of existing files in Main branch
Overview of files in current working branch
List branches in this repository
Set active branch
Create a new branch
Get files from a directory
Search issues and pull requests
Search code
Create review request

Include release tools:

By default, the toolkit does not include release-related tools. You can include them by setting include_release_tools=True when initializing the toolkit:

.. code-block:: python

toolkit = GitHubToolkit.from_github_api_wrapper(
    github, include_release_tools=True
)

Setting include_release_tools=True will include the following tools:

.. code-block:: none

Get latest release
Get releases
Get release

Use within an agent:

.. code-block:: python

from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

# Select example tool
tools = [tool for tool in toolkit.get_tools() if tool.name == "Get Issue"]
assert len(tools) == 1
tools[0].name = "get_issue"

llm = ChatOpenAI(model="gpt-4o-mini")
agent_executor = create_react_agent(llm, tools)

example_query = "What is the title of issue 24888?"

events = agent_executor.stream(
    {"messages": [("user", example_query)]},
    stream_mode="values",
)
for event in events:
    event["messages"][-1].pretty_print()

.. code-block:: none

 ================================[1m Human Message [0m=================================

What is the title of issue 24888?
==================================[1m Ai Message [0m==================================
Tool Calls:
get_issue (call_iSYJVaM7uchfNHOMJoVPQsOi)
Call ID: call_iSYJVaM7uchfNHOMJoVPQsOi
Args:
    issue_number: 24888
=================================[1m Tool Message [0m=================================
Name: get_issue

{"number": 24888, "title": "Standardize KV-Store Docs", "body": "..."
==================================[1m Ai Message [0m==================================

The title of issue 24888 is "Standardize KV-Store Docs".