GitHubToolkit#

class langchain_community.agent_toolkits.github.toolkit.GitHubToolkit[source]#

Bases: BaseToolkit

GitHub Toolkit.

Security Note: This toolkit contains tools that can read and modify

the state of a service; e.g., by creating, deleting, or updating, reading underlying data.

For example, this toolkit can be used to create issues, pull requests, and comments on GitHub.

See [Security](https://python.langchain.com/docs/security) for more information.

Setup:

See detailed installation instructions here: https://python.langchain.com/v0.2/docs/integrations/tools/github/#installation

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

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:

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:

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

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

Use within an agent:

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()

 ================================[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".

Parameters:: tools – List[BaseTool]. The tools in the toolkit. Default is an empty list.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

param tools: List[BaseTool] = []#

classmethod from_github_api_wrapper(github_api_wrapper: GitHubAPIWrapper) → GitHubToolkit[source]#

Create a GitHubToolkit from a GitHubAPIWrapper.

Parameters:: github_api_wrapper (GitHubAPIWrapper) – GitHubAPIWrapper. The GitHub API wrapper.
Returns:: GitHubToolkit. The GitHub toolkit.
Return type:: GitHubToolkit

get_tools() → List[BaseTool][source]#

Get the tools in the toolkit.

Return type:: List[BaseTool]

Examples using GitHubToolkit

Github Toolkit