ai-cr 2.0.0.dev1

AI code review tool that works with any language model provider. It detects issues in GitHub pull requests or local changes—instantly, reliably, and without vendor lock-in.

Gito is an open-source AI code reviewer that works with any language model provider. It detects issues in GitHub pull requests or local changes—instantly, reliably, and without vendor lock-in.

Get consistent, thorough code reviews in seconds—no waiting for human availability.

✨ Why Gito?

• [⚡] Lightning Fast: Get detailed code reviews in seconds, not days — powered by parallelized LLM processing
• [🔧] Vendor Agnostic: Works with any language model provider (OpenAI, Anthropic, Google, local models, etc.)
• [🌐] Universal: Supports all major programming languages and frameworks
• [🔍] Comprehensive Analysis: Detect issues across security, performance, maintainability, best practices, and much more
• [📈] Consistent Quality: Never tired, never biased—consistent review quality every time
• [🚀] Easy Integration: Automatically reviews pull requests via GitHub Actions and posts results as PR comments
• [🎛️] Infinitely Flexible: Adapt to any project's standards—configure review rules, severity levels, and focus areas, build custom workflows

🎯 Perfect For

• Solo developers who want expert-level code review without the wait
• Teams looking to catch issues before human review
• Open source projects maintaining high code quality at scale
• CI/CD pipelines requiring automated quality gates

✨ See code review in action ✨

🚀 Quickstart

1. Review Pull Requests via GitHub Actions

Create a .github/workflows/gito.yml file:

name: "Gito: AI Code Review"
on: { pull_request: { types: [opened, synchronize, reopened] } }
jobs:
  review:
    runs-on: ubuntu-latest
    permissions: { contents: read, pull-requests: write } # 'write' for leaving the summary comment
    steps:
    - uses: actions/checkout@v4
      with: { fetch-depth: 0 }
    - name: Set up Python
      uses: actions/setup-python@v5
      with: { python-version: "3.13" }
    - name: Install AI Code Review tool
      run: pip install gito.bot~=2.0
    - name: Run AI code analysis
      env:
        LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
        LLM_API_TYPE: openai
        MODEL: "gpt-4.1"
        GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
      run: |
        gito --verbose review
        gito github-comment --token ${{ secrets.GITHUB_TOKEN }}
    - uses: actions/upload-artifact@v4
      with:
        name: ai-code-review-results
        path: |
          code-review-report.md
          code-review-report.json

⚠️ Make sure to add LLM_API_KEY to your repository’s GitHub secrets.

💪 Done!
PRs to your repository will now receive AI code reviews automatically. ✨
See GitHub Setup Guide for more details.

2. Running Code Analysis Locally

Initial Local Setup

Prerequisites: Python 3.11 / 3.12 / 3.13

Step1: Install gito.bot using pip.

pip install gito.bot

Troubleshooting:
pip may be also available via cli as pip3 depending on your Python installation.

Step2: Perform initial setup

The following command will perform one-time setup using an interactive wizard. You will be prompted to enter LLM configuration details (API type, API key, etc). Configuration will be saved to ~/.gito/.env.

gito setup

Troubleshooting:
On some systems, gito command may not became available immediately after installation.
Try restarting your terminal or running python -m gito instead.

Perform your first AI code review locally

Step1: Navigate to your repository root directory.
Step2: Switch to the branch you want to review.
Step3: Run following command

gito review

Note: This will analyze the current branch against the repository main branch by default.
Files that are not staged for commit will be ignored.
See gito --help for more options.

Reviewing remote repository

gito remote [e-mail]:owner/repo.git <FEATURE_BRANCH>..<MAIN_BRANCH>

Use interactive help for details:

gito remote --help

🔧 Configuration

Change behavior via .gito/config.toml:

• Prompt templates, filtering and post-processing using Python code snippets
• Tagging, severity, and confidence settings
• Custom AI awards for developer brilliance
• Output customization

You can override the default config by placing .gito/config.toml in your repo root.

See default configuration here.

More details can be found in 📖 Configuration Cookbook

💻 Development Setup

Install dependencies:

make install

Format code and check style:

make black
make cs

Run tests:

pytest

🤝 Contributing

Looking for a specific feature or having trouble?
Contributions are welcome! ❤️
See CONTRIBUTING.md for details.

📝 License

Licensed under the MIT License.

© 2025 Vitalii Stepanenko