🤖 Git AI

Intelligent commit messages with sophisticated multi-step analysis

Git AI seamlessly integrates ChatGPT with git hooks to automate commit message generation based on your staged files. Using a sophisticated multi-step analysis process, it analyzes each file individually, calculates impact scores, and generates multiple commit message candidates before selecting the best one.

✨ Why Git AI?

🧠 Multi-Step Analysis - Sophisticated divide-and-conquer approach that analyzes files individually ⚡ Lightning Fast - Rust-powered with parallel processing and intelligent optimization 🎯 Smart Integration - Uses OpenAI's Assistant API, expertly tailored for git diffs 🧠 Contextual Learning - Maintains dedicated threads per project for improved relevance 🔄 Intelligent Fallbacks - Multiple fallback strategies ensure you always get meaningful messages 🏠 Local Optimization - Hosts exclusive assistant instance learning from all your projects

🚀 Quick Start

# Install Git AI
cargo install git-ai

# Set your OpenAI API key
git-ai config set openai-api-key sk-your-key-here

# Install the git hook in your repository
git-ai hook install

# Make changes, stage them, and commit without a message
git add .
git commit --all --no-edit
# ✨ Watch Git AI's multi-step analysis generate your perfect commit message!

🎬 How It Works

Git AI uses a sophisticated multi-step analysis process:

┌─────────────┐     ┌─────────────┐     ┌─────────────┐     ┌─────────────┐     ┌─────────────┐
│ Git Commit  │────▶│ Parse Diff  │────▶│  Analyze    │────▶│   Score     │────▶│  Generate   │
│  (no msg)   │     │   Files     │     │   Files     │     │   Files     │     │  Messages   │
└─────────────┘     └─────────────┘     └─────────────┘     └─────────────┘     └─────────────┘
                           │                    │                    │                    │
                           ▼                    ▼                    ▼                    ▼
                    ┌─────────────┐     ┌─────────────┐     ┌─────────────┐     ┌─────────────┐
                    │ auth.rs     │     │ Lines: +50  │     │ Score: 0.95 │     │ Candidates: │
                    │ test.rs     │     │ Lines: -10  │     │ Score: 0.65 │     │ 1. "Add JWT"│
                    │ main.rs     │     │ Category:   │     │ Score: 0.62 │     │ 2. "auth:   │
                    └─────────────┘     │   source    │     └─────────────┘     │    impl"    │
                                       └─────────────┘                           └─────────────┘
                                                                                         │
                                                                                         ▼
                                                                                 ┌─────────────┐
                                                                                 │   Select    │
                                                                                 │    Best     │
                                                                                 │  Message    │
                                                                                 └─────────────┘

Multi-Step Process

Parse - Splits the git diff into individual files
- Handles different diff formats (standard, commit with hash, raw output)
- Extracts file paths, operation types, and diff content
- Supports added, modified, deleted, renamed, and binary files
Analyze - Examines each file in parallel for:
- Lines added/removed (counts actual +/- lines)
- File type categorization (source, test, config, docs, binary, build)
- Change significance and summary generation
- Uses OpenAI function calling for structured analysis
Score - Calculates impact scores based on:
- Operation type weights (add: 0.3, modify: 0.2, delete: 0.25, rename: 0.1, binary: 0.05)
- File category weights (source: 0.4, test: 0.2, config: 0.25, build: 0.3, docs: 0.1, binary: 0.05)
- Lines changed (normalized up to 0.3)
- Total score capped at 1.0
Generate - Creates multiple commit message candidates
- Action-focused style (e.g., "Add authentication")
- Component-focused style (e.g., "auth: implementation")
- Impact-focused style (e.g., "New feature for authentication")
- Respects max length constraints
Select - Chooses the best message based on:
- Highest impact files
- Overall change context
- Conventional commit format when appropriate

Intelligent Fallback Strategy

┌──────────────────┐
│ Multi-Step + API │ ──── Fail ───┐
└────────┬─────────┘              │
         │ Success                ▼
         ▼                 ┌──────────────────┐
   ┌───────────┐           │ Local Multi-Step │ ──── Fail ───┐
   │  Message  │           └────────┬─────────┘              │
   │ Generated │ ◀──────────────────┘ Success                ▼
   └───────────┘                                   ┌──────────────────┐
         ▲                                         │ Single-Step API  │
         └─────────────────────────────────────────┴──────────────────┘

Git AI automatically falls back through multiple strategies:

Multi-Step with API - Full analysis using OpenAI's function calling
Local Multi-Step - Local analysis without API (when API is unavailable)
Single-Step API - Direct prompt-based generation as final fallback

This ensures you always get meaningful commit messages, even when the API is unavailable.

🌟 Key Features

🧠 Multi-Step Analysis (Default)

Uses a sophisticated divide-and-conquer approach that analyzes each file individually, calculates impact scores, and generates multiple commit message candidates before selecting the best one.

🎯 Smart Integration

Leverages OpenAI's powerful Assistant API, expertly tailored to transform git diffs into insightful commit messages.

📚 Contextual Learning

Maintains a dedicated thread for each project, allowing the assistant to build context over time and improve performance and message relevance with every commit.

🏠 Local Optimization

Hosts an exclusive assistant instance on your machine, learning from all your projects to elevate the quality of commit messages throughout your development environment.

🛡️ Intelligent Fallbacks

Automatically falls back to local analysis when API is unavailable, ensuring you always get meaningful commit messages.

📦 Installation

Option 1: Cargo (Recommended)

cargo install git-ai

Option 2: Pre-compiled Binaries

cargo install cargo-binstall
cargo binstall git-ai

Option 3: From Source

git clone https://github.com/oleander/git-ai
cd git-ai
cargo install --path .

Prerequisites

Rust and Cargo installed on your machine
Git repository
OpenAI API key

🎯 Usage

Basic Setup

# 1. Configure your API key
git-ai config set openai-api-key sk-your-key-here

# 2. Install the git hook
git-ai hook install

# 3. Start committing with multi-step analysis!
git add some-file.rs
git commit --all --no-edit  # Git AI takes over here

Advanced Configuration

# Choose your AI model
git-ai config set model gpt-4.1       # Latest (default)
git-ai config set model gpt-4o        # Optimized, better quality
git-ai config set model gpt-4o-mini   # Faster processing
git-ai config set model gpt-4         # Original GPT-4

# Customize output and performance
git-ai config set max-commit-length 72    # Limit message length
git-ai config set max-tokens 512          # Control API usage (default)

# Reset to defaults
git-ai config reset

Hook Management

git-ai hook install      # Install hook in current repo
git-ai hook uninstall    # Remove hook
git-ai hook reinstall    # Reinstall hook

🛠️ Development

Using Justfile Commands

The project includes a Justfile with useful development commands:

# Install locally with debug symbols and setup hooks
just local-install

# Run integration tests in Docker
just integration-test

# Build Docker image
just docker-build

# Run GitHub Actions locally
just local-github-actions

Building from Source

# Build the project
cargo build

# Run tests
cargo test

# Install locally for development
cargo install --path .

# Quick local installation with hook setup
just local-install

📖 Examples

Feature Addition with Multi-Step Analysis

// auth.rs (Score: 0.95 - High impact source file)
+ fn validate_jwt_token(token: &str) -> Result<Claims, AuthError> {
+     decode::<Claims>(token, &DecodingKey::from_secret("secret"), &Validation::default())
+ }

// test.rs (Score: 0.65 - Supporting test file)
+ #[test]
+ fn test_jwt_validation() {
+     assert!(validate_jwt_token("valid_token").is_ok());
+ }

Generated commit: Add JWT token validation with comprehensive error handling

Bug Fix Analysis

// config.rs (Score: 0.82 - Important config change)
- if user.age > 18 {
+ if user.age >= 18 {

Generated commit: Correct age validation to include 18-year-olds in config

⚙️ Configuration Reference

Setting	Description	Default
`openai-api-key`	Your OpenAI API key	Required
`model`	AI model to use	`gpt-4.1`
`max-tokens`	Maximum tokens per request	`512`
`max-commit-length`	Max commit message length	`72`

🏗️ Architecture

Core Components

CLI Interface (src/main.rs) - Command-line interaction and configuration
Git Hook (src/bin/hook.rs) - Prepare-commit-msg hook integration
Multi-Step Analysis (src/multi_step_analysis.rs, src/multi_step_integration.rs) - Sophisticated file analysis and scoring
Diff Processing (src/hook.rs) - Parallel processing and optimization
API Integration (src/openai.rs, src/ollama.rs) - OpenAI and Ollama support
Function Calling (src/function_calling.rs) - Structured commit message generation

Key Workflows

Hook Installation - Symlinks executable to .git/hooks/prepare-commit-msg
Multi-Step Analysis - Parse → Analyze → Score → Generate → Select
Intelligent Fallbacks - API → Local → Single-step as needed
Performance Optimization - Parallel processing, token management, smart truncation

🧪 Testing

# Run all tests
cargo test

# Run integration tests
./scripts/integration-tests

# Test hook functionality
./scripts/hook-stress-test

# Run comprehensive test suite
./scripts/comprehensive-tests

🚀 Roadmap

🌐 Support for more AI providers (Anthropic, Cohere)
🎨 Customizable commit message templates
📊 Enhanced contextual learning across projects
🔄 Integration with popular Git GUIs
🌍 Multi-language commit message support

❓ FAQ

Q: How does multi-step analysis improve commit messages? A: By analyzing files individually and calculating impact scores, Git AI understands which changes are most significant and crafts messages that reflect the true purpose of your commit.

Q: What happens if the API is down? A: Git AI automatically falls back to local multi-step analysis, then single-step API if needed. You'll always get a meaningful commit message.

Q: Will this work with any Git repository? A: Yes! Git AI works with any Git repository. Just install the hook and you're ready to go.

Q: What if I want to write my own commit message? A: Just use git commit -m "your message" as usual. Git AI only activates when no message is provided.

🤝 Contributing

Your feedback and contributions are welcome! Join our community to help improve Git AI by submitting issues, offering suggestions, or contributing code. See our contributing guidelines for more details.

📜 License

Git AI is proudly open-sourced under the MIT License. See LICENSE for more details.

Made with ❤️ by developers, for developers

⭐ Star this repo if Git AI's multi-step analysis improves your Git workflow!

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🤖 Git AI

✨ Why Git AI?

🚀 Quick Start

🎬 How It Works

Multi-Step Process

Intelligent Fallback Strategy

🌟 Key Features

🧠 Multi-Step Analysis (Default)

🎯 Smart Integration

📚 Contextual Learning

🏠 Local Optimization

🛡️ Intelligent Fallbacks

📦 Installation

Option 1: Cargo (Recommended)

Option 2: Pre-compiled Binaries

Option 3: From Source

Prerequisites

🎯 Usage

Basic Setup

Advanced Configuration

Hook Management

🛠️ Development

Using Justfile Commands

Building from Source

📖 Examples

Feature Addition with Multi-Step Analysis

Bug Fix Analysis

⚙️ Configuration Reference

🏗️ Architecture

Core Components

Key Workflows

🧪 Testing

🚀 Roadmap

❓ FAQ

🤝 Contributing

📜 License

FilesExpand file tree

README.md

Latest commit

History

README.md

File metadata and controls

🤖 Git AI

✨ Why Git AI?

🚀 Quick Start

🎬 How It Works

Multi-Step Process

Intelligent Fallback Strategy

🌟 Key Features

🧠 Multi-Step Analysis (Default)

🎯 Smart Integration

📚 Contextual Learning

🏠 Local Optimization

🛡️ Intelligent Fallbacks

📦 Installation

Option 1: Cargo (Recommended)

Option 2: Pre-compiled Binaries

Option 3: From Source

Prerequisites

🎯 Usage

Basic Setup

Advanced Configuration

Hook Management

🛠️ Development

Using Justfile Commands

Building from Source

📖 Examples

Feature Addition with Multi-Step Analysis

Bug Fix Analysis

⚙️ Configuration Reference

🏗️ Architecture

Core Components

Key Workflows

🧪 Testing

🚀 Roadmap

❓ FAQ

🤝 Contributing

📜 License