🚀 Phoenix - AI-Powered C++ Documentation Suite

✨ Introduction

Phoenix is a comprehensive AI-powered toolkit for automated C++ code documentation, analysis, and maintenance.
It combines the power of tree-sitter parsing, Ollama AI models, and a modern GUI interface to revolutionize how developers document and maintain their C++ codebases.

🔥 Why Phoenix?

Phoenix tackles the toughest challenges developers face when working with legacy C++ code base:

1. Understand legacy code faster – make even decades-old codebases easier to read and maintain.
2. Keep your code secure – all documentation is generated locally on your system, never leaving your machine.
3. Onboard new developers instantly – newcomers can quickly grasp project structure and flow.
4. From zero to full documentation – transform undocumented projects into fully documented codebases.
5. Seamless Doxygen integration – generate complete Doxygen documentation directly from AI-powered docs.
6. Continuous Documentation Updates – once full documentation is generated, Phoenix also keeps your docs up to date by tracking Git changes since the last documentation date.
7. Catch hidden issues – AI powered function-by-function analysis of entire code based, detects potential glitches and bugs, producing a structured JSON report.

📋 Basic Requirement

• The C++ codebase must be a Git repository.
• Computer with GPU having 24GB memory and 7k CUDA cores for faster processing.

🌟 Key Features

🤖 AI-Powered Documentation Generation

• Doxygen-style Comments: Automatically generates comprehensive function documentation
• Inline Code Comments: Smart contextual comments for complex logic blocks
• Multi-line Statement Handling: Correctly handles complex C++ constructs

🔍 Git Integration & Change Tracking

• Smart Change Detection: Identifies modified, added, and deleted functions
• Historical Analysis: Compare functions across commits and time ranges
• Automated Processing: Process only changed functions for efficiency

🖥️ Modern GUI Interface

• Intuitive Design: Clean, modern interface built with Streamlit
• Real-time Progress: Live logging and status updates with advanced logging mechanism
• Customizable Settings: Flexible configuration options

📊 Static Code Quality Analysis

• Critical Glitch Detection: Identifies memory leaks, null pointer dereferences
• Performance Analysis: Spots potential bottlenecks and issues
• Security Assessment: Detects buffer overflows and injection vulnerabilities

🛠️ Installation

Prerequisites

• Python 3.8 or higher
• Git (for repository analysis)
• Ollama server (local or remote)

Quick Install

# Clone the repository
git clone https://github.com/pranaycv/phoenix.git
cd phoenix

# Install dependencies
pip install -r requirements.txt

# For development setup
pip install -e .

Ollama Setup

# Install and start Ollama
curl -fsSL https://ollama.ai/install.sh | sh
ollama pull gpt-oss:20b  # or your preferred model
ollama serve

🚀 Quick Start

1. GUI Mode (Recommended)

streamlit run phoenix.py

Default Login Credentials:

• Username: phoenix
• Password: phoenix

Configuration Options:

• Directory Path: Your C++ project directory
• Last Document Date: Process changes since this date
• Ollama Host: AI model server URL
• Branch: Git branch to analyze (optional)

2. Command Line Usage

Extract Single Function:

python extract_function_code_2.py
# Edit the file_path and line_number variables

Analyze Git Changes:

python get_git_changes.py --start-date 2024-01-01 --branch main

Batch Process Files:

python generate_docs_ollama.py
# Configure source_directory in the script

📁 Project Structure

phoenix/
├── 🎯 phoenix.py                   # Main Streamlit GUI application
├── 🔍 extract_function_code_2.py   # Function extraction utility
├── 📝 generate_docs_ollama.py      # Batch documentation generator
├── 🔄 get_git_changes.py          # Git change analyzer
├── 📋 requirements.txt            # Dependencies
├── 🏗️ setup.py                   # Package setup
├── 📚 docs/                       # Documentation
├── 🧪 examples/                   # Usage examples
└── ⚙️ config/                    # Configuration files

🎮 Usage Examples

Example 1: Document Recent Changes

# Set your project path
repo_path = "D:/YourProject"

# Process changes from last week
last_date = "2024-01-15"

# Run with GUI
streamlit run phoenix.py

Example 2: Extract Specific Function

from extract_function_code_2 import FunctionExtractor

extractor = FunctionExtractor("src/main.cpp", 42)
extractor.ExtractAndSave()

Example 3: Analyze Git Changes

from get_git_changes import ChangeProcessor, GitRepoHandler, CppParser, FunctionExtractor

parser = CppParser()
extractor = FunctionExtractor(parser)
git_handler = GitRepoHandler("./")
processor = ChangeProcessor(git_handler, extractor, ('.cpp', '.hpp'))
processor.ProcessChanges('HEAD~10')

⚙️ Configuration

Environment Variables

export OLLAMA_HOST="http://localhost:11434"
export PHOENIX_MODEL="gpt-oss:20b"
export PHOENIX_TEMP_DIR="/tmp/phoenix"

Config File (config/phoenix.json)

{
  "ollama": {
    "host": "http://127.0.0.1:11434",
    "model": "gpt-oss:20b",
    "temperature": 0.0
  },
  "git": {
    "extensions": [".cpp", ".hpp", ".cc", ".h"],
    "ignore_patterns": ["**/build/**", "**/test/**"]
  },
  "documentation": {
    "include_doxygen": true,
    "inline_comments": true,
    "code_review": true
  }
}

🏗️ Architecture

Core Components

🧠 AI Engine (CustomOllamaGenerator)

• Direct HTTP API integration with Ollama
• Robust error handling and retry logic
• Optimized prompts for C++ documentation

🌳 Parsing Engine (CppParser)

• Tree-sitter based C++ parsing
• Accurate function extraction
• Multi-file support with encoding detection

📁 File Management (FileProcessor)

• Smart encoding detection
• Batch processing capabilities
• Status tracking and resumable operations

🔄 Version Control (GitRepoHandler)

• Git integration for change detection
• Support for branches and commit ranges
• Staged and unstaged change handling

Data Flow

C++ Source Files → Tree-sitter Parser → Function Extraction 
                                             ↓
Git Change Analysis → AI Documentation → Code Integration
                                             ↓
Quality Review → Updated Source Files → Status Tracking

🤝 Contributing

We welcome contributions! Please see CONTRIBUTING.md for guidelines.

Development Setup

# Fork and clone the repository
git clone https://github.com/pranaycv/phoenix.git
cd phoenix

# Create virtual environment
python -m venv venv
source venv/bin/activate  # or venv\Scripts\activate on Windows

# Install development dependencies
pip install -r requirements.txt
pip install -e .

# Run tests
pytest tests/

Code Standards

• Black for code formatting
• flake8 for linting
• mypy for type checking
• pytest for testing

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🙏 Acknowledgments

• Tree-sitter team for the excellent parsing library
• Ollama team for making AI models accessible
• Streamlit for the modern GUI framework
• Open Source Community for continuous inspiration

📞 Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Wiki: Project Wiki

🗺️ Roadmap

• VS Code Extension integration
• Multiple AI Model support (OpenAI, Claude, etc.)
• Java/Python language support
• Team Collaboration features
• CI/CD Pipeline integration
• Cloud-based processing options

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