Code Analysis Pipeline

A comprehensive tool for analyzing codebases through file traversal, content summarization, and interactive querying.

Features

• File Path Collection: Recursively traverse directories and collect file paths
• Content Summarization: Generate detailed summaries of code files using AI
• Interactive Query Interface: Query your codebase using natural language with voice support

Setup

1. Clone the repository:

git clone <repository-url>
cd file_path_tool

2. Install dependencies:

pip install -r requirements.txt
cd rag_query_tool
pip install -r requirements.txt

3. Configure environment variables:

cp .env.example .env
# Edit .env with your API keys and preferences

4. Run the complete pipeline:

python MASTER.py

Or run individual components:

python main.py              # File path collection
python summarize_files.py   # Content summarization
python rag_query_tool/query_interface.py  # Interactive querying

Components

1. File Path Collection

• Traverses directories recursively
• Identifies empty folders
• Generates timestamped output files

2. Content Summarization

• Processes files in batches or all at once
• Skips README files automatically
• Creates mirrored directory structure for summaries
• Supports multiple OpenAI models

3. RAG Query Tool

• Natural language querying
• Voice input/output support
• Multiple TTS voices
• Response caching
• Offline fallback options

Configuration

See .env.example for all available configuration options:

• OpenAI API settings
• ElevenLabs TTS configuration
• Speech recognition options
• Application preferences

Requirements

• Python 3.8+
• OpenAI API key
• ElevenLabs API key (optional, for TTS)
• Google Cloud credentials (optional, for STT)

Directory Structure

file_path_tool/
├── docs/               # Documentation
├── src/               # Core functionality
├── rag_query_tool/    # Query interface
├── summaries/         # Generated summaries
├── main.py           # File traversal script
├── summarize_files.py # Summarization script
└── MASTER.py         # Pipeline runner

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

[Your chosen license]