🤖 CodeRAG: AI-Powered Code Retrieval & Assistance

Note: This POC was innovative for its time, but modern tools like Cursor and Windsurf now apply this principle directly in IDEs. This remains an excellent educational project for understanding RAG implementation.

✨ What is CodeRAG?

CodeRAG combines Retrieval-Augmented Generation (RAG) with AI to provide intelligent coding assistance. Instead of limited context windows, it indexes your entire codebase and provides contextual suggestions based on your complete project.

🎯 Core Idea

Most coding assistants work with limited scope, but CodeRAG provides the full context of your project by:

• Real-time indexing of your entire codebase using FAISS vector search
• Semantic code search powered by OpenAI embeddings
• Contextual AI responses that understand your project structure

🚀 Quick Start

Prerequisites

• Python 3.11+
• OpenAI API Key (Get one here)

Installation

# Clone the repository
git clone https://github.com/your-username/CodeRAG.git
cd CodeRAG

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\\Scripts\\activate

# Install dependencies (installs the package with dev extras)
pip install -r requirements.txt

# Configure environment
cp example.env .env
# Edit .env with your OpenAI API key and settings