🚀 RAG Codebase Explorer

A Retrieval-Augmented Generation (RAG) powered tool that allows users to analyze any GitHub repository using natural language.

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🧠 Features

• 🔍 Ask questions about any GitHub repo\
• ⚡ Fast semantic search using vector embeddings\
• 🧩 Code-aware chunking\
• 🗂️ File-level insights\
• 🧠 LLM-powered explanations\
• 🔄 Async ingestion\
• 🧹 Automatic cleanup\
• 🧱 Multi-repository support

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Architecture

User → Repo URL → Clone → Chunk → Embed → Store → Query → LLM Answer

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Tech Stack

• FastAPI\
• LangChain\
• OpenAI\
• Qdrant\
• React\
• Docker

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⚙️ Setup

git clone <repo>
cd RAG-Codebase-Explorer
python -m venv venv
venv\Scripts\activate
pip install -r requirements.txt

Create .env:

OPENAI_API_KEY=your_key

Run Qdrant:

docker run -p 6333:6333 qdrant/qdrant

Run backend:

python -m uvicorn server:app --reload

Run frontend:

cd frontend
npm install
npm run dev

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🚀 Usage

Ingest Repo

POST /ingest

Check Status

GET /status/{repo_id}

Query

POST /query

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Structure

ingest/
embeddings/
rag/
pipeline/
server.py
frontend/
repos/

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Highlights

• Repo isolation via repo_id
• Qdrant per repo collection
• Auto repo cleanup
• Async ingestion

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Future Work

• Streaming responses\
• Hybrid search\
• Reranking\
• Deployment

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Author

Bipin Kumar