Codebase AI Assistant

An intelligent AI-powered codebase assistant that allows users to upload a repository and ask questions about the code.
Built using RAG (Retrieval-Augmented Generation) with Qdrant + LLM + FastAPI + React.

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Live Demo

• 🔗 Frontend: https://codebase-ai-assistant-frontend.vercel.app/
• 🔗 Backend API: https://kirankumar29-codebase-assitant.hf.space

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Features

• Upload GitHub repository or local codebase
• Semantic search using vector embeddings
• Ask questions about your code
• Get file-based explanations
• Supports multiple programming languages
• ⚡ Fast retrieval using Qdrant vector database

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Architecture

User Question
↓
Frontend (React / Vercel)
↓
FastAPI Backend (Hugging Face)
↓
Qdrant Vector DB
↓
Relevant Code Context
↓
LLM (Groq)
↓
Answer

Tech Stack

🔹 Backend

• FastAPI
• LangChain
• Qdrant Vector Database
• Groq LLM (LLaMA 3)
• HuggingFace Embeddings

🔹 Frontend

• React / Next.js
• Tailwind CSS
• Vercel Deployment

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⚙️ How It Works

1. Upload a repository
2. Files are filtered and processed
3. Converted into embeddings
4. Stored in Qdrant
5. User asks a question
6. Relevant code is retrieved
7. LLM generates answer based on context

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Installation (Backend)

git clone https://github.com/kumar-kiran-24/Codebase-AI-Assistant.git
cd Codebase-AI-Assistant

pip install -r requirements.txt

Environment Variables(.env)

QDRANT_URL=your_qdrant_url
QDRANT_API_KEY=your_api_key
GROQ_API=your_groq_api_key