AI Repository Intelligence Platform (RepoDoc)

RepoDoc is an advanced, AI-powered static analysis platform designed to inspect GitHub repositories. It evaluates code health, predicts bug-prone files using AI, generates dependency graphs, identifies semantic duplicates using CodeBERT, and detects security violations.

🚀 Features

• Live Analysis Streaming: Watch the analysis progress in real-time.
• Security & Violation Detection: Scans for hardcoded secrets, missing licenses, and unsafe patterns.
• AI Bug Prediction: Predicts risk levels of files based on complexity, churn, and size.
• Semantic Clone Detection: Uses CodeBERT to find structurally distinct but functionally identical code blocks.
• Architecture Graphing: Generates an interactive Cytoscape dependency graph of the repository modules.
• Actionable Refactoring Suggestions: Provides specific advice on decoupling and simplifying code.
• Report Generation: Export comprehensive PDF, Markdown, and JSON reports.

🏗 Architecture

The platform uses a modern decoupled architecture designed for ephemeral serverless and PaaS deployments.

• Backend: FastAPI (Python)
• Frontend: Next.js (React)
• Deployment Targets: Vercel (Frontend), Render (Backend)
• AI Engine: HuggingFace transformers (CodeBERT)

🛠 Local Development Installation

1. Backend Setup

1. Navigate to the backend directory:

   cd backend

2. Set up a virtual environment and install dependencies:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\\Scripts\\activate
   pip install -r requirements.txt

3. Set up environment variables:

   cp .env.example .env

   Edit .env if necessary.
4. Start the FastAPI server:

   uvicorn src.main:app --reload

   The backend runs on http://localhost:8000.

2. Frontend Setup

1. Navigate to the frontend directory:

   cd frontend

2. Install dependencies:

   npm install
   # or
   yarn install

3. Set up environment variables:

   cp .env.example .env.local

   Ensure NEXT_PUBLIC_API_URL points to your backend.
4. Start the Next.js development server:

   npm run dev

   The frontend runs on http://localhost:3000.

🚀 Production Deployment

Deploying the Backend to Render

1. Create a new Web Service on Render connected to your GitHub repository.
2. Set the Root Directory to backend.
3. Set the Environment to Python.
4. Set the Build Command:

   pip install -r requirements.txt

5. Set the Start Command (Render provides dynamic ports via $PORT):

   uvicorn src.main:app --host 0.0.0.0 --port $PORT

6. (Optional) Add render.yaml configurations to auto-deploy your infrastructure.

Deploying the Frontend to Vercel

1. Create a new project on Vercel and import your repository.
2. Set the Root Directory to frontend.
3. Vercel will automatically detect Next.js and apply the correct build settings (npm run build).
4. Critical: In the Environment Variables section, add:
   • Key: NEXT_PUBLIC_API_URL
   • Value: https://your-render-backend-url.onrender.com
5. Deploy!

🧹 Ephemeral Storage Note

The analyzer utilizes ephemeral storage to clone GitHub repositories during analysis. On Render's free tier, the system automatically deletes the cloned directory after the report is sent to the client to immediately free up space for subsequent analyses and prevent hitting disk limits.

📜 License

MIT License.