ReCode - DSA Solution Generator & Revision Tracker

A modern web application that helps developers master Data Structures and Algorithms through AI-powered solution generation and smart revision tracking.

Features

🚀 AI-Powered Solution Generation

• Get brute force, better, and optimal solutions for any DSA problem
• Powered by Qubrid AI with multi-tier caching (Redis → MongoDB)
• Supports multiple programming languages

📚 Smart Revision Tracking

• Save and organize your solved problems
• Track patterns and categories
• Review time/space complexity

🔐 Secure Authentication

• Email verification with OTP
• Password reset functionality
• JWT-based session management

📊 Admin Dashboard

• User analytics
• Cache management
• Solution statistics

Tech Stack

Frontend:

• React 18 + TypeScript
• Vite
• TailwindCSS

Backend (Serverless):

• Vercel Serverless Functions
• MongoDB (Mongoose)
• Upstash Redis

AI:

• Qubrid AI (Qwen3-Coder)

Getting Started

Prerequisites

• Node.js 18+
• MongoDB database
• Upstash Redis (optional, for faster caching)
• Qubrid API key

Installation

1. Clone the repository

   git clone https://github.com/WillyEverGreen/ReCode.git
   cd ReCode

2. Install dependencies

   npm install

3. Configure environment variables

   cp .env.example .env

   Fill in your .env file:

   # MongoDB
   MONGO_URI=mongodb+srv://...
   
   # JWT Secret
   JWT_SECRET=your-secret-key
   
   # Qubrid AI
   QUBRID_API_KEY=your-qubrid-api-key
   
   # Admin
   ADMIN_PASSWORD=your-admin-password
   
   # Redis (Optional - for faster caching)
   UPSTASH_REDIS_REST_URL=https://...
   UPSTASH_REDIS_REST_TOKEN=...

4. Run development server

   # Using Vercel CLI (recommended - tests serverless functions)
   vercel dev
   
   # Or using Vite only (frontend only)
   npm run dev

5. Open http://localhost:3000

Local LLM (Optional)

If you want to run local LLMs (Ollama) for offline AI generation during development, follow these steps:

• Install and run Ollama separately and ensure models are available (e.g. qwen2.5-coder:7b, qwen2.5:7b, deepseek-r1:7b).
• In your local .env set:

AI_PROVIDER=ollama
OLLAMA_BASE_URL=http://127.0.0.1:11434/v1
OLLAMA_MODEL_CODING=qwen2.5-coder:7b
OLLAMA_MODEL_EXPLANATION=qwen2.5:7b
OLLAMA_MODEL_REASONING=deepseek-r1:7b
VITE_API_URL=http://localhost:5000

• Start the backend and frontend in separate terminals:

npm run server   # starts Express API on port 5000
npm run dev      # starts Vite frontend on port 3000

The local Ollama integration is opt-in — by default the app uses the existing remote AI provider (Qubrid). This ensures your production deployment on Vercel is unaffected.

Deployment

Vercel (Recommended)

1. Push code to GitHub
2. Import project in Vercel
3. Add environment variables in Vercel dashboard
4. Deploy!

Note: The repository changes are backward compatible — if AI_PROVIDER is not set to ollama the deployed app will continue to use the existing remote AI provider. Do not commit your .env file; keep secrets in Vercel's dashboard.

Environment Variables for Production

Variable	Required	Description
MONGO_URI	✓	MongoDB connection string
JWT_SECRET	✓	Secret for JWT tokens
QUBRID_API_KEY	✓	Qubrid AI API key
ADMIN_PASSWORD	✓	Admin panel password
UPSTASH_REDIS_REST_URL		Upstash Redis URL
UPSTASH_REDIS_REST_TOKEN		Upstash Redis token

API Endpoints

Endpoint	Method	Description
/api/health	GET	Health check
/api/auth/signup	POST	User registration
/api/auth/login	POST	User login
/api/auth/verify-email	POST	Verify email OTP
/api/auth/forgot-password	POST	Request password reset
/api/auth/reset-password	POST	Reset password
/api/solution	POST	Generate DSA solution
/api/questions	GET/POST	User's saved questions
/api/admin/stats	GET	Admin statistics

Project Structure

ReCode/
├── api/                    # Vercel Serverless Functions
│   ├── _lib/               # Shared utilities
│   ├── admin/              # Admin endpoints
│   ├── auth/               # Authentication endpoints
│   ├── questions/          # Questions CRUD
│   └── solution/           # Solution generation
├── components/             # React components
├── models/                 # MongoDB models
├── services/               # Frontend services
├── config/                 # Configuration
└── types/                  # TypeScript types

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

This project is licensed under the MIT License.

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Made with ❤️ by WillyEverGreen