MITS SkillFlare 🎓

A comprehensive student talent marketplace and mentorship platform for MITS. It empowers students and teachers to collaborate seamlessly through a task-based economy, professional mentorships, real-time messaging, and intelligent AI assistance.

🌟 Key Features

For Students

• Browse Tasks: Discover tasks posted by teachers, mentors, and peers.
• Take & Complete Tasks: Gain hands-on experience and earn credit points for valid submissions.
• Mentorship: Connect with experienced developers and mentors or apply to become one.
• Build Portfolio: Showcase completed work and earn badges on your profile.
• Leaderboard: Compete with peers and climb the ranks using gamified credit points.

For Mentors

• Become a Mentor: Apply by detailing skills, coding profiles, and professional links.
• Manage Profile: Update your availability dynamically and adjust technical skillsets.
• Guide Students: Accept mentorship requests and conduct 1-on-1 sessions.

For Teachers

• Post Tasks: Create assignments with descriptions, deadlines, and credit point rewards.
• Review Submissions: Approve completed tasks or request revisions with direct feedback.
• Rate Students: Provide constructive ratings to boost student portfolios.
• Monitor Progress: Track the completion pipeline of posted tasks through the dashboard.

🤖 Buddy AI Assistant (Powered by Ollama)

SkillFlare comes with an embedded, context-aware AI named Buddy AI.

• Built on a dynamic backend architecture connected to Ollama (Mistral/Llama backend)
• Trained specifically on the internal architecture of MITS SkillFlare.
• Highly moderated to ensure completely safe, educational, and relevant outputs.
• Acts as a real-time guide to navigating tasks, finding mentors, or general platform query solving.

Platform Features

• 🔒 Secure Authorization: JWT-based robust authentication with distinct Role-Based Access Controls.
• 💬 Real-Time Communication: Live web sockets using Socket.io for instant messaging.
• 👨‍💻 Developer Hub: Easily explore the passionate student team building SkillFlare.
• 🌙 Dark-Mode First UI: A modernized, sleek, and glow-textured interface.
• 📱 Mobile Responsive: Fluid layout that operates gracefully on phones, tablets, and desktops.

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🛠️ Tech Stack

Frontend

• React 18 (Vite build system)
• Tailwind CSS (Custom theme presets and glassmorphic designs)
• React Router DOM v6
• Socket.IO-Client for real-time live chats
• Lucide React & React Icons for beautiful UI iconography
• Axios for API data fetching
• React Hot Toast for sleek user notifications

Backend

• Node.js & Express.js
• MongoDB & Mongoose for the database schema
• JWT (JSON Web Tokens) for security layers
• Bcrypt.js for password hashing and salting
• Socket.IO for event-driven asynchronous chat
• Ollama / Axios for LLM handling and prompt optimization
• Express Rate Limit & Helmet for robust web security

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🚀 Getting Started

Prerequisites

Make sure you have installed on your local environment:

• Node.js (v18 or higher)
• MongoDB (Local or Atlas instance)
• Ollama (Only necessary if you intend to run the Buddy AI local server capabilities)

General Installation

1. Clone the repository

   git clone https://github.com/KD2303/MITS-CampusSkill.git
   cd MITS-CampusSkill

2. Configure Backend

   cd backend
   npm install
   cp .env.example .env

   Update your .env to include:

   • MONGODB_URI - Your MongoDB connection string
   • JWT_SECRET - Secure random encryption string
   • OLLAMA_API_URL - Default: http://localhost:11434/api/generate (If utilizing Buddy AI)

3. Configure Frontend

   cd ../frontend
   npm install

Running the Application

1. Start MongoDB (if running a local DB)

   mongod

2. Start Backend Server

   cd backend
   npm run dev

   Backend defaults to: http://localhost:5000

3. Start Frontend Server

   cd frontend
   npm run dev

   Frontend defaults to: http://localhost:5173

(Note: Run ollama serve if you are using AI functionalities)

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📁 Project Structure

MITS-CampusSkill/
├── backend/
│   ├── src/
│   │   ├── config/       # Environment & Local DB mapping
│   │   ├── controllers/  # API business logic
│   │   ├── middleware/   # Custom Auth, Security & Upload middlewares
│   │   ├── models/       # Mongoose DB Schemas
│   │   ├── routes/       # Express route mapping
│   │   ├── services/     # Standalone services (e.g. AI Prompt logic)
│   │   ├── utils/        # Generic formatting tools
│   │   └── server.js     # Entry point
│   └── package.json
└── frontend/
    ├── public/           # Static assets, branding, vectors
    ├── src/
    │   ├── components/   # Reusable UI (Nav, Modals, AIChat)
    │   ├── context/      # React Context (Auth, Theme, Sockets)
    │   ├── hooks/        # Custom React Hooks
    │   ├── pages/        # Fully rendered React app routes
    │   ├── services/     # Axios API integrations
    │   ├── App.jsx       # Root Router Mapping
    │   └── main.jsx      # React DOM Render target
    ├── tailwind.config.js
    └── package.json

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📡 Essential Core Endpoints

Authentication

• POST /api/auth/register - Create An Account
• POST /api/auth/login - Authenticate & Retrieve Token
• GET /api/auth/me - Fetch Secure User Model

Tasks & Progression

• GET /api/tasks - Browse Available Tasks
• POST /api/tasks - Teacher Task Creation
• POST /api/tasks/:id/take - Student Accepting Task
• POST /api/tasks/:id/submit - Task Evaluation Submit

Buddy AI & Messaging

• POST /api/ai/chat - Interact with Platform's Assistant
• POST /api/chat/room - Private User-to-User Threading
• POST /api/chat/message - Live dispatch transmission

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⚙️ Configuration

Environment Variables

Backend (.env)

# Database
MONGODB_URI=mongodb://localhost:27017/skillflare

# Authentication
JWT_SECRET=your_secure_random_key_here

# AI & LLM
OLLAMA_API_URL=http://localhost:11434/api/generate
OLLAMA_MODEL=mistral

# Server
PORT=5000
NODE_ENV=development

Frontend

No additional environment configuration needed, connects to backend at http://localhost:5000

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🐳 Docker Deployment

# Build and run with Docker Compose
docker-compose up -d

# Check status
docker-compose ps

# View logs
docker-compose logs -f backend
docker-compose logs -f frontend

# Stop services
docker-compose down

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🧪 Testing

Unit & Integration Tests

cd backend
npm test

E2E Tests

cd frontend
npx playwright test

Load Testing

cd backend
k6 run tests/performance/load.test.js

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📊 API Response Format

All API responses follow this structure:

{
  "success": true,
  "data": { /* response data */ },
  "message": "Operation successful"
}

Error responses:

{
  "success": false,
  "error": "Error message",
  "statusCode": 400
}

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🔐 Security Features

• JWT Authentication: Role-based access control (Student, Mentor, Teacher, Admin)
• Password Security: Bcrypt hashing with salt rounds
• Input Sanitization: XSS protection via express-sanitize
• Rate Limiting: Prevents API abuse
• CORS: Configured to allow frontend requests only
• Helmet: HTTP headers security

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🎯 Key Features in Detail

Task Economy

• Teachers/Mentors post tasks with difficulty levels and credit rewards
• Students accept and complete tasks for portfolio building
• Peer-to-peer task support through real-time messaging
• Gamified leaderboard system tracking credit accumulation

Mentorship Program

• Application-based mentor onboarding
• Skill verification through coding profiles (GitHub, LeetCode, HackerRank)
• Dynamic availability management
• 1-on-1 mentorship tracking
• Mentor ratings and student testimonials

Buddy AI Assistant

• Context-aware responses about platform features
• Role-specific guidance (different for students, mentors, teachers)
• Academic integrity compliance
• Real-time chat interface
• Conversation history and analytics

Real-Time Features

• Socket.IO powered instant messaging
• Live notification system
• Real-time task status updates
• Active mentor/student presence detection

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📈 Project Status

• ✅ Database: MongoDB with Mongoose schemas
• ✅ Authentication: JWT-based with role model
• ✅ Real-time Chat: Socket.IO implementation complete
• ✅ AI Integration: Ollama-based Buddy AI deployed
• ✅ Frontend: React 18 with Vite build system
• ✅ Testing: 80%+ code coverage with automated tests
• ✅ Deployment: Docker & CI/CD ready
• ✅ Production: Ready for deployment (Score: 8.6/10)

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📋 Quick Commands Reference

# Development
npm run dev              # Start with hot reload

# Production
npm run build            # Build for production
npm start                # Run production build

# Testing
npm test                 # Run all tests
npm run test:watch       # Watch mode testing

# Database
npm run db:seed          # Seed sample data
npm run db:migrate       # Run migrations

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👨‍💻 Development Team

MITS SkillFlare Team:

• Project Mentor: Dr. Devesh Kumar Lal
• Full Stack: Krish Dargar
• Frontend: Sheetal Gourh
• Backend: Arin Gupta, Anurag Mishra, Vivek Chaurasiya
• QA & Testing: Ashish Garg

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📚 Additional Documentation

• ARCHITECTURE.md - System design and technical architecture
• QUICK_REFERENCE.md - Command reference card
• DEPLOYMENT_CHECKLIST.md - Production deployment guide
• TESTING_GUIDE.md - Testing procedures
• MONITORING_AND_ALERTING.md - Operations & monitoring setup

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🤝 Contributing

We welcome contributions! Please follow these steps:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/YourFeature)
3. Follow the code style guidelines
4. Commit your changes with clear messages
5. Push to the branch and open a Pull Request
6. Ensure all tests pass

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📄 License

This project is proprietary and licensed under PRIVATE license.

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Made with ❤️ by MITS Students for MITS Students.