🚀 HackTrack

AI-Powered Hackathon Discovery & Team Formation Platform

🌐 Live Demo • 📖 Deployment Guide • 🔗 Backend API • 🤖 AI Service

🎯 Discover • Connect • Build • Win

The ultimate platform for hackathon enthusiasts to find events, form dream teams, and build award-winning projects

🌟 Live Deployment

🎨 Frontend

hacktrack-frontend.vercel.app

_{Deployed on Vercel}

_{✅ Auto-deploys from main branch}

⚙️ Backend

hacktrack-server-674s.onrender.com

_{Deployed on Render}

_{Auto-deploys from main branch}

🤖 AI Service

hacktrack-embedding.onrender.com

_{Deployed on Render}

_{✅ Sentence-Transformers}

✨ Key Features

🎪 For Participants

🔍 500+ Hackathons - Real-time aggregation from Devpost, MLH, and Clist
🏷️ Smart Status Labels - See ONGOING, UPCOMING, or FINISHED at a glance
🤖 AI Teammate Matching - Sentence-transformers powered recommendations (384-dim embeddings)
💬 Real-time Chat - Socket.io for instant team communication
📚 Smart Bookmarks - Save and organize favorite events
🔍 Advanced Filters - Filter by platform, status, location, timeframe, and more
📊 Personal Dashboard - Track your hackathon journey
🏆 Portfolio Building - Showcase your achievements

🎯 For Organizers

📅 Event Management - Create and manage hackathons
📈 Analytics Dashboard - Track engagement and registrations
👥 Participant Management - Review submissions and teams
📢 Promotion Tools - Reach thousands of developers
💼 Professional Profile - Build your organizer brand

🎨 How It Works

Event Discovery

Real-time Aggregation: Backend fetches events from multiple sources every 6 hours
Smart Caching: Events are cached to reduce API load and improve performance
Status Calculation: Real-time calculation of event status (ongoing/upcoming/finished)
Advanced Filtering: 7 filter categories with instant results
Pagination: Smooth pagination with 24/48/96 events per page

Event Status System

Events are automatically labeled based on their dates:

🟢 ONGOING - Event has started but not ended (with pulse animation)
🔵 UPCOMING - Event hasn't started yet
🔴 FINISHED - Event has ended

AI Teammate Matching

Profile Embedding: User profiles are converted to 384-dimensional vectors using sentence-transformers
Similarity Calculation: Cosine similarity computed between user embeddings
Smart Filtering: Results filtered by location, college, skills, graduation year
Ranking: Top 15 matches returned based on similarity score
Real-time Updates: Recommendations update as profiles change

Real-time Chat

Socket.io Connection: Persistent WebSocket connection for instant messaging
Room-based Chat: Each team/event has its own chat room
Message History: All messages stored in MongoDB
Typing Indicators: See when teammates are typing
Online Status: See who's currently online

🏗️ Tech Stack

Frontend

React 18 - UI library with hooks
Vite 5 - Lightning-fast build tool
TailwindCSS 3 - Utility-first CSS framework
shadcn/ui - Beautiful component library
React Router 6 - Client-side routing
Axios - HTTP client with interceptors
Socket.io Client - Real-time communication

Backend

Node.js 18 - JavaScript runtime
Express 4 - Web framework
MongoDB Atlas - Cloud database (M0 free tier)
Mongoose 8 - MongoDB ODM
Passport.js - Authentication middleware
- Google OAuth 2.0
- GitHub OAuth
- LinkedIn OAuth
JWT - Token-based authentication
Socket.io - WebSocket server
Express Session - Session management with MongoDB store
Bcrypt - Password hashing
Helmet - Security headers
CORS - Cross-origin resource sharing

AI Service

Python 3.12.8 - Latest stable Python
Flask 3 - Lightweight web framework
Sentence-Transformers 3.3 - State-of-the-art embeddings
- Model: all-MiniLM-L6-v2
- Dimensions: 384
- Speed: ~50ms per embedding
PyTorch 2.5 - ML framework (CPU-only for efficiency)
NumPy 2.2 - Numerical computing
Flask-CORS - CORS support

Event Sources

Clist API v4 - Programming contests and competitions
Devpost API - Hackathon platform
MLH API - Major League Hacking events
Custom Events - User-created hackathons

🚀 Quick Start

Prerequisites

✅ Node.js 18+ (LTS recommended)
✅ MongoDB (local or Atlas account)
✅ Python 3.12+ (for AI features)
✅ Git

Installation

# 1. Clone repository
git clone https://github.com/satvik-sharma-05/SE.git
cd SE

# 2. Install backend dependencies
cd server
npm install

# 3. Install frontend dependencies
cd ../client
npm install

# 4. Install AI service dependencies
cd ../embedding-service
pip install -r requirements.txt

Configuration

Backend - Create server/.env:

# Database
MONGO_URI=mongodb://localhost:27017/hacktrack
# Or use MongoDB Atlas:
# MONGO_URI=mongodb+srv://username:password@cluster.mongodb.net/HackTrack

# Authentication
JWT_SECRET=your_super_secret_jwt_key_min_32_chars_long
SESSION_SECRET=your_session_secret_key_also_32_chars

# Service URLs
FRONTEND_URL=http://localhost:5173
EMBEDDING_URL=http://localhost:5002

# OAuth (Optional - for social login)
GOOGLE_CLIENT_ID=your_google_client_id
GOOGLE_CLIENT_SECRET=your_google_client_secret
GOOGLE_CALLBACK_URL=http://localhost:5000/api/auth/google/callback

GITHUB_CLIENT_ID=your_github_client_id
GITHUB_CLIENT_SECRET=your_github_client_secret
GITHUB_CALLBACK_URL=http://localhost:5000/api/auth/github/callback

LINKEDIN_CLIENT_ID=your_linkedin_client_id
LINKEDIN_CLIENT_SECRET=your_linkedin_client_secret
LINKEDIN_CALLBACK_URL=http://localhost:5000/api/auth/linkedin/callback

# Event Sources (Required for event aggregation)
CLIST_USERNAME=your_clist_username
CLIST_API_KEY=your_clist_api_key

# Email (Optional - for password reset)
EMAIL_USER=your_email@gmail.com
EMAIL_PASS=your_app_password

# Environment
NODE_ENV=development
PORT=5000

Frontend - Create client/.env:

VITE_API_BASE_URL=http://localhost:5000/api

Run Development

# Terminal 1 - AI Service (Port 5002)
cd embedding-service
python app.py

# Terminal 2 - Backend (Port 5000)
cd server
npm run dev

# Terminal 3 - Frontend (Port 5173)
cd client
npm run dev

Visit http://localhost:5173 🎉

📁 Project Structure

hacktrack/
├── client/                    # React frontend
│   ├── public/               # Static assets
│   ├── src/
│   │   ├── api/              # API clients
│   │   ├── components/       # React components
│   │   │   ├── events/       # Event-related components
│   │   │   ├── layout/       # Layout components
│   │   │   └── ui/           # Reusable UI components
│   │   ├── context/          # React context (Auth)
│   │   ├── pages/            # Page components (30+)
│   │   ├── services/         # API services
│   │   └── utils/            # Utility functions
│   ├── .env                  # Environment variables
│   ├── .env.production       # Production env vars
│   └── package.json
│
├── server/                    # Node.js backend
│   ├── data/                 # Cache files
│   ├── src/
│   │   ├── cache/            # API cache
│   │   ├── config/           # Configuration
│   │   │   ├── db.js         # MongoDB connection
│   │   │   ├── passport.js   # OAuth strategies
│   │   │   └── env.js        # Environment config
│   │   ├── controllers/      # Business logic
│   │   │   ├── auth.controller.js
│   │   │   ├── events.controller.js
│   │   │   └── user.controller.js
│   │   ├── middleware/       # Express middleware
│   │   │   ├── auth.js       # JWT authentication
│   │   │   ├── rateLimiter.js # Rate limiting
│   │   │   └── validation.js  # Input validation
│   │   ├── models/           # MongoDB schemas
│   │   │   ├── User.js
│   │   │   ├── Event.js
│   │   │   ├── Chat.js
│   │   │   └── Message.js
│   │   ├── routes/           # API routes
│   │   ├── services/         # External API services
│   │   │   ├── clist.js      # Clist API
│   │   │   ├── devpost.service.js # Devpost API
│   │   │   └── mlhService.js  # MLH API
│   │   └── utils/            # Utility functions
│   ├── .env                  # Environment variables (gitignored)
│   ├── .env.example          # Example env file
│   └── package.json
│
├── embedding-service/         # Python AI service
│   ├── app.py                # Flask application
│   ├── requirements.txt      # Python dependencies
│   └── runtime.txt           # Python version
│
├── README.md                 # This file
├── DEPLOY.md                 # Deployment guide
└── CHANGES.md                # Recent changes log

🎯 API Endpoints

Authentication

POST   /api/auth/register          # Register new user
POST   /api/auth/login             # Login with email/password
GET    /api/auth/logout            # Logout user
GET    /api/auth/me                # Get current user
GET    /api/auth/google            # Google OAuth login
GET    /api/auth/github            # GitHub OAuth login
GET    /api/auth/linkedin          # LinkedIn OAuth login
POST   /api/auth/forgot-password   # Request password reset
POST   /api/auth/reset-password    # Reset password with token

Events

GET    /api/events/live            # Get live events (all sources)
GET    /api/events/mlh             # Get MLH events only
GET    /api/events/devpost         # Get Devpost events only
GET    /api/events/:id             # Get event by ID
POST   /api/events/:id/bookmark    # Toggle bookmark
GET    /api/events/me/bookmarks    # Get user's bookmarks
GET    /api/events/statistics      # Get event statistics

AI Teammates

POST   /api/teammates/find         # Search teammates with AI
POST   /api/teammates/recommend    # Get AI recommendations
GET    /api/teammates/form-teams   # Auto team formation

Users

GET    /api/users/profile          # Get current user profile
PUT    /api/users/profile          # Update profile
GET    /api/users/:id              # Get public user profile

Chat

GET    /api/chats                  # Get user's chats
POST   /api/chats                  # Create new chat
GET    /api/chats/:id/messages     # Get chat messages
POST   /api/chats/:id/messages     # Send message

Health

GET    /api/health                 # Backend health check
GET    /health                     # AI service health check

🚀 Deployment

Production URLs

Frontend: https://hacktrack-frontend.vercel.app
Backend: https://hacktrack-server-674s.onrender.com/api
AI Service: https://hacktrack-embedding.onrender.com

Deployment Process

All services auto-deploy on push to main branch:

git add .
git commit -m "your changes"
git push origin main

Deployment Times:

Frontend (Vercel): 1-2 minutes
Backend (Render): 2-3 minutes
AI Service (Render): 2-3 minutes

Environment Variables (Production)

Render Dashboard → hacktrack-server-674s → Environment:

# Required
MONGO_URI=mongodb+srv://username:password@cluster.mongodb.net/HackTrack
JWT_SECRET=your_production_jwt_secret
SESSION_SECRET=your_production_session_secret
EMBEDDING_URL=https://hacktrack-embedding.onrender.com
FRONTEND_URL=https://hacktrack-frontend.vercel.app

# OAuth Callbacks
GOOGLE_CALLBACK_URL=https://hacktrack-server-674s.onrender.com/api/auth/google/callback
GITHUB_CALLBACK_URL=https://hacktrack-server-674s.onrender.com/api/auth/github/callback
LINKEDIN_CALLBACK_URL=https://hacktrack-server-674s.onrender.com/api/auth/linkedin/callback

# Event Sources
CLIST_USERNAME=your_username
CLIST_API_KEY=your_api_key

# Environment
NODE_ENV=production

Vercel Dashboard → hacktrack-frontend → Settings → Environment Variables:

VITE_API_BASE_URL=https://hacktrack-server-674s.onrender.com/api

See DEPLOY.md for detailed deployment instructions and troubleshooting.

🤖 AI Features Deep Dive

Sentence-Transformers Model

We use all-MiniLM-L6-v2 for high-quality embeddings:

Model Size: 80MB (lightweight)
Dimensions: 384 (compact yet powerful)
Speed: ~50ms per embedding on CPU
Quality: State-of-the-art semantic similarity
No GPU Required: Optimized for CPU inference

How Teammate Matching Works

Profile Embedding Generation:

# Combine user data
profile_text = f"{bio} {skills} {interests} {domain}"

# Generate embedding
embedding = model.encode(profile_text)  # 384-dim vector

Similarity Calculation:

# Cosine similarity
similarity = dot(vec1, vec2) / (norm(vec1) * norm(vec2))

Filtering & Ranking:
- Filter by location, college, graduation year
- Sort by similarity score (0-1)
- Return top 15 matches
Real-time Updates:
- Embeddings regenerated when profile changes
- Background job updates all embeddings nightly

API Endpoints

# Generate embedding
POST /embed
{
  "text": "Full-stack developer interested in AI and blockchain"
}
# Returns: {"embedding": [0.123, -0.456, ...]}  # 384 numbers

# Calculate similarity
POST /similarity
{
  "vec1": [0.123, ...],
  "vec2": [0.456, ...]
}
# Returns: {"similarity": 0.87}  # 0-1 score

📊 Performance & Optimization

Backend Performance

API Response Time: < 100ms average
Event Caching: 6-hour cache reduces API calls by 95%
Database Queries: Indexed for fast lookups
Rate Limiting: Prevents abuse and ensures fair usage
Compression: Gzip compression reduces payload size by 70%

Frontend Performance

Page Load: < 1.5s on 3G
Code Splitting: Lazy loading reduces initial bundle
Image Optimization: WebP format with fallbacks
Caching: Service worker caches static assets
Pagination: Only loads 24 events at a time

AI Service Performance

Inference Time: < 500ms per request
Memory Usage: ~150MB
Concurrent Requests: Handles 10+ simultaneous requests
Cold Start: < 5s (Render free tier)

Caching Strategy

Event Sources → 6-hour cache → Background refresh
User Profiles → Real-time → Nightly embedding update
Static Assets → CDN → Browser cache
API Responses → Redis (future) → Client cache

🔒 Security Features

✅ JWT Authentication: Secure token-based auth
✅ Password Hashing: Bcrypt with salt rounds
✅ HTTPS Only: All production traffic encrypted
✅ CORS Protection: Whitelist of allowed origins
✅ Rate Limiting: Prevents brute force attacks
✅ Input Validation: Sanitizes all user input
✅ SQL Injection Protection: MongoDB prevents SQL injection
✅ XSS Protection: React escapes all output
✅ CSRF Protection: SameSite cookies
✅ Helmet.js: Security headers
✅ Session Security: Encrypted session store

🤝 Contributing

Contributions are welcome! Here's how:

Fork the repository
Create a feature branch:
```
git checkout -b feature/AmazingFeature
```
Commit your changes:
```
git commit -m 'Add some AmazingFeature'
```
Push to the branch:
```
git push origin feature/AmazingFeature
```
Open a Pull Request

Development Guidelines

Follow existing code style
Write meaningful commit messages
Add tests for new features
Update documentation
Ensure all tests pass

📜 License

This project is licensed under the MIT License - see LICENSE file for details.

🙏 Acknowledgments

Clist API - Programming contest aggregation
Devpost - Hackathon platform and API
MLH - Major League Hacking events
Shadcn/ui - Beautiful component library
Vercel - Frontend hosting
Render - Backend and AI service hosting
MongoDB Atlas - Database hosting
Sentence-Transformers - State-of-the-art embeddings
Hugging Face - Model hosting

📞 Contact & Support

Developer: Satvik Sharma

GitHub: @satvik-sharma-05

Repository: https://github.com/satvik-sharma-05/SE

Issues: Report a bug

Discussions: Ask a question

📈 Project Stats

🗺️ Roadmap

Current Features ✅

Upcoming Features 🚧

💖 Support the Project

If you find HackTrack helpful, please consider:

⭐ Starring the repository

🐛 Reporting bugs and issues

💡 Suggesting new features

🤝 Contributing code

📢 Sharing with friends

⭐ Star History

Made with ❤️ by developers, for developers

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Name		Name	Last commit message	Last commit date
Latest commit History 59 Commits
.github/workflows		.github/workflows
.vscode		.vscode
client		client
embedding-service		embedding-service
server		server
.gitignore		.gitignore
.nvmrc		.nvmrc
CHANGES.md		CHANGES.md
DEPLOY.md		DEPLOY.md
README.md		README.md
render.yaml		render.yaml

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🚀 HackTrack

AI-Powered Hackathon Discovery & Team Formation Platform

🎯 Discover • Connect • Build • Win

🌟 Live Deployment

🎨 Frontend

⚙️ Backend

🤖 AI Service

✨ Key Features

🎪 For Participants

🎯 For Organizers

🎨 How It Works

Event Discovery

Event Status System

AI Teammate Matching

Real-time Chat

🏗️ Tech Stack

Frontend

Backend

AI Service

Event Sources

🚀 Quick Start

Prerequisites

Installation

Configuration

Run Development

📁 Project Structure

🎯 API Endpoints

Authentication

Events

AI Teammates

Users

Chat

Health

🚀 Deployment

Production URLs

Deployment Process

Environment Variables (Production)

🤖 AI Features Deep Dive

Sentence-Transformers Model

How Teammate Matching Works

API Endpoints

📊 Performance & Optimization

Backend Performance

Frontend Performance

AI Service Performance

Caching Strategy

🔒 Security Features

🤝 Contributing

Development Guidelines

📜 License

🙏 Acknowledgments

📞 Contact & Support

📈 Project Stats

🗺️ Roadmap

Current Features ✅

Upcoming Features 🚧

💖 Support the Project

⭐ Star History

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