🏥 AI Medical Symptom Checker

A modern full-stack medical application with React frontend and Flask backend that analyzes symptoms using AI and provides medical guidance. Features Gemini AI integration for intelligent medical conversations.

🚀 Features

• 🔍 Symptom Analysis - Advanced matching against medical database
• 🤖 AI Chat Assistant - Powered by Google Gemini AI
• 📚 Medical Database - Browse conditions and treatments
• 📱 Mobile Responsive - Works on all devices
• 🇮🇳 Indian Emergency Services - Complete contact information
• ⚡ Fast & Reliable - Separate deployments for optimal performance

🏗️ Architecture

┌─────────────────┐    API Calls    ┌─────────────────┐
│   React Frontend │ ◄──────────────► │   Flask Backend │
│   (Vercel)      │                 │   (Render)      │
│                 │                 │                 │
│ • UI Components │                 │ • API Endpoints │
│ • State Management│                │ • AI Integration│
│ • Routing       │                 │ • Data Processing│
└─────────────────┘                 └─────────────────┘

📁 Project Structure

├── 📁 backend/              # Flask API (Deploy to Render)
│   ├── api.py              # Main API server
│   ├── requirements.txt    # Python dependencies
│   ├── symptoms.csv        # Medical database
│   ├── .env               # Environment variables
│   └── render.yaml        # Render deployment config
├── 📁 frontend/            # React App (Deploy to Vercel)
│   ├── 📁 src/
│   │   ├── 📁 components/  # React components
│   │   ├── 📁 config/     # API configuration
│   │   └── App.js         # Main app
│   ├── 📁 public/         # Static files
│   ├── package.json       # Node dependencies
│   └── vercel.json        # Vercel deployment config
└── README.md              # This file

🚀 Quick Deployment

Option 1: Separate Deployment (Recommended)

Backend → Render.com:

1. Create Web Service on render.com
2. Connect GitHub, set root directory to backend
3. Build: pip install -r requirements.txt
4. Start: gunicorn -b 0.0.0.0:$PORT api:app
5. Add env var: GEMINI_API_KEY

Frontend → Vercel:

1. Import project on vercel.com
2. Set root directory to frontend
3. Add env var: REACT_APP_API_URL=https://your-backend-url
4. Deploy!

Option 2: Local Development

# Backend
cd backend
pip install -r requirements.txt
python api.py

# Frontend (new terminal)
cd frontend
npm install
npm start

🔑 Environment Setup

Backend (.env)

GEMINI_API_KEY=your_gemini_api_key_here

Frontend (Vercel)

REACT_APP_API_URL=https://your-backend-url.onrender.com

🎯 API Endpoints

Endpoint	Method	Description
/	GET	Health check
/analyze	POST	Analyze symptoms
/api/conditions	GET	Get all conditions
/api/gemini-chat	POST	AI chat
/api/stats	GET	Database stats

🌟 Key Benefits

✅ Separate Deployments - Better performance & reliability
✅ No Build Conflicts - Frontend & backend deploy independently
✅ Fast Loading - Optimized for each platform
✅ Easy Scaling - Scale components separately
✅ Professional Setup - Industry-standard architecture

🚨 Indian Emergency Services

• 108 - Advanced Medical Emergency
• 102 - Government Ambulance
• 104 - Medical Advice & Blood Bank
• 1097 - Pregnancy/Maternal Helpline
• 14567 - Senior Citizen Helpline
• 1800-599-0019 - Mental Health (KIRAN)

📖 Detailed Deployment Guide

See DEPLOYMENT-SEPARATE.md for complete step-by-step instructions.

⚠️ Medical Disclaimer

This application is for informational purposes only and should not replace professional medical advice. Always consult qualified healthcare providers for proper diagnosis and treatment.

🤝 Contributing

1. Fork the repository
2. Create feature branch
3. Make changes
4. Submit pull request

📄 License

MIT License - see LICENSE file for details.

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🎉 Ready to deploy your AI medical assistant!