PMAi is a comprehensive healthcare application that combines AI-powered symptom analysis, personalized diet recommendations, medication management, and health tracking. Built with modern web technologies and powered by Google's Gemini AI.

• Symptom Analysis: Get instant insights about health symptoms with AI-powered analysis
• Diet Recommendations: Personalized nutrition advice based on health goals and restrictions
• Meal Planning: Complete meal plans with calorie targets and dietary preferences
• AI Chat: Interactive health conversations with context awareness

• Authentication: Secure login/signup with JWT tokens
• Google OAuth: One-click login with Google accounts
• Face Recognition: Biometric authentication using facial recognition
• Profile Management: Comprehensive health profiles with medical history

• Medication Management: Track medications, dosages, and schedules
• Symptom Logging: Record and monitor health symptoms
• Health Statistics: Comprehensive health metrics and insights
• Diet Plans: Save and manage personalized nutrition plans

• Rate Limiting: Protected against API abuse
• Input Validation: Robust error handling and data validation
• CORS Configuration: Secure cross-origin resource sharing
• Compression: Optimized response times

• React 18 with TypeScript
• Vite for fast development and building
• Tailwind CSS for modern, responsive design
• React Router for navigation
• Axios for API communication

• Node.js with Express.js
• MongoDB with Mongoose ODM
• Google Gemini AI for intelligent responses
• JWT for authentication
• Passport.js for OAuth strategies
• Multer for file uploads
• Rate Limiting for API protection

• Google Generative AI (Gemini 2.0 Flash)
• Custom AI Prompts for healthcare and nutrition
• Context-Aware Responses with conversation history
• Personalized Recommendations based on user profiles

PMAi/
├── backend/                 # Backend server
│   ├── config/             # Configuration files
│   ├── controllers/        # Route controllers
│   ├── middleware/         # Custom middleware
│   ├── models/             # Database models
│   ├── routes/             # API routes
│   ├── services/           # Business logic & AI services
│   ├── utils/              # Utility functions
│   └── uploads/            # File upload directory
├── src/                    # Frontend source code
│   ├── components/         # React components
│   ├── contexts/           # React contexts
│   ├── hooks/              # Custom React hooks
│   ├── pages/              # Page components
│   ├── types/              # TypeScript type definitions
│   └── utils/              # Utility functions
└── docs/                   # Documentation

• POST /auth/google - Google OAuth client-side authentication
• GET /auth/google - Google OAuth server-side flow
• GET /auth/google/callback - Google OAuth callback
• POST /auth/logout - User logout
• GET /auth/status - Authentication status check
• GET /auth/face-status - Face registration status
• POST /auth/register-face - Face registration
• POST /auth/login-face - Face authentication
• POST /auth/identify-face - Face identification

• POST /users/register - User registration
• POST /users/login - User login
• GET /users/profile - Get user profile
• PUT /users/profile - Update user profile
• POST /users/upload-avatar - Profile picture upload
• DELETE /users/account - Delete user account

• POST /api/ai/analyze-symptoms - Symptom analysis with AI
• POST /api/ai/diet-recommendations - Personalized diet advice
• POST /api/ai/chat - AI-powered health conversations
• POST /api/ai/meal-plan - Complete meal planning
• GET /api/ai/health - AI service health check

• GET /api/medications - Get user medications
• POST /api/medications - Add new medication
• PUT /api/medications/:id - Update medication
• DELETE /api/medications/:id - Delete medication
• PATCH /api/medications/:id/taken - Mark medication as taken

• GET /api/health/symptoms - Get user symptoms
• POST /api/health/symptoms - Add new symptom
• GET /api/health/stats - Health statistics
• GET /api/health/diet-plans - Get saved diet plans
• POST /api/health/diet-plans - Save new diet plan

• GET /health - Server health check
• POST /debug - Debug endpoint for testing

• Node.js 18+ and npm
• MongoDB instance
• Google Cloud account (for Gemini AI)
• Google OAuth credentials (optional)

1. Clone the repository

   git clone <repository-url>
   cd PMAi/backend

2. Install dependencies

   npm install

3. Environment Configuration Create a .env file in the backend directory:

   # Server Configuration
   PORT=5001
   NODE_ENV=development
   
   # MongoDB Configuration
   MONGODB_URI=mongodb://localhost:27017/PMAi
   
   # JWT Configuration
   JWT_SECRET=your-super-secret-jwt-key-here
   
   # Session Configuration
   SESSION_SECRET=your-session-secret-key-here
   
   # Google OAuth Configuration
   GOOGLE_CLIENT_ID=your-google-client-id
   GOOGLE_CLIENT_SECRET=your-google-client-secret
   GOOGLE_CALLBACK_URL=http://localhost:5001/auth/google/callback
   
   # Frontend URL
   FRONTEND_URL=http://localhost:5173
   
   # Google AI Configuration
   GEMINI_API_KEY=your-gemini-api-key
   
   # Bcrypt Configuration
   BCRYPT_ROUNDS=12

4. Start the server

   # Development mode
   npm run dev
   
   # Production mode
   npm start

1. Navigate to frontend directory

   cd ../src

2. Install dependencies

   npm install

3. Start development server

   npm run dev

The AI service uses carefully crafted prompts for optimal responses:

• Health Assistant: Medical guidance with safety disclaimers
• Diet Planner: Nutritional advice with personalization
• Meal Planner: Structured meal plans with nutritional balance

• Content filtering and safety settings
• Medical consultation recommendations
• Allergy and dietary restriction awareness
• Rate limiting to prevent abuse

• JWT Authentication with secure token handling
• Rate Limiting for all API endpoints
• Input Validation with comprehensive error handling
• CORS Configuration for secure cross-origin requests
• Helmet.js for security headers
• File Upload Validation with size and type restrictions

• Response Compression for faster data transfer
• MongoDB Indexing for optimized queries
• Rate Limiting to maintain service quality
• Error Handling with graceful fallbacks
• Logging with Morgan for monitoring

cd backend
npm test

Use tools like Postman or curl to test endpoints:

# Health check
curl http://localhost:5001/health

# Test AI endpoint
curl -X POST http://localhost:5001/api/ai/analyze-symptoms \
  -H "Content-Type: application/json" \
  -d '{"symptoms": ["headache", "fatigue"]}'

1. Set environment variables for production
2. Use PM2 or similar process manager
3. Configure MongoDB Atlas for production database
4. Set up proper CORS origins

1. Build the project: npm run build
2. Deploy to Vercel, Netlify, or similar platforms
3. Update API base URL in environment variables

All API endpoints follow a consistent format:

Success Response:

{
  "success": true,
  "data": {...},
  "message": "Operation successful"
}

Error Response:

{
  "error": "Error type",
  "message": "Detailed error message",
  "success": false
}

Most endpoints require JWT authentication:

Authorization: Bearer <your-jwt-token>

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

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

For support and questions:

• Create an issue in the repository
• Check the documentation
• Review the API endpoints

AI Service 500 Errors: If you're getting 500 errors on AI endpoints, check the Troubleshooting Guide for solutions.

Quick Fix: Most AI issues are resolved by setting the correct GEMINI_API_KEY environment variable.

• API Documentation - Complete API reference
• Setup Guide - Installation and deployment
• Troubleshooting Guide - Common issues and solutions

• ✅ Complete API endpoint implementation
• ✅ Enhanced AI prompts for better responses
• ✅ Comprehensive security features
• ✅ File upload system with validation
• ✅ Rate limiting and abuse protection
• ✅ Input validation and error handling
• ✅ Medication and health tracking APIs
• ✅ Face recognition authentication
• ✅ Google OAuth integration

PMAi - Empowering healthcare with AI technology 🚀