A microservices-based wellness platform integrating fitness tracking, nutrition planning, restaurant discovery, and skin/hair analysis.

WellBeing uses a microservices architecture with 4 independent modules sharing JWT authentication:

What_Now/
├── base/                       # Main app (port 3000)
│   ├── Authentication system (JWT)
│   ├── Fitness tracker with MediaPipe Pose
│   ├── User profile management
│   └── Homepage with feature carousel
├── skin-hair-analysis/         # Port 3002
│   ├── Skin condition analysis
│   ├── Hair health tracking
│   └── Product recommendations
├── nutrition-wellness/         # Port 3003
│   ├── Pantry meal planner
│   ├── Recipe optimization
│   └── Wellness insights
├── nutrition-yelp/
│   ├── backend/                # Port 3001 (API)
│   └── frontend/               # Port 3004
│       ├── Restaurant search (Yelp API)
│       ├── AI health scoring
│       └── Food photo scanning
└── docs/                       # Documentation

1. Authentication System

• User registration and login
• JWT token-based auth across all microservices
• HttpOnly cookies for security
• Password hashing with bcrypt

2. Physical Fitness Tracker

• Real-time pose detection with MediaPipe
• Bicep curls and lateral raises analysis
• Form validation (posture, arm position, leg straightness)
• Voice feedback with priority queue
• Rep counting with strict validation
• Session history storage

3. Skin & Hair Analysis

• Image upload for analysis
• AI-powered condition scoring
• Product recommendations
• Loved products tracking
• Wellness insights

4. Nutrition Wellness

• Pantry-based meal generation
• Authentic dish optimization
• Recipe library with search/filters
• Custom recipe creation
• Session-based wellness insights (15-min tracking)

5. Find Restaurants

• Yelp restaurant search by location/category/price
• AI health scoring (Gemini-powered)
• Food photo scanning for nutrition
• Favorite restaurants tracking
• Automatic dining preference insights

6. User Profile Management

• Extended profile fields (DOB, height, weight, lifestyle)
• Mobile-responsive grid layout
• Separate storage for extended data

See docs/HOW_TO_RUN.md for detailed instructions.

# Terminal 1: Base App
cd base && npm run dev                              # Port 3000

# Terminal 2: Skin-Hair Analysis
cd skin-hair-analysis && npm run dev                # Port 3002

# Terminal 3: Nutrition Wellness
cd nutrition-wellness && npm run dev                # Port 3003

# Terminal 4: Restaurant Backend
cd nutrition-yelp/backend && npm run dev            # Port 3001

# Terminal 5: Restaurant Frontend
cd nutrition-yelp/frontend && npm run dev           # Port 3004

Open http://localhost:3000 in your browser.

Each microservice needs a .env.local file. Important: All must share the same JWT_SECRET.

MONGODB_URI=your_mongodb_connection
MONGODB_DB=wellbeing_app
GEMINI_API_KEY=your_gemini_key
JWT_SECRET=your_shared_secret
JWT_EXPIRES_IN=7d

Copy the same JWT_SECRET to:

• skin-hair-analysis/.env.local
• nutrition-wellness/.env.local
• nutrition-yelp/frontend/.env.local

See docs/HOW_TO_RUN.md for complete environment variable documentation.

• Frontend: Next.js 14, React, TypeScript
• Styling: Tailwind CSS (custom doom theme)
• Database: MongoDB (Cloud or Local)
• Authentication: JWT with httpOnly cookies
• AI: Google Gemini API
• Pose Detection: MediaPipe Pose (WebAssembly)
• Voice: Web Speech API
• External APIs: Yelp Fusion API

Authentication (MongoDB: wellbeing_app)

• users - Email, password, name, timestamps
• userProfiles - Extended profile data (DOB, height, weight, lifestyle)

Fitness (MongoDB: wellbeing_app)

• sessions - Exercise session data with form scores

Skin-Hair (MongoDB: skin_hair)

• profiles - Skin/hair type and concerns
• analyses - Analysis results
• loved_products - Favorited products
• recommendations - AI-generated recommendations

Nutrition Wellness (MongoDB: wellbeing_app)

• nutrition_profiles - Dietary preferences
• nutrition_recipes - Generated and custom recipes
• nutrition_pantry_items - Saved ingredients
• nutrition_insight_sessions - Activity tracking
• nutrition_insight_memory - AI insights

Restaurant Finder (MongoDB: via backend)

• favorites - Liked restaurants
• clicks - Activity tracking
• yelp-insights - Dining preference insights

1. User logs in at base app (localhost:3000)
2. JWT token stored in httpOnly cookie
3. All microservices verify token automatically
4. Shared JWT_SECRET enables cross-service auth
5. Single logout clears token everywhere

All microservices share a consistent navigation bar:

• Home
• Physical Fitness
• Nutrition
• Find Restaurants
• Skin & Hair Analysis
• Profile (user information)
• Logout

See docs/ folder for:

• HOW_TO_RUN.md - Complete setup guide
• SESSION_NOTES.md - Detailed implementation notes
• Additional architecture and API documentation

Port conflicts: Kill process with lsof -ti:PORT | xargs kill -9

JWT auth fails: Verify all .env.local files have identical JWT_SECRET

MongoDB connection: Check URI and network connectivity

Module errors: Run npm install and restart with rm -rf .next && npm run dev

Repository: github.com:charithcherry/NowWhat.git

Last Updated: March 8, 2026