SkinSenseAI 🌟

🚀 Your AI-Powered Skincare Companion

Personalized beauty solutions powered by cutting-edge AI technology

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📱 Product Screenshots

✨ Key Features

🔬 Smart Product Analysis

• Ingredient Scanner: Upload photos of product labels for instant AI analysis
• Suitability Score: Get personalized 1-10 compatibility ratings
• Allergen Detection: Identify potential skin irritants based on your profile
• Ingredient Breakdown: Detailed analysis of beneficial and concerning ingredients

🎯 Personalized Skin Assessment

• Comprehensive Quiz: Advanced skin type determination algorithm
• Custom Recommendations: Tailored advice based on your unique skin profile
• Progress Tracking: Monitor your skin journey over time
• Concern Analysis: Address specific skin issues with targeted solutions

🧠 AI-Powered Chat Assistant

• 24/7 Skincare Expert: Get instant answers to your skincare questions
• Contextual Advice: Personalized recommendations based on your skin profile
• Product Suggestions: Smart recommendations for your specific needs
• Memory Integration: AI remembers your history for better advice

📊 Skin Memory System

• Issue Tracking: Monitor skin problems and their progress
• Allergen Database: Personal record of ingredients to avoid
• Analysis History: Complete log of all product analyses
• Trend Analysis: Identify patterns in your skin's responses

🔐 Secure & Private

• End-to-End Encryption: Your data is always protected
• GDPR Compliant: Full control over your personal information
• Offline Mode: Core features work without internet connection
• Data Export: Download your complete skincare history

🛠️ Technology Stack

Frontend (React Native)

// Core Technologies
React Native 0.72
Expo SDK 49
TypeScript
NativeWind (Tailwind CSS)

// State Management & Navigation
React Navigation 6
AsyncStorage
Context API

// UI/UX Libraries
Expo Linear Gradient
React Native Reanimated
Lottie React Native

Backend (FastAPI)

# API Framework
FastAPI 0.104
SQLAlchemy ORM
Alembic Migrations
Pydantic Validation

# AI & ML Integration
Google Gemini AI
OpenAI GPT Integration
Image Processing
Natural Language Processing

# Database & Storage
PostgreSQL
Redis Cache
Supabase Storage

DevOps & Infrastructure

# Deployment
Docker Containers
GitHub Actions CI/CD
Azure Cloud Services

# Monitoring & Analytics
Sentry Error Tracking
Analytics Dashboard
Performance Monitoring

🚀 Quick Start

Prerequisites

• Node.js 18+
• Python 3.12+
• Expo CLI
• Android Studio / Xcode

1. Clone the Repository

git clone https://github.com/yourusername/skinsenseai.git
cd skinsenseai

2. Backend Setup

# Navigate to backend directory
cd fastapi-backend

# Create virtual environment
python -m venv myvenv
myvenv\Scripts\activate  # On Windows

# Install dependencies
pip install -r requirements.txt

# Set up environment variables
cp .env.example .env
# Edit .env with your API keys and database config

# Run database migrations
alembic upgrade head

# Start the server
uvicorn main:app --host 0.0.0.0 --port 8000 --reload

3. Frontend Setup

# Navigate to frontend directory
cd SkinSenseAI

# Install dependencies
npm install

# Set up environment variables
cp .env.example .env
# Edit .env with your backend URL and API keys

# Start the development server
npm start

4. Mobile App Testing

# For iOS (requires Xcode)
npx expo run:ios

# For Android (requires Android Studio)
npx expo run:android

# Or scan QR code with Expo Go app

📁 Project Structure

skinsenseai/
├── 📱 SkinSenseAI/                 # React Native Frontend
│   ├── 🎨 src/
│   │   ├── components/             # Reusable UI components
│   │   ├── screens/               # App screens
│   │   ├── services/              # API services
│   │   ├── contexts/              # React contexts
│   │   └── utils/                 # Utility functions
│   ├── 🎯 assets/                 # Images, fonts, etc.
│   └── 📋 package.json
├── 🖥️ fastapi-backend/            # FastAPI Backend
│   ├── 🔧 app/
│   │   ├── api/                   # API endpoints
│   │   ├── models/                # Database models
│   │   ├── services/              # Business logic
│   │   └── core/                  # Core configurations
│   ├── 🗄️ alembic/               # Database migrations
│   └── 📋 requirements.txt
└── 📚 docs/                       # Documentation

🎨 Design System

Color Palette

/* Primary Colors */
--primary-cyan: #00f5ff
--primary-blue: #0080ff
--primary-purple: #8000ff

/* Status Colors */
--success: #00ff88
--warning: #ffaa00
--error: #ff4444
--info: #00f5ff

/* Neutral Colors */
--background: #000000
--surface: #1a1a1a
--text-primary: #ffffff
--text-secondary: #888888

Typography

• Headers: SF Pro Display / Roboto
• Body: SF Pro Text / Roboto
• Code: SF Mono / Roboto Mono

📊 API Documentation

Core Endpoints

Authentication

POST /api/v1/auth/register
POST /api/v1/auth/login
POST /api/v1/auth/refresh
DELETE /api/v1/auth/logout

Product Analysis

POST /api/v1/products/analyze
GET /api/v1/products/history
GET /api/v1/products/{id}

Skin Profile

POST /api/v1/skin/assessment
GET /api/v1/skin/profile
PUT /api/v1/skin/profile

AI Chat

POST /api/v1/chat/sessions
GET /api/v1/chat/sessions
POST /api/v1/chat/{session_id}/messages

Response Format

{
  "success": true,
  "data": {
    "product_name": "Sample Product",
    "suitability_score": 8,
    "analysis_result": {
      "beneficial_ingredients": ["Niacinamide", "Hyaluronic Acid"],
      "concerning_ingredients": ["Fragrance"],
      "recommendation": "Suitable for your skin type"
    }
  },
  "message": "Analysis completed successfully"
}

🚀 Deployment

Frontend Deployment (Expo)

# Build for production
eas build --platform all

# Submit to app stores
eas submit --platform all

Backend Deployment (FastAPI)

-Its deployed on Azure App Service

📈 Performance Metrics

• App Launch Time: < 2 seconds
• Image Analysis: < 5 seconds
• API Response Time: < 500ms
• Offline Capability: 80% of features
• Cross-Platform: iOS & Android

🤝 Contributing

We welcome contributions! Please see our Contributing Guide for details.

Development Workflow

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

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

🙏 Acknowledgments

• Google Gemini AI for powerful image analysis
• Expo Team for excellent React Native tools
• FastAPI for the amazing Python framework
• Open Source Community for inspiration and support

📞 Support & Contact

Need Help?

🐛 Bug Reports: GitHub Issues

📚 Documentation: docs.skinsenseai.com

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Made with ❤️ by the SkinSenseAI Team

© 2025 SkinSenseAI. All rights reserved.