A Flutter application that helps users track their nutritional intake by analyzing food product labels and meals using AI, built with clean MVVM architecture.

• 📸 Scan product labels and food items using your device's camera
• 🔍 AI-powered nutrition analysis using Google's Gemini API
• 📊 Track daily nutrient intake with detailed breakdowns
• 📅 View historical food consumption data
• 📈 Visual representations of macronutrient distribution
• ⚡ Real-time nutritional insights and recommendations
• 🧩 Built with MVVM architecture for clean, maintainable code
• 🔄 Provider for robust state management

Food Scan AI follows the MVVM (Model-View-ViewModel) architecture pattern:

• Models: Data structures and business logic
• Views: UI components (screens and widgets)
• ViewModels: Intermediaries that handle UI logic and data operations
• Repositories: Abstractions for data sources (AI API, local storage)

lib/
├── core/
│   └── constants/         # App-wide constants
├── config/
│   └── env_config.dart    # Environment configuration
├── models/                # Data models
├── repositories/          # Data access layer with interfaces
├── theme/                 # App theme definitions  
├── viewmodels/            # ViewModels for business logic
├── views/                 # UI components
│   ├── screens/           # Full page views
│   └── widgets/           # Reusable UI components
└── main.dart              # Application entry point

• Flutter SDK (>=3.4.3)
• Dart SDK
• Google Gemini API key

1. Clone the repository

git clone https://github.com/nikhileshmeher0204/read_the_label.git

2. Navigate to the project directory

cd read_the_label

3. Create a .env file in the root directory and add your Gemini API key:

GEMINI_API_KEY=your_api_key_here

4. Install dependencies

flutter pub get

5. Run the app

flutter run

This application uses Provider for state management:

• BaseViewModel: Foundation class for all ViewModels
• ViewModels:
  • UiViewModel: Handles UI state and navigation
  • ProductAnalysisViewModel: Manages product scanning and analysis
  • MealAnalysisViewModel: Handles food image analysis
  • DailyIntakeViewModel: Controls daily consumption tracking

• Flutter SDK (>=3.4.3)
• Dart SDK
• Google Generative AI (Gemini) for AI-powered analysis
• Provider for state management
• SharedPreferences for local storage
• Material Design 3 with custom theme
• Various Flutter packages:
  • image_picker for camera integration
  • flutter_dotenv for environment variables
  • fl_chart for data visualization
  • rive for animations

• Spring Boot backend integration for cross-device synchronization
• User authentication and profiles
• Enhanced nutritional insights with AI recommendations
• Social sharing features

Contributions are welcome! Please feel free to submit a Pull Request.

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

• Google Generative AI for the Gemini API
• Flutter team for the amazing framework