# Smart Fridge Project

A sophisticated kitchen management system that uses AI and computer vision to track inventory, suggest recipes, monitor nutrition, and prevent food waste.

## Features

- 🎯 **Inventory Management**: Automatic tracking of food items using computer vision
- 🍳 **Recipe Suggestions**: Smart recipe recommendations based on available ingredients
- 📊 **Health Tracking**: Monitor nutritional intake and progress towards health goals
- ♻️ **Waste Prevention**: Track expiration dates and get alerts for at-risk items
- 🔍 **Advanced Recipe Search**: Filter recipes by dietary restrictions, cooking time, and difficulty
- 🤖 **AI-Powered Assistant**: Chat with an AI kitchen assistant for cooking advice and help
- 📈 **Analytics**: Visual reports of inventory trends and nutritional data

## Prerequisites

- Python 3.9 or higher
- PostgreSQL (optional, SQLite is used by default)
- OpenCV for computer vision
- FFmpeg for audio processing

## Installation

1. Clone the repository:
```bash
git clone https://github.com/yourusername/smart-fridge-project.git
cd smart-fridge-project

2. Create and activate a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows use: .venv\Scripts\activate

3. Install required packages:

pip install -r requirements.txt

4. Create a .env file in the project root with the following keys:

SPOONACULAR_API_KEY=your_spoonacular_api_key
DATABASE_URL=sqlite:///smartfridge.db  # Or your PostgreSQL URL
SECRET_KEY=your_secret_key_here
OPENAI_API_KEY=your_openai_api_key
NUTRITIONIX_APP_ID=your_nutritionix_app_id
NUTRITIONIX_API_KEY=your_nutritionix_api_key

Running the Application

1. Initialize the database:

flask db upgrade

2. Run the application:

flask run

The application will be available at http://localhost:5000

API Keys Required

This project uses several external APIs. You'll need to obtain API keys from:

• Spoonacular - For recipe data
• OpenAI - For AI assistant features
• Nutritionix - For nutritional data

Default Login

A test user is created automatically with these credentials:

• Username: testuser
• Password: testpassword

Project Structure

smart-fridge-project/
├── src/
│   ├── ai/
│   ├── camera/
│   ├── core/
│   ├── inventory/
│   ├── recipes/
│   ├── health/
│   └── waste_prevention/
├── static/
├── templates/
├── requirements.txt
└── main.py

Features in Detail

Inventory Management

• Real-time tracking of food items
• Automatic detection using computer vision
• Expiration date tracking
• Category-based organization

Recipe Management

• Recipe suggestions based on available ingredients
• Dietary restriction filters
• Difficulty levels and cooking time estimates
• Nutritional information

Health Tracking

• Daily nutritional intake monitoring
• Progress towards health goals
• Visual nutrition reports
• Custom goal setting

Waste Prevention

• Expiration alerts
• Smart usage suggestions
• Inventory optimization
• Food waste tracking

Contributing

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

Known Issues

• FFmpeg warning on startup can be ignored if you're not using audio features
• Local image paths need to be adjusted based on your system

Future Development

Planned features include:

• Voice control system
• Multi-user family management
• Smart leftover tracking
• Cost management system
• Mobile application integration

License

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

Acknowledgments

• Uses YOLOv3 for object detection
• OpenAI's GPT models for AI assistance
• Spoonacular API for recipe data
• Nutritionix API for nutritional information

Support

For support, please open an issue in the GitHub repository.

Security

Please note that this project is for educational purposes. In a production environment, additional security measures should be implemented.