SmartCart - AI-Powered Personalized E-Commerce

SmartCart is a multi-agent system that delivers hyper-personalized product recommendations using advanced AI and machine learning techniques. The system consists of three intelligent agents working together to understand customer behavior, analyze products, and provide tailored recommendations.

Features

• 🤖 Multi-agent architecture (Customer, Product, and Recommendation Agents)
• 🧠 Gemini AI-powered persona generation and product profiling
• 🎯 Hyper-personalized product recommendations
• 📊 Explainable AI for transparent recommendations
• 😊 Mood-based dynamic suggestions
• 📖 AI-generated product storytelling
• 🔄 Continuous learning from customer feedback

System Architecture

The system is built using:

• FastAPI for the backend
• Google's Gemini API for AI capabilities
• SQLite for data persistence
• Modern RESTful API design

Setup Instructions

1. Clone the repository:

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

2. Create and activate a virtual environment:

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

3. Install dependencies:

pip install -r requirements.txt

4. Set up environment variables:

• Copy .env.example to .env
• Add your Gemini API key to the .env file

5. Run the application:

uvicorn src.main:app --reload

The API will be available at http://localhost:8000

API Documentation

Once the server is running, you can access:

• Swagger UI: http://localhost:8000/docs
• ReDoc: http://localhost:8000/redoc

Key Endpoints

• POST /api/v1/customer/persona - Generate customer persona
• POST /api/v1/product/profile - Generate product profile
• POST /api/v1/recommendations - Get personalized recommendations
• POST /api/v1/recommendations/explain - Get recommendation explanation
• POST /api/v1/recommendations/mood - Get mood-based recommendations
• POST /api/v1/product/story - Generate product story
• POST /api/v1/recommendations/feedback - Update recommendation based on feedback

Data Structure

Customer Data

• CustomerID
• Name
• Age
• Gender
• Location
• BrowsingHistory
• PurchaseHistory
• PreferredCategories

Product Data

• ProductID
• ProductName
• Category
• Price
• Rating
• Description
• Features

Contributing

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

License

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

Acknowledgments

• Google Gemini API
• FastAPI
• SQLAlchemy
• All contributors and supporters