AI Shopping Recommender 🛍️

An intelligent shopping assistant that combines product search with AI-powered analysis to help users make informed purchasing decisions. The application leverages SerpAPI for product search and Groq's LLM for detailed product analysis and personalized recommendations.

🌟 Features

• Smart Product Search: Search products across multiple stores with location-based results
• AI-Powered Analysis: Get personalized product recommendations based on your preferences
• Beautiful UI: Clean, modern interface with responsive design
• Location-Based Results: Get relevant product listings based on your location
• Detailed Comparisons: AI-generated analysis of features, prices, and value propositions

🚀 Quick Start

Using Docker

# Clone the repository
git clone https://github.com/We4TechAI/AI-Shopping-Recommender.git
cd AI-Shopping-Recommender

# Build Docker image
docker build --tag ai_shopping_recommender:latest .

# Run container
docker run -d --name ai_shopping_recommender -p 8501:8501 ai_shopping_recommender:latest

Manual Installation

1. Clone the repository:

git clone https://github.com/We4TechAI/AI-Shopping-Recommender.git
cd AI-Shopping-Recommender

2. Create and activate 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: Create a .env file in the project root with:

SERPAPI_KEY=your_serpapi_key
GROQ=your_groq_api_key

5. Run the application:

streamlit run app.py

📦 Dependencies

• Python 3.8+
• Streamlit
• SerpAPI
• Groq
• python-dotenv
• pandas

💻 Usage

1. Open your browser and navigate to http://localhost:8501
2. Enter the product you're looking for
3. Specify your location for relevant results
4. Enter your preferences (budget, features, brand preferences, etc.)
5. Click "Search and Analyze" to get personalized recommendations

🔧 Configuration

The application can be configured through environment variables:

Variable	Description	Required
SERPAPI_KEY	Your SerpAPI API key	Yes
GROQ	Your Groq API key	Yes

📝 API Documentation

SerpAPI Integration

The application uses SerpAPI's Google Shopping search with the following parameters:

• engine: google_shopping
• google_domain: google.com
• hl: hi (Hindi language support)
• gl: in (India region)
• Location-based searching

Groq Integration

Uses Groq's LLM (llama-3.3-70b-versatile) for:

• Product analysis
• Feature comparison
• Personalized recommendations
• Price analysis

🛠️ Development

Project Structure

AI-Shopping-Recommender/
├── main.py
├── Dockerfile
├── requirements.txt
├── .env.example
├── .env
└── README.md
 

Adding New Features

1. Create a new branch:

git checkout -b feature/your-feature-name

2. Make your changes
3. Test thoroughly
4. Submit a pull request

🤝 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

🔐 Security

• Never commit your .env file
• Keep API keys secure
• Regularly update dependencies
• Follow security best practices

🐛 Troubleshooting

Common Issues

1. API Key Issues

   • Ensure your API keys are correctly set in .env
   • Verify API key permissions

2. Docker Issues

   • Ensure ports are not in use
   • Check Docker logs: docker logs ai_shopping_recommender

3. Search Issues

   • Verify internet connection
   • Check SerpAPI quota
   • Ensure location format is correct

📞 Support

For support, please:

1. Check existing issues
2. Create a new issue with detailed information
3. Join our community discussions

✨ Acknowledgments

• SerpAPI for product search capabilities
• Groq for AI analysis
• Streamlit for the web framework
• All contributors who have helped shape this project

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Made with ❤️ by We4TechAI Team