Clothing Search Agent

An intelligent AI-powered agent that searches for clothing items across multiple e-commerce platforms, helping users find the best deals and options based on their preferences.

Features

• Multi-Platform Search: Searches across Amazon, eBay, Etsy, ASOS, and more
• AI-Powered Filtering: Uses OpenAI to understand natural language queries
• Price Tracking: Monitors price changes and sends alerts
• Preference Learning: Learns user preferences over time
• Smart Notifications: Email alerts for price drops and new matches
• Data Persistence: Stores search history and preferences

Installation

1. Clone the repository:

git clone <repository-url>
cd clothing-search-agent

2. Create 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
   • Fill in your API keys and configuration

Configuration

Required API Keys

• OpenAI API Key: For AI-powered search and filtering
• SERP API Key: For enhanced search capabilities
• Email Credentials: For notifications (optional)

Environment Variables

See .env file for all configuration options.

Usage

Basic Usage

from src.agents.clothing_agent import ClothingAgent

agent = ClothingAgent()

# Search for clothing items
results = agent.search("blue denim jacket under $100")

# Get filtered results based on preferences
filtered_results = agent.filter_results(results, preferences)

Command Line Interface

# Run the agent with default settings
python scripts/run_agent.py

# Search for specific items
python scripts/run_agent.py --query "red summer dress size M"

# Set up user preferences
python src/main.py --setup-preferences

Project Structure

clothing-search-agent/
├── src/                     # Main source code
│   ├── agents/             # AI agents
│   ├── scrapers/           # Web scrapers
│   ├── models/             # Data models
│   ├── services/           # Services (notifications, storage)
│   └── utils/              # Utilities
├── data/                   # Data storage
├── tests/                  # Test files
├── docs/                   # Documentation
├── notebooks/              # Jupyter notebooks
└── scripts/                # Utility scripts

API Documentation

See docs/api_docs.md for detailed API documentation.

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests
5. Submit a pull request

Testing

# Run all tests
pytest

# Run specific test category
pytest tests/test_agents/
pytest tests/test_scrapers/

# Run with coverage
pytest --cov=src tests/

Logging

Logs are stored in logs/app.log. Adjust log level in .env file.

License

MIT License - see LICENSE file for details.

Support

For questions or issues, please open a GitHub issue.