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AI Wardrobe Assistant

An intelligent wardrobe recommendation system that uses AI to generate personalized clothing suggestions based on user preferences, style, and context. The system leverages OpenAI's API and a multi-agent architecture to provide detailed wardrobe recommendations with real product suggestions.

Features

  • Personalized Recommendations: Generates wardrobe suggestions based on user's style preferences, occasion, and needs
  • Real Product Search: Integrates with Walmart's product catalog to find actual clothing items
  • Structured Output: Organizes recommendations by category (tops, bottoms, outerwear, etc.)
  • Detailed Information: Provides product names, prices, descriptions, and URLs for each item
  • Styling Tips: Includes personalized advice on how to combine and wear the suggested items
  • REST API: Offers a Flask-based API endpoint for easy integration

Setup

  1. Clone the repository
  2. Install dependencies:
pip install -r requirements.txt
  1. Create a .env file with your OpenAI API key:
OPENAI_API_KEY=your-api-key-here

Usage

API Endpoint

Start the Flask server:

python main.py

Make a request:

curl -X POST http://127.0.0.1:5000/api/wardrobe/recommend \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "I need a minimalist wardrobe with neutral colors for a professional setting"
  }'

Example Response

{
  "theme": "Professional Minimalist Wardrobe",
  "styling_tips": "Mix and match these versatile pieces...",
  "tops": [
    {
      "name": "Classic White Oxford Shirt",
      "price": "$45.99",
      "description": "Crisp cotton oxford shirt...",
      "product_url": "https://...",
      "image_url": "https://..."
    }
  ],
  // Other categories: bottoms, outerwear, headwear, footwear, accessories
}

Architecture

The system uses a multi-agent approach:

  • Product Search Agent: Finds real clothing items matching the user's requirements
  • Style Advisor Agent: Provides fashion advice and styling tips
  • Main Wardrobe Agent: Coordinates the recommendations and ensures coherent output

Technologies

  • Python 3.8+
  • OpenAI API
  • Flask
  • Pydantic for data validation
  • Colorama for formatted console output
  • Async support with nest_asyncio

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