🧠 StylistExpert Backend

This is the backend for StylistExpert, a robust, rule-based expert system for fashion recommendations, built with FastAPI and Python.

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🚩 Features

• Intelligent Recommendations: Rule-based expert system with forward chaining inference
• Comprehensive API: Accepts detailed user profiles, returns tailored advice
• Test Suite: Pytest-based tests for rules and API endpoints

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🛠️ Tech Stack

• FastAPI (API framework)
• Python 3.10+
• Pydantic (data validation)
• Pytest (testing)

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🚀 Getting Started

1. Navigate to the backend directory:

   cd backend

2. Install dependencies:

   pip install -r requirements.txt

3. Start the FastAPI server:

   uvicorn main:app --reload --host 0.0.0.0 --port 8000

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

   • Interactive docs: /docs
   • Alternative docs: /redoc

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🧪 Running Tests

python -m pytest test_engine.py -v

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📡 API Usage

POST /api/recommend

Get personalized fashion recommendations.

Request Example:

{
  "gender": "female",
  "occasion": "formal",
  "weather": "mild",
  "body_type": "athletic",
  "preferred_style": "classic",
  "color_preference": "neutral",
  "height": "average"
}

Response Example:

{
  "recommendations": [
    {
      "title": "Elegant Sheath Dress or Blazer Suit",
      "items": ["Sheath dress or tailored blazer and trousers", "Heels or loafers", "Delicate jewelry"],
      "explanation": "A structured dress or blazer suit projects confidence and works well for formal settings.",
      "images": ["https://source.unsplash.com/800x600/?women,formal,dress"],
      "confidence": 0.95,
      "matched_rules": ["R2"]
    }
  ]
}

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🧠 Knowledge Base

• 12+ rules for various fashion scenarios:
  • Formal, casual, special events, athletic, body type, weather, style preferences

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🏗️ Architecture

• Rules Engine: Forward chaining, confidence scoring, rule merging, fallback system
• API: FastAPI endpoints for recommendations

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📁 Project Structure

backend/
├── main.py         # FastAPI app & rules engine
├── test_engine.py  # Test suite
└── requirements.txt

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🚧 Limitations & Future Work

• Static rule base (no ML adaptation)
• Limited cultural/regional diversity
• Basic image sourcing from Unsplash
• No real-time trend integration

Planned:

• Machine learning integration
• Computer vision outfit analysis
• Social/sharing features
• Shopping integration
• Personalization engine
• AR/VR try-on

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📄 License

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

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🧑‍💻 Author

Nduoma Chinomso Christian
AKA Buzz Brain

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Built with ❤️ for fashion lovers everywhere.