AIris is an intelligent fashion advisory system that leverages Large Language Models (LLMs) and computer vision to provide personalized style recommendations. Built with modern AI technologies, it demonstrates practical applications of artificial intelligence in the fashion domain.
AIris System Architecture
- 🧠 Intelligent Style Analysis: Uses LLMs to analyze and provide contextual fashion advice
- 👁️ Image Recognition: Processes uploaded fashion items using computer vision
- 🔄 Multi-Modal Interaction: Combines text and image inputs for comprehensive analysis
- 🌤️ Context-Aware: Considers weather, occasion, and personal style preferences
- ⚡ Flexible Architecture: Supports both online (Groq API) and offline modes
- 💻 Modern UI: Built with Gradio for an intuitive user experience
| Category | Technologies |
|---|---|
| Backend | Python 3.8+, FastAPI |
| AI/ML | LlamaIndex, Groq API, PIL |
| Frontend | Gradio, FastAPI |
| Data | Custom Knowledge Base |
| DevOps | Docker, Environment Management |
-
Clone and Setup
git clone https://github.com/AnvitaPrasad/AgenticAIChatbot-AnvitaPrasad.git cd AgenticAIChatbot-AnvitaPrasad python -m venv venv source venv/bin/activate # On Windows: venv\Scripts\activate pip install -r requirements.txt
-
Configure Environment
cp .env.example .env # Add your Groq API key to .env file -
Run the Application
python simple_ui.py
from src.agents.fashion_advisor import AIris
# Initialize AIris with online mode
advisor = AIris(offline_mode=False)
# Get contextual outfit advice
advice = advisor.get_outfit_advice(
"What should I wear to a summer wedding?",
weather="hot",
occasion="wedding",
style="elegant"
)
# Get style inspiration with specific parameters
inspiration = advisor.get_inspiration(
style="bohemian",
season="summer",
occasion="casual"
)
# Analyze an uploaded image
from PIL import Image
image = Image.open("outfit.jpg")
analysis = advisor.analyze_image(image).
├── src/
│ ├── agents/ # AI agent implementations
│ │ ├── base_agent.py # Base agent class
│ │ └── fashion_advisor.py # Main AIris implementation
│ ├── data/ # Knowledge base and data models
│ │ └── fashion_knowledge.py # Fashion rules
│ └── utils/ # Utility functions
│ ├── image_processor.py # Image processing
│ └── fashion_scraper.py # Data collection
├── app.py # FastAPI application
├── simple_ui.py # Gradio web interface
├── requirements.txt # Project dependencies
├── Dockerfile # Container configuration
└── README.md
- 🎯 Agent Architecture: Modular agent system with base class for extensibility
- 📚 Knowledge Management: Structured data models for fashion knowledge
- 🛡️ Error Handling: Comprehensive error handling for API calls
- ✅ Type Safety: Python type hints for better code reliability
- ⚡ Async Support: Async/await patterns for efficient API interactions
- 🎨 UI/UX: Responsive web interface with real-time updates
Try AIris now on Hugging Face Spaces!
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.
Anvita Prasad
- GitHub: @AnvitaPrasad
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