A FastAPI-based backend service for managing Interactive Non-Fungible Tokens (iNFTs) with AI-powered chat capabilities and semantic search functionality.

• iNFT Management: Create, store, and manage iNFTs with metadata and traits
• AI-Powered Chat: Interactive chat functionality with each iNFT using ASI API
• Semantic Search: Vector-based similarity search using sentence transformers and FAISS
• Feedback System: Rating and feedback mechanism for iNFTs with score computation
• Web3 Storage: Mock Web3 storage integration for file management
• SQLite Database: Persistent storage for iNFTs and feedback data

• Framework: FastAPI
• Database: SQLite
• AI/ML:
  • ASI API for chat completions
  • Sentence Transformers (all-MiniLM-L6-v2) for embeddings
  • FAISS for vector similarity search
• Dependencies:
  • uvicorn - ASGI server
  • python-dotenv - Environment variable management
  • requests - HTTP client
  • pydantic - Data validation

Backend/
├── __init__.py          # Package initialization
├── main.py             # FastAPI application entry point
├── config.py           # Configuration and environment variables
├── db.py              # Database initialization and schema
├── routes.py          # API endpoints and route handlers
├── utils.py           # Utility functions (Web3 storage, ASI API calls)
└── embedding.py       # Vector embeddings and semantic search

Create a .env file in the root directory with the following variables:

ASI_API_KEY=your_asi_api_key_here
ASI_MODEL=asi1-mini

• id: Primary key (auto-increment)
• name: iNFT name
• owner: Owner address/identifier
• tag: Category/tag
• cid: Content identifier (Web3 storage)
• traits_json: JSON string of traits/metadata
• score: Average rating score (0-10)
• created_at: Timestamp

• id: Primary key (auto-increment)
• inft_id: Reference to iNFT
• rating: Rating score (0-10)
• comment: Optional feedback comment
• created_at: Timestamp

• POST /create_inft - Create a new iNFT with metadata
• GET /list_infts - List all iNFTs with their details

• POST /chat/{inft_id} - Chat with a specific iNFT using AI

• POST /feedback/{inft_id} - Submit rating and feedback for an iNFT

• Each iNFT has a unique persona based on its name, tag, and traits
• Uses ASI API for generating contextual responses
• Incorporates relevant memory through semantic search

• Converts text data into vector embeddings using sentence transformers
• Stores embeddings in FAISS index for fast similarity search
• Retrieves relevant context for chat interactions

1. iNFT Creation:

   • Store metadata in database
   • Generate embeddings from traits
   • Mock upload to Web3 storage

2. Chat Interaction:

   • Retrieve iNFT persona and traits
   • Search for relevant memories using embeddings
   • Generate AI response with context

3. Feedback Processing:

   • Store user feedback
   • Recompute average score
   • Update iNFT rating

1. Install Dependencies:

   pip install -r requirements.txt

2. Set Environment Variables: Create .env file with ASI API credentials

3. Run the Server:

   cd Backend
   uvicorn main:app --reload

4. Access API Documentation: Visit http://localhost:8000/docs for interactive API documentation

• CORS middleware configured for cross-origin requests
• Input validation using Pydantic models
• Error handling for API failures
• SQLite connection with thread safety

• In-memory FAISS index for fast vector search
• Connection pooling for database operations
• Efficient embedding generation and storage
• Mock Web3 storage for development/testing

• Uses mock Web3 storage implementation for development
• Fallback mock responses when ASI API is unavailable
• Thread-safe database operations
• Comprehensive error handling and HTTP status codes

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

This project is part of the iNFT Agent ecosystem for creating interactive and intelligent NFTs with AI capabilities.