ChatFlet is a production-ready AI chatbot backend built with FastAPI.

The system is designed to power WhatsApp chatbots, desktop clients, and REST API integrations.
It includes AI-based message interpretation, inventory/property management, and image gallery support.

A public online demo is available via Swagger UI and runs in safe demo mode without requiring external credentials.

The project includes Docker support for local development and an optional Flet-based desktop client for extended usage.

- FastAPI REST backend
- Swagger UI interactive documentation
- AI-powered message interpretation
- WhatsApp chatbot integration (Twilio)
- Safe demo mode without credentials
- Inventory / property management
- Image gallery support
- Dockerized MySQL setup
- SQLite fallback for demo
- Optional Flet desktop client

- Python 3.10 or higher
- Internet connection (for optional AI and WhatsApp integrations)
- Docker & Docker Compose (optional, for MySQL setup)
- Basic knowledge of REST APIs

Requirements:
- Python 3.10+
- Docker & Docker Compose (optional)

Local installation (demo mode):
1. Clone the project
2. Create and activate a virtual environment
3. Install dependencies from requirements.txt
4. Run:
   uvicorn model:app --reload

Docker installation (MySQL):
1. Run:
   docker-compose up --build
2. Open:
   http://localhost:8000/docs