Fiscozen ChatAI 🤖

An intelligent chat system that seamlessly transitions between AI assistance, customer service, and tax advisory services.

🌟 Features

• Smart Routing: Automatically directs conversations to:

  • AI Assistant for general queries
  • Customer Service representatives for complex cases
  • Tax Advisors for tax-related matters

• Recommendation System: Uses Microsoft's Recommenders library to:

  • Provide contextual responses
  • Suggest relevant information
  • Learn from conversation patterns

• Modern UI: Built with Streamlit for:

  • Clean, responsive interface
  • Real-time updates
  • Easy interaction

🚀 Getting Started

Prerequisites

• Python 3.8+
• pip package manager

Installation

1. Clone the repository:

git clone git@github.com:DavidVart/recommendations-project.git
cd recommendations-project

2. Set up the UI environment:

python -m venv venv-ui
source venv-ui/bin/activate  # On Windows: venv-ui\Scripts\activate
pip install -r requirements-ui.txt
pip install -e .

3. Set up the recommender service environment:

python -m venv venv-recommender
source venv-recommender/bin/activate  # On Windows: venv-recommender\Scripts\activate
pip install -r requirements-recommender.txt
pip install -e .

Running the Application

1. Start the recommender service (in the recommender environment):

python run_recommender.py

2. In a new terminal, start the UI (in the UI environment):

python run_chat.py

The chat interface will be available at http://localhost:8501

🏗️ Project Structure

jorgelib/
├── ui/                 # Chat interface
├── recommender_service/# FastAPI service
├── models/            # Recommendation models
├── datasets/          # Data handling
├── routing/           # Conversation routing
└── chat/             # Core chat logic

🛠️ Development

• The project uses two separate environments to handle dependency conflicts
• UI runs on port 8501 (Streamlit)
• Recommender service runs on port 8000 (FastAPI)
• All code changes in jorgelib/ are immediately reflected due to development installation

📚 Technologies Used

• Streamlit - UI Framework
• Microsoft Recommenders - Recommendation Engine
• FastAPI - API Framework
• pandas - Data Processing

🤝 Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📝 License

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