TUI AI Agent 🤖

A Terminal User Interface (TUI) AI Assistant that provides intelligent responses and code execution capabilities.

Project Structure

src/
├── __init__.py          
├── agent.py             # Main agent controller
├── code_executor.py     # Python code execution handling
├── services/
│   └── llm_service.py   # LLM service integration
├── ui/
│   └── layout_manager.py # TUI layout management
└── prompts/
    └── system.prompt    # System prompts for AI behavior

Features

• 🎨 Rich TUI interface powered by the Rich library
• 💬 AI-powered responses with streaming capability
• 🚀 Secure Python code execution
• 📝 Markdown rendering support
• ⚡ Real-time status updates
• 🛡️ Resource-managed execution environment

Installation

1. Clone the repository:

git clone https://github.com/josebenitezg/agentui.git
cd tui-ai-agent

2. Create and activate a virtual environment:

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install required dependencies:

pip install -r requirements.txt

4. Create a .env file with your configuration:

ANTHROPIC_API_KEY=your_api_key_here

Usage

To start the TUI AI Agent:

python -m src.agent

Components

Layout Manager

The UI component uses Rich library for:

• Console output formatting
• Dynamic layout management
• Panel rendering
• Markdown and syntax highlighting

Agent

Core controller that manages:

• User interactions
• AI response processing
• Code execution coordination
• Layout updates

Code Executor

Handles Python code execution with:

• Memory usage limits
• Timeout protection
• Input/Output capture
• Error handling

LLM Service

Manages AI communication with:

• Message streaming
• Tool integration
• System prompt handling
• Response formatting

Development

Prerequisites

• Python 3.8+
• Virtual environment
• Anthropic API key

Testing

The project emphasizes:

• Code validation
• Input/output testing
• Edge case handling
• Performance optimization
• Proactive bug detection

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

[Add your license information here]

Acknowledgments

• Rich for the TUI components
• Anthropic for the Claude AI model