💻 Code Execution Chat

A Streamlit-based chat application that executes Python and Node.js code in secure E2B sandboxes using OpenAI's function calling capabilities.

✨ Features

• 🤖 AI-Powered Code Generation - Uses OpenAI GPT-4 to understand requests and generate code
• 🐍 Python Execution - Run Python code with automatic dependency installation
• 🟢 Node.js/JavaScript - Execute JavaScript with npm package support
• 📊 Visualization Support - Display matplotlib plots, charts, and images inline
• 🔒 Secure Sandboxes - Code runs in isolated E2B cloud sandboxes
• 💬 Chat Interface - Natural conversation flow with code execution

🚀 Quick Start

Prerequisites

• Python 3.9+
• OpenAI API key
• E2B API key (get one at e2b.dev)

Installation

1. Clone the repository

   git clone https://github.com/yourusername/code-execution-chat.git
   cd code-execution-chat

2. Create a virtual environment

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

3. Install dependencies

   pip install -r requirements.txt

4. Set up environment variables

   cp .env.example .env

   Edit .env and add your API keys:

   OPENAI_API_KEY=your_openai_api_key_here
   E2B_API_KEY=your_e2b_api_key_here
   

5. Run the application

   streamlit run app.py

📁 Project Structure

code-execution-chat/
├── app.py                 # Main Streamlit application
├── src/
│   ├── __init__.py
│   ├── config.py         # Configuration and constants
│   ├── sandbox.py        # E2B sandbox execution logic
│   ├── chat.py           # OpenAI chat handling
│   └── ui.py             # Streamlit UI components
├── requirements.txt       # Python dependencies
├── .env.example          # Example environment variables
├── .gitignore
└── README.md

🎯 Usage Examples

Python - Plot a Sine Wave

"Create a Python app that plots a sine wave"

Node.js - Express Server

"Build an Express server with a hello world endpoint and test it with axios"

Data Analysis

"Write a Python script to generate sample sales data and create a bar chart"

🔧 Configuration

Environment Variables

Variable	Description	Required
OPENAI_API_KEY	Your OpenAI API key	Yes
E2B_API_KEY	Your E2B sandbox API key	Yes

Available Models

• GPT-4o (default)
• GPT-4o-mini
• GPT-4-turbo
• GPT-3.5-turbo

🛠️ Supported Technologies

Python

• Any pip package (auto-installed)
• Matplotlib, NumPy, Pandas, etc.
• Data visualization libraries

Node.js/JavaScript

• ES Modules support
• Top-level await
• npm packages (auto-installed)
• Express.js, Axios, etc.

🔒 Security

• All code executes in isolated E2B cloud sandboxes
• Sandboxes are automatically destroyed after execution
• No persistent storage between executions
• API keys are never exposed to executed code

📝 License

MIT License - see LICENSE for details.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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

🙏 Acknowledgments

• OpenAI for GPT models and function calling
• E2B for secure code execution sandboxes
• Streamlit for the amazing web framework