jarvis-ipybox 0.4.0

Python code execution sandbox based on IPython and Docker

ipybox

ipybox is a lightweight, stateful and secure Python code execution sandbox built with IPython and Docker. Designed for AI agents that interact with their environment through code execution, like the freeact agent system, it is also well-suited for general-purpose code execution. ipybox is fully open-source and free to use, distributed under the Apache 2.0 license.

Features

• Secure Execution: Executes code in isolated Docker containers, preventing unauthorized access to the host system
• Stateful Execution: Maintains variable and session state across commands using IPython kernels
• Real-Time Output Streaming: Provides immediate feedback through direct output streaming
• Enhanced Plotting Support: Enables downloading of plots created with Matplotlib and other visualization libraries
• Flexible Dependency Management: Supports package installation and updates during runtime or at build time
• Resource Management: Controls container lifecycle with built-in timeout and resource management features
• Reproducible Environments: Ensures consistent execution environments across different systems

Documentation

The ipybox documentation is available here.

Quickstart

Install ipybox Python package:

pip install ipybox

Execute Python code inside ipybox:

import asyncio
from ipybox import ExecutionClient, ExecutionContainer

async def main():
    async with ExecutionContainer(tag="ghcr.io/gradion-ai/ipybox:minimal") as container:
        async with ExecutionClient(port=container.port) as client:
            result = await client.execute("print('Hello, world!')")
            print(f"Output: {result.text}")

if __name__ == "__main__":
    asyncio.run(main())

Find out more in the user guide.