This agent provides a general-purpose, sandboxed environment for executing Python code to accomplish user-defined tasks. It leverages a Large Language Model (LLM) to interpret a natural language task, generate Python code, and execute it within a Docker container. The agent operates by creating an interactive session with a Jupyter kernel running inside the container, allowing it to iteratively write code, execute it, and use the output to inform its next steps until the task is complete.

To run this agent, a Docker daemon must be available and running on the host machine. The agent itself is a Python command-line application. It pulls a specified Docker image (defaulting to jupyter/datascience-notebook:latest) to create the execution environment.

• execute_code
• restart_kernel
• complete_task

uv run python_agent/main.py --model "anthropic/claude-haiku-4-5-20251001" --task "please generate an interesting dataset, and visualize it"