Skip to main content

Use Cases

The available Agents support following use cases.

  • Automated Data Analysis - Generate and execute Python scripts to analyze data, create visualizations, or preprocess datasets.
  • Error Debugging - Identify and explain errors in code execution, with actionable suggestions to fix them.
  • Notebook Refactoring - Automatically optimize code structure, improve readability, or add detailed documentation.

We are building new Agents to support more use cases.

  • Creating a UI for Chatting with the Agent in JupyterLab - Developing an interactive interface within JupyterLab where users can directly communicate with the Jupyter AI Agent, issuing commands and receiving real-time responses in a conversational format.
  • Building a Code Refactoring Agent - Developing an agent that can automatically refactor code in Jupyter Notebooks, improving code quality, readability, and maintainability.