User Guide

Getting Started

After installing JupyDeep for the first time, you’ll need to configure a few settings to get the engine running:

1. Locate Settings

Open the JupyterLab Settings Editor and search for options prefixed with jupydeep.

2. Configure Your LLM

The agent engine requires an LLM backend to function. Set up your model provider (e.g., OpenAI) by following the configurations below (Required).

_images/jupydeep_llm.png

Note

While OpenAI is used here as an example, any other supported LLM provider you have access to will work perfectly. Please refer to the available models listed in the Pydantic AI (KnownModelName Section). You can also configure local proxies—such as Ollama running on your local machine or network.

3. Configure Your MCP

To maximize productivity within the Jupyter workspace, it is highly recommended to configure the Jupyter MCP using the guidelines below (Recommended).

_images/jupydeep_mcp.png

Warning

Ensure the URL prefix and port match those in your browser’s address bar.

4. Meet Your Built-in Agents

Once your LLM is connected, two default agents will instantly populate your jupydeep.agent panel.

_images/jupydeep_agent.png

  • 🐵 Wu Kong: Built for heavy-lifting code execution and technical problem-solving.

  • 🐴 Monk Tang: Built for high-level tactical planning and orchestration.

Tip

You can easily customize their skillsets and capabilities to fit your needs. If the agents do not appear, try refreshing the page.

5. Global Setting

This section primary configures the global behavior of the engine and agents. This includes settings for the default agent and model, token usage limits, tool-call timeouts, and backend configurations.

_images/jupydeep_global.png

Warning

Some of these parameters are currently placeholders and have not been implemented yet.