NotebookFlow turns a Jupyter notebook into a visual workflow without moving execution out of your local environment. Arrange notebook cells as connected nodes, inspect their data flow, and run the pipeline from the canvas beside the notebook.
Get started
- Install the extension and open an
.ipynbfile. - Select the NotebookFlow: Open Canvas button in the notebook toolbar, or run that command from the Command Palette.
- On the first run, approve installation of the released NotebookFlow engine. The extension creates a private Python environment in VS Code's extension storage and reuses it on later runs. The engine includes the scientific Python runtime, so its first download can take several minutes.
The Microsoft Jupyter extension is installed automatically as an extension
dependency. The local engine requires Python 3.11, 3.12, or 3.13. Node.js,
uv, and a NotebookFlow source checkout are not required.
What it does
- Builds a pipeline graph from cells across a Jupyter notebook.
- Keeps canvas edits and notebook source synchronized.
- Streams local execution progress and cell outputs back into the notebook.
- Provides Ask, Compose, Explain, and node-synthesis tools with your own LLM provider key.
- Optionally opens and saves notebooks in a NotebookFlow Cloud account.
Local execution and privacy
Pipeline code runs in the local notebookflow-app engine launched by the
extension. Notebook contents and execution data are not sent to NotebookFlow
Cloud. Cloud sign-in and cloud notebook commands are optional. If you enable
an LLM feature, its request is sent directly to the provider selected in your
settings using the key stored in VS Code SecretStorage.
Settings
| Setting | Purpose |
|---|---|
notebookflow.pythonPath |
Optional Python 3.11–3.13 executable for managed-engine setup. |
notebookflow.enginePath |
Development-only override for an engine checkout run with uv. |
notebookflow.llm.provider |
LLM provider used by AI-assisted commands. |
notebookflow.llm.model |
Optional provider model ID. |
notebookflow.cloud.baseUrl |
Hosted NotebookFlow origin used only by optional cloud commands. |
Use NotebookFlow: Set LLM API Key to store a key; it is never written to workspace settings.
Troubleshooting
- Python was not found: install Python 3.11–3.13, restart VS Code, or set
notebookflow.pythonPathto its executable. - Engine installation or startup failed: open Output: Show Output Channels and select NotebookFlow Engine. Check network access to PyPI for the first installation.
- The canvas command asks for a notebook: open an
.ipynbfile with the Jupyter extension first. - Remote development: the extension and managed Python engine run on the remote extension host, beside the notebook files.
Report bugs and request features in the NotebookFlow issue tracker.
License
MIT