Skip to main content

A JupyterLab extension for chat functionality with MCP (Model Context Protocol) support.

Project description

jupyterchatz

Github Actions Status

A JupyterLab extension that provides chat functionality with MCP (Model Context Protocol) support, enabling interactive communication within the JupyterLab environment.

Requirements

  • JupyterLab >= 4.0.0

Install

To install the extension, execute:

# Install the package
pip install jupyterchatz

# Build JupyterLab extension
jupyter lab build

# Enable the extension (if not automatically enabled)
jupyter labextension enable jupyterchatz

Uninstall

To remove the extension, execute:

pip uninstall jupyterchatz

Contributing

Development install

Note: You will need NodeJS to build the extension package.

The jlpm command is JupyterLab's pinned version of yarn that is installed with JupyterLab. You may use yarn or npm in lieu of jlpm below.

# Clone the repo to your local environment
# Change directory to the jupyterchatz directory
# Install package in development mode
pip install -e "."
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Rebuild extension Typescript source after making changes
jlpm build

You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.

# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm watch
# Run JupyterLab in another terminal
jupyter lab

With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).

By default, the jlpm build command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:

jupyter lab build --minimize=False

Development uninstall

pip uninstall jupyterchatz

In development mode, you will also need to remove the symlink created by jupyter labextension develop command. To find its location, you can run jupyter labextension list to figure out where the labextensions folder is located. Then you can remove the symlink named jupyterchatz within that folder.

Testing the extension

Frontend tests

This extension is using Jest for JavaScript code testing.

To execute them, execute:

jlpm
jlpm test

Integration tests

This extension uses Playwright for the integration tests (aka user level tests). More precisely, the JupyterLab helper Galata is used to handle testing the extension in JupyterLab.

More information are provided within the ui-tests README.

Packaging the extension

See RELEASE

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

jupyterchatz-0.1.10.tar.gz (192.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

jupyterchatz-0.1.10-py3-none-any.whl (39.3 kB view details)

Uploaded Python 3

File details

Details for the file jupyterchatz-0.1.10.tar.gz.

File metadata

  • Download URL: jupyterchatz-0.1.10.tar.gz
  • Upload date:
  • Size: 192.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.4

File hashes

Hashes for jupyterchatz-0.1.10.tar.gz
Algorithm Hash digest
SHA256 0ae5bf46809f485bd4fcf3962c3808f787813640aaef79b7b6e4644970fa3172
MD5 ec66e9e767d3a18b2bf1fb20472f4bbc
BLAKE2b-256 4fb0f78fe576b457219461f7b1cc9701ef0359042b8e063fffd335de632a3e9f

See more details on using hashes here.

File details

Details for the file jupyterchatz-0.1.10-py3-none-any.whl.

File metadata

  • Download URL: jupyterchatz-0.1.10-py3-none-any.whl
  • Upload date:
  • Size: 39.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.4

File hashes

Hashes for jupyterchatz-0.1.10-py3-none-any.whl
Algorithm Hash digest
SHA256 1fe52b19dd284adcf4be9b266a9e29990a39372bf5b295904b6b11006bf0b96d
MD5 960b6aa7d3899ed296bfb38542a1daef
BLAKE2b-256 e1acaa882c898e9446e10c05645c64061adaf39dc8f1786a7b010c8774b42f7d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page