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jupyterlab_ws_chat

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A chat extension for Jupyterlab, based on websocket for exchanging messages.

This package is composed of a Python package named jupyterlab_ws_chat for the server side and a NPM package named jupyterlab-ws-chat

screenshot

Requirements

  • JupyterLab >= 4.0.0

Install

To install the package, execute:

pip install jupyterlab_ws_chat

Uninstall

To remove the package, execute:

pip uninstall jupyterlab_ws_chat

Using the chat

The chat UI is composed of a list of messages and an input to send new messages.

A message can be edited or deleted by its author, using a dedicated toolbar in the message.

Open the chat

The chat can be opened from the left panel .

Notifications and navigation

If enabled in settings, new unread messages generate a notification.

A down arrow in the messages list allow to navigate to the last message. This button is highlighted if some new messages are unread.

(code-toolbar)=

Code toolbar

When code is inserted in a message, a toolbar is displayed under the code section (the options must be set up from the settings).

From this toolbar, the code can be copied to the clipboard:

If a notebook is opened and visible (and has an active cell), other actions are available:

  • copy the code to a new cell above the active one:
  • copy the the code to a new cell below the active one:
  • replace the content of the active cell with the code:

Chat settings

Some jupyterlab settings are available for the chats in the setting panel (menu Settings->Settings Editor), with the entry Chat.

These settings includes:

  • sendWithShiftEnter

    Whether to send a message using Shift-Enter instead of Enter.
    Default: false

  • stackMessages

    Whether to stack consecutive messages from same user.
    Default: true

  • unreadNotifications

    Whether to enable or not the notifications on unread messages.
    Default: true

  • enableCodeToolbar

    Whether to enable or not the code toolbar.
    Default: true

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
# Install package in development mode
pip install -e ".[test]"
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Server extension must be manually installed in develop mode
jupyter server extension enable jupyterlab_ws_chat
# Rebuild 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

# Server extension must be manually disabled in develop mode
jupyter server extension disable jupyterlab_ws_chat
pip uninstall jupyterlab_ws_chat

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 jupyterlab-ws-chat within that folder.

Testing the package

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

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An extension providing a chat based on websocket

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