@jupyter-ai/core

jupyter_ai

A generative AI extension for JupyterLab

This extension is composed of a Python package named jupyter_ai for the server extension and a NPM package named jupyter_ai for the frontend extension.

Requirements

• JupyterLab >= 4.0.0
• Jupyter Server >= 2.0.0

Installation

You can use conda or pip to install Jupyter AI. If you're using macOS on an Apple Silicon-based Mac (M1, M1 Pro, M2, etc.), we strongly recommend using conda.

Before you can use Jupyter AI, you will need to install any packages and set environment variables with API keys for the model providers that you will use. See our documentation for details about what you'll need.

With pip

$ pip install jupyter_ai

With conda

First, install conda and create an environment that uses Python 3.11:

$ conda create -n jupyter-ai python=3.11
$ conda activate jupyter-ai
$ pip install jupyter_ai

Uninstall

To remove the extension, execute:

$ pip uninstall jupyter_ai

Troubleshoot

If you can see the extension UI, but it is not working, check that the server extension is enabled:

jupyter server extension list

If the server extension is installed and enabled, but you don't see the extension UI, verify that the frontend extension is installed:

jupyter labextension list

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 jupyter_ai directory
# Install package in development mode
pip install -e .
# 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 jupyter_ai
# 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

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

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 jupyter_ai within that folder.

Testing the extension

Server tests

This extension is using Pytest for Python code testing.

Install test dependencies (needed only once):

pip install -e ".[test]"

To execute them, run:

pytest -vv -r ap --cov jupyter_ai

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

Changelog

2.13.0

(Full Changelog)

Enhancements made

• Improve support for custom providers #713 (@dlqqq)
• Update Anthropic providers to use langchain_anthropic partner package #700 (@dlqqq)
• Add Claude-3-Haiku #696 (@srdas)
• Use AZURE_OPENAI_API_KEY for Azure OpenAI provider #691 (@aroffe99)
• /export added #658 (@apurvakhatri)

Bugs fixed

• Fix rendering of model IDs with a colon in their name #704 (@dlqqq)
• Update Anthropic providers to use langchain_anthropic partner package #700 (@dlqqq)
• Use new langchain-openai partner package #653 (@startakovsky)

Contributors to this release

(GitHub contributors page for this release)

@apurvakhatri | @aroffe99 | @dlqqq | @lumberbot-app | @srdas | @startakovsky | @welcome