A generative AI extension for JupyterLab
Project description
jupyter_ai
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 >= 3.5 (not JupyterLab 4)
- 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.
Because of Ray's incompatibility with Python 3.11, you must use Python 3.9, or 3.10 with Jupyter AI. The instructions below presume that you are using Python 3.10.
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 3.10:
$ conda create -n jupyter-ai python=3.10
$ conda activate jupyter-ai
$ pip install jupyter_ai
If you are using an Apple Silicon-based Mac (M1, M1 Pro, M2, etc.), you need to uninstall the pip provided version of grpcio and install the version provided by conda instead.
$ pip uninstall grpcio; conda install grpcio
Uninstall
To remove the extension, execute:
$ pip uninstall jupyter_ai
Usage with GPT-3
To use the GPT3ModelEngine in jupyter_ai, you will need an OpenAI API key.
Copy the API key and then create a Jupyter config file locally at config.py to
store the API key.
c.GPT3ModelEngine.api_key = "<your-api-key>"
Finally, start a new JupyterLab instance pointing to this configuration file.
jupyter lab --config=config.py
If you are doing this in a Git repository, you can ensure you never commit this
file on accident by adding it to .git/info/exclude.
Alternately, you can also specify your API key while launching JupyterLab.
jupyter lab --GPT3ModelEngine.api_key=<api-key>
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
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
Release history Release notifications | RSS feed
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