Install / setup

Structure

A Beaker install consists of the following:

• A Jupyter kernel (beaker-kernel)
• A Jupyter server (beaker-server) (optional but recommended)
• LLM integration (archytas) (optional)
• Custom contexts (contexts) (optional)

Installing the kernel

Beaker-kernel can be installed as a normal Python package via pip, by using Hatch, or as a docker image.

python (local)

Normal installation:

$ pip install .

Dev installation:

$ pip install -e .

During pip install, the kernel is automatically installed in the proper location in your development environment.

Dev setup

This package is bundled with a basic development UI for development and testing, wrapped in a docker image

To get started run this command:

$ make dev-install

This will ensure that all prerequisites are installed and ready for use, but you will need to update the .env file with your OpenAI/GPT API key to use the LLM.

To connect to the Terarium data service, you will need to update the .env file with the url of a running instance.

Once you have set up the environment and added your keys you can start the dev server by running:

$ make dev

This will start the Jupyter service and launch a specialized notebook interface in your browser similar to if you ran $ jupyter notebook normally.

Adding python dependencies/updating requirements

The python requirements are maintained by Hatch and are defined in the pyproject.toml file.

Please see the Hatch dependency documentation for more details.