Simon Willison’s Weblog

marimo v0.9.0 with mo.ui.chat. The latest release of the Marimo Python reactive notebook project includes a neat new feature: you can now easily embed a custom chat interface directly inside of your notebook.

Marimo co-founder Myles Scolnick posted this intriguing demo on Twitter, demonstrating a chat interface to my LLM library “in only 3 lines of code”:

import marimo as mo
import llm

model = llm.get_model()
conversation = model.conversation()
mo.ui.chat(lambda messages: conversation.prompt(messages[-1].content))

I tried that out today - here’s the result:

marimo.ui.chat() takes a function which is passed a list of Marimo chat messages (representing the current state of that widget) and returns a string - or other type of renderable object - to add as the next message in the chat. This makes it trivial to hook in any custom chat mechanism you like.

Marimo also ship their own built-in chat handlers for OpenAI, Anthropic and Google Gemini which you can use like this:

mo.ui.chat(
    mo.ai.llm.anthropic(
        "claude-3-5-sonnet-20240620",
        system_message="You are a helpful assistant.",
        api_key="sk-ant-...",
    ),
    show_configuration_controls=True
)

# 5th October 2024, 10:59 pm / llm, marimo, python, llms, ai, generative-ai

Serializing package requirements in marimo notebooks. The latest release of Marimo - a reactive alternative to Jupyter notebooks - has a very neat new feature enabled by its integration with uv:

One of marimo’s goals is to make notebooks reproducible, down to the packages used in them. To that end, it’s now possible to create marimo notebooks that have their package requirements serialized into them as a top-level comment.

This takes advantage of the PEP 723 inline metadata mechanism, where a code comment at the top of a Python file can list package dependencies (and their versions).

I tried this out by installing marimo using uv:

uv tool install --python=3.12 marimo

Then grabbing one of their example notebooks:

wget 'https://raw.githubusercontent.com/marimo-team/spotlights/main/001-anywidget/tldraw_colorpicker.py'

And running it in a fresh dependency sandbox like this:

marimo run --sandbox tldraw_colorpicker.py

Also neat is that when editing a notebook using marimo edit:

marimo edit --sandbox notebook.py

Just importing a missing package is enough for Marimo to prompt to add that to the dependencies - at which point it automatically adds that package to the comment at the top of the file:

# 17th September 2024, 6:06 pm / uv, python, marimo

marimo.app. The Marimo reactive notebook (previously) - a Python notebook that's effectively a cross between Jupyter and Observable - now also has a version that runs entirely in your browser using WebAssembly and Pyodide. Here's the documentation.

# 29th June 2024, 11:07 pm / jupyter, pyodide, webassembly, python, observable, marimo

Marimo (via) This is a really interesting new twist on Python notebooks.

The most powerful feature is that these notebooks are reactive: if you change the value or code in a cell (or change the value in an input widget) every other cell that depends on that value will update automatically. It’s the same pattern implemented by Observable JavaScript notebooks, but now it works for Python.

There are a bunch of other nice touches too. The notebook file format is a regular Python file, and those files can be run as “applications” in addition to being edited in the notebook interface. The interface is very nicely built, especially for such a young project—they even have GitHub Copilot integration for their CodeMirror cell editors.

# 12th January 2024, 9:17 pm / jupyter, open-source, python, observable, github-copilot, marimo