marimo VS unstructured

marimo (https://marimo.io/) - raising the bar for ML and data science notebooks

> Another advantage that I didn't see mentioned in TFA is parallelism

That's something we're thinking about and designing:

https://github.com/marimo-team/marimo/issues/1103

Feel free to join the conversation there if you have thoughts!

We do support GitHub Copilot in the pip/conda installable version that you can run locally on your computer. (https://github.com/marimo-team/marimo)

We have considered adding more copilot features for refactoring or text-to-cell.

i use marimo for this sort of stuff. Its a jupyter alike, but can be used to make simple internal apps

https://github.com/marimo-team/marimo

He is an example: https://marimo.io/@public/signal-decomposition

We use web components in our project (a reactive Python notebook that, among other things, lets users build simple web apps [1]) to make it easy for the user to instantiate and compose our UI elements. Users can easily interpolate these elements into markdown, for example, since their representation is just HTML.

[1] https://github.com/marimo-team/marimo

Thanks for sharing! marimo is free and open source (Apache 2.0): https://github.com/marimo-team/marimo

It's been under development for over a year and is used in research, science, and education across a number of labs and companies. We'll have lots more to share soon!

Be careful with unstructured:

https://github.com/Unstructured-IO/unstructured/blob/d11c70c...

from: https://github.com/open-webui/open-webui/issues/687

I’ve been looking at this

https://freeling-user-manual.readthedocs.io/en/v4.2/modules/...

at the freeling library in general, also spaCy and NLTK. The chunking algorithms being used in the likes of LangChain are remarkably bad surprisingly.

There is also

https://github.com/Unstructured-IO/unstructured

But I don’t like it, can’t explain why yet.

My intuition is that 1st step is clean sentences and paragraphs and titles/labels/headers. Then probably an LLM can handle outlining and table of contents generation using a stripped down list of objects in the text.

BRIO/BERT summarization could also have a role of some type.

Those are my ideas so far.

Unstructured is the best one I’ve used so far: https://www.unstructured.io

https://www.unstructured.io/ can parse PDFs, then you can feed all of them to Claude, which has a 100k context window.

If the copy & pase method does not work: One approach is to use the functionality of Unstructured to parse the PDF. If need be, it can do OCR on the PDF too if you have Detectron2 installed. After conversion you would still have to save it as an excel file though.

I would check out https://github.com/Unstructured-IO/unstructured (what lang chain uses) or https://github.com/axa-group/Parsr (probably what unstructured copied to get their startup off the ground lol)