SciencePlots VS paperetl

This seems quite similar to plotnine [0], which also provides a grammar of graphics interface for Python. That said, I love ggplot and I can't wait to use this in my research! I hope we can port/re-implement ggthemes, scientificplots [1], and other ggplot libraries for lets-plot.

0: https://plotnine.readthedocs.io/en/stable/

1: https://github.com/garrettj403/SciencePlots

What is it about matplotlib that you object to? If it’s just the number of commands needed to get it right, you can look at something like https://github.com/garrettj403/SciencePlots that will get you most of the way.

I know a lot of academics that do, but wouldn't recommend it personally. Also, there is https://github.com/garrettj403/SciencePlots

Seeing as you're doing bioinformatics, I recommend Juptyer notebooks and pandas if you're not already. The pandas documentation is very extensive which is helpful. I also recommend SciencePlots for publication quality plots.

I have also found SciencePlots. Should I use this in addition to cmcrameri?

Nice project!

I've spent quite a lot of time in the medical/scientific literature space. With regards to LLMs, specifically RAG, how the data is chunked is quite important. With that, I have a couple projects that might be beneficial additions.

paperetl (https://github.com/neuml/paperetl) - supports parsing arXiv, PubMed and integrates with GROBID to handle parsing metadata and text from arbitrary papers.

paperai (https://github.com/neuml/paperai) - builds embeddings databases of medical/scientific papers. Supports LLM prompting, semantic workflows and vector search. Built with txtai (https://github.com/neuml/txtai).

While arbitrary chunking/splitting can work, I've found that integrating parsing that has knowledge of medical/scientific paper structure increases the overall accuracy and experience of downstream applications.

paperai | paperetl

paperai and paperetl are a set of projects to consider for this task.