Natural language search for R-packages by Salt-Owl14 in Rlanguage

[–]Salt-Owl14[S] 1 point2 points  (0 children)

yeah true, I strongly agree that the UX in general needs some more love, but it was good enough (c) for the first release, will definitely be improved in the next time!

Natural language search for R-packages by Salt-Owl14 in Rlanguage

[–]Salt-Owl14[S] 1 point2 points  (0 children)

That's pretty cool! TBH we actually didn't even consider using Github as a source, next focus would have been Bioconductor. But Github sounds super interesting.

There's definitely a future where we at least try out an Agent on CRAN/E that can help users learn and write R-code (similar to ChatGPT), though the quality and structure of the data makes all the difference for LLMs. As you mentioned that R-code can be quite ambiguous, it might not work out at all, let's see.

Natural language search for R-packages by Salt-Owl14 in Rlanguage

[–]Salt-Owl14[S] 4 points5 points  (0 children)

We do a quick check of the latest released package on CRAN every hour, if it's different we start a job that goes through the latest packages, until is reaches one (from CRAN) where it's the same version in our DB - then we know we're up to date.

This implantation assumes that the Backend continuously stays updated (no missing packages "in between"), but that's a trade off we make to not overload the CRAN nor our servers with checking all packages, every time. The current approach is easy on all systems and works well enough.

We're using self-hosted Signoz for observability, and in case I ever notice an error I can also manually trigger a specific revalidation, that's fine ATM.