Tomasz Kalinowski
@t-kalinowski.bsky.social
2K followers 950 following 33 posts
Software Engineer at Posit PBC. I mostly post about R, Python, and Deep Learning. Github: https://github.com/t-kalinowski
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Reposted by Tomasz Kalinowski
smachlis.bsky.social
The {ragnar} #RStats 📦 has a new function to inspect a data store: ragnar_store_atlas() , which visualizes the store, @t-kalinowski.bsky.social tells #Positconf2025
Reposted by Tomasz Kalinowski
smachlis.bsky.social
My Workshop for Ukraine is THIS THURSDAY, 11 Sept! Donate to help medics save lives in Ukraine *and* learn how to query text data with R and the {ragnar} #RStats 📦
Can't make it from noon to 2 ET? Register and you'll get access to recording and materials. Thank you! ❤️
www.machlis.com/workshop/
Sharon's Workshop for Ukraine
Help medics save lives in Ukraine. Learn a skill or sponsor a student & support a cause.
www.machlis.com
Reposted by Tomasz Kalinowski
vincentab.bsky.social
I'd love feedback on this #marginaleffects WIP.

In GLMs with many parameters, the marginaleffects 📦 can get a 5–20x speedup (and better SEs) by calling JAX for automatic differentiation.

Try the instructions at this link and let me know if you run into trouble.

Thanks!

github.com/vincentarelb...
Reposted by Tomasz Kalinowski
dariia.bsky.social
❗️Our next workshop will be on September 11th, 6 pm CEST, on RAG in R with ragnar by @smachlis.bsky.social

Register or sponsor a student by donating to support Ukraine!
Details: bit.ly/3wBeY4S
Please share!
#AcademicSky #EconSky #RStats
Reposted by Tomasz Kalinowski
andrewholz.bsky.social
Finally got Glimpse out focused on what the Posit open source team has been up to. Turns out its quite a bit! posit.co/blog/posit-g...
I continue to be happy with the approach we (Posit) are taking with LLMs and AI. Too impactful to ignore but focus on useful and safe as much as possible.
Posit
Posit's latest glimpse newsletter highlights new product releases, including the Positron IDE and several new LLM-powered tools.
posit.co
t-kalinowski.bsky.social
New release of quickr v0.2.0 on CRAN #rstats!

New: runif(), more control flow, more ops, many many bug fixes.

Also, I've been experimenting with chatgpts codex (cloud) in quickr. It's pretty useful! I added some setup scripts to make it easier to get started.

changelog: github.com/t-kalinowski...
t-kalinowski.bsky.social
ragnar v0.2.1 is now on CRAN.

It's full of small improvements! The most impactful is that registered retrieval tools now never return previously seen chunks, giving LLMs a robust ability to do deep searches.

announcement: www.tidyverse.org/blog/2025/08...
changelog: ragnar.tidyverse.org/news/
ragnar 0.2
ragnar 0.2 introduces a tidy, transparent toolkit for building Retrieval-Augmented Generation (RAG) pipelines in R.
www.tidyverse.org
Reposted by Tomasz Kalinowski
handle.invalid
There's so many parallel sessions at #JSM2025 that it's hard to choose where to go, so I web-scraped the schedule and made a chatbot to help.

I've made it public, so hopefully it can help you too - try it out 👉 shiny.mitchelloharawild.com/jsm2025/
A screenshot of my JSM 2025 Agenda Chat bot, featuring the answer to "when is Mitchell O'Hara-Wild presenting".
t-kalinowski.bsky.social
This would be a prime example to showcase quickr!
t-kalinowski.bsky.social
ragnar should support this if you provide a custom `embed` function, e.g., using a local graph embedding model via reticulate, or if you just insert chunks with precomputed embeddings. This would be a good example for us to add to docs! Feel free to open a github issue if you run into any problems!
Reposted by Tomasz Kalinowski
strictlystat.bsky.social
The @posit.co new reticulate package with managed/uv python implementation really changed the game (and speed) of using modules without a huge condaenv overhead. In scripts but also big for packages with python deps.
Reposted by Tomasz Kalinowski
t-kalinowski.bsky.social
It works with shiny! We’ve deployed ragnar on a few connect apps already.
Some models are more or less eager to call tools; it depends on the model. If you’re seeing an error, please open a github issue!
t-kalinowski.bsky.social
Other highlights:

- `read_as_markdown()` handles HTML better, now supports selectors
- Store inspector now displays chunk context and looks nicer.
- More embedding providers (Google, Databricks, Bedrock)

Full changelog: ragnar.tidyverse.org/news/
Changelog
ragnar.tidyverse.org
t-kalinowski.bsky.social
#ragnar 0.2.0 is on CRAN #rstats!

It has a MUCH improved chunker; markdown_chunk() picks better boundaries, builds context, segments by headings, and handles overlapping chunks. Oh, and ragnar_retrieve() can deoverlap retrieved chunks now.

Website got a big update too: ragnar.tidyverse.org
Retrieval-Augmented Generation (RAG) Workflows
Provides tools for implementing Retrieval-Augmented Generation (RAG) workflows with Large Language Models (LLM). Includes functions for document processing, text chunking, embedding generation, storag...
ragnar.tidyverse.org
t-kalinowski.bsky.social
Can’t believe I forgot to share this back in February... Check out this intro to RAG by @christophscheuch.bsky.social! blog.tidy-intelligence.com/posts/rapid-...

RAG before ragnar!

It’s also a good intro to ragnar internals, since ragnar makes similar implementation choices.
Reposted by Tomasz Kalinowski
jonocarroll.fosstodon.org.ap.brid.gy
New post: https://jcarroll.com.au/2025/06/29/counting-digits-quickly/

What if you could just wave a magic wand over your R #rstast :rstats: code and have it transform into something that ran as fast as or faster than C? @t_kalinowski's {quickr} 'R to Fortran Transpiler' does that for you! […]
Original post on fosstodon.org
fosstodon.org
t-kalinowski.bsky.social
Easiest way is probably to pin all package versions to a known working date:

py_require(exclude_newer = "2025-06-09")
t-kalinowski.bsky.social
We recently added a new "Getting Started" guide ragnar.tidyverse.org/articles/rag...

Blog post coming soon!
t-kalinowski.bsky.social
I wonder what happens if you train with a regularizer that penalizes super weights like this. I’m guessing the model quantizes better, maybe becomes more robust, or makes more efficient use of weights.
Reposted by Tomasz Kalinowski
posit.co
Posit @posit.co · May 27
Introducing the btw package for teaching LLM chat apps about your #RStats package!

Inject "invisible" messages into chats via system prompts and use tool calls to dynamically fetch context when needed.

Check out a dplyr example and learn more in @simonpcouch.com's post! posit.co/blog/custom-...
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