Hands-On Large Language Models

What Hacker News says

1. 384028345Oct 2026
   Ask and... ye shall receive! Check out `Hands-On Large Language Models: Language Understanding and Generation`.

   ...I wanna mention this book as well, although it doesn't fit the criteria: https://www.thelittlelearner.com[

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2. ofrzetaSep 2026
   This should include "Hands-on Large Language Models" by Jay Alammar and Maarten Grootendorst.
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3. jayalammarNov 2024
   We actually just wrote a book with your profile in mind -- especially if by "AI" you're especially interested in LLMs and if you're a visual learner. It's called Hands-On Large Language Models and it contains 300 original figures explaining the main couple hundred intuitions and applications for these models. You can also read it online on the O'Reilly platform. I find that after acquiring the main intuitions, people find it much easier to move on to code implementations or papers.
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4. qwertoxApr 2025

     Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
   

   No text of the book in there.
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5. jamestimminsJan 2025
   Have you read his book Hands-On Large Language Models?

   Looks interesting, but I'm skeptical that a book can feasibly stay up to date with the speed of development.

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6. d4rkp4tternDec 2024
   Indeed, it has become the LLM equivalent of IBM, as in -- "No one ever got fired for choosing LangChain". A certain well-known ML person even runs a course on LangChain, as if it's a "fundamental" thing to know about LLMs. I was also surprised/disappointed to see that the otherwise excellent "Hands-on Large Language Models" book from O'Reilly has extensive examples using this library.

   In Apr 2023 we (CMU/UW-Madison researchers) looked into this lib to build a simple RAG workflow that was slightly different from the canned "chains" like RetrievalQAConversation or others, and ended up wasting time hunting docs and notebooks all over the place and going up and down class hierarchies to find out what exactly was going on. We decided it shouldn't have to be this hard, and started building Langroid as an agent-oriented LLM programming framework.

   In Langroid you set up a ChatAgent class which encapsulates an LLM-interface plus any state you'd like. There's a Task class that wraps an Agent and allows inter-agent communication and tool-handling. We have devs who've found our framework easy to understand and extend for their purposes, and some companies are using it in production (some have endorsed us publicly). A quick tour gives a flavor of Langroid: https://langroid.github.io/langroid/tutorials/langroid-tour/

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