Those are great links. I’ve been using:

https://github.com/npiv/chatblade https://github.com/tbckr/sgpt

I totally agree with LLM+CLI are perfect fit.

One pattern I used recently was httrack + w3m dump + sgpt images with gpt vision to generate a 278K token specific knowledge base with a custom perl hack for a RAG that preserved the outline of the knowledge.

Which brings me to my question for you - have you seen anything unix philosophy aligned for processing inputs and doing RAG locally?

EDIT. Turns out OP has done quite a bit toward what I’m asking. Written up here:

https://simonwillison.net/2023/Oct/23/embeddings/

Something I’m currently a bit hung up on is finding a toolchain for chunking content on which to create embeddings. Ideally it would detect location context, like section “2.1 Failover” or “Chapter 8: The dream” or whatever from the original text, also handle 80 character wide source unwrapping, smart splitting so paragraphs are kept together, etc etc.