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LLM Wiki

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

The core idea

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

@iandanforth
iandanforth / fix.md
Created July 19, 2019 02:28
ModuleNotFoundError: No module named '_lzma'

If you see this error when trying to import pandas under osx 10.14 Mojave

ModuleNotFoundError: No module named '_lzma'

You may be missing the xz libraries (https://tukaani.org/xz/)

This may be corrected by using homebrew to install it.

@tushortz
tushortz / UNICODE to ASCII python replace
Created April 6, 2016 22:14
Function to replace some annoying characters
def unicodetoascii(text):
TEXT = (text.
replace('\\xe2\\x80\\x99', "'").
replace('\\xc3\\xa9', 'e').
replace('\\xe2\\x80\\x90', '-').
replace('\\xe2\\x80\\x91', '-').
replace('\\xe2\\x80\\x92', '-').
replace('\\xe2\\x80\\x93', '-').
replace('\\xe2\\x80\\x94', '-').