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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.

@tonyc726
tonyc726 / exchange.js
Created December 24, 2015 11:45
JS数字金额大写转换
var digitUppercase = function(n) {
var fraction = ['角', '分'];
var digit = [
'零', '壹', '贰', '叁', '肆',
'伍', '陆', '柒', '捌', '玖'
];
var unit = [
['元', '万', '亿'],
['', '拾', '佰', '仟']
];
@staltz
staltz / introrx.md
Last active April 29, 2026 16:47
The introduction to Reactive Programming you've been missing
@gre
gre / easing.js
Last active March 22, 2026 21:46
Simple Easing Functions in Javascript - see https://github.com/gre/bezier-easing
/*
* This work is free. You can redistribute it and/or modify it under the
* terms of the Do What The Fuck You Want To Public License, Version 2,
* as published by Sam Hocevar. See the COPYING file for more details.
*/
/*
* Easing Functions - inspired from http://gizma.com/easing/
* only considering the t value for the range [0, 1] => [0, 1]
*/
EasingFunctions = {