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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.

@BinaryMuse
BinaryMuse / README.md
Last active February 1, 2017 00:51
Integrating React with Marionette

Integrating React with Marionette

See ReactComponentView and BackboneModelWatchMixin, below.

Notes

The BackboneModelWatchView could use some additional methods to allow adding/removing watched models after the component is created.

@bobholt
bobholt / resources.md
Last active August 8, 2022 21:03
Roost Resources
@Vp3n
Vp3n / gist:5340891
Created April 8, 2013 21:55
Allowing CORS (Cross-Origin Resource Sharing) requests from grunt server
//Allowing CORS (Cross-Origin Resource Sharing) requests from
// grunt server, put this into Gruntfile.js
grunt.initConfig({
connect: {
livereload: {
options: {
port: 9000,
hostname: 'localhost',
middleware: function (connect) {
return [