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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.

A non-exhaustive list of WebGL and WebGPU frameworks and libraries. It is mostly for learning purposes as some of the libraries listed are wip/outdated/not maintained anymore.

Engines and libraries ⚙️

Name	Stars	Last Commit	Description
three.js	![GitHub

Configuring Gammu for Mac OSX 10.11

Requirements

Disconnect modem first
Download and Install Driver USB Prolific for PL2303 Mac OS X
Reboot Mac
Install Homebrew

Step by step:

Type below command :

Setup a Local Only Email Server (Linux, Unix, Mac)

1 - Point localhost.com to your machine

Most of programs will not accept an email using just @localhost as domain. So, edit /etc/hosts file to make the domain localhost.com point to your machine, including this content to the file:

127.0.0.1 localhost.com

2 - Install Postfix

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

	"""Async and await example using subprocesses

	Note:
	Requires Python 3.6.
	"""

	import sys
	import time
	import platform
	import asyncio

	<!DOCTYPE html>
	<html>
	<body>
	<!-- 1. The <iframe> (and video player) will replace this <div> tag. -->
	<div id="player"></div>
	<div>Current Time: <span id="time"></span></div>

	<script>
	// 2. This code loads the IFrame Player API code asynchronously.
	var tag = document.createElement('script');

	function slugify(string) {
	const a = 'àáäâãåăæçèéëêǵḧìíïîḿńǹñòóöôœṕŕßśșțùúüûǘẃẍÿź·/_,:;'
	const b = 'aaaaaaaaceeeeghiiiimnnnoooooprssstuuuuuwxyz------'
	const p = new RegExp(a.split('').join('\|'), 'g')

	return string.toString().toLowerCase()
	.replace(/\s+/g, '-') // Replace spaces with -
	.replace(p, c => b.charAt(a.indexOf(c))) // Replace special characters
	.replace(/&/g, '-and-') // Replace & with 'and'
	.replace(/[^\w\-]+/g, '') // Remove all non-word characters

	var express = require('express');
	var app = express();
	var fs = require('fs');

	app.listen(3000, function() {
	console.log("[NodeJS] Application Listening on Port 3000");
	});

	app.get('/api/play/:key', function(req, res) {
	var key = req.params.key;