nezz imtaehyun

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.

Generating OpenAPI Swagger Documentation from Source Code, with GPT-4.1

written by atjsh

Idea

chatgpt can understand code
chatgpt can generate json
swagger documentations are written in json and spec are publicly accessable

[Project Name]

Every time you choose to apply a rule(s), explicitly state the rule(s) in the output. You can abbreviate the rule description to a single word or phrase.

Project Context

[Brief description ]

[more description]
[more description]
[more description]

LibreLinkUp HTTP-Dump

This document describes the HTTP communication of LibreLinkUp which functions as follower app to receive cgm data. Some data in the responses were masked.

Context

This dump was created on an android device with LibreLinkUp app. Capturing was done with HttpToolkit over adb.

API Url

how to leverage oracle's temping offers

free tier limits

The limits of the free tier say that you can create up to 4 instances.

x2 x86 instances (2core/1g)
x2 ampere instances (with 4core/24g spread between them)
200GB total boot volume space across all intances (minimum of 50G per instance)

[!WARNING]

AWS 학습 링크집 시리즈

AWS 트레이닝 및 자격증 소개 http://bit.ly/aws-tnc-intro
AWS 학습 자료집 http://bit.ly/aws-study-resource
AWS 공인 솔루션스 아키텍트 - 어소시에이트 수험 가이드 http://bit.ly/sacertguide
AWS 공인 개발자 - 어소시에이트 수험 가이드 http://bit.ly/devcertguide
AWS 보안 관련 컨텐츠 모음집 http://bit.ly/secontents
AWS 기반 빅데이터 학습자료집 http://bit.ly/bdonaws
AWS 딥러닝 학습 자료 모음집 http://bit.ly/dlonaws
2019년 re:Invent 에서 공개된 AI/ML관련 서비스 소개 http://bit.ly/2019-ml-recap

	// ==UserScript==
	// @name Medium Paywall Bypass
	// @namespace Violentmonkey Scripts
	// @run-at document-start
	// @match ://.medium.com/*
	// @match ://medium.com/
	// @match :///*
	// @grant none
	// @version 3.0
	// @inject-into content

	new Promise((resolve, reject) => {
	var xhr = new XMLHttpRequest();
	xhr.open("GET", `https://endic.naver.com/searchAssistDict.nhn?query=${text}`, true);
	xhr.onreadystatechange = function() {
	if (xhr.readyState == 4) {
	const content_word = /<div class="box_a">((.\|\n)*?)<\/div>/g
	const filter_word = /<span class="fnt_k20"><strong>(.+)<\/strong><\/span>/g

	const body = xhr.responseText;
	let words = [];

	// create a bookmark and use this code as the URL, you can now toggle the css on/off
	// thanks+credit: https://dev.to/gajus/my-favorite-css-hack-32g3
	javascript: (function() {
	var elements = document.body.getElementsByTagName('*');
	var items = [];
	for (var i = 0; i < elements.length; i++) {
	if (elements[i].innerHTML.indexOf('* { background:#000!important;color:#0f0!important;outline:solid #f00 1px!important; background-color: rgba(255,0,0,.2) !important; }') != -1) {
	items.push(elements[i]);
	}
	}

	import 'dart:io';

	import 'package:flutter/material.dart';

	void main() => runApp(new MyApp());

	class MyApp extends StatelessWidget {
	@override
	Widget build(BuildContext context) {
	return new MaterialApp(