Byungwoo Jeon byung-u

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.

AWS CLI JMESPath cheatsheet

Random query recipes of JMESPath for the AWS CLI tools that I might have written or stumbled upon.

Examples

An Ansible summary

Jon Warbrick, July 2014, V3.2 (for Ansible 1.7)

Configuration file

intro_configuration.html

First one found from of

	function gbr --description "Git browse commits"
	set -l log_line_to_hash "echo {} \| grep -o '[a-f0-9]\{7\}' \| head -1"
	set -l view_commit "$log_line_to_hash \| xargs -I % sh -c 'git show --color=always % \| diff-so-fancy \| less -R'"
	set -l copy_commit_hash "$log_line_to_hash \| xclip"
	set -l git_checkout "$log_line_to_hash \| xargs -I % sh -c 'git checkout %'"
	set -l open_cmd "open"

	if test (uname) = Linux
	set open_cmd "xdg-open"
	end

	" FZF.vim now supports this command out of the box
	" so this code is no longer needed.
	command! -bang -nargs=* Rg
	\ call fzf#vim#grep(
	\ 'rg --column --line-number --hidden --ignore-case --no-heading --color=always '.shellescape(<q-args>), 1,
	\ <bang>0 ? fzf#vim#with_preview({'options': '--delimiter : --nth 4..'}, 'up:60%')
	\ : fzf#vim#with_preview({'options': '--delimiter : --nth 4..'}, 'right:50%:hidden', '?'),
	\ <bang>0)

	upstream upstream_close_server_keepalive_timeout_0 {
	server upstream:10443;
	}

	upstream upstream_keepalive_server_keepalive_timeout_0 {
	server upstream:11443;
	keepalive 64;
	}

	upstream upstream_close_server_keepalive_timeout_300 {

	import boto3
	import sys

	ec2 = boto3.client('ec2')

	# Grab where backup retention is 14 days so we can reduce it to 7
	instances = ec2.describe_instances(Filters=[{'Name': 'tag:Retention', 'Values': ['14']}])

	ids = []

	{
	"Version": "2012-10-17",
	"Id": "arn:aws:sqs:YOUR-AWS-REGION:YOUR-AWS-ACCOUNT-ID:YOUR-QUEUE-NAME/SQSDefaultPolicy",
	"Statement": [
	{
	"Sid": "example-statement-ID",
	"Effect": "Allow",
	"Principal": {
	"AWS": "*"
	},

	import socket

	hostname, sld, tld, port = 'www', 'integralist', 'co.uk', 80
	target = '{}.{}.{}'.format(hostname, sld, tld)

	# create an ipv4 (AF_INET) socket object using the tcp protocol (SOCK_STREAM)
	client = socket.socket(socket.AF_INET, socket.SOCK_STREAM)

	# connect the client
	# client.connect((target, port))

	man() {
	env \
	LESS_TERMCAP_mb=$(printf "\e[1;31m") \
	LESS_TERMCAP_md=$(printf "\e[1;31m") \
	LESS_TERMCAP_me=$(printf "\e[0m") \
	LESS_TERMCAP_se=$(printf "\e[0m") \
	LESS_TERMCAP_so=$(printf "\e[1;44;33m") \
	LESS_TERMCAP_ue=$(printf "\e[0m") \
	LESS_TERMCAP_us=$(printf "\e[1;32m") \
	man "$@"