idvoretskyi

= Arch Linux step-by-step installation =
= http://blog.fabio.mancinelli.me/2012/12/28/Arch_Linux_on_BTRFS.html =


== Boot the installation CD ==

== Create partition ==

cfdisk /dev/sda
 * Create a partition with code 8300 (Linux)

scrubmx

mysql -p
expect 'Enter password:'
send 'YOUR_MYSQL_PASSWORD'

# Create the development database
CREATE DATABASE IF NOT EXISTS develop
GRANT ALL ON develop.* TO 'forge'@'localhost'

# Create the production database
CREATE DATABASE IF NOT EXISTS production

xxblx

upstream php-handler {
    server  unix:/run/php-fpm/www.sock;
}

server {
    #listen 443 ssl;
    listen 80;
    server_name 192.168.1.8;

    #ssl_certificate /etc/ssl/nginx/cloud.example.com.crt;

sarthology

let regex;

/* matching a specific string */
regex = /hello/; // looks for the string between the forward slashes (case-sensitive)... matches "hello", "hello123", "123hello123", "123hello"; doesn't match for "hell0", "Hello" 
regex = /hello/i; // looks for the string between the forward slashes (case-insensitive)... matches "hello", "HelLo", "123HelLO"
regex = /hello/g; // looks for multiple occurrences of string between the forward slashes...

/* wildcards */
regex = /h.llo/; // the "." matches any one character other than a new line character... matches "hello", "hallo" but not "h\nllo"
regex = /h.*llo/; // the "*" matches any character(s) zero or more times... matches "hello", "heeeeeello", "hllo", "hwarwareallo"

karpathy

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.