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.

rexim

// cc -w -include time.h -o qlock qlock.c // MIT Copyright (c) Tsoding
char*s="// cc -w -include time.h -o qlock qlock.c // MIT Copyright (c) Tsoding\n"
"char*s=\"?\";x,y,d[8],i,dx;f[]={31599,19812,14479,31207,23524,29411,29679,\n"
"30866,31727,31719,1040};char*so,*si;p(ch){i=x/2/(3+2);dx=x/2%(3+2);if(i<8&&(y-5)\n"
"/2<5&&dx<3&&(f[d[i]]>>((5-(y-5)/2-1)*3+dx))&1)printf(\"\\033[1;41;30m%c\\033[0m\",ch\n"
");else printf(\"%c\",ch);if(ch=='\\n'){y+=1;x=0;}else x+=1;}gd(){time_t t=time(NULL);struct\n"
" tm*tm=localtime(&t);d[0]=tm->tm_hour/10;d[1]=tm->tm_hour%10;d[2]=10;d[3]=tm->tm_min\n"
"/10;d[4]=tm->tm_min%10;d[5]=10;d[6]=tm->tm_sec/10;d[7]=tm->tm_sec%10;}main(){for\n"
"(gd();;printf(\"\\n\\033[%dA\\033[%dD\",y+1,x),sleep(1),gd())for(so=s,x=0,y=0;*so;so++\n"
")if(*so==63)for(si=s;*si;si++)switch(*si){case'\\n':p('\\\\');p('n');p('\"');p('\\n')\n"

joelonsql

🗺🐘 1000+ PostgreSQL EXTENSIONs

This is a list of URLs to PostgreSQL EXTENSION repos, listed in alphabetical order of parent repo, with active forks listed under each parent.

⭐️ >= 10 stars
⭐️⭐️ >= 100 stars
⭐️⭐️⭐️ >= 1000 stars
Numbers of stars might not be up-to-date.

sebawebber

package main

import (
	"log"
	"time"

	"github.com/go-pg/pg"
)

const maxWorkers = 5

clarkdave

#
# Reference implementation of a load balanced PgBouncer service on Amazon ECS
#
# see: https://engineering.loyaltylion.com/load-balanced-pgbouncer-service-on-amazon-ecs-f02120d1733e
#

resource "aws_lb" "pgbouncer" {
  name               = "${var.environment}-pgbouncer"
  internal           = true
  load_balancer_type = "network"

gvilarino

while true;do clear; curl https://banco.santanderrio.com.ar/exec/cotizacion/index.jsp 2> /dev/null | grep \<td\>| sed -n 2p|awk '{ gsub("[<td>\/]*[[:blank:]]*","");print}'; sleep 60; done;

magnetikonline

Add user ssh-agent as daemon to Ubuntu 18.04LTS server

Create a new systemd user unit, which starts ssh-agent upon login to server. Will remain resident until the final session for the user has logged out.

Steps

• Create /etc/systemd/user/ssh-agent.service.

• Run the following commands (under your user account, not root) to install the systemd unit and start:

ErikAugust

#include <stdio.h>
#include <stdlib.h>
#include <stdint.h>
#ifdef _MSC_VER
#include <intrin.h> /* for rdtscp and clflush */
#pragma optimize("gt",on)
#else
#include <x86intrin.h> /* for rdtscp and clflush */
#endif

terabyte

Prologue

I wrote this answer on stackexchange, here: https://stackoverflow.com/posts/12597919/

It was wrongly deleted for containing "proprietary information" years later. I think that's bullshit so I am posting it here. Come at me.

The Question

Amazon is a SOA system with 100s of services (or so says Amazon Chief Technology Officer Werner Vogels). How do they handle build and release?

fabriziomello

ssl = off 
maintenance_work_mem = 2GB 
work_mem = 2GB 
fsync = off 
synchronous_commit = off 
wal_level = minimal
max_wal_senders = 0 
archive_mode = off 
wal_buffers = -1
wal_writer_delay = 20ms