fairchild

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.

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.

rmtbb

javascript:(function(){try{navigator.clipboard.readText().then(function(t){if(t){var e=window.open("","_blank","width=800,height=600");e.document.open(),e.document.write(t),e.document.close()}else alert("Clipboard is empty. Please copy some text to the clipboard first.")}).catch(function(t){console.error("Failed to read clipboard contents: ",t),alert("An error occurred while trying to access the clipboard. Please ensure your browser allows clipboard access.")})}catch(t){console.error("An error occurred:",t),alert("An error occurred while trying to open the new window with the clipboard content.")}})();//bookmarklet_title: HTML Preview from Clipboard

cpursley

PostgreSQL is Enough

See the new site: https://postgresisenough.dev

---

• Simplify: move code into database functions
• Just Use Postgres for Everything
• Just use Postgres
• PostgreSQL is the worlds’ best database

rain-1

Purpose

Bootstrap knowledge of LLMs ASAP. With a bias/focus to GPT.

Avoid being a link dump. Try to provide only valuable well tuned information.

Prelude

Neural network links before starting with transformers.

kshirsagarsiddharth

vrslev

import os

import arel
from fastapi import FastAPI, Request
from fastapi.templating import Jinja2Templates

app = FastAPI()
templates = Jinja2Templates("templates")

if _debug := os.getenv("DEBUG"):

pcreux

#!/usr/bin/env ruby
# Generate a dbdiagram for dbdiagram.io from a dbt project.
#
# Usage:
#   1. Run `dbt docs generate` first.
#   2. Run `dbt_to_dbdiagram.rb`
#   3. Paste the output in https://dbdiagram.io/

require 'yaml'
require 'json'

mashhoodr

addEventListener('fetch', event => {
  event.respondWith(handleRequest(event.request))
})

/**
 * Respond to the request
 * adapted from https://github.com/xiaoyang-liu-cs/workers-proxy
 * @param {Request} request
 */
async function handleRequest(request) {

abelsonlive

#!/usr/bin/env python
import json
import copy
import sys
import argparse
from datetime import datetime, timedelta
from subprocess import Popen, PIPE


# dictionary of partiton names to variable generating functions