Discover gists

## nigeria-state-and-lgas.json
[
  {
    "state": "Adamawa",
    "alias": "adamawa",
    "lgas": [
      "Demsa",
      "Fufure",
      "Ganye",
      "Gayuk",
      "Gombi",

## llm-wiki.md

      
              1 file
            
          
              222 forks
            
          
                20 comments
              
            
              1593 stars
            
          
                rohitg00
                / llm-wiki.md
            
            
              Last active
              July 21, 2026 21:43
                — forked from karpathy/llm-wiki.md
            
              
                LLM Wiki v2 — extending Karpathy's LLM Wiki pattern with lessons from building agentmemory
              
          
    LLM Wiki v2

A pattern for building personal knowledge bases using LLMs. Extended with lessons from building agentmemory 20K+ Stars ⭐️, a persistent memory engine for AI coding agents.
This builds on Andrej Karpathy's original LLM Wiki idea file. Everything in the original still applies. This document adds what we learned running the pattern in production: what breaks at scale, what's missing, and what separates a wiki that stays useful from one that rots.
What the original gets right

The core insight is correct: stop re-deriving, start compiling. RAG retrieves and forgets. A wiki accumulates and compounds. The three-layer architecture (raw sources, wiki, schema) works. The operations (ingest, query, lint) cover the basics. If you haven't read the original, start there.

  
## index.html
<!DOCTYPE html>
<html>
<head>
    <title></title>
	<meta charset="utf-8" />
    <script src="Scripts/jquery-1.9.1.min.js"></script>
    <link href="Content/bootstrap.min.css" rel="stylesheet" />
    <script src="Scripts/isRockFx.js"></script>
    <script>
        $(function () {

## LLM-RAG-OS.md

      
              1 file
            
          
              1 fork
            
          
                0 comments
              
            
              3 stars
            
          
                csnyder256
                / LLM-RAG-OS.md
            
            
              Created
              July 21, 2026 18:07
            
              
                Share this file with any agent. A 2nd brain OS for any LLM, fully genericized architecture spec with explicit builder fork points. Remote control, RAG, multi-agent/cross-family dispatching, sharing the same CLI that avoids degradation while continuously improving cross-repo/cross-org knowledge.
              
          
    Build Your Own Personal AI Operating System

A brand-, harness-, and frontend-agnostic blueprint you hand to a coding agent.
This document describes how to build a persistent, always-on personal AI system: a supervised background process that turns an incoming message into either an answer or real work in a real code repository, accumulates knowledge that compounds over time, runs governed background jobs, stays reachable from your phone or terminal, and never lets a language model's context window, an untrusted document, or a compromised account cross a safety boundary.
It is not a chatbot. The intelligent layer decides and delegates. It does not hold the durable state itself. The founding rule that everything else follows from: durable state lives in files and a database, brains are ephemeral, and the coordinating kernel is small and boring. No model context outlives a single session. Anything that must survive a crash, a restart, or a model downgrade lives on disk, never in a context window.


## Resources-Multitenant-Architecture.md

      
              1 file
            
          
              1 fork
            
          
                0 comments
              
            
              2 stars
            
          
                santoshshinde2012
                / Resources-Multitenant-Architecture.md
            
            
              Last active
              July 21, 2026 21:20
            
              
                Resources to start with Multi-tenant Architecture 
              
          
    Resources to start with Multi-tenant Architecture

Introduction

Multi tenant architecture is an ecosystem or model, in which a single environment can serve multiple tenants utilising a scalable, available, and resilient architecture. The underlying infrastructure is completely shared, logically isolated, and with fully centralised services.
SaaS Deep Dive: Designing and Building Multi-Tenant Solutions • Tod Golding • GOTO 2020

Creating a multi-tenant software-as-a-service (SaaS) application requires developers and architects to take new approaches to how they design, build, operate, and deploy their solutions. SaaS touches every dimension of your design, including how you decompose your system into services, how those services are built, how they are secured, how they store data, and how they are deployed.

  
## polars.md

      
              1 file
            
          
              9 forks
            
          
                2 comments
              
            
              20 stars
            
          
                bitsnaps
                / polars.md
            
            
              Last active
              July 21, 2026 21:18
            
              
                A cheat sheet for polars python package
              
          
    Polars Cheat Sheet

Here's a cheat sheet for the Polars Python package, covering many of its key functions and features:
Installation

pip install polars 

# Install Polars with all optional dependencies:
pip install 'polars[all]'

  
## gist:7dead7c1b517390e061e07759ed80277
# ============================================
# Ghostty Terminal - Complete Configuration
# ============================================
# File: ~/.config/ghostty/config
# Reload: Cmd+Shift+, (macOS)
# View options: ghostty +show-config --default --docs

# --- Typography ---
font-family = "Maple Mono NF CN"
font-size = 14

## llm-wiki.md

      
              1 file
            
          
              9001 forks
            
          
                994 comments
              
            
              43537 stars
            
          
                karpathy
                / llm-wiki.md
            
            
              Created
              April 4, 2026 16:25
            
              
                llm-wiki
              
          
    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.

  
## user-rt-true-score.js
(function() {
  'use strict';

  const waitForElement = (selector) => {
    return new Promise(resolve => {
      if (document.querySelector(selector)) return resolve(document.querySelector(selector));
      const observer = new MutationObserver(() => {
        const el = document.querySelector(selector);
        if (el) {
          observer.disconnect();

## Makefile
deploy:
	docker compose down -v && docker compose up -d
	[
	{
	"state": "Adamawa",
	"alias": "adamawa",
	"lgas": [
	"Demsa",
	"Fufure",
	"Ganye",
	"Gayuk",
	"Gombi",
	<!DOCTYPE html>
	<html>
	<head>
	<title></title>
	<meta charset="utf-8" />
	<script src="Scripts/jquery-1.9.1.min.js"></script>
	<link href="Content/bootstrap.min.css" rel="stylesheet" />
	<script src="Scripts/isRockFx.js"></script>
	<script>
	$(function () {
	# ============================================
	# Ghostty Terminal - Complete Configuration
	# ============================================
	# File: ~/.config/ghostty/config
	# Reload: Cmd+Shift+, (macOS)
	# View options: ghostty +show-config --default --docs

	# --- Typography ---
	font-family = "Maple Mono NF CN"
	font-size = 14
	(function() {
	'use strict';

	const waitForElement = (selector) => {
	return new Promise(resolve => {
	if (document.querySelector(selector)) return resolve(document.querySelector(selector));
	const observer = new MutationObserver(() => {
	const el = document.querySelector(selector);
	if (el) {
	observer.disconnect();