Colter Bowman MojoCreator

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.

Spatial SQL and PostGIS

This set of instructions goes with this presentation deck.

Installing PostGIS

PGDG Yum Repository

https://yum.postgresql.org/

yum install postgis24_10

Introduction

So HAProxy is primalery a load balancer an proxy for TCP and HTTP. But it may act as a traffic regulator. It may also be used as a protection against DDoS and service abuse, by maintening a wide variety of statistics (IP, URL, cookie) and when abuse is happening, action as denying, redirecting to other backend may undertaken ([haproxy ddos config], [haproxy ddos])

	import type {
	CollectionBeforeOperationHook,
	FileData,
	Plugin,
	UploadCollectionSlug,
	} from 'payload'

	type AspectRatios = Record<string, number>

	type Collections = Partial<Record<UploadCollectionSlug, AspectRatios>>

	import argparse
	import json
	import logging
	import os
	import re
	import shutil
	from concurrent.futures import ProcessPoolExecutor, as_completed
	from dataclasses import dataclass
	from datetime import datetime
	from typing import Any, Callable, Dict, List, Literal, Optional, Tuple

	'''
	https://arxiv.org/abs/2312.00858
	1. put this file in ComfyUI/custom_nodes
	2. load node from <loaders>

	start_step, end_step: apply this method when the timestep is between start_step and end_step
	cache_interval: interval of caching (1 means no caching)
	cache_depth: depth of caching
	'''

	CREATE TABLE dict_english (
	word varchar NOT NULL
	);

	CREATE UNIQUE INDEX dict_english_word_idx ON dict_english (word);

	# IMPORTANT!
	# This gist has been transformed into a github repo
	# You can find the most recent version there:
	# https://github.com/Neo23x0/auditd

	# ___ ___ __ __
	# / \| __ ______/ (_) /_____/ /
	# / /\| \|/ / / / __ / / __/ __ /
	# / ___ / /_/ / /_/ / / /_/ /_/ /
	# /_/ \|_\__,_/\__,_/_/\__/\__,_/

	function custom_pre_get_posts_query( $q ) {

	$tax_query = (array) $q->get( 'tax_query' );

	$tax_query[] = array(
	'taxonomy' => 'product_cat',
	'field' => 'slug',
	'terms' => array( 'clothing' ), // Don't display products in the clothing category on the shop page.
	'operator' => 'NOT IN'
	);