BigBlueHat BigBlueHat

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.

Best AI Box Hardware for Your Home Server — 2026 Buyer's Guide

🦀 Get ClawBox — OpenClaw, ready out of the box in 5 minutes · 15W · one-time €549 → clawbox.tech

The "AI box" category exploded in 2025. Now there are a dozen options, and the specs are confusing. This guide cuts through the noise and tells you what actually matters when picking AI box hardware for a home AI server setup.

What Is an AI Box?

An AI box is a compact, purpose-built device designed to run local AI workloads — language models, vision models, voice recognition — without cloud connectivity. Think of it as a NAS, but for AI inference.

Case 1: Match literal followed_account_id, Finds 3 Rows
Case 2: Where followed_account_id = SUBQUERY, Finds 0 Rows
Case 3: Join via CTE Finds 3 Rows
Case 4: Join via Temp Table Finds 3 Rows
Case 5: Where followed_account_id = SUBQUERY (of Temp Table), Finds 0 Rows
Analysis

Knowledge Space

https://w3id.org/knowledge-space/

version 1.0, 27 April 2026

by Tobias Kuhn

Cite as: Tobias Kuhn. Knowledge Space. https://w3id.org/knowledge-space/. Version 1.0. 2026.

Highlight Selection Ranges

Code here takes a DOM Selection Range instance and starts traversing a DOM starting from startContainer up to endContainer and wraps Text elements with elements that have semi-transparent background & swaps img elements with clones that are styled to have semi-transparent yellow overlay.

Issues

Only handles selecting text and images & would not cover divs with backgrounds for instance.

	{
	"vc-data-model-2.0": {
	"introduction": [],
	"conformance": [
	"A conforming processor is any algorithm realized as software and/or hardware that generates and/or consumes a conforming secured document according to the relevant normative statements in Section 4. Algorithms. Conforming processors MUST produce errors when non-conforming documents are consumed."
	],
	"basic-concepts": [
	"The type property MUST be present. It is used to express the type of verifiable presentation. One value of this property MUST be VerifiablePresentation, but additional types MAY be included. The related normative guidance in Section 4.5 Types MUST be followed."
	],
	"contexts": [],

	const jsonld = require('jsonld');

	const input = {
	"@context": {
	"@vocab": "http://vocab.example/"
	},
	"age": {
	"@value": "27",
	"@type": "http://www.w3.org/2001/XMLSchema#integer"
	}

	{% assign relBase = '' %}
	{% assign tempDepth = page.url \| append: 'hackish-solution' \| split: '/' \| size \| minus: 2 %}
	{% for i in (1..tempDepth) %}
	{% assign relBase = relBase \| append: "../" %}
	{% endfor %}
	{% if relBase == '' %}
	{% assign relBase = './' %}
	{% endif %}

	#!/bin/bash

	echo "#############################################################"
	echo "#############################################################"
	echo "## Infoblox to bind export script ##"
	echo "## This script should be run on ##"
	echo "## a server allowed transfer the zones ##"
	echo "## the zones by transfer ##"
	echo "#############################################################"
	echo "#############################################################"