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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.

area_data = {
'臺北市': [
'中正區', '大同區', '中山區', '萬華區', '信義區', '松山區', '大安區', '南港區', '北投區', '內湖區', '士林區', '文山區'
],
'新北市': [
'板橋區', '新莊區', '泰山區', '林口區', '淡水區', '金山區', '八里區', '萬里區', '石門區', '三芝區', '瑞芳區', '汐止區', '平溪區', '貢寮區', '雙溪區', '深坑區', '石碇區', '新店區', '坪林區', '烏來區', '中和區', '永和區', '土城區', '三峽區', '樹林區', '鶯歌區', '三重區', '蘆洲區', '五股區'
],
'基隆市': [
'仁愛區', '中正區', '信義區', '中山區', '安樂區', '暖暖區', '七堵區'
],