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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.

'621098' => '邮储银行-绿卡通-借记卡',
'622150' => '邮储银行-绿卡银联标准卡-借记卡',
'622151' => '邮储银行-绿卡银联标准卡-借记卡',
'622181' => '邮储银行-绿卡专用卡-借记卡',
'622188' => '邮储银行-绿卡银联标准卡-借记卡',
'955100' => '邮储银行-绿卡(银联卡)-借记卡',
'621095' => '邮储银行-绿卡VIP卡-借记卡',
'620062' => '邮储银行-银联标准卡-借记卡',
'621285' => '邮储银行-中职学生资助卡-借记卡',
'621798' => '邮政储蓄银行-IC绿卡通VIP卡-借记卡',
@JerryC8080
JerryC8080 / RexChainesPhone.js
Created March 21, 2016 08:08
匹配中国电话号码的正则表达式
/**
电信
中国电信手机号码开头数字
2G/3G号段(CDMA2000网络)133、153、180、181、189
4G号段 177
联通
中国联通手机号码开头数字