Skip to content

Instantly share code, notes, and snippets.

View siegrainwong's full-sized avatar
💢
Learning

BaiYue siegrainwong

💢
Learning
  • Practice everything
View GitHub Profile

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.

@BSoD123456
BSoD123456 / dummy_9parchments.py
Created May 29, 2019 17:20
九张羊皮纸 STEAM版用 联机辅助脚本
#! python2
# -*- coding: utf-8 -*-
# 九张羊皮纸 STEAM版用 联机辅助脚本
# 本脚本用于,减少STEAM游戏九张羊皮纸在线游戏时的频繁掉线现象。
# 安装方法:
# 1, 请去Python官方网站下载Python 2.7版安装程序并安装。
# 版本一定必须是2.7或其子版本,若使用3以上版本将无法正确运行。
# 2, 请修改操作系统中的HOSTS文件,增加条目: 127.0.0.1 master.frozenbyte-online.com
using System;
using System.Runtime.CompilerServices;
using System.Threading.Tasks;
public static class TaskTupleExtensions
{
#region (Task<T1>)
public static TaskAwaiter<T1> GetAwaiter<T1>(this ValueTuple<Task<T1>> tasks)
{