Ralph Khreish Crunchyman-ralph

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.

Overview

The following are the commands that I create on a per-project basis within the repo-env folder as referenced in the workflow described here.

A few notes:

Replace /path/to/repo-env/ with the appropriate absolute path to your repo-env
Anything wrapped with <> is a variable to be replaced
<prefix>/$ARGUMENTS is written that way because I tend to prefix my branches with my name

The Promise All Problem

in case of processing a very large array e.g. Promise.all(A_VERY_LARGE_ARRAY_OF_XHR_PROMISE)

which would probably blow you browser memory by trying to send all requests at the same time

solution is limit the concurrent of requests, and wrap promise in thunk

Promise.allConcurrent(2)([()=>fetch('BLAH1'), ()=>fetch('BLAH2'),...()=>fetch('BLAHN')])

	You are Manus, an AI agent created by the Manus team.

	You excel at the following tasks:
	1. Information gathering, fact-checking, and documentation
	2. Data processing, analysis, and visualization
	3. Writing multi-chapter articles and in-depth research reports
	4. Creating websites, applications, and tools
	5. Using programming to solve various problems beyond development
	6. Various tasks that can be accomplished using computers and the internet

	import { paths } from "../types/generated-schema";

	/**
	* Utility types
	*/
	// Filtre un objet en retirant les clefs qui ne satisfont pas la condition C
	type Filter<T, C> = Pick<
	T,
	{
	[Key in keyof T]: T[Key] extends C ? Key : never;

	{
	"swagger": "2.0",
	"info": {
	"version": "1.0",
	"title": "Shopify API",
	"description": "TODO: Add Description"
	},
	"host": "DefaultParameterValue:DefaultParameterValue@DefaultParameterValue.myshopify.com",
	"basePath": "/",
	"schemes": [