Jim Ratliff jimratliff

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.

Unpacking “package” terminology in Python

Introduction

“Package” is an overloaded term in the context of Python projects

In the context of Python projects, “package” is often used, confusingly, to refer to at least three non-equivalent entities:

A structure that organizes modules for importation or execution, often a directory containing a __init__.py file, that contains one or more Python modules.
The Python project itself
A file (such as a wheel (.whl) or a source archive) associated with a particular release and even a particular platform of a particular Python project. This file can be downloaded and installed to make the project’s code available to the user.

Leading Python organizations provide definitions that could and should prevent confusion, but even those organizations continue to use “package” in confusing ways

	\definejdrsgame{3}{4}
	% Define the players' names
	\renewcommand{\Rplayernm}{Ms.\ Row}
	\renewcommand{\Cplayernm}{Mr.\ Column}

	% Define Column's strategies
	\readarray{ColumnStrategies}{A&B&C&D&E&F&G&H&I&J}
	%\ColumnStrategies(1)={A}
	%\ColumnStrategies(2)={B}
	%\ColumnStrategies(3)={C}