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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.

<!-- i have to warn you, this code SUCKS! i DO NOT recommend using this code, but you can if you want -->
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@greenstevester
greenstevester / how-to-setup-ollama-on-a-macmini.md
Last active April 4, 2026 20:28
April 2026 TLDR setup for Ollama + Gemma 4 12B on a Mac mini (Apple Silicon) — auto-start, preload, and keep-alive

April 2026 TLDR setup for Ollama + Gemma 4 on a Mac mini (Apple Silicon) — auto-start, preload, and keep-alive

April 2026 TLDR Setup for Ollama + Gemma 4 on a Mac mini (Apple Silicon)

Prerequisites

  • Mac mini with Apple Silicon (M1/M2/M3/M4/M5)
  • At least 16GB unified memory for Gemma 4 (default 8B)
  • macOS with Homebrew installed