RamstorageAI

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.

RamstorageAI

import requests

url = "https://api.mistral.ai/v1/chat/completions"
token = "API_KEY"
model = "mistral-medium"

prompt = """
John and Mark are in a room with a ball, a basket and a box. John puts the ball in the box, then leaves for work. While John is away, Mark puts the ball in the basket, and then leaves for school. They both come back together later in the day, and they do not know what happened in the room after each of them left the room. Where do they think the ball is?
"""