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vec715 / llm-wiki.md
Created April 5, 2026 11:09 — forked from karpathy/llm-wiki.md
llm-wiki

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.

@vec715
vec715 / Setup Podman on Chrome OS Flex and Crostini.md
Last active December 2, 2025 22:59
Setup Podman on Chrome OS Flex and Crostini

Actual versions for this guide:

  • Operating System: Debian GNU/Linux 12 (bookworm)
  • Kernel: Linux 6.1.64-09049-g010fe86d9eae
  • Architecture: x86-64
  • Podman: v1.7.1

Installation

1. Install Podman:

sudo apt install podman
@vec715
vec715 / aws_json_to_env.py
Created June 29, 2023 21:13
Parse AWS JSON ENV into .env format
import json
def aws_json_to_env(input_json):
with open('.env', 'w') as file:
for item in input_json:
try:
file.write(f'{item["name"]}={item["value"]}\n')
except TypeError:
print(f"Expected a dictionary, but got: {item}")
except KeyError: