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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.

@gocarlos
gocarlos / Eigen Cheat sheet
Last active June 25, 2026 19:12
Cheat sheet for the linear algebra library Eigen: http://eigen.tuxfamily.org/
@zfogg
zfogg / fizzbuzz.hs
Last active June 25, 2026 19:11
overly-complex fizzbuzz
import Data.List (transpose)
-- These are infinite lists with a cycle of a "string" followed by N "" empty strings,
-- ["string", "", "", "string", "", "", ...]
fizzs = concat $ repeat $ "Fizz" : replicate 2 ""
buzzs = concat $ repeat $ "Buzz" : replicate 4 ""
fizzBuzzs = concat $ repeat $ "FizzBuzz" : replicate 14 ""
-- All the non-negative integers as strings
-- ["0", "1", "2", ...]
@KrasimirKralev
KrasimirKralev / README.md
Last active June 25, 2026 19:10
Hermes Agent on NVIDIA Jetson Orin Nano — Practical setup guide, config, and health-check script for running a self-hosted AI agent on edge hardware

Hermes Agent on NVIDIA Jetson Orin Nano — Field Notes

Practical setup tips, performance observations, and gotchas from running a self-hosted AI agent runtime on a Jetson Orin Nano (8 GB) in production-like conditions.

Why the Orin Nano?

The Jetson Orin Nano is an odd duck: ARM64, 7–8 GB RAM shared between CPU/GPU, no x86 emulation shortcuts, and a Linux kernel that's just different enough to trip you up. But it's also:

  • Cheap to run (~15 W under load)
  • Silent (fan-cooled, no coil whine)
import json
import pickle
import struct
import zipfile
import numpy as np
from sentencepiece import SentencePieceProcessor
def rms_norm(x): return (x / np.sqrt(np.square(x).mean(-1, keepdims=True) + 1e-6))
def softmax(x): return (np.exp(x - np.max(x, axis=-1, keepdims=True))) / np.sum((np.exp(x - np.max(x, axis=-1, keepdims=True))), axis=-1, keepdims = True)

The Pack Optimizer, introduced in Minecraft Preview v1.26.40.27, is invoked by passing a config file path as a command-line argument to the server executable. It is used to optimize creator packs for runtime loading.

bedrock_server.exe PackOptimizerConfigPath=<config.json>

Note

This is a standalone operation. The server processes the packs and exits, it does not start a normal game session.


@fufexan
fufexan / macos_accel.py
Created September 12, 2024 20:18
macOS-like acceleration curve for libinput
@DiegoRBaquero
DiegoRBaquero / readme.md
Last active June 25, 2026 18:59
Running Claude Code with a local LLM