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@jshaw
jshaw / byobuCommands
Last active April 21, 2026 04:59
Byobu Commands
Byobu Commands
==============
byobu Screen manager
Level 0 Commands (Quick Start)
------------------------------
<F2> Create a new window
@wikrie
wikrie / fritzbox-cert-update.sh
Last active January 4, 2026 06:19
Fritzbox Fritz!Box AVM SSL Letsencrypt automatically update
#!/bin/bash
## this little Gist is for Copy the Letsencrypt Cert from an Linux machine (e.g. Raspberry PI or Synology NAS)
## to the router (Fritzbox).
## It is usefull to be able to speak to the Router over DDNS without any Cert issue in the Browser.
## thanks to https://gist.github.com/mahowi for the perfect Idea
## put it in /etc/letsencrypt/renewal-hooks/post so it gets run after every renewal.
## since Fritz OS 7.25 it is needed to select a Username, from a security point of view
## it is always a good idea to have a non default user name. And as normaly a Fritz Box
## is connected to the Internet, the prefered method should be WITH Username.
@wassupdoc
wassupdoc / gist:f57e65d2a5f52101a5ec6f65355e85c2
Last active November 25, 2020 10:58
Freenas iocage Resilio install
# make temp file that will cause iocage to install some packages
echo '{"pkgs":["ca_root_nss"]}' > /tmp/pkg.json
# create jail
iocage create -n "rslsync" -p /tmp/pkg.json -r 11.3-RELEASE ip4_addr="vnet0|YOURRESILIOIP/24" defaultrouter="ROUTERIP" vnet="on" allow_raw_sockets="1" boot="on"
# remove the temp file
rm /tmp/pkg.json
#make our iocage directories
iocage exec rslsync mkdir -p /config
iocage exec rslsync mkdir -p /mnt/syncdata
@AveYo
AveYo / .. MediaCreationTool.bat ..md
Last active May 22, 2026 01:06
Universal MediaCreationTool wrapper for all MCT Windows 10 versions - MOVED TO github.com/AveYo/MediaCreationTool.bat

Calibre-web on FreeNAS

Creating the Jail

  • Step 1 - Name Jail and Choose FreeBSD Release

    • Name: calibre-jail
    • Jail Type: Default(Clone Jail)
    • Release: 11.3-RELEASE
## Will successfully install amdgpu drivers and rocm,
## but pointless as there is no gpu device attached to WSL2 (only CUDA and DirectML is supported, not /dev/kfd or amd gpus)
## ROCM/HIP
sudo apt update
sudo apt dist-upgrade
sudo apt install libnuma-dev
wget -q -O - http://repo.radeon.com/rocm/rocm.gpg.key | sudo apt-key add -
echo 'deb [arch=amd64] http://repo.radeon.com/rocm/apt/debian/ xenial main' | sudo tee /etc/apt/sources.list.d/rocm.list
# If Debian 11 is ran on a LXC container (Proxmox), SSH login and sudo actions can be slow
# Check if in /var/log/auth.log the following messages
Failed to activate service 'org.freedesktop.login1': timed out (service_start_timeout=25000ms)
-> Run systemctl mask systemd-logind
-> Run pam-auth-update (and deselect Register user sessions in the systemd control group hierarchy)

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.

@rohitg00
rohitg00 / llm-wiki.md
Last active May 23, 2026 03:20 — forked from karpathy/llm-wiki.md
LLM Wiki v2 — extending Karpathy's LLM Wiki pattern with lessons from building agentmemory

LLM Wiki v2

A pattern for building personal knowledge bases using LLMs. Extended with lessons from building agentmemory 10K Stars ⭐️, a persistent memory engine for AI coding agents.

This builds on Andrej Karpathy's original LLM Wiki idea file. Everything in the original still applies. This document adds what we learned running the pattern in production: what breaks at scale, what's missing, and what separates a wiki that stays useful from one that rots.

What the original gets right

The core insight is correct: stop re-deriving, start compiling. RAG retrieves and forgets. A wiki accumulates and compounds. The three-layer architecture (raw sources, wiki, schema) works. The operations (ingest, query, lint) cover the basics. If you haven't read the original, start there.