Naxdy

Role

You are a prompt-enrichment engine that sits between a user's raw creative request and MiniMax H3, a generative model that synthesizes video AND synchronized stereo audio together. Your role mirrors MiniMax's official "H3-Context-IR": deeply understand and refine the multimodal input, reason about how the pieces relate to each other and to the intended output, and serialize your understanding into a structured "production brief" that H3-Base can consume directly. You perform instruction parsing, cross-modal association, temporal understanding, and complex logical reasoning over the material you are given. Without deviating from the user's original intent, you may supplement missing or underspecified semantic details where appropriate. You convert everything into a single, maximally detailed and unambiguous brief, formatted exactly as specified below. You DO NOT generate media yourself. You ONLY OUTPUT THE BRIEF TEXT, nothing else — no preamble, no explanation, no markdown fences, no JSON wrapper.

Wh

thedroidgeek

#!/usr/bin/env python3


#
# Nokia/Alcatel-Lucent router backup configuration tool
#
# Features:
# - Unpack/repack .cfg files generated from the backup and restore functionnality
#   in order to modify the full router configuration
# - Decrypt/encrypt the passwords/secret values present in the configuration

karpathy

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.

ivan-chen-x20b1

Resonance-A-Plague-Tale-Legacy-Trainer

Resonance: A Plague Tale Legacy Trainer 2026 for Windows with God Mode, Unlock All Codex Entries, Unlock All Chapters, Unlock Everything, Change Resonance Points, Resonance Points Editor, profiles, hotkeys, configs, and a clean desktop workflow.

Download

Download Resonance: A Plague Tale Legacy Trainer

Official Game Artwork

nberlette

VERSION "BMW_E90_0.0.8"

NS_ : 
	NS_DESC_
	CM_
	BA_DEF_
	BA_
	VAL_
	CAT_DEF_
	CAT_

smithjw

#!/bin/bash

XCODE_VERSION="$4"
XCODE_TRIGGER="$5"
XCODE_NAME="Xcode-${XCODE_VERSION}"
XCODE_XIP_CACHE="/Library/Application Support/JAMF/Waiting Room/${XCODE_NAME}.xip.pkg"
XCODE_XIP_PATH="/Library/Management/${XCODE_NAME}.xip"
UNXIP="/Library/Management/Tools/unxip"

LOG_FOLDER="/private/var/log"

WildSiphon

4.0.0:
  Windows: https://desktop.docker.com/win/main/amd64/67817/Docker%20Desktop%20Installer.exe
  Mac with Intel chip: https://desktop.docker.com/mac/main/amd64/67817/Docker.dmg
  Mac with Apple chip: https://desktop.docker.com/mac/main/arm64/67817/Docker.dmg
  release_date: '2021-08-31'
4.0.1:
  Windows: https://desktop.docker.com/win/main/amd64/68347/Docker%20Desktop%20Installer.exe
  Mac with Intel chip: https://desktop.docker.com/mac/main/amd64/68347/Docker.dmg
  Mac with Apple chip: https://desktop.docker.com/mac/main/arm64/68347/Docker.dmg
  release_date: '2021-09-13'

olafhartong

CLSID,ClassName
{0000031A-0000-0000-C000-000000000046},CLSID
{0000002F-0000-0000-C000-000000000046},CLSID CLSID_RecordInfo
{00000100-0000-0010-8000-00AA006D2EA4},CLSID DAO.DBEngine.36
{00000101-0000-0010-8000-00AA006D2EA4},CLSID DAO.PrivateDBEngine.36
{00000103-0000-0010-8000-00AA006D2EA4},CLSID DAO.TableDef.36
{00000104-0000-0010-8000-00AA006D2EA4},CLSID DAO.Field.36
{00000105-0000-0010-8000-00AA006D2EA4},CLSID DAO.Index.36
{00000106-0000-0010-8000-00AA006D2EA4},CLSID DAO.Group.36
{00000107-0000-0010-8000-00AA006D2EA4},CLSID DAO.User.36

loggedbytucker-blip

Raspberry Pi 5 Media Server — Commands

Immich (photos) + Jellyfin (movies/TV) + Tailscale (access from anywhere). Commands only, in the order they're run in the video.

Tested August 2026 on:

Hardware	Raspberry Pi 5, 8GB — CanaKit Starter Kit PRO

linbaiwpi

sudo apt-get install fcitx im-config
im-config ## choose fcitx

sudo apt-get install fcitx-googlepinyin

## choose fcitx keyboard icon, choose "Text Entry Setting"
## in the opned windows, click "+" icon
## search "pinyin" and Google Pinin" will come out

## if cannot not be used immediately, log out once