| 127.0.0.1 http://www.hqhole.com | |
| 127.0.0.1 http://www.hdsexdino.com | |
| 127.0.0.1 http://pornbigvideo.com/ | |
| 127.0.0.1 http://www.sweetshow.com | |
| 127.0.0.1 http://mylust.com/ | |
| 127.0.0.1 https://www.sleazyneasy.com | |
| 127.0.0.1 http://www.sexpulse.tv | |
| 127.0.0.1 http://www.sexmole.com | |
| 127.0.0.1 www.spankbang.com/ | |
| 127.0.0.1 http://spankbang.com/ |
People
 :bowtie: |
😄 :smile: |
😆 :laughing: |
|---|---|---|
😊 :blush: |
😃 :smiley: |
:relaxed: |
😏 :smirk: |
😍 :heart_eyes: |
😘 :kissing_heart: |
😚 :kissing_closed_eyes: |
😳 :flushed: |
😌 :relieved: |
😆 :satisfied: |
😁 :grin: |
😉 :wink: |
😜 :stuck_out_tongue_winking_eye: |
😝 :stuck_out_tongue_closed_eyes: |
😀 :grinning: |
😗 :kissing: |
😙 :kissing_smiling_eyes: |
😛 :stuck_out_tongue: |
The Microsoft Kinect for Azure (k4a) is only supported officially for Ubuntu 18.04.
Here are instructions to install its library in a more recent OS:
# Download these two .deb files:
wget https://packages.microsoft.com/ubuntu/18.04/prod/pool/main/libk/libk4a1.4-dev/libk4a1.4-dev_1.4.1_amd64.deb
wget https://packages.microsoft.com/ubuntu/18.04/prod/pool/main/libk/libk4a1.4/libk4a1.4_1.4.1_amd64.deb
The CLO Standalone program is a software application used for designing and simulating garments in a digital environment. It allows users to create 3D models of clothing from 2D patterns. The program can simulate fabric properties and garment behavior, showing how materials drape and move. Users can adjust patterns and fabrics and see the changes in real time. CLO Standalone supports importing and exporting various file formats for patterns and 3D models. It provides tools for measuring,
| # latest supported electron version as of october 2024 | |
| LATEST_SUPPORTED_VERSION=30 | |
| RED='\033[0;31m' | |
| GREEN='\033[0;32m' | |
| NC='\033[0m' # no color | |
| mdfind "kind:app" 2>/dev/null | sort -u | while read app; | |
| do | |
| filename="$app/Contents/Frameworks/Electron Framework.framework/Electron Framework" | |
| if [[ -f $filename ]]; then |
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.
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.
Content :
| #!/bin/bash | |
| set -euo pipefail | |
| # ----------------------------------------------------------------------------- | |
| # AWS ECS Shell Connector | |
| # ----------------------------------------------------------------------------- | |
| # Purpose: | |
| # Interactive helper to open a shell (or run a command) inside an ECS | |
| # container using AWS Systems Manager ExecuteCommand. | |
| # |
| // the cursor itself glides between cells instead of jumping. | |
| // Unlike a trail shader, this one is the focused cursor, so it | |
| // requires ghostty's own cursor to be hidden: | |
| // | |
| // cursor-opacity = 0 | |
| // custom-shader = "./shaders/cursor_glide.glsl" | |
| // --- CONFIGURATION --- | |
| const float DURATION = 0.14; // seconds for one glide |