timmyy123/llm-hub/init-gpu-server
Claude Code and agent skill by timmyy123/llm-hub
- community
Checking that the SKILL.md file is still in the repository.
Initialize a Draw Things GPU server with GPUScript, including script sync, Docker/CUDA/NVIDIA runtime setup, 7T data disk mounting, mergerfs, and end-to-end GPU verification.
Install
npx vskill@latest install timmyy123/llm-hub/init-gpu-serverSKILL.md
Init GPU Server Skill
Use this workflow when bringing up a new Draw Things GPU server reachable as root@HOST.
Goal
Prepare the server for Draw Things GPU workloads:
- sync GPUScript utilities to
/root/utils - install Docker, CUDA Toolkit, NVIDIA Container Toolkit, mergerfs, and Python utilities
- mount data disks at
/mnt/modelsand/mnt/loraModels - expose a merged model path at
/mnt/official-models - verify Docker can access all GPUs
Source Scripts
Repo source:
Important files:
update_scripts.sh: uploads files fromfiles_to_copy.txtto/root/utils/init_gpu_server.sh: installs Docker/CUDA/NVIDIA runtime, Python deps, network sysctl, and the Draw Things Docker imageLaunchGPU/remount_disk.sh: historical reference for disk remounting and mergerfs setupverify_gpu_setup.sh: remote verification helper
Script Hygiene
Before running the init script:
If working from an older branch, make sure init_gpu_server.sh has these properties:
- Uses noninteractive apt/dpkg with a lock timeout:
- Uses the remote OS version for the CUDA repo, not a hardcoded Ubuntu release:
- Propagates the remote SSH exit code from
init_server; do not forcereturn 0. - Does not require
ssh -tfor automation. - Disk prompt
readlines tolerate EOF, for exampleread -p "..." DISK1 || DISK1="". - Avoids single quotes inside the large single-quoted
INIT_COMMANDSstring.
Upload Scripts
Accept the SSH host key if needed:
Upload the GPUScript files:
Expected remote destination:
Run Init
Run:
This should install/configure:
- Docker CE and containerd
- CUDA Toolkit
- NVIDIA Container Toolkit
- mergerfs
/opt/draw-things-venvwithtqdm,schedule, andboto3- network sysctl tuning for large TCP buffers and BBR
drawthingsai/draw-things-grpc-server-cli:latest
It is acceptable to skip disk mounting inside this script. Mount disks explicitly after inspecting lsblk.
Apt/Dpkg Recovery
If apt or dpkg fails on a conffile prompt, such as /etc/cloud/cloud.cfg, repair the remote package state:
If a new run hits an apt lock, inspect first:
If an earlier init process is still installing packages, wait. Do not kill package-manager processes unless the user explicitly asks.
Disk Inspection
Inspect block devices and current mounts before changing disks:
Target shape:
Do not assume device names. Pick the two 7T data disks from actual lsblk output. On one validated host the mapping was:
Raw 7T Disk Setup
If the two 7T disks are raw disks with no partitions and no filesystem, get explicit user approval before partitioning and formatting. This destroys data on those disks.
After approval, replace MODELS_DISK and LORA_DISK with the inspected devices:
For non-NVMe disks, adjust partition paths accordingly. NVMe partition paths normally use the p1 suffix.
Mount And Persist
After partitions/filesystems exist, mount them by UUID and persist in /etc/fstab:
Use /mnt/official-models, not /mnt/official_models, for Draw Things GPU server conventions.
Verification
Always verify directly, even if the init script prints success:
Then run an end-to-end Docker GPU test:
Success means the container sees GPUs through the NVIDIA runtime.
Expected Healthy State
For an 8x RTX 5090 host, a healthy result looked like:
nvidia-smilists 8 GPUs- host driver version is
580.173.02 /usr/local/cuda/bin/nvcc --versionreports CUDA Toolkit13.3nvidia-ctk --versionreports NVIDIA Container Toolkit1.19.1- Docker has an
nvidiaruntime drawthingsai/draw-things-grpc-server-cli:latestexists locally- Docker GPU test container runs
nvidia-smisuccessfully lsblkshows both 7T partitions mounted:
df -hshows/mnt/models,/mnt/loraModels, and/mnt/official-models
Reboot
If /var/run/reboot-required exists, tell the user. GPU/Docker may work before reboot, but reboot is the clean final state after kernel, firmware, CUDA, or driver setup:
Security
- Security scanPassed, 90 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingios/LLMHub/LocalPackages/draw-things-community/.agents/skills/init-gpu-server/SKILL.md
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