serverAppConfigs/docs/deployment.md

Deployment and Update Process

This page describes how to deploy and update the LLM servers on Dankserver and Dankclaw. The process uses git as the single source of truth. All script edits flow through this repository.

Overview

Two servers run LLM inference services. Each server pulls its scripts from this repository. The deployment process moves a committed change from the repository to a running service.

Target	Host	Runtime	Service	Port
Dankserver	dank@dankserver	llama.cpp FastMTP (Qwen3.8-27B IQ4_XS + FastMTP 32K draft + ngram-mod)	frank-default-large	7770
Dankclaw	dank@dankclaw	vLLM ROCm (Avesed Qwen3.6-35B-A3B INT8 W8A8, ngram spec)	frank-default-small	52625

Workflow

The deployment workflow has six steps.

graph LR
    A[Edit scripts locally] --> B[Commit]
    B --> C[Push to origin<br>Gitea on Dankclaw]
    C --> D[Pull on target<br>git pull]
    D --> E[Restart systemd service]
    E --> F[Verify health endpoint]

1. Fetch the current script from the target machine.
2. Commit the fetched version in this repository.
3. Edit the script locally in the working tree.
4. Commit and push the change to origin.
5. Pull the change on the target machine.
6. Restart the service and verify that it is healthy.

Deploy Script

The scripts/deploy.sh script executes steps 4 through 6. Run it from the repository root.

Run this command to deploy to Dankserver:

FRANK_SUDO_PW=... ./scripts/deploy.sh dankserver

Run this command to deploy to Dankclaw:

FRANK_SUDO_PW=... ./scripts/deploy.sh dankclaw

Add the --dry-run flag to preview without making changes:

./scripts/deploy.sh dankserver --dry-run

The script does these actions:

1. Verifies that the local working tree has no uncommitted changes.
2. Pushes the main branch to origin.
3. Pulls the repository on the target machine.
4. Symlinks the systemd unit, reloads systemd, enables, and restarts the service.
5. Waits for the health endpoint to respond (over ssh).

Set FRANK_SUDO_PW when running headless, so that remote sudo reads the password from stdin (sudo -S). The passwordless restart helpers from the retired topology are obsolete and are not used.

Health endpoints:

• Dankserver: http://127.0.0.1:7770/health
• Dankclaw: http://127.0.0.1:52625/health

Manual Update

Update Dankserver (frank-default-large)

Run these commands on Dankserver:

cd /home/dank/vLLM
git pull origin main
sudo ln -sf /home/dank/vLLM/scripts/frank-default-large.service /etc/systemd/system/frank-default-large.service
sudo systemctl daemon-reload
sudo systemctl restart frank-default-large
curl -sf http://127.0.0.1:7770/health

Update Dankclaw (frank-default-small)

Run these commands on Dankclaw:

cd /home/dank/vllmScripts
git pull origin main
sudo ln -sf /home/dank/vllmScripts/scripts/frank-default-small.service /etc/systemd/system/frank-default-small.service
sudo systemctl daemon-reload
sudo systemctl restart frank-default-small
curl -sf http://127.0.0.1:52625/health

Service Units

Dankserver — frank-default-large

The active service on Dankserver is llama.cpp serving Qwen3.8-27B-Uncensored-HauhauCS-Aggressive-IQ4_XS.gguf under the alias frank-default-large on port 7770. It runs the patched FastMTP build (/home/dank/llama.cpp-fastmtp/build/bin/llama-server, commit 4df29be + the HauhauCS patch) with the FastMTP 32K draft sidecar (--spec-type draft-mtp, --spec-draft-n-max 2, --spec-draft-ngl all) and the ngram-mod fallback. Context 131072 (128K, single slot), KV K q8_0 + V f16, batch 2048 / ubatch 1024, --no-mmap, full GPU offload. The unit file is scripts/frank-default-large.service. It launches through scripts/serve-frank-large.sh, which reads tunables from scripts/frank-default-large.env.

Dankclaw — frank-default-small

The active service on Dankclaw is vLLM (ROCm) serving Avesed/Qwen3.6-35B-A3B-INT8-W8A8 under the served model name frank-default-small on port 52625. Full 262144 context, unquantized KV cache, --max-num-seqs 4, --max-num-batched-tokens 16384, ngram speculative decoding, --reasoning-parser qwen3. The unit file is scripts/frank-default-small.service. It launches through scripts/serve-frank-small.sh, which reads tunables from scripts/frank-default-small.env.

Validation

The deploy script checks the health endpoint after a restart. For deeper checks, run a completion request against the endpoint:

curl -s http://127.0.0.1:7770/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"frank-default-large","messages":[{"role":"user","content":"Say OK"}]}'

Troubleshooting

If the health check fails after a deploy:

1. Read the service logs with journalctl -u <service> -n 200.
2. Confirm that the model files exist in the cache.
3. Confirm that the GPU has free memory (nvidia-smi on Dankserver, rocm-smi on Dankclaw).
4. Check the service status with systemctl status <service>.

Incident: HIP Runtime Crash From the TEMP Env Variable (2026-08-13)

On 2026-08-13 the old frank-default-large service crash-looped for hours on Dankclaw. Root cause: the env files exported TEMP=1.0 (a sampling default). The ROCm HIP runtime reads TEMP as its JIT kernel-cache directory, used the path 1.0, failed, and segfaulted on a NULL object. Fix: rename the sampling variable to TEMPERATURE (commit 227ce01).

If a service segfaults at load with no obvious cause, compare the exported env against the HIP runtime's env reads. Do not name any tunable TEMP, HOST, or GPU_MAX_HEAP_SIZE.

Incident: Jobs "Released Prematurely" Under Parallel Load (2026-08-13)

Historical: on the retired topology, parallel jobs on the Dankserver 35B service died with a cuBLAS crash under researcher load. The affected service is retired. A client abort logs W srv stop: cancel task, id_task = N; a natural stop logs only slot release with truncated = 0. The server never preempts a running generation.

See Also

• AGENTS.md — the git workflow rules
• README.md — repository overview
• index.md — knowledge base index
• frank-redo-2026-08-17.md — the full redo runbook
• serverAppConfigs knowledge base — the sibling Podman app stack on the same hosts