Files
serverAppConfigs/AGENTS.md
T
Frank 7010f5b754 docs(frank-large): unsloth Qwen3.8-Flash-Next runbook; retire the CIRU Orca runbook
New runbook frank-large-unsloth-qwen38-flash-next.md (runtime, payload,
deployed config, the explicit -md, the 114 GiB GTT memory model, client
contract, rollback). frank-large-ciru-orca.md marked RETIRED (rollback
target, payload and runtime intact on disk). AGENTS.md topology row,
frank-large section, harness note, runbook index, and the GPU-budget
lesson (GTT aperture ~114 GiB, not the stale 64 GiB rocm-smi figure —
the CIRU Orca held 92.6 GiB on the same device). LLM index header,
mermaid, active list, and the vault root index updated. Work-log entry.
2026-09-21 12:30:35 -07:00

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# AGENTS.md — serverAppConfigs Agent Rules
## Overview
This repository is the single source of truth for the two homelab servers and
the FrankBook-Pro Mac mini. It tracks the Podman container stacks and the LLM
inference fleet. One repo, one checkout per host, one deploy script. All
services run from `/home/dank/serverAppConfigs` on each host (the 2026-08-22
merge absorbed the former `vllmScripts` repo, history preserved).
- **Dankserver** (192.168.0.235) — media/library stack (RomM, Copyparty,
Calibre-Web, Jellyfin, Plex) plus the `frank-medium` LLM service.
- **Dankclaw** (192.168.0.143) — AI/search/dev/observability stack (SearXNG
via Gluetun, ComfyUI, OpenWebUI, Hermes, Gitea, Grafana, Prometheus, Loki,
Alloy, Pi-hole) plus TWO LLM services: `frank-large` (unsloth llama.cpp prebuilt on
the gfx1151 iGPU) and `frank-small` (llama.cpp on the RTX 3090). Caddy on
Dankclaw reverse-proxies both hosts.
- **FrankBook-Pro** (192.168.0.112) — macOS mini running the *arr stack
(Prowlarr, Sonarr, Radarr, Lidarr, Readarr, qBittorrent) as quadlets inside
its podman machine; all egress rides the Gluetun WireGuard netns. Deployed
via the `frankbook-pro` handler.
## Fleet topology (ACTIVE)
| Target | Service | Runtime | Model | Port |
|--------|---------|---------|-------|------|
| Dankserver | `frank-medium` | vllm-radiance 0.9.3 (rootless Quadlet, image `localhost/radiance-vllm:0.9.3`, gfx1201) | orcarouter Qwen3.8-27B-Uncensored-FP8 (FP8 E4M3 block-wise, 30.9 GB / 7 shards) with the z-lab DFlash2 external drafter (depth 7, live mean accept length 4.24/7 — A/B tested and beats MTP self-speculation on decode: 100.0 vs 85.9 t/s), 2x Radeon AI PRO R9700 in ONE tensor-parallel process (TP=2 over the R4D one-shot allreduce — no RCCL collective; both cards on CPU root ports at Gen5 x8 since the 2026-09-20 ProArt B850-Creator swap), 262144 ctx over up to 8 conversations (auto-sized 384,238-token KV pool = 1.47x the window), fp8 KV, prefix caching, vision | 7770 |
| Dankclaw | `frank-large` | unsloth llama.cpp b11030 prebuilt (ROCm gfx1151, root systemd unit) | unsloth Qwen3.8-Flash-Next UD-IQ4_XS on the gfx1151 iGPU (Strix Halo LPDDR, 114 GiB GTT), 200000 ctx single stream (1 slot), MTP depth 2 via the explicit `-md` shared-Q8_0 head, text only | 7770 |
| Dankclaw | `frank-small` | mainline llama.cpp master 37b53fd (root systemd unit) | HauhauCS Gemma4-12B-QAT-Uncensored-Balanced Q4_K_M (BF16 mmproj + MTP assistant sidecar, `draft-mtp,ngram-mod`) on the RTX 3090, 1048576 pool / 4 slots of 262,144, q8_0 KV, the fleet's fastest vision endpoint | 7771 |
Retired endpoints (`frank-npu`, and every prior runtime) are in
the [runbook index](#runbook-index). The full swap history lives in
`serverAppConfigs-docs/LLM/index.md` — do not grow it here.
## Repository Layout
- `dankserver/` — compose.yaml + Caddyfile + .env.example for the media stack
- `dankclaw/` — compose.yaml + Caddyfile + .env.example for the AI stack
- `shared/` — homepage, Prometheus, Loki, Alloy, SearXNG configs
- `scripts/` — `deploy.sh` / `deploy-plan.py` / `deploy-remote.sh`, LLM serve
scripts, systemd units, env tunables, bench harnesses
- `old/` — retired LLM scripts (reference only)
- `serverAppConfigs-docs/` — knowledge base (Obsidian vault, OKF format)
- `tests/` — bats suite + Playwright e2e
## Git Workflow
All edits flow through git. Never edit files on a remote machine directly.
1. **Source** the live config from the target machine
2. **Commit** the fetched version here (redact secrets into `.env`)
3. **Edit** locally
4. **Test** — `./tests/run.sh` must pass
5. **Commit and push** — origin is Gitea on Dankclaw
6. **Pull** on the target (`deploy.sh` does this)
7. **Deploy** — `scripts/deploy.sh` plans and dispatches only changed services
## Deployment
```
./scripts/deploy.sh dankclaw
./scripts/deploy.sh dankserver
./scripts/deploy.sh dankclaw --service searxng
./scripts/deploy.sh dankserver --service frank-medium
./scripts/deploy.sh dankclaw --dry-run
```
The planner maps changed paths to services; the remote runner restarts only
the selected service and records its revision outside the checkout.
Documentation-only changes are a no-op. LLM services are selected only by
their own files — `frank-large`/`frank-small` by their unit/env/serve trio in
`scripts/`, `frank-medium` by its Quadlet unit, entrypoint and healthcheck under
`dankserver/frank-medium/` — so
unrelated
container changes cannot interrupt inference. Set `FRANK_SUDO_PW` for headless
runs on a host without passwordless sudo; the value never enters the repo.
### Deployment completeness (MANDATORY)
A deploy is **not complete** when `deploy.sh` exits green. It requires:
1. `./tests/run.sh` — all seams green, and
2. the Playwright e2e suite (`tests/e2e/run.sh`) — runs **automatically** as
the `[3/3]` gate at the end of `deploy.sh` against the LIVE fleet; a
behavior-affecting deploy that fails it exits `DEPLOY INCOMPLETE`. Bypass
only with `--skip-e2e` in an emergency.
```mermaid
graph LR
A[Edit locally] --> B[Tests pass] --> C[Commit + push]
C --> D[deploy.sh plan] --> E[Target pulls ff-only]
E --> F[Dispatch selected service] --> G[Per-service health]
G --> H[Playwright e2e gate] --> I{green?}
I -->|yes| J[Deploy complete]
I -->|no| K[DEPLOY INCOMPLETE]
```
## Boot Persistence & Self-Healing (MANDATORY)
Every deployed, working Podman container MUST have a self-healing,
boot-persistent Quadlet unit. A container that runs only from `compose.yaml`
or a manual `podman run` dies silently at reboot — rootless Podman does not
auto-start bare containers, and `restart: unless-stopped` does not survive the
explicit stop that shutdown performs. Never report such a service as "up".
Unit requirements:
- **Boot persistence** — `[Install] WantedBy=default.target`, installed to
`~/.config/containers/systemd/<name>.container`, enabled in the user
manager, with linger on for the deploy user (`loginctl show-user dank -p
Linger` → `Linger=yes`).
- **Self-healing** — `Restart=always` (or `on-failure`) with a short
`RestartSec`; quadlet health check where the service has one.
- **Repo provenance** — the `.container` file lives in this repo
(`<host>/<svc>/quadlet/`), is installed by the deployer, and is covered by
the quadlet test seam. The host-side unit is generated state; the repo file
is the source of truth.
Before declaring a service deployed: `systemctl --user is-enabled <name>` →
`enabled`, `is-active` → `active`, and the container answers its health check.
A running container with no unit is a gap: write the unit, test it, deploy it.
This rule exists because reboots found gaps twice (2026-08-26: Caddy as a
bare compose container never returned; 2026-09-11: five observability
services had no units). The observability services now have units under
`dankclaw/observability/quadlet/` and their compose definitions were removed —
one owner per container name. The stack is **configured and delivering as of
2026-09-17**: a Grafana datasource and the `llm-fleet` dashboard are
provisioned from `shared/grafana/provisioning/`, `shared/prometheus/rules/
llm-fleet.yml` loads 5 alert rules + 1 recording rule, and firing rules are
delivered: Prometheus → Alertmanager (`dankclaw/observability/quadlet/
alertmanager.container`, loopback :9093) → host-side Signal relay
(`scripts/signal-relay.py`, user unit, 192.168.0.143:18093 — the host LAN
IP, the one bind a container can reach as `host.containers.internal`;
iptables admits loopback, the host and the podman bridge subnet only) → signal-cli account 318311.
Prometheus targets read down for structural reasons (HTML-scraped "probes",
Gitea metrics off); the remedy is a blackbox exporter. See
`serverAppConfigs-docs/Infrastructure/Observability.md`.
## Testing
Tests are mandatory before commit (`bats` required on the dev machine):
```
./tests/run.sh
```
Seams: compose validity, env consistency (no leaked secrets), Caddyfile
validity, quadlet units, docs completeness **including vault link integrity**,
script syntax (shell + python), LLM unit integrity, LLM secret hygiene,
deployment flow, service-scoped planning, homepage config/pages/deploy/checker,
and `e2e_scaffold` — which fails if a Playwright spec file's number prefix is in
no project, because such a spec silently never runs.
See `serverAppConfigs-docs/Architecture/Testing Policy.md`.
## Secret Rules
- Never commit real secrets. The live Gitea DB password and sudo password are
test-enforced leak checks.
- `.env` files are git-ignored; commit only `.env.example` with placeholders.
Exception: `scripts/*.env` LLM tunables (paths and numbers, never
credentials).
- Do not document passwords anywhere in the repo. SSH keys are the auth
mechanism; `FRANK_SUDO_PW` covers headless sudo and never enters the repo.
- **A token passed as `curl -H "Authorization: Bearer …"` is world-readable.**
It lands in `/proc/<pid>/cmdline`, so any `ps`/`pgrep -a` on the host prints
it — that leaked an HF token into a session transcript on 2026-09-16, while
merely checking whether a download was still running. Pass secrets out of
band (`curl -K <mode-600 file>` carrying the header, or `HF_TOKEN` in the
environment for `hf`/`hf_transfer`) and never `pgrep -a` a fetch command that
carries an auth header.
## External Exposure Policy (MANDATORY)
Every Caddy-proxied service is either behind the auth chain (Anubis :8923 →
Authentik embedded outpost) or explicitly internal-only — no public DNS name,
no vhost. New services default to internal-only until guarded.
When guarding a new vhost — provider first, then route:
1. Create the outpost proxy provider FIRST (`external_host` = exact vhost URL
with trailing slash; `internal_host = http://caddy:8017`). If the vhost
flips first, authenticated traffic hits the outpost error page.
2. Flip the vhost to `reverse_proxy anubis:8923` with
`header_up X-Real-Ip {remote_host}`, and add the post-auth
`@<svc> host <vhost>` handler on the `http://:8017` listener routing to
the real upstream.
3. Anubis guard set, Caddy TLS edge, and outpost provider list change
together in one deploy.
4. Service-to-service traffic targets internal addresses (`loki:3100`), never
the public hostname — non-browser clients cannot solve challenges.
Exempt categories (document the reason in the vhost comment): the IdP itself
(`auth.`), git smart-HTTP endpoints, services with their own complete auth.
## Deletion & Trash Policy (MANDATORY)
Never `rm`. Move deletions into trash so they stay recoverable:
1. In-repo files → `.AGENTTRASH/` beside the item's directory.
2. Elsewhere → dated staging dir `~/.AGENTTRASH/YYYYMMDD-topic`.
3. List staged items and sizes; wait for explicit user approval to purge.
`rm`, `rm -rf`, and `git clean -f` are forbidden without explicit permission.
`git * --no-verify` is forbidden. The trash is a temporary hold, not an
archive.
## Benchmarking Policy (MANDATORY)
**STOP the production service BEFORE benchmarking** — these servers serve
real users, and a bench beside a live service starves the GPU and corrupts
results. Use the runtime's own harness: `llama-bench` for every llama.cpp
endpoint (all three are llama.cpp now). Rolling your own bench
requires asking first.
Scratch ports are not used on LLM hosts — a
test process cannot share the single GPU anyway; validate against the service
itself.
This covers **any GPU experiment, not just benchmarks** — including a bare
2-rank RCCL/`torch.distributed` probe. On 2026-09-16 one such probe was run
against the live service "because it only needs 200 MB of VRAM"; the host went
hard down ~20 minutes later (no ARP reply, 100% ICMP loss from two subnets, no
recovery — a power cycle was required). A hung AQL dispatch wedging the GPU
driver is the plausible mechanism, and this host has precedent for going
unreachable until a power cycle. If an experiment needs GPUs, stop and mask
first, or use a host that serves nobody. Telling an off machine from a wedged
one: `ip neigh show <ip>` from a peer — FAILED means off/NIC dead, while a
merely wedged kernel usually still answers ARP.
1. Stop and mask (self-healing would restart it):
- Dankclaw `frank-large` (root unit, CIRU llama.cpp on the iGPU):
`sudo systemctl stop frank-large && sudo systemctl mask frank-large`
- Dankclaw `frank-small` (root unit, llama.cpp on the 3090):
`sudo systemctl stop frank-small && sudo systemctl mask frank-small`
- Dankserver `frank-medium` (**rootless Quadlet since 2026-09-20** — the
system unit is retired, so `sudo systemctl` sees nothing):
`systemctl --user stop frank-medium && systemctl --user mask frank-medium`
2. Bench.
3. Unmask and start; verify `curl http://192.168.0.<host>:7770/health`.
**CRITICAL:** never `systemctl disable` a system unit on these hosts — it
deletes the unit file from `/etc/systemd/system/`, not just the symlink.
`mask` symlinks to `/dev/null` and is safe/reversible.
## Model Config (harness)
The harness reaches the fleet through `.omp/agent/models.yml` in the
operator's home — `/home/blank/.omp/agent/models.yml` on the dev box, which is
where the harness runs; there is no copy on the servers. Each provider is one
HOST:PORT; each model `id` is the served alias: `frank-medium` →
`192.168.0.235:7770`, `frank-large` → `192.168.0.143:7770`, `frank-small` →
`192.168.0.143:7771`. Per-role routing lives beside it in `config.yml` under
`modelRoles`.
Resolution rules: the default model resolves as a `defaultProvider` +
`defaultModel` pair (the provider must serve the model); a subagent override
uses a bare model `id`, which resolves only when unique across providers. Two
ports on one host need two providers — the file cannot express "same host,
different port".
When renaming a service, retiring an endpoint, or moving a model: update the
provider block, model `id`, `contextWindow`, `maxTokens`, `input` in
`models.yml`, then fix every `modelRoles` entry that named the old endpoint —
a role pointing at a provider the file does not define fails at call time. As
of 2026-09-20 both `frank-small` and `frank-medium` accept images
(`input: [text, image]`) — frank-medium's checkpoint serves vision through the
Gemma4 merge path with no separate mmproj, verified on held-out synthetic
images; `frank-large` remains text-only because its unsloth deployment loads no
vision projector (the F16 mmproj is on disk, one env flip away). Note also that
the reasoning channel differs by runtime: llama.cpp endpoints emit
`reasoning_content`, vLLM emits `reasoning`.
There is **no audio**
input anywhere in the fleet: that capability left with the FLM NPU endpoint on
2026-09-11.
### frank-large — unsloth llama.cpp Qwen3.8-Flash-Next UD-IQ4_XS (Dankclaw, ACTIVE)
The unsloth llama.cpp prebuilt `app-b11030-mix-5ff778e` (ROCm gfx1151,
`/home/dank/GitPackages/unsloth-llama-b11030/`, bundles its own ROCm runtime —
no host SDK gate, no venv) as a **root systemd unit** (`scripts/
frank-large.service`, `User=dank`), serving
`unsloth/Qwen3.8-Flash-Next-GGUF:UD-IQ4_XS` (87.3 GiB main GGUF, three HF
split parts concatenated, + a 2.6 GiB MTP head, all sha256-verified) on port
7770 from the gfx1151 iGPU. One stream, 200,000 ctx (`PARALLEL_SLOTS=1`,
operator's requested shape; the trained window is 262,144), MTP depth 2
(`SPEC_DRAFT_N_MAX=2`, the model card's default), reasoning extracted to
`reasoning_content`, and **no vision projector** (the F16 mmproj is on disk,
`ENABLE_VISION=0` — one env flip to enable). It replaced the CIRU v4.4.1
Orca runtime, which had replaced halogen-flash-server.
The runtime is the first with an MTP graph for the qwen4exp architecture
(stock ggml-org mainline has none), so the unsloth prebuilt is the
llama.cpp-compatible choice. The MTP head is loaded via an **explicit
`-md`**: sidecar auto-discovery does not search the `mtp/` subfolder, and
without it `--spec-type draft-mtp` silently runs at the main model's speed.
The serve script (`scripts/serve-frank-large.sh`) validates binary → main
GGUF → MTP head and exits with a pointer message if any is missing, then
`exec`s `llama-server` with `--jinja --alias frank-large --chat-template-
kwargs '{"preserve_thinking":true}'` (Qwen3.8's template needs this to
carry thinking blocks across turns; a request-level value still wins).
The iGPU addresses **114 GiB** (the GTT aperture over the shared LPDDR,
`gtt_total` in `/sys/class/drm/card1/device/`; `rocm-smi`'s 2 GiB "dedicated"
is not the budget). The 87.3 GiB model is mmap'd in with `-ngl 999`; budget
at 200k ≈ 100 GiB (weights + MTP head + KV + buffers), leaving ~14 GiB of
aperture headroom. The n-gram embedding (PLE) is inside the GGUF — no
external PLE payload or pager, unlike the CIRU Orca packaging.
Fetch: `scripts/download-frank-large-unsloth.sh` (resumable, each part
verified against its LFS sha256 fetched live from the Hub tree API, then the
assembled GGUF against `SHA256SUMS`; `--verify-only` re-checks).
Runbook: `serverAppConfigs-docs/LLM/frank-large-unsloth-qwen38-flash-next.md`.
Rollback: [[frank-large-ciru-orca]] (payload and runtime intact on disk).
### frank-small — llama.cpp on the RTX 3090 (Dankclaw, ACTIVE)
Mainline llama.cpp master `37b53fd` (CUDA build with
`-DGGML_CUDA_FA_ALL_QUANTS=ON`) as a **root systemd unit** (repo
`scripts/frank-small.service`, `relink_unit`ed into `/etc/systemd/system/`),
serving `HauhauCS/Gemma4-12B-QAT-Uncensored-HauhauCS-Balanced` at Q4_K_M.
The MTP head is a SEPARATE assistant file (`mtp-gemma-4-12B-it.gguf`, 4
nextn layers) loaded via `--model-draft`; the draftless **ngram-mod**
matcher chains behind it in the same `--spec-type` value. BF16 mmproj,
port 7771, q8_0 KV, `CTX_SIZE=1048576` / `PARALLEL=4`
(four FULL 262,144-token slots — the measured card ceiling), batch
**8192/1024**, greedy default. Deployed flags are in
`scripts/frank-small.env`; the serve script refuses to start if the
weights, the projector, the sidecar or the binary are missing.
Verified at deploy (2026-09-17): `/v1/models` reports `frank-small`; a
chat completion returns content plus `reasoning_content`; a tool call
returns `tool_calls`; an image request is answered from the projector;
an `input_audio` WAV transcribes verbatim. Post-tuning live numbers at
max length: pp@254k ~965 t/s, tg@253k 226–302 t/s with ~94% draft
acceptance; idle 23,300 MiB of 24,576. The throughput sweep (and why
ubatch 2048 OOMs the draft's pp buffer, and why draft depth 4 + poll
100 is WORSE at long ctx) is tabled in the runbook.
Runbook: `serverAppConfigs-docs/LLM/frank-small-gemma4-12b.md`.
Rollback: [[frank-small-qwen38-gsq-rco]].
### frank-medium — radiance TP=2, DFlash2 drafter (Dankserver, ACTIVE)
vllm-radiance **0.9.3** (`localhost/radiance-vllm:0.9.3`, rootless **Quadlet**
`dankserver/frank-medium/quadlet/frank-medium.container`) serving
`orcarouter/Qwen3.8-27B-Uncensored-FP8` (FP8 E4M3 block-wise 128×128, dynamic
activation quant, 30.9 GB / 7 shards) with the **z-lab DFlash2 external
drafter** (`num_speculative_tokens: 7`, live mean accept 4.24/7) in **one
tensor-parallel process across both R9700s** (`--tensor-parallel-size 2`).
262,144 ctx, `--max-num-seqs 8`, chunk 8192, fp8 KV, prefix caching, GPU fill
0.98, **no KV-memory pin** — the pool auto-sized to 384,238 tokens (1.47× the
full window; the DFlash2 drafter's 2.1 GiB costs the pool vs MTP's 461,540).
DFlash2 was A/B tested against MTP self-speculation on this checkpoint and
wins on decode (100.0 vs 85.9 t/s) — see the runbook. Tools via `qwen3_coder`,
reasoning via `qwen3` (the field is `reasoning`, not llama.cpp's
`reasoning_content`), vision through the Gemma4 merge path, chat template
Qwen-Sharp v22.4.0 (froggeric, repo-tracked at `dankserver/frank-medium/`,
terse system prompt by default).
**The entrypoint is quantization-aware.** `radiance-entrypoint.sh` reads
`quantization_config.quant_method` from the checkpoint's `config.json` and
serves the plain FP8 path (no MXFP4 patches, `--quantization fp8`,
`ROCM_AITER_UNIFIED_ATTN`, the DFlash2 drafter) or the MXFP4 patch-and-serve
path (the DFlash2 external drafter). A checkpoint swap is therefore four quadlet
env vars (`SNAP`, `SPEC_METHOD`, `SPEC`, `KV_MEM`) — the deploy handler reads
the serving shape from the quadlet and gates on the right assets. The MXFP4
checkpoint (`just1moremodel/Qwen3.8-27B-Uncensored-MXFP4-awq` + the z-lab
DFlash2-FP8 drafter) remains on disk as the rollback target. Full swap
process + toolchain: [[frank-medium-model-swap]].
**TP=2 runs because the board changed.** The predecessor board (TUF GAMING
B650-E) put card #2 behind chipset bridges advertising `AtomicOpsCap: Routing-`
and no collective could be dispatched there. The ProArt B850-Creator WiFi NEO
routes both cards to CPU GPP root ports (`00:01.1 → 03:00.0`,
`00:01.3 → 07:00.0`, Gen5 x8, every hop `Routing+`, both endpoints `ReqEn+`).
The collective in use is vLLM's **R4D one-shot allreduce**, which never touches
RCCL (TheRock RCCL has no gfx1201 device code; the Ubuntu RCCL 2.27 build does,
and that is what `scripts/build-llama-rdna4.sh GGML_HIP_RCCL=ON` links).
**Measured, not assumed** (`scripts/bench-conversation.py`, 10 real prompts,
max_tokens 512, greedy, salted per arm, service stopped between arms):
radiance TP=2 95.8 t/s decode geomean / 0.21 s TTFT / 259.4 t/s burst-4, vs the
llama.cpp layer split's 45.7 / 0.72 / 71.7 and llama.cpp `--split-mode tensor`'s
30.5 / 0.71 / 54.3. Honest caveat: the arms also differ in quantization (MXFP4
vs Q8_0), so part of the margin is the quant, not the parallelism. Re-measured
against production after deploy: 92.4 t/s, 0.22 s, 248.9.
Files: `dankserver/frank-medium/quadlet/frank-medium.container`,
`dankserver/frank-medium/radiance-entrypoint.sh` (quantization-aware),
`dankserver/frank-medium/frank-medium-healthcheck.py`. Swap toolchain:
`scripts/hf-manifest.py` (generate a `<filename> <size> <sha256>` manifest
from the live repo tree), `scripts/hf-fetch.sh` (resumable, byte + sha256
verified, idempotent fetch), `scripts/swap-frank-medium.sh` (generate
manifest → download → detect quantization → edit the quadlet → deploy). The
llama.cpp layer-split trio (`scripts/frank-medium.service`, `.env`,
`serve-frank-medium.sh`) is archived in `scripts/.AGENTTRASH/
20260920-llama-layersplit/`; `deploy-remote.sh`'s `retire_llama_medium_unit`
moved the installed unit symlink there rather than `systemctl disable`, which
would delete it. The deploy handler reads `SNAP`/`SPEC_METHOD` from the
quadlet, gates on the image tag + the checkpoint's `config.json` (drafter only
for `dflash`, `libr4d` only for `mxfp4`/`quark`), then waits for :7770 and
gates on `/health`.
Runbook: `serverAppConfigs-docs/LLM/frank-medium-radiance-mxfp4.md` (serving
details); swap process + toolchain: `serverAppConfigs-docs/LLM/
frank-medium-model-swap.md`.
Rollback: the MXFP4 checkpoint on disk (`SPEC_METHOD=dflash`, `SPEC=7`);
before that, [[frank-medium-llamacpp-dflash2]] (SUPERSEDED 2026-09-20).
## Key Lessons Learned
Durable operational lessons from the fleet's history. Full detail in the
linked runbooks.
**PCIe / multi-GPU**
- **RCCL collectives need PCIe atomics on every participating GPU.** RCCL's
kernels carry a hidden hostcall-buffer parameter; ROCr refuses to dispatch
them when the device has no atomics, and the failure surfaces as
`hipErrorIllegalState` ("the operation cannot be performed in the present
state") from `hipLaunchKernel`, not as anything that names atomics. The
value is consumed at driver probe time, so writing the AtomicOp Requester
bit with `setpci` at runtime changes nothing. Check the *chain*:
`lspci -vv -s <gpu>` and every upstream bridge must show
`AtomicOpsCap: Routing+` (a `Routing-` bridge is a hardware wall), and the
endpoint's Device Control 2 (`setpci -s <gpu> CAP_EXP+28.w`) must have bit
6 set. AMD desktop platforms put one card on CPU root ports (atomics work)
and the rest behind the chipset (usually not) — that asymmetry is what
blocked frank-medium's TP=2. A one-card collective proves nothing: NCCL
short-circuits at `world_size=1`.
- **That wall was physical, and it was fixed on 2026-09-20 by a board swap.**
Both paths that put two cards on CPU root ports were: an M.2→PCIe x4 riser
into a *CPU-attached* M.2 slot, or a board whose CPU lanes bifurcate to
x8/x8. dankserver took the second: **ASUS ProArt B850-Creator WiFi NEO**,
`PCIEX16_1` + `PCIEX16_2` at x8/x8 Gen5 on root ports `00:01.1` / `00:01.3`,
every bridge now `Routing+` and **both endpoints `ReqEn+`** — the exact
precondition the old test plan named. Bandwidth was never the constraint (a
27B TP=2 allreduce at batch 4 is ≈10 MB per token-step, ≈1.4 ms at Gen4 x4
and under 0.4 ms at Gen5 x8).
**Proven on the same day.** vLLM's R4D one-shot allreduce runs TP=2 here and
frank-medium serves on it; llama.cpp's RCCL path was built too
(`GGML_HIP_RCCL=ON`) and its tensor mode measured — real collective, slower
shape. Note the collective choice matters: TheRock's RCCL builds lack gfx1201
device code (`invalid device function`), which is why R4D is the path vLLM
uses at all. Evidence matrix and the measured three-arm verdict:
[[Dual-R9700-Cooperation]].
- **When a GPU collective dies, read the runtime, not the framework.** The
message that identified the cause came from `AMD_LOG_LEVEL=3`
(`Pcie atomics not enabled, hostcall not supported` → `AQL dispatch
failed!`), not from vLLM or RCCL. `AMD_LOG_LEVEL` costs one env var and
prints the failing HIP call with its return code.
- **The software path that puts both cards on ONE model without a collective:
llama.cpp's layer split.** On the old board vLLM could not do it in any of its
parallelisms — TP needs an allreduce, PP needs the same p2p primitive, and both
died on the card that could not dispatch an RCCL kernel. `--split-mode
layer` in llama.cpp needs no
collective: layers are distributed in order and only the boundary activation
crosses PCIe, once per forward pass. Measured here: 1991 t/s prefill /
18.8 tok/s decode layer-split, against 272 / 26.3 tensor (butterfly
fallback).
This was what `frank-medium` ran until 2026-09-20, when the board swap made
collectives legal and radiance TP=2 beat it on every axis (95.8 vs 45.7 t/s
decode, 0.21 vs 0.72 s TTFT, 259 vs 72 t/s burst-4) — see
[[frank-medium-radiance-mxfp4]]; the llama shape is the rollback target
[[frank-medium-llamacpp-dflash2]].
- **Layer split is also the cross-vendor answer — and `-ot` is what cannot be
combined with it.** On Dankclaw (2026-09-16) a CUDA 3090 + Vulkan iGPU layer
split ran a real two-device graph: `-dev CUDA0/Vulkan1 -sm layer -ts 0.15/0.85`
held 14,994 MiB on the 3090 and gave 27.2 tok/s with 268.5 t/s prefill at 64k
depth (iGPU alone: 25.8 / 231.8). What does NOT work is per-tensor placement
across devices: `--override-tensor <group>=<device>` sets
`has_tensor_overrides()`, a REQUIRED term of the scheduler's
`pipeline_parallel` flag (llama-context.cpp:433 — the only place in the tree
that reads it), and that flag is what sets `n_copies` in
`ggml_backend_sched_new`; with `n_copies == 1` a pre-allocated weight on a
non-primary device has no backend and the graph aborts (`ggml-backend.cpp:941`,
reported with the leaf's own op name `(NONE)`). `=CPU` is the only override
target that works, because the CPU backend is last in the list. Pure Vulkan
changes nothing here — the gate is the override, not the driver mix. See
[[x4-pair-experiment]].
- **A host↔3090 link at x4 measures 6.72 GB/s, and that is a design
constraint, not a detail.** `pcie-link-test.cu` on Dankclaw (2026-09-16,
services stopped): pinned H2D 6.72 GB/s, D2H 6.60 GB/s — 85 % of the Gen4 x4
ceiling — with async no better than sync and pageable within 1 % of pinned,
i.e. the copies are link-limited rather than staging-limited (the usual
"pageable costs 2x" rule does not apply here). The card is x16-capable and the
Strix Halo port beneath it is x8-capable (`LnkCap: 16GT/s, Width x8` on
`00:03.1`), so the x4 lives in the adapter or cable; the link idles at
2.5 GT/s x4 and trains up under load. Consequence for any engine that
*streams* weights across it: a 3 MiB slab costs 474 us, and a 111 GiB A3B
model needs ~1.70 GiB of active experts per token ⇒ **3.7 tok/s** (4.6 with a
20 % resident cache), against **20.46 tok/s** for the same model with the
experts *computed* in host RAM by llama.cpp (`-ot exps=CPU`, whence the link
carries activations only) and 25–26.5 on the iGPU. Streaming over PCIe loses;
computing in RAM does not care. FreeToken — expert LRU in host RAM, exactly
this streaming shape — also loads only modelopt block-FP8 safetensors for
`qwen3_5_moe`, so a Q4_K_M GGUF is unloadable there before bandwidth is even
the question. See [[x4-pair-experiment]].
**ROCm / GPU**
- **Layer split was the deployed shape on both multi-device llama.cpp services,
for two different reasons.** On Dankserver it was the *only* way both R9700s
served one model (no collective could be dispatched on card #2) until the
2026-09-20 board swap; frank-medium now runs radiance TP=2 instead. On a
RCCL-less fork build it is also the fast one: tensor parallel falls back to
a butterfly allreduce and collapses prefill ~7x (measured 271.8 vs 1991 t/s).
Pin the spec-decode drafter to one device — an unpinned draft under tensor
mode aborts the KV build, and on a layer split the natural home is the card
that ends up holding the target's last layers.
- **Bundling a ROCm runtime next to a llama.cpp binary: `cp -r SRC DST/` is a
trap.** With a missing `DST`, cp creates `DST` as a copy of `SRC` and drops
one directory level. rocBLAS and hipBLASLt look for their device code at a
fixed depth (`../lib/rocblas/library`, `../lib/hipblaslt/library/<arch>`),
and the flattened copy fails at *request* time, not load time: the engine
reads the weights, answers `/health` and dies on the first completion with
`Cannot read .../TensileLibrary.dat: No such file or directory for GPU arch
: gfx1201`. Declare the destination, then copy the contents.
- **mmap must stay on** for the big-PLE models: `--no-mmap` forces the
~50 GiB PLE table into anonymous memory → silent cgroup kill, dmesg is the
only evidence. mmap pages ARE page cache. Never pin the PLE tensor with
`-ot` (23 → 13.4 t/s).
- **HIP reads bare env vars** `TEMP`, `HOST`, `GPU_MAX_HEAP_SIZE`. Serve
scripts export env files with `set -a`, so a tunable named `TEMP` leaks
into HIP (`TEMP=1.0` sent the JIT cache to path `1.0` and segfaulted every
load, fixed 2026-08-13 by renaming to `TEMPERATURE`). Never name a tunable
these; check with
`strings /opt/rocm-*/lib/libamdhip64.so.* | grep -xE "TEMP|HOST|GPU_MAX_HEAP_SIZE"`.
- **`-DGGML_CUDA_FA_ALL_QUANTS=ON` is required** for q8_0 KV + flash
attention on CUDA builds; without it prefill collapses ~12x (95 vs 1300+
t/s, measured 2026-08-17).
- **Flash-Next MTP heads do not load on any current loader** — they need full
per-layer `blk.<il>.hc_attn_norm.weight` and ship only `blk.48` (verified
3x). Don't re-attempt without new loader support.
- **QSA flash-attn assert:** `GGML_ASSERT(a-type == GGML_TYPE_F32)` on
qwen4exp needs `scripts/patches/qwen4exp-qsa-f32-mask.patch` — but only on
the agentionai FAST layer set; the kingjones STRIX set works unpatched.
- **GPU budget on Dankclaw is the GTT aperture (~114 GiB), not the
rocm-smi "dedicated" figure.** The Radeon 8060S (gfx1151) reports
116,732 MiB (`llama-server --list-devices`;
`gtt_total=122402963456` in `/sys/class/drm/card1/device/`). The older
"64 GiB, SVM-backed" lesson was already stale — the CIRU Orca predecessor
held 92.6 GiB of weights on the iGPU. `free`/`dmidecode` show the
CPU-side carve-out — intentional, do not change.
**Load / crash diagnosis**
- Model load is slow (minutes cold); health returns 503 while loading; do
not kill the process. `deploy.sh` waits up to 20 minutes (`LLM_WAIT`). On
halogen, the FIRST request after a (re)start can go silent ~45–60 s
(health `engine_unresponsive`, 503s) and then self-recovers — do not
restart over it.
- Crash-loop procedure: (1) `journalctl -u <svc> -n 100` + kernel line via
`journalctl -k` (segfault at address 8 in `libamdhip64` = NULL unref in
HIP); (2) run serve script, then raw binary — different outcome isolates
the env file; (3) `gdb -batch -ex run -ex "bt 25" --args bash
scripts/serve-<svc>.sh` — llama-server buffers stdout and loses the log
tail on SIGSEGV; trust gdb, not the log; (4) `amdgpu: SVM mapping failed`
spam is a symptom, not a root cause.
- Journal signatures: client abort logs `W srv stop: cancel task, id_task =
N`; natural stop logs only `slot release` with `truncated = 0`. The server
never preempts a running generation; excess tasks queue when slots are
busy.
**Host memory / swap**
- Swap resize ordering: create and `swapon` the replacement BEFORE `swapoff`
of the old one, or live pages must land in RAM that `MemAvailable`
overstates. Dankclaw swap (64 GiB at `/swap.img`, fstab-driven) protects
the co-tenants, not frank-large — pinned weights don't swap, and paging
the KV pool is worse than the OOM it prevents.
- Host swap state is invisible to `deploy.sh` (no repo file) — check
`swapon --show` before reasoning about headroom.
**Runtime-specific guards**
- **Kairic Edge** (if ever re-deployed): the pinned CK commit needs
`third_party/composable_kernel/include/ck/config.h` generated manually
(untracked; `git clean` removes it), and its greedy-argmax fastpath rejects
non-greedy requests and reasoning budgets. Re-test chat before production.
- **FastMTP sidecar**: build must be commit `4df29be4` + the HauhauCS patch;
stock binaries fail the draft load with a tensor-shape mismatch.
**llama.cpp serving**
- **MTP is a property of the FILE, not of the flags.** The `-mtp` GGUF build
carries the head as `blk.<n>.nextn.*` (`qwen35.nextn_predict_layers = 1`);
`--spec-type draft-mtp` then sets `load_mtp`, and the draft context runs on
the MAIN model's weights (`shares_model`), so there is no second copy of a
12 GiB model in VRAM and no `-md` argument. The plain build has no MTP
tensors at all, and pointing `--model-draft` at the file would load it twice.
- **What can be chained, and what cannot.** `--spec-type a,b` builds every
enabled implementation and chains drafting through them, in a fixed internal
order (ngram types first, then the drafters — CLI order is irrelevant). The
gate is `ctx_dft`: **draftless** types (the ngram family) are added
unconditionally, while `draft-mtp`, `draft-dflash`, `draft-dspark` and
`draft-eagle3` all require a draft CONTEXT. So a chain may hold one
context-backed drafter plus any number of ngram types — `draft-dflash,ngram-mod`
is legal and measured (2.6x the drafter alone on prompt-echo traffic, byte-
identical to it on prose at the fleet's 48/64 window) — but
`draft-mtp,draft-dflash` dies at load: *"context type MTP requested but model
doesn't contain MTP layers"*, because MTP builds its context against whatever
model the draft context holds. Two context-backed types cannot share one
process, and MTP's head only loads when MTP **is** the draft model.
- **A drafter's KV scales with the TARGET's context, and its window policy
decides how much that costs.** The draft context is built with
`cparams.n_ctx = llama_n_ctx(ctx_tgt)` (`common/speculative.cpp`) — there is
no flag to cap it — so a drafter that declares NO sliding window caches the
whole window on whatever device `--spec-draft-device` names. Swapping DFlash2
(`dflash.attention.sliding_window = 2048`, ~40 MiB of draft KV) for DSpark
(no window; 5 layers x 2 x 8 kv heads x 128 dim x 2 B = 20 KiB per position,
so **5.0 GiB at 262144**) put ROCm1 at 33.9 GB of 34.2 GB and killed the
FIRST draft graph capture with `ROCm error: out of memory` — after the model
had loaded and `/health` had answered. Read `sliding_window` out of the
drafter's GGUF header before sizing any spec-decode deployment, and prefer a
skewed `-ts` over a context cut when the full window matters. The pair was
swapped DFlash2 -> DSpark -> DFlash2 in one day (2026-09-16) and the round
trip moved the balance point FOUR layers (~4.3 GiB of headroom, 40:25 ->
36:29), which is the practical size of the effect. See
[[frank-medium-llamacpp-dflash2]].
- **`--ubatch-size` has an OPTIMUM on this stack, not a plateau — and its
compute buffers land about TWICE as heavy on the card that holds the output
layers and the drafter.** Measured on frank-medium 2026-09-16 at the deployed
shape (262144 over two slots, a 64k prefill measured at 64k depth,
`scripts/bench-batch-ubatch.sh`): prefill runs 1046 tok/s at ubatch 256, 1068
at 384, **1193 at 512 (the peak)**, 1135 at 768, 1152 at 1024, 1151 at 1280,
1165 at 1536, 1148 at 1792 and 1078 at 2048. Both ends lose — below 512 the
SMs are not saturated, and 2048 is 10 % off the peak — and 512 -> 1536 costs
ROCm0 1.30 GiB and ROCm1 2.41 GiB to go 2.4 % SLOWER. The logical
`--batch-size` does not matter: 2048 through 8192 land within 2 % of each
other at a fixed ubatch and use identical VRAM. Decode never moves at all
(15.88 tok/s at depth 65536 on every cell). Because the buffers are
asymmetric, a split balanced at one batch is unbalanced at another: 512 ->
1536 shifted frank-medium's balance by a layer, so 36:29 became 35:30.
Re-measure the balance after changing the batch. (8192/2048 failed to allocate
its 2020 MiB pp buffer here under the DSpark drafter, when ROCm1 had 0.08 GiB
free. That was a CONTIGUITY failure, not a total-bytes one, and no totals
model — the sweep's or the seam's — can see it.)
- **One `-ts` step is one LAYER, and a hybrid stack's layers are not the same
size.** qwen35 is 16 x (3 Gated DeltaNet + 1 Gated Attention), so a step is
worth ~0.43 GiB on a DeltaNet boundary and ~1.43 GiB on a full-attention one
(0.45 GiB of weights plus ~1.0 GiB of its own f16 KV at 262144) — both
measured on frank-medium. Balance by measurement, never by interpolating
between two splits; an affine fit reproduces the deployed point and overstates
the gaps in between. `tests/frank_medium_unit.bats` encodes that fit as a
gate. See [[frank-medium-llamacpp-dflash2]].
- **ngram-mod prints no startup banner.** The load log shows the drafter's
`adding speculative implementation 'draft-dflash'` and nothing at all for the
matcher, so a chain can look unengaged while it is working. Identify it
behaviourally (`draft_n` > 0 only where text repeats) or by the per-task
`draft acceptance = ... mean len = ...` line. It costs no VRAM (a 64 MiB
host-RAM hash table) and its window decides which traffic it can see: too
short and it proposes on ordinary prose fragments, which costs verification
without acceptance.
- **`--jinja` is what `tools` needs.** On 2026-09-16 a subagent died with
`500 tools param requires --jinja flag`, from the ik_llama.cpp runtime that
then served frank-large: every tool-using agent on that endpoint was broken
and the failure read like a model fault. Mainline llama.cpp 0.4.1 defaults
`--jinja` on and the serve script pins it; halogen also accepts `tools` and
returns `tool_calls`. Check tool support before routing a role at an endpoint.
- **Quantized KV on CUDA needs `GGML_CUDA_FA_ALL_QUANTS=ON`** — the same
option and the same ~12x prefill collapse described in the ROCm note above.
f16 KV needs nothing; frank-small ran f16 for that reason until
2026-09-17, when `build-cuda` was rebuilt with the option ON so the
endpoint could take q8_0 KV.
- **llama-bench separates a LIST with `/` and SWEEP values with `,`.** Both
`-dev` and `-ts` follow this: `-dev CUDA0,Vulkan1` is two *single-device*
configurations, never one two-device run, and `-ts 0.85,0.15` is two sweep
values each becoming `[0.85, 0, …]` / `[0.15, 0, …]`, i.e. device 0 takes
everything. Write `-dev A/B -ts x/y`. This artifact produced a wrong fleet
conclusion on 2026-09-16 — "CUDA + Vulkan cannot serve one model", with two
bogus OOMs that were really "all 111 GiB on the 24 GiB card" — and the bench
table's own `dev` column was printing the truth the whole time. Any
placement-dependent number needs an independent check: sample the other
device's memory (`nvidia-smi`) while the run is loaded.
- **A model's own template can REJECT the harness's thinking level.** Qwen3.8's
template accepts only `xhigh`, `medium` and `low` for `reasoning_effort` and
raises on anything else — HTTP 500, not a clamp — so the harness's levels
must be folded onto that set in `models.yml` (`compat.reasoningEffortMap`).
A role whose level is unmapped fails on its FIRST request, and the failure
names Jinja, not the model: every subagent on `frank-small` died with
`Unexpected reasoning effort high` until `high: xhigh` was added on
2026-09-16. Halogen accepts the wider set, so the two entries legitimately
differ.
**Ops**
- Never `pkill -f` a pattern that appears in your own command line — it kills
your ssh session. Use `pkill -x <exact-name>`.
- Both hosts allow passwordless sudo for the deploy user. Use plain `sudo` in
committed scripts (no `echo pw | sudo -S`); `FRANK_SUDO_PW` covers hosts
without it.
- ComfyUI on Dankclaw runs with **GPU access** (`/dev/kfd` + `/dev/dri` via
`AddDevice`, `GroupAdd=keep-groups`, plus the udev rule that makes those nodes
world-writable — user-unit spawns carry no supplementary groups). It must NOT
pass `--cpu`: the gfx1151 ROCm wheels exist and the unit's `--cpu` era ended
2026-09-16, when a stale device-less container was found restarted 9,146
times (`RuntimeError: No HIP GPUs are available`).
- SearXNG outbound traffic must stay on the Gluetun tunnel; do not move its
ports off the gluetun service.
- `amd_iommu=off` on Dankclaw (bought 13–16 % prefill for frank-large,
2026-09-11) permanently retired the XDNA2 NPU: the driver's SVA/PASID bind
needs an enabled IOMMU (`/dev/accel/accel0` fails `err=-19`). Revert path
in `serverAppConfigs-docs/LLM/dankclaw-iommu-translation-off.md`.
- Rootless Quadlet containers run with `--replace --rm`: `podman logs` covers
only the CURRENT instance; history across recreations lives in
`journalctl --user -u <name>.service`. Read rootless storage WITHOUT sudo
(per-user storage — `sudo podman logs` finds nothing).
- **A dead rootless podman pause process breaks ALL container management on the
host, and `podman system migrate` panics in 5.7.0.** Symptoms: every `podman`
command fails with `invalid internal status … could not find any running
process`, every container start fails binding podman's bridge addresses
(`Error starting server failed to bind udp listener on 10.89.x.1:53: Cannot
assign requested address`), and every `Restart=always` quadlet loops. Container
storage is intact; what is gone is `/run/user/<uid>/libpod/tmp/alive` (a UUID
token, not a pid) and the rootless netns holding the bridges — deleting the
stale token is not enough, and `podman system migrate` segfaults in
`teardownNetworkBackend`. Repair: **reboot** (`/run/user` clears and all 28
quadlets return on their own — check `Linger=yes` and `WantedBy=default.target`
first). Seen 2026-09-16, hours into heavy GPU work on the same host — but the
trigger is NOT established (`journalctl -k` recorded no OOM kill; the kernel
had no other word on it). Treat the pause process as host state that can die
for its own reasons, and reach for the reboot when it does.
- **A container cannot reach a `Network=host` service at the host's LAN IP.**
netavark DNATs *published* ports only: from a bridge container
`192.168.0.143:<published>` answers while `192.168.0.143:<host bind>` and the
gateway `10.89.1.1` are both refused. Use `host.containers.internal`
(169.254.1.2). This is what 502'd `hermes.franksdank.cloud` until the Caddyfile
upstream was changed on 2026-09-16 (its vhost comment had claimed the LAN IP
was open from that bridge — it never was).
- **A `*.gguf` filter misses mradermacher's payloads: large quants ship as
`.partNofM` fragments.** `mradermacher/Qwen3.8-Flash-Next-Uncensored-i1-GGUF`
carries Q4_K_M (37.00 + 37.00 + 36.97 = 110.97 GiB) and Q4_K_S (35.00 + 35.00
+ 34.09 = 104.09 GiB) as parts, while the smaller rungs (Q2_K, Q3_K_*, IQ3_*,
IQ4_XS) are single files. Fetch the parts, verify each against the Hub's LFS
sha256, concatenate in numeric order — that is how the deployed 111 GiB file
was assembled. Listing the Hub tree and filtering `endswith(".gguf")` makes
Q4_K_S look like it does not exist.
- **A fetch script must `-f` and verify, or it reports success on an access
error.** `curl -o FILE URL` exits 0 on HTTP 401/403 and writes the error body
as the "artifact": a gated repo yielded three 153-byte shards with identical
sha256 values and a cheerful `DOWNLOAD_DONE` in 20 seconds for 104 GiB. Use
`-f`/`--fail-with-body`, compare each file's byte count to the Hub's declared
size, and check the LFS sha256 — `scripts/download-frank-medium-gguf.sh`
already does all three; ad-hoc fetches tend not to. Gated repos (e.g.
`orcarouter/Qwen3.8-Flash-Next-Uncensored-GGUF`, same 104.09 GiB Q4_K_S)
return 403 even with the host's HF token until that account accepts the gate.
## Runbook Index
Active:
| Service | Runbook |
|---------|---------|
| frank-large (unsloth llama.cpp Qwen3.8-Flash-Next UD-IQ4_XS, Dankclaw) | `serverAppConfigs-docs/LLM/frank-large-unsloth-qwen38-flash-next.md` |
| frank-small (llama.cpp Gemma4-12B QAT, Dankclaw) | `serverAppConfigs-docs/LLM/frank-small-gemma4-12b.md` |
| frank-medium (radiance TP=2 + MTP, Dankserver) | `serverAppConfigs-docs/LLM/frank-medium-radiance-mxfp4.md` |
| frank-medium model swap (toolchain + process) | `serverAppConfigs-docs/LLM/frank-medium-model-swap.md` |
| Dankclaw kernel posture (`amd_iommu=off`) | `serverAppConfigs-docs/LLM/dankclaw-iommu-translation-off.md` |
| Deployment flow + incidents | `serverAppConfigs-docs/LLM/deployment.md` |
Retired (rollback targets and history):
| Runtime | Host | Window | Runbook |
|---------|------|--------|---------|
| kingjones STRIX Qwen3.8-Flash-Next ROCmFP4 | Dankclaw | 2026-08-30 → 09-11 | `kingjones-strix-rocmfp4.md` |
| ik_llama.cpp Qwen3.8-Flash-Next-Uncensored i1-Q4_K_M (`frank-large`) | Dankclaw | 2026-09-15 → 09-16 | `frank-large-ik-uncensored.md` |
| halogen-flash-server Qwen3.8-Flash-Next w4b (`frank-large`) | Dankclaw | 2026-09-16 → 09-19 | `halogen-flash-server.md` |
| CIRU v4.4.1 Orca Qwen3.8-Flash (`frank-large`) | Dankclaw | 2026-09-19 → 09-21 | `frank-large-ciru-orca.md` |
| ISTA-DASLab Qwen3.8-27B-GSQ-RCO IQ3_S (`frank-small`) | Dankclaw | 2026-09-16 → 09-17 | `frank-small-qwen38-gsq-rco.md` |
| vLLM Gemma4-12B w4a16 (`frank-small`) | Dankclaw | 2026-09-19 (same-day revert) | `frank-small-vllm-gemma4.md` |
| agentionai ROCmFP4-FAST imatrix | Dankclaw | 2026-08-29 → 08-30 | `agentionai-fast-imatrix.md` |
| eemin Qwen3.8-27B ROCmI4 W4A4 MTP | Dankclaw | 2026-08-18 → 08-25 | `eemin-rocmi4-mtp.md` |
| Kairic Edge IU4 | Dankclaw | 2026-08-22 (same-day revert) | `kairic-edge.md` |
| CIRU ActiveFPX v3 / PromptForge | Dankclaw | through 2026-08-22 | `ciru-activefpx-promptforge.md` |
| DFlash2 Vulkan | Dankclaw | 2026-08-21 (same-day revert) | `dflash2-large-vulkan.md` |
| FastFlowLM NPU (`frank-npu`) | Dankclaw | twice, retired 2026-09-11 | `frank-npu.md`, `FastFlowLM NPU Inference.md` |
| FreeToken (official + Huihui FP8, `frank-small`) | Dankserver | 2026-09-02 → 09-15 | `freetoken-frank-small.md` |
| FastMTP patched llama.cpp | Dankserver | retired 2026-08-18 | `qwen3.8-spec-matrix.md` |
| ik_llama.cpp Ornith CRACK | Dankserver | retired 2026-09-02 | `ikllama-ornith-dankserver.md` |
| llama.cpp layer split + DFlash2 (`frank-medium`) | Dankserver | 2026-09-16 → 09-20 | `frank-medium-llamacpp-dflash2.md` |
Retired runbooks are under `serverAppConfigs-docs/LLM/`. Retired scripts live
in `old/` and `.AGENTTRASH/`.
## Why
Direct edits on the remote drift from version control, and future agents
won't know what changed. Git is the single source of truth. The two workloads
share two hosts, one Caddy, and one Gitea; one repo keeps them in one
history.
## Summary
| Context | Action |
|---------|--------|
| Editing a compose/Caddyfile/serve script | **Through git** — fetch, commit, edit, test, push, pull, deploy. Never edit on the remote. |
| Config exists only on remote | **Pull it into the repo first** — commit the fetched version (redacted) before editing. |
| Unstaged local changes | **Commit or discard** — check `git status` before starting work; ask if unsure. |
| Deploying a committed change | **`scripts/deploy.sh <target>`** — pushes, pulls ff-only, plans, dispatches, health-checks. |
| Container without a Quadlet unit | **Give it one** — boot-persistent, self-healing `.container` via git. |
| Benchmarking | **Stop and mask the service first**, bench, unmask, restart, verify health. |
| Deleting a file | **Move it to trash** — `.AGENTTRASH/` (in-repo) or `~/.AGENTTRASH/YYYYMMDD-topic`. Never `rm`. |
| Tests exist | **Run them** — verify tests pass after every change. Do not commit failing tests. |
| Real secrets | **Never commit** — host `.env` files; `.env.example` holds placeholders only. |