Cross-cutting rename of the current llama.cpp endpoint on the RTX 3090
(port 7771) from frank-small to frank-secondary:
- Service trio: scripts/{frank-small.env,frank-small.service,
serve-frank-small.sh,download-frank-small.sh} → frank-secondary.*
- Test: tests/frank_small_unit.bats → tests/frank_secondary_unit.bats
- Runbooks: serverAppConfigs-docs/LLM/frank-small-*.md →
frank-secondary-*.md (9 files); the FreeToken runbook stays
freetoken-frank-small.md (it documents the retired CUDA-era service)
- Identifiers: FRANK_SMALL→FRANK_SECONDARY, llm_small→llm_secondary,
LLM_SMALL_*→LLM_SECONDARY_*, deploy_llm_small→deploy_llm_secondary
- Historical references to the OLD frank-small (FreeToken/CUDA on the
3090, and the Dankserver service that became frank-medium) are
preserved verbatim — they describe what the service was called
at the time.
72 KiB
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-primaryLLM 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(flash-server container on the gfx1151 iGPU) andfrank-secondary(llama.cpp CUDA 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-prohandler.
Fleet topology (ACTIVE)
| Target | Service | Runtime | Model | Port |
|---|---|---|---|---|
| Dankserver | frank-primary |
radiance (StillDeadcode v1.0.7 line; image stilldeadcode/radiance@sha256:4c3f484564… digest-pinned INDEX digest, 287 MiB, libr4d gfx1201 kernels, plain podman run, root systemd unit) |
Qwen/Qwen3.8-Flash-Next-FP8 official (172.8 GB, 131 shards, sha256-verified) converted no-recipe to qwen4exp-fp8-native.rad (177,109 MiB measured = 173.0 GiB) — native modelopt block-FP8, no requantisation — on BOTH R9700s TP=2 (--tp-wire wht6), experts in a 40 GiB/rank pinned host pool + VRAM cache (--placement expert_tiered, --expert-vs-cache-ratio 0.82 = the 99 %-hit point), PLE 47.7 GiB pinned to host RAM (--ngram-placement ram; root unit + LimitMEMLOCK=infinity), fp8 KV 7.32 KiB/token, MTP spec decode depth 3, *… |
|
| Dankclaw | frank-large |
halogen-flash-server 0.16.2 (ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84…, digest-pinned, plain podman run via scripts/serve-frank-large.sh, root systemd unit) |
Quat3rnion/halogen-swift1.5-qwen3.8-flash-next-v2-abliterated qwen38-flash-next-v2-swift15-abliterated.hgn (66,687,678,464 B = compacted r2 of the card's 89,775,868,032 B original, ~62 GiB resident; the v2 .hgn format loads in NO other engine), + REQUIRED qwen38-flash-next-ngram.hgn (51,200,246,144 B, peonist @5cc17cea — read beside the checkpoint) + vision tower (897,916,416 B, @e053f488 — vision ON, image_url parts only, ≥256 px probes), MTP spec decode ALWAYS-ON (HALOGEN_SPEC_ADAPT=0 — the adaptive default disables the head per request and HALVES decode), MTP head INSIDE the checkpoint (HALOGEN_MTP_HEAD unset; no sidecar fetched), 2 slots × 200,192 ctx (KV pool 400,384 positions ≈ 10.7 GiB at ~28 KiB/position; the 27B slots>1-disables-drafting law does NOT carry over — batching and speculation coexist, the card's quickstart ships 2 with the head), server-side sampler 1.0/0.95/20 (card recipe; models.yml extraBody matches), coupled cap/timeout 65536/7200, prompt cache ON by default (warm 100k turn ≈ 2 s vs ≈ 88 s cold) |
7770 |
| Dankclaw | frank-secondary |
llama.cpp master (0.5.0-dev, commit 5fc4f3c), CUDA sm_86 build (root systemd unit, relinked) |
ajgazin/Swift-1.5-Qwen3.8-27B-Uncensored-Dynamic-MTP-GGUF RCO-IQ3_XXS -mtp (27B dense qwen3_5 hybrid, 10,442,827,392 B; a per-tensor allocation mix of stock types; the MTP head in the file drafted — spec ON (draft-mtp depth 3) since 2026-10-06 evening, ngram skipped on the recurrent-rollback law) + the publisher's own BF16 mmproj for vision, on the RTX 3090, 2 × 131,072 (Frank's 128k cap each; the tightest fit in the endpoint's history — 489 MiB measured free, the 2-3 GiB floor knowingly violated) with q8_0 K + q8_0 V (FP8 class, 34 KiB/token) under flash attention, batch 4096 / ubatch 512; 63.3 t/s recipe decode (MTP acceptance 49.8 %; 48.0 no-spec). Supersedes the same-morning IQ3_S-mtp payloads: the two-slot no-spec shape and the one-slot MTP shape (both 2026-10-06; payload on disk). | 7771 |
Retired endpoints (frank-npu, and every prior runtime) are in
the 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 stackdankclaw/— compose.yaml + Caddyfile + .env.example for the AI stackshared/— homepage, Prometheus, Loki, Alloy, SearXNG configsscripts/—deploy.sh/deploy-plan.py/deploy-remote.sh, LLM serve scripts, systemd units, env tunables, bench harnessesold/— retired LLM scripts (reference only)serverAppConfigs-docs/— knowledge base (Obsidian vault, OKF format). The managed skill library is distilled there one page per skill-cluster:LLM/index.md→ Cross-Cutting References, plusOperations/index.md,Agent/index.md, and the Infrastructure/Dankclaw/FrankBook-Pro service pages (serverAppConfigs-docs/log.mdcarries the wave plan and results)tests/— bats suite + Playwright e2e
Git Workflow
All edits flow through git. Never edit files on a remote machine directly.
- Source the live config from the target machine
- Commit the fetched version here (redact secrets into
.env) - Edit locally
- Test —
./tests/run.shmust pass - Commit and push — origin is Gitea on Dankclaw
- Pull on the target (
deploy.shdoes this) - Deploy —
scripts/deploy.shplans 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-primary
./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 — every endpoint (frank-large/frank-secondary/frank-primary)
by its unit/env/serve trio in scripts/ — 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.
deploy.sh <target> with no --service is a fleet-wide DRAIN, not a sync.
It also walks every per-service revision marker under the deploy-state dir and
restarts each service whose marker is behind HEAD and whose paths changed
since that marker — so a backlog accumulated by service-scoped deploys fires
all at once, and one failing health gate aborts the run with every later
service left pending. Name the service unless a drain is what you want
(./scripts/deploy.sh dankserver --service frank-primary).
Deployment completeness (MANDATORY)
A deploy is not complete when deploy.sh exits green. It requires:
./tests/run.sh— all seams green, and- the Playwright e2e suite (
tests/e2e/run.sh) — runs automatically as the[3/3]gate at the end ofdeploy.shagainst the LIVE fleet; a behavior-affecting deploy that fails it exitsDEPLOY INCOMPLETE. Bypass only with--skip-e2ein an emergency. The gate runs the conditionalfrankbookPlaywright project (the*arr/qBittorrent walk,tests/e2e/specs/19-frankbook.spec.ts) ONLY when a frankbook blast-radius path changed since origin/main — that spec,frankbook-pro/**,shared/homepage/services.json, or thedankclaw/Caddyfileserving the arr vhosts — so a sleeping FrankBook-Pro never fails an unrelated deploy. The default project set excludes it everywhere else (E2E_INCLUDE_FRANKBOOK=1opts in; seeserverAppConfigs-docs/Architecture/E2E Suite.md).
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(oron-failure) with a shortRestartSec; quadlet health check where the service has one. - Repo provenance — the
.containerfile 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.
.envfiles are git-ignored; commit only.env.examplewith placeholders. Exception:scripts/*.envLLM tunables (paths and numbers, never credentials).- Do not document passwords anywhere in the repo. SSH keys are the auth
mechanism;
FRANK_SUDO_PWcovers 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 anyps/pgrep -aon 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, orHF_TOKENin the environment forhf/hf_transfer) and neverpgrep -aa 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:
- 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. - Flip the vhost to
reverse_proxy anubis:8923withheader_up X-Real-Ip {remote_host}, and add the post-auth@<svc> host <vhost>handler on thehttp://:8017listener routing to the real upstream. - Anubis guard set, Caddy TLS edge, and outpost provider list change together in one deploy.
- 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:
- In-repo files →
.AGENTTRASH/beside the item's directory. - Elsewhere → dated staging dir
~/.AGENTTRASH/YYYYMMDD-topic. - 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 the llama.cpp
endpoints; a live llama.cpp server also reports honest per-request numbers in the /completion timings object (prefill/decode rates, draft_n, draft_n_accepted), which is how frank-large and frank-secondary were measured. 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.
(A gufo-era law; frank-large ran ROCmFPX llama.cpp 2026-10-02 → 10-05, the
halogen 27B container 2026-10-05 → 10-06, and is flash-server since, but the
rollback tags keep it live.) gufo bench cannot rank speculative-decode
settings, and will invert the ranking.
Measured 2026-09-28 on frank-large at depth 32768: its corpus
reports acceptance=0.933 ± 0.000 with an identical trace sha256 across
draft widths, i.e. the same highly-predictable text every run, and 93 % of
every proposal accepted. It reported 29–37 t/s decode where real traffic
gives ~15 t/s, and it made --draft-tokens 16 look 6 % faster than 7 when
real text made it 14 % slower. Use it for shape, not for A/B. For an A/B,
replay real text through the live server and read the Server-Timing
header — but note the unit rides in the name half (ttft;dur=402.485),
so splitting on = alone keys the dict ttft;dur and every lookup silently
returns nothing. Generate at least 128 tokens for the measurement: at 8
tokens, inter_token is first-token noise and the run-to-run spread swamps
every real difference.
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.
- Stop and mask (self-healing would restart it):
- Dankclaw
frank-large(root unit, halogen podman on the iGPU):sudo systemctl stop frank-large && sudo systemctl mask frank-large - Dankclaw
frank-secondary(root unit, llama.cpp on the 3090):sudo systemctl stop frank-secondary && sudo systemctl mask frank-secondary
- Dankclaw
- Dankserver
frank-primary(root unit, radiance on both R9700s, TP=2):sudo systemctl stop frank-primary && sudo systemctl mask frank-primary
- Bench.
NOTE:
systemctl maskFAILS on a relinked unit (the unit file in/etc/systemd/system/is itself a symlink into the checkout — mask refuses to replace it). Stop is enough for the bench window; the deploy restores the unit, so re-deploy after benching instead of unmasking. - 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-primary →
192.168.0.235:7770, frank-large → 192.168.0.143:7770, frank-secondary →
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 2026-10-06 all three endpoints accept images (input: [text, image]) — frank-large returned to vision with the flash-server v2 swap
(the v2 vision tower loads beside the checkpoint; the text-only halogen
27B window closed 2026-10-06) — while
frank-primary takes them natively (radiance runs the checkpoint's
27-layer Qwen-VL tower — patching, pad-token expansion and 3-part rotary
are the engine core; --mm-max-patches available),
and frank-secondary through
mmproj-MiMo-V2.6-Distill-Qwen-9B-f16.gguf passed as --mmproj — the MiMo
GGUF itself carries no vision tensors. frank-secondary's contextWindow is
200704 (resliced from 180224 on 2026-10-03), the per-slot window, not the
model's native 262144: the harness must compact before llama.cpp answers a
longer prompt with a 400. Note also
that
the reasoning channel differs by runtime: llama.cpp AND SGLang (qwen3
parser, live-verified) emit reasoning_content, vLLM emits reasoning —
models.yml sets reasoningContentField per endpoint to match.
There is no audio
input anywhere in the fleet: that capability left with the FLM NPU
endpoint on 2026-09-11, returned 2026-09-17 with the Gemma4 projector's
audio encoder, and left again with the Gemma4 retirement on 2026-10-01
(the MiMo tower is vision-only).
frank-large — halogen-flash-server 0.16.2, Qwen3.8-Flash-Next v2 Swift1.5 ABLITERATED (Dankclaw, ACTIVE)
The flash-server engine (ghcr.io/peonist-ai/halogen-flash-server@sha256:0c61bf84…,
digest-pinned, published tag 0.16.2, 3.6 GB image) as a podman container
driven by scripts/serve-frank-large.sh under a root systemd unit
(scripts/frank-large.service, User=dank, Restart=always,
ExecStop=podman stop -t 60 frank-large-halogen, the script runs podman run FOREGROUND — the container's exit code is the service's exit so
Restart=always stays real, and the engine ledger lands on disk) on port
7770 from the Strix Halo iGPU. Engine stdout goes to
/home/dank/logs/frank_large.log — the boot ledger (weights resident, KV
pool, MTP head, prompt cache, any clamp) lives there, not in the journal.
Cutover 2026-10-06 from the halogen 27B-dense era
(frank-large-halogen27b-dflash2, retired the same window).
Serving Quat3rnion/halogen-swift1.5-qwen3.8-flash-next-v2-abliterated:
qwen38-flash-next-v2-swift15-abliterated.hgn (66,687,678,464 B ≈ 62.1
GiB, sha256 9c880b8b… — a compacted r2 of the card's 89,775,868,032 B
append-only original; the abliteration workflow appends and the repo's
tooling drops dead padding, live tensors byte-identical) + the REQUIRED
n-gram lookup table qwen38-flash-next-ngram.hgn (51,200,246,144 B,
peonist @5cc17cea) + the vision tower qwen38-flash-next-vision.hgn
(897,916,416 B, @e053f488) + the flat tokenizer/ directory (6 files,
fetched fresh from peonist). Cutover 2026-10-06 from the halogen
27B-dense shape, chosen by Frank for the ABLITERATED base.
The format is the lock. The v2 .hgn loads ONLY in the
flash-server line — the 27B-era halogen 0.1.4 container refuses it, so the
engine moved with the model. The MTP head is INSIDE the checkpoint
(HALOGEN_MTP_HEAD stays unset; the separate qwen38-flash-next-mtp.hgn
sidecar is deliberately not fetched).
Product facts vs the 27B era, both regressions FIXED: the base is abliterated (the 27B was a censored-base finetune; refusals were an accepted trade there) and vision is ON (the 27B engine silently ignored its encoder — frank-secondary owned images for exactly one day at this endpoint).
Engine laws that shape the config (all in scripts/frank-large.env
with evidence): HALOGEN_SPEC_ADAPT=0 is MANDATORY — the default adaptive
policy disables the MTP head for whole requests after low acceptance and
HALVES decode; the head stays on and temp-1.0 traffic pays some acceptance
for it (accepted). HALOGEN_CTX=200192 is the PER-SLOT hard ceiling (400
naming the limit, never truncation); models.yml contextWindow: 200192
must match, and compaction at 70 % = 140,134 + 57,344 budget = 197,478 fits.
HALOGEN_KV_SLOTS=2 is LEGAL here — the 27B "slots>1 disables the drafter"
law does NOT carry over; batching and speculation coexist (the card's
quickstart ships 2 slots with the head), so 2 is concurrent capacity.
HALOGEN_KV_POOL_POSITIONS=400384 (explicit 2 × ctx; ~28 KiB/position ⇒
~10.7 GiB). HALOGEN_MAX_TOK=8192 is only the per-request DEFAULT (the
harness always sends 57,344); HALOGEN_MAX_TOKENS_CAP=65536 +
HALOGEN_QUEUE_TIMEOUT=7200 are a coupled pair (FLAGS.md table).
A server-side sampler EXISTS (HALOGEN_TEMPERATURE/TOP_P/TOP_K =
1.0/0.95/20, the card's thinking recipe) — an absent temperature is no
longer greedy; models.yml extraBody carries the same values, consistent
not load-bearing. Prompt cache is ON by default (PROMPT_CACHE=2): a warm
100k follow-up costs ~2 s vs ~88 s cold — the 27B engine's manual
HALOGEN_CACHE_MB pin era is over. response_format is unsupported.
Thinking lands in reasoning_content; the v2 chat template rejects
reasoning_effort outside xhigh|medium|low, so the models.yml fold
stays mandatory. Thinking tokens COUNT against the budget (empty content +
finish_reason: "length" when exhausted mid-thought). Vision: OpenAI
image_url content parts only; ≥256 px probe images or the model answers
"video".
Memory ledger (121.2 GiB unified; the referee is the boot ledger):
weights ~62 + KV ~10.7 + arena ~8 (3.8 + 8.4 × MAX_TOK/16384) + vision
~2 ≈ 82.7 GiB engine-side + HALOGEN_HOST_RESERVE_GIB=20 → ~18 GiB
margin over baseline co-tenancy. The 51.2 GB n-gram table rides as mmap'd
page cache beside the checkpoint — the card's quickstart arithmetic does
not bill it as resident, but READ the boot ledger and re-size if the
engine prints a clamp.
Fetch: scripts/download-frank-large-flashnext.sh into
/home/dank/models/halogen-flashnext-v2/ (-f + exact byte counts + LFS
sha256 + --verify-only, no token on the command line; resume goes
against the RESOLVED CDN URL because curl drops Range across HF's 302).
The serve gates mirror the deployer EXACTLY (byte-exact checkpoint +
n-gram + vision tower, flat tokenizer with all six files as regular
files) — the 2026-10-01 crash-loop lesson.
Runbook:
serverAppConfigs-docs/LLM/frank-large-flash-server-v2-swift15.md.
Rollback: revert the swap commit and redeploy — the 27B payload
(/home/dank/models/halogen-qwen3.8-27b/), its fetch script and the
halogen 0.1.4 image digest all remain on disk; the ROCmFPX door behind
that (scripts/build-rocmfpx.sh, pin 36e9acd) is untouched.
frank-secondary — llama.cpp on the RTX 3090 (Dankclaw, ACTIVE)
llama.cpp master (0.5.0-dev, commit 5fc4f3c; CUDA sm_86 build
/home/dank/GitPackages/llama-master/build-cuda/bin/llama-server,
GGML_CUDA_FA_ALL_QUANTS=ON) as a root systemd unit
(scripts/frank-secondary.service, relink_united into
/etc/systemd/system/), serving ajgazin/Swift-1.5-Qwen3.8-27B-Uncensored-Dynamic-MTP-GGUF
at RCO-IQ3_XXS -mtp (10,442,827,392 B, sha256 e13d3e74…) plus
the publisher's own mmproj-BF16.gguf (931,145,888 B, sha256
19acd7fc…), both /home/dank/models/Swift15-UncIQ3XXS/, on port 7771.
Cutover 2026-10-05 (evening) on Frank's explicit contract: 128k
context cap, KV at FP8, vision on, as many 128k contexts as fit;
reshaped twice on 2026-10-06 — morning to two 131,072 slots no-spec,
evening to this UNCERSED RCO-IQ3_XXS payload with MTP back on. The
same-day payloads it supersedes: the LIVE MiMo-V2.6 Q6_K shape and the
Ornith-1.5-9B Q8_0 swap that was committed (77decb5..380aafa) but never
deployed (blocked at the docs gate; the docs debt is what this section
settles).
Architecture: qwen3_5 hybrid, bigger — block_count 65 (64 real layers +
the blk.64 MTP head), full_attention_interval 4 ⇒ 16 full-attention +
48 Gated DeltaNet, native 262,144 window, dense. KV exists only in the 16
attention layers (4 KV heads × 256 dim): 64 KiB/token at f16, 34 KiB/token
at q8_0. The DeltaNet state is a fixed per-slot buffer (~150 MiB/slot at
48 linear layers × 48 value heads). Header facts were read from the Hub
file by HTTP range + struct parse before anything was downloaded.
The shape (2026-10-06, Frank's tight-fit order, MTP back on in the
evening): --ctx-size 262144 --parallel 2 = TWO 131,072-token
conversations (Frank's 128k cap each; n_ctx_slot = CTX_SIZE / PARALLEL), --flash-attn on pinned, q8_0 K + q8_0 V (llama.cpp's
FP8 class — no true fp8 KV dtype exists; 8.5 effective bits; supersedes
the same-day f16/f16 rule written for the Ornith 9B fit), all layers on
the GPU, --mmproj for vision, batch 4096 / ubatch 512. Speculative
decoding is ON (draft-mtp, depth 3): the -mtp file's head is drafted
against the main model's own weights; ngram-mod skipped on purpose — on
a qwen35 hybrid ngram disables recurrent-state rollback, so a rejected
draft corrupts the DeltaNet state.
Measured at the two-slot MTP boot (2026-10-06 evening): 23,636 used /
489 MiB free (nvidia-smi free field) — the tightest fit in the
endpoint's history, under the old 2-3 GiB floor BY ORDER; a 512×512
solid-red image still answers Red afterwards (489 MiB free after the
probe), so the fit carries the vision transients. The MTP draft ctx
costs ~2.4 GiB measured (23,636 − 22,728 + 1,561) — ~6× the ~0.4 GiB
the one-slot era assumed, because the drafter's KV is built against the
target's full 262,144 context (the draft window), not the 3-token
proposal depth; the lighter RCO-IQ3_XXS quant (−1.56 GiB vs IQ3_S-mtp)
funds it. Decode: 63.3 tok/s (recipe temp 1.0) / 72.9 (temp 0) with
MTP acceptance 49.8–62.4 % (48.0 no-spec — the drafter earned its
2.4 GiB). reasoning_effort probe unchanged: xhigh 200, high → 500
Jinja raise (the models.yml fold stays mandatory).
Vision with the publisher's own projector: ajgazin's repo SHIPS
mmproj-BF16.gguf in the same repo (the IQ3_S era's unsloth mmproj was
built from the SHARED BASE Qwen/Qwen3.8-27B, legal because Swift-1.5's
vision stack was hash-proven byte-identical to the base). The probe
traps carry over: ≥256 px probe images or the model answers "video";
only the OpenAI image_url content part reaches the model. New on
this payload: the uncensored model thinks more than the censored
Swift 1.5 — a 64-token budget is eaten entirely by
reasoning_content (empty content); 128 tokens clears the vision
probe.
The RCO-IQ3_XXS tier is a per-tensor allocation mix of stock quant types (IQ3_S 97 / BF16 96 / IQ3_XXS 83 / IQ2_S 72 / IQ4_XS 33 / IQ2_XS 32 / IQ2_XXS 30 / Q2_K 28 / Q4_K 19 / Q6_K 8 / IQ1_S 4 / IQ1_M 4) — stock llama.cpp loads it; the tensor-type histogram is the law (see Key Lessons). Publisher KLD vs Swift BF16: mean 0.002631 / 90th 0.042136 / max 34.49 — RCO is the publisher's "more experimental" family, and the payload is the UNCECERSED Swift 1.5 (23/100 refusals vs Swift 1.5's 98/100, KL 0.0884).
Runbook:
serverAppConfigs-docs/LLM/frank-secondary-llama-swift15-unc-iq3xxs-mtp-131072.md.
Rollback: /home/dank/models/Swift15-IQ3S/ (the IQ3_S-mtp payload live
until the 2026-10-06 evening swap — revert da36fa3 for the two-slot
no-spec shape) or /home/dank/models/MiMo-Q6K/ (revert to the
2×200,704 f16 shape — frank-secondary-llama-mimo-q6k-2x200704) or
/home/dank/models/Ornith-Q8/ (the committed-never-deployed Q8_0;
revert to 380aafa's tree).
frank-primary — Radiance (StillDeadcode), Qwen3.8-Flash-Next FP8 native, TP=2 (Dankserver, ACTIVE)
The radiance engine (StillDeadcode, Apache-2.0; image
stilldeadcode/radiance@sha256:4c3f484564bb2872784e4… digest-pinned,
287 MiB, libr4d@0.5.0 kernels prebuilt for gfx1201, engine as the image
entrypoint) serving the official Qwen/Qwen3.8-Flash-Next-FP8
checkpoint at NATIVE precision — modelopt block-FP8 throughout, no
requantisation, no calibration. Plain podman run through
scripts/serve-frank-primary.sh under the root systemd unit
(frank-primary.service, User=dank, LimitMEMLOCK=infinity); the
container name is the unit name (frank-primary). Cutover LIVE 2026-10-06
00:55 (chain built 2026-10-05/06);
rollback tag frank-primary-freetoken-pr587-20261005 (the FreeToken trio
- Dockerfile are in the tag; the image and the orcarouter payload stay on
disk until the window closes), older rollback
frank-primary-vllm-shapeG-20261003.
Payload chain: official checkpoint → staging dir whose config.json
drops quantization_config → stack-qwen38-official-fp8.py (two
value-preserving reshapes: experts byte-stacked into the plugin's stacked
gate_up_proj/down_proj layout with _scale_inv at the same index — 49
stacks × 512 experts, no requantisation; PLE's 128 scaleless fp8 shards
decoded to one bf16 shard with the checkpoint's own bf16 scale
1.9931793212890625e-04) → rad-convert with ONE --quant rule — pure
copy for every weight, and the rtn rule re-encodes the bf16 PLE at that
same fixed scale, an exact round-trip that restores the original codes and
lands the plugin's one-element scale plane →
/home/dank/models/rad/qwen4exp-fp8-native.rad (177,109 MiB measured,
floor FRANK_PRIMARY_RAD_MIN_MIB=177000). The staging drop is the plugin
SELECTION law (spec §2.4): the descriptor is (arch_id, quant) matched
exactly, no shipped plugin claims (qwen4exp, "fp8"), the shipped
qwen4exp_fp8 plugin claims (qwen4exp, "") — and the descriptor is only
the selection key, per-weight encodings are data, so nothing else is
requantised.
Raw serve AND unmodified convert both refuse; that is the design. The
checkpoint itself is sha256-verified against the Hub (131/131 shards,
2026-10-05). Built by scripts/build-frank-primary-rad.sh (--plan-only
first — its declare phase is the engine's own, so a resolving plan boots).
Shape (both R9700s, TP=2): --tp-wire wht6 (fused lossy all-reduce,
+5.6–6.3 % prefill / ~−1.3 % 8-stream decode at TP2), --max-num-seqs 2
(Frank's first boot; raise from the ledger + slot occupancy), --max-model-len 200000 (native 262,144; the harness contextWindow must quote this — a longer
prompt is refused, never truncated), --placement expert_tiered --host-pool-mib 40960 (native FP8 experts are 112.8 GiB total, 56.4 GiB
per rank slice — the pinned pool is the price of native precision),
--expert-vs-cache-ratio 0.82 (the measured 99 %-hit point; 0.87 collapses
to 0 %), --kv-cache-dtype fp8 (7.32 KiB/token; a 200K sequence is
1.43 GiB), --num-speculative-tokens 3 (the checkpoint's own MTP head —
3,101 mtp.* tensors, probe depth 3), --max-num-batched-tokens 2048,
prefix cache 4 GiB pinned host + 64 GiB disk at
/home/dank/radiance-state, and --ngram-placement ram: the 47.7 GiB
PLE n-gram table (51.2 GB = 29 % of all parameters) serves from pinned
host RAM. Froggeric v22.5 chat template vendored
(scripts/qwen38-froggeric-v22.5.jinja, --override-chat-template).
The pinned-RAM ledger is why this is a root unit: 2 × 40 GiB pools +
47.7 GiB PLE + 4 GiB prefix host ≈ 134 GiB charged against
RLIMIT_MEMLOCK. ttm.pages_limit/pages_max cap GPU-mappable pinned
pages (pre-cutover cap 123 GiB — BELOW the plan); the serve script's
TTM preflight (FRANK_PRIMARY_TTM_MIN_MIB=140000) refuses to start until
both knobs are raised in the stop window (sysfs write first, kernel
cmdline + reboot only if read-only).
Contract facts (source-verified): the HTTP listener binds AFTER the
full load, so a bare curl /health gate is honest (/health == /ping,
200 serving / 503 stopping); sampling params temperature…preserve_thinking
accepted, unknown params 400 (models.yml's extraBody set is fully
inside it); response_format supported; logprobs REFUSED; reasoning in
reasoning_content and tool calls in the qwen3.8 dialect via the auto
chat format — no parser flags; vision native (the 27-layer Qwen-VL tower,
--mm-max-patches); /metrics carries vLLM-compatible names +
radiance:* families — the Dankclaw Prometheus scrape is re-added.
Runbook: serverAppConfigs-docs/LLM/frank-primary-radiance-qwen38-native-fp8.md.
Retired FreeToken era: serverAppConfigs-docs/LLM/frank-primary-freetoken-pr587.md.
Retired vLLM era: serverAppConfigs-docs/LLM/dankserver-qwen38-fp8-expert-offload-tuning.md.
Retired GLM experiment: serverAppConfigs-docs/LLM/frank-primary-glm53-flash-w4a16.md.
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") fromhipLaunchKernel, not as anything that names atomics. The value is consumed at driver probe time, so writing the AtomicOp Requester bit withsetpciat runtime changes nothing. Check the chain:lspci -vv -s <gpu>and every upstream bridge must showAtomicOpsCap: Routing+(aRouting-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 atworld_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_2at x8/x8 Gen5 on root ports00:01.1/00:01.3, every bridge nowRouting+and both endpointsReqEn+— 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_LEVELcosts 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 layerin 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 whatfrank-mediumran 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
-otis 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 0.15/0.85held 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>setshas_tensor_overrides(), a REQUIRED term of the scheduler'spipeline_parallelflag (llama-context.cpp:433 — the only place in the tree that reads it), and that flag is what setsn_copiesinggml_backend_sched_new; withn_copies == 1a 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)).=CPUis 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.cuon 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 x8on00:03.1), 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 forqwen3_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 createsDSTas a copy ofSRCand 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
/healthand 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.
- **Bundling a ROCm runtime next to a llama.cpp binary:
- mmap must stay on for the big-PLE models:
--no-mmapforces 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 withset -a, so a tunable namedTEMPleaks into HIP (TEMP=1.0sent the JIT cache to path1.0and segfaulted every load, fixed 2026-08-13 by renaming toTEMPERATURE). Never name a tunable these; check withstrings /opt/rocm-*/lib/libamdhip64.so.* | grep -xE "TEMP|HOST|GPU_MAX_HEAP_SIZE". -DGGML_CUDA_FA_ALL_QUANTS=ONis 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.weightand ship onlyblk.48(verified 3x). Don't re-attempt without new loader support. - QSA flash-attn assert:
GGML_ASSERT(a-type == GGML_TYPE_F32)on qwen4exp needsscripts/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=122402963456in/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/dmidecodeshow 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.shwaits up to 20 minutes (LLM_WAIT). On halogen, the FIRST request after a (re)start can go silent ~45–60 s (healthengine_unresponsive, 503s) and then self-recovers — do not restart over it. - Crash-loop procedure: (1)
journalctl -u <svc> -n 100+ kernel line viajournalctl -k(segfault at address 8 inlibamdhip64= 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 failedspam is a symptom, not a root cause. - Journal signatures: client abort logs
W srv stop: cancel task, id_task = N; natural stop logs onlyslot releasewithtruncated = 0. The server never preempts a running generation; excess tasks queue when slots are busy.
Host memory / swap
- Swap resize ordering: create and
swaponthe replacement BEFOREswapoffof the old one, or live pages must land in RAM thatMemAvailableoverstates. 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) — checkswapon --showbefore reasoning about headroom. - Silent RAM corruption outranks every software theory. frank-primary's ~40k-token output corruption (2026-10-04/05, repetition/garbage in long agent conversations) was marginal DDR5 at 4800 MT/s on four DIMMs, fixed by 4600. Consumer non-ECC memory raises no MCE for a silent flip, and a short in-band pattern check (60 s, 8 GiB of 246 GiB) is not a stability proof — combined, those two instruments said "ruled out" while the RAM was the cause. "4800 is the JEDEC floor on 5600-rated DIMMs" is a rating, not a margin guarantee. When the fault is data-shaped (NaN states, garbage tokens) and a software revert doesn't move it, price in the RAM before the runtime — and remember a revert tested under the same marginal hardware is itself confounded. See the runbook's 2026-10-05 section.
Runtime-specific guards
- Rootless podman cannot RAISE rlimits, and
--ulimit nofile=1048576dies at container create, not at runtime. runc reportserror setting rlimit type 7: operation not permitted(type 7 = RLIMIT_NOFILE) when the requested hard limit exceeds the host process's hard limit — on Dankclaw that ceiling is 524288. Inherited-equal limits are fine, somemlock=-1:-1works iff the unit grantsLimitMEMLOCK=infinity(systemd is privileged; the value flows through podman to runc without any raise). Upstream halogen's own run lines pass NO--ulimitat all — copy vendor run lines before adding flags (measured 2026-10-05 on the frank-large cutover). - Kairic Edge (if ever re-deployed): the pinned CK commit needs
third_party/composable_kernel/include/ck/config.hgenerated manually (untracked;git cleanremoves 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. - A GGUF's custom tensor type picks the runtime — read the histogram before
promising a file to a loader.
Qwen3.8-27B-Q8_0_ROCMFPX_AGENT.ggufis ftype 115 with 311 tensors of type 103 (GGML_TYPE_Q8_0_ROCMFPX); stock llama.cpp and gufo refuse it at load, so ROCmFPX was not a preference but the only door. Counting tensor types out of the GGUF KV section takes one python read and settles a runtime argument in minutes. The build identity matters as much as the fork: the 2026-08-25 ROCmFPX builds SIGSEGV inggml_compute_forward_set_rowson this same file, soscripts/build-rocmfpx.shpins commit36e9acdby SHA. - Speculative-decode flags move as a SET. Handing the ROCmFPX fork
--model-draftwith no--spec-type(the naive way to build a "no MTP" bench arm) segfaulted at load, core dumped, no diagnostic (2026-10-02). A baseline arm must strip--model-draftAND every--spec-draft-*AND--spec-type, or it measures a crash instead of the absence of drafting. - An orphaned scratch server taxes the whole host. A bench child left
alive by a client-side exception kept ~26 GiB of weights resident on a
121 GiB box, pushed
availableto 3 GiB, and every later rate was suspect. Record the child pid and kill it in afinally, then provefreecame back before believing a number. Kill by pid — neverpkill -f llama-server, which also hits frank-secondary.
llama.cpp serving
- MTP is a property of the FILE, not of the flags. The
-mtpGGUF build carries the head asblk.<n>.nextn.*(qwen35.nextn_predict_layers = 1);--spec-type draft-mtpthen setsload_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-mdargument. The plain build has no MTP tensors at all, and pointing--model-draftat the file would load it twice. - What can be chained, what cannot, and what a chain costs on a hybrid.
--spec-type a,bbuilds 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 isctx_dft: draftless types (the ngram family) are added unconditionally, whiledraft-mtp,draft-dflash,draft-dsparkanddraft-eagle3all require a draft CONTEXT. So a chain may hold one context-backed drafter plus any number of ngram types —draft-dflash,ngram-modis 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) — butdraft-mtp,draft-dflashdies 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 LEGAL chain can still lose on a recurrent model:draft-mtp,ngram-modon frank-large's qwen35 hybrid measured −15 % prose / −7 % block-copy (2026-10-03) — adding the ngram layer logsrecurrent state rollback is not compatible with 'ngram-mod' - disabling rollback support, and MTP verification depends on that rollback, so acceptance drops on ALL traffic even where the matcher fires. Measure chains per architecture, never by analogy. - 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-devicenames. 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 withROCm error: out of memory— after the model had loaded and/healthhad answered. Readsliding_windowout of the drafter's GGUF header before sizing any spec-decode deployment, and prefer a skewed-tsover 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-sizehas an OPTIMUM on the 2x R9700 layer split, not a plateau — and the curve is BACKEND-SPECIFIC, so never carry it across (next bullet). 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-sizedoes 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.)- On the CUDA 3090 the same knob has NO interior optimum up to 2048, so
frank-secondary ships 4096/2048. Measured 2026-10-05 by boot-pair A/B on the
live service: at 8,928 prompt tokens ubatch 1024 gives 3,972 / 4,077 t/s and
ubatch 2048 gives 4,207 / 4,212 — +4.6 % — for 616 MiB (free 2,849 →
2,279). Decode did not move (91.9–93.0 vs 93.8–94.3, i.e. noise), and a
279-token prompt, which is below either ubatch, came back identical — that is
the mechanical proof the knob was the only variable, since a prompt shorter
than the ubatch cannot see it. The logical
--batch-sizewas again free. And the predecessor's "ubatch 2048 failed the scratch boot" was a shape observation, not a law: the same file boots 2048 clean at 2 × 200,704. Bench it by restarting the SERVICE through a transientFRANK_SECONDARY_ENV_FILEdrop-in, never a scratch port — one card holds one server. See frank-secondary-llama-mimo-q6k-2x200704. - One
-tsstep 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.batsencodes 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-taskdraft 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. --paralleldivides the pool, so MORE conversations cost WINDOW, and the per-slot number is the contract — notctx-size.n_ctx_slot = CTX_SIZE / PARALLEL, and llama.cpp refuses a prompt longer than the SLOT (400 exceed_context_size_error: request (184001 tokens) exceeds the available context size (180224 tokens)) even when the pool has room. So frank-secondary's 2 → 3 reslice moved each conversation from the model's native 262,144 down to 180,224, andmodels.ymlcontextWindowhad to follow or the harness would discover the ceiling as a 400 on a long conversation. Side effect worth knowing: the shorter slot made decode ~5 % FASTER (106.8 vs 100.4 tok/s) — less attention to scan and one fewer DeltaNet state resident. The 2026-10-03 reslice went the other way (3 → 2 slots, 180,224 → 200,704, pool 401,408) to fund unquantized f16 V, andcontextWindowfollowed again; decode landed 104.8 tok/s — the ~2 % off 106.8 is the exact-V tax. The same day the freed space also bought the Q6_K rung (now 94.4 tok/s — the rung itself is a further measured −10 %, weight-bandwidth, not slot geometry). All moves measured; both slot directions cost or buy window, never pool. See frank-secondary-llama-mimo-q6k-2x200704.- Price a VRAM budget from two boots, never from a formula — and an mmproj
costs ~1.5x its file size. The frank-secondary 3090 fit was solved from two
measurements: 2 × 262,144 with no projector = 20,190 MiB used (KV 12,800 ⇒
non-KV 7,390), 3 × 196,608 with the f16 projector = 22,972 used (KV
14,113 ⇒ non-KV 8,859). The difference is the vision tower: a 918 MB file
that bills ~1.4 GiB, because the encoder's activation and compute buffers
ride with it. Subtracting the two rows is exact; extrapolating weights+KV+
"a bit for buffers" is what leaves 1.1 GiB free when you meant 2.7. Then
solve
KV ≤ card − non-KV − headroomand round to a multiple ofPARALLEL × 4096. Recorded inscripts/frank-secondary.envso the next resize starts from measurement. imagesandimage_urlare NOT interchangeable: only the content part reaches the model.--mmprojloads,usage.prompt_tokensrises, and the model still invents an answer if the client used the legacy top-levelimagesfield on/v1/chat/completions— frank-secondary answered "Brown." for a solid-red PNG that way and "Red." through the OpenAIimage_urlpart. The failure is silent because a hallucinated color is a plausible answer. Probe vision with a solid color and expect an exact word.--jinjais whattoolsneeds. On 2026-09-16 a subagent died with500 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--jinjaon and the serve script pins it; halogen also acceptstoolsand returnstool_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-secondary ran f16 for that reason until 2026-09-17, whenbuild-cudawas rebuilt with the option ON so the endpoint could take q8_0 KV. - llama-bench separates a LIST with
/and SWEEP values with,. Both-devand-tsfollow this:-dev CUDA0,Vulkan1is two single-device configurations, never one two-device run, and-ts 0.85,0.15is 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 owndevcolumn 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,mediumandlowforreasoning_effortand raises on anything else — HTTP 500, not a clamp — so the harness's levels must be folded onto that set inmodels.yml(compat.reasoningEffortMap). A role whose level is unmapped fails on its FIRST request, and the failure names Jinja, not the model: every subagent onfrank-secondarydied withUnexpected reasoning effort highuntilhigh: xhighwas added on 2026-09-16. Halogen accepts the wider set, so the two entries legitimately differ.
Ops
- Never
pkill -fa pattern that appears in your own command line — it kills your ssh session. Usepkill -x <exact-name>. - Both hosts allow passwordless sudo for the deploy user. Use plain
sudoin committed scripts (noecho pw | sudo -S);FRANK_SUDO_PWcovers hosts without it. - ComfyUI on Dankclaw runs with GPU access (
/dev/kfd+/dev/driviaAddDevice,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--cpuera 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=offon 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/accel0failserr=-19). Revert path inserverAppConfigs-docs/LLM/dankclaw-iommu-translation-off.md.- Rootless Quadlet containers run with
--replace --rm:podman logscovers only the CURRENT instance; history across recreations lives injournalctl --user -u <name>.service. Read rootless storage WITHOUT sudo (per-user storage —sudo podman logsfinds nothing). - A dead rootless podman pause process breaks ALL container management on the
host, and
podman system migratepanics in 5.7.0. Symptoms: everypodmancommand fails withinvalid 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 everyRestart=alwaysquadlet 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, andpodman system migratesegfaults inteardownNetworkBackend. Repair: reboot (/run/userclears and all 28 quadlets return on their own — checkLinger=yesandWantedBy=default.targetfirst). Seen 2026-09-16, hours into heavy GPU work on the same host — but the trigger is NOT established (journalctl -krecorded 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=hostservice at the host's LAN IP. netavark DNATs published ports only: from a bridge container192.168.0.143:<published>answers while192.168.0.143:<host bind>and the gateway10.89.1.1are both refused. Usehost.containers.internal(169.254.1.2). This is what 502'dhermes.franksdank.clouduntil 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
*.gguffilter misses mradermacher's payloads: large quants ship as.partNofMfragments.mradermacher/Qwen3.8-Flash-Next-Uncensored-i1-GGUFcarries 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.
- 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
- A fetch script must
-fand verify, or it reports success on an access error.curl -o FILE URLexits 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 cheerfulDOWNLOAD_DONEin 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.shalready 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 (flash-server 0.16.2, abliterated Swift1.5 v2 .hgn + MTP always-on, 2×200,192, vision ON, Dankclaw) | serverAppConfigs-docs/LLM/frank-large-flash-server-v2-swift15.md |
| frank-secondary (llama.cpp CUDA, Swift-1.5-27B Uncensored RCO IQ3_XXS-mtp, 2×131,072 draft-mtp q8_0 KV, Dankclaw) | serverAppConfigs-docs/LLM/frank-secondary-llama-swift15-unc-iq3xxs-mtp-131072.md |
| frank-primary (radiance StillDeadcode, Qwen3.8-Flash-Next-FP8 native, 2×R9700 TP=2, Dankserver) | serverAppConfigs-docs/LLM/frank-primary-radiance-qwen38-native-fp8.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 |
|---|---|---|---|
halogen 0.1.4 Qwen3.8-27B p1w4d-d2 + DFlash2 (frank-large) |
Dankclaw | 2026-10-05 → 10-06 (rollback target — payload + fetch script + image digest on disk; owns the prompt-cache pin and FA-tile lessons) | frank-large-halogen27b-dflash2.md |
ROCmFPX llama.cpp fork Qwen3.8-27B Uncensored Q6_0_ROCMFPX_AGENT + MTP (frank-large) |
Dankclaw | 2026-10-03 → 10-05 (rollback target, payload + fork build on disk) | frank-large-rocmfpx-q6agent-uncensored-mtp.md |
tcclaviger vLLM fork Qwen3.8-Flash-Next-Uncensored FP8, TP=2, shape G (frank-primary) |
Dankserver | 2026-09-29 → 10-05 (rollback target — tag frank-primary-vllm-shapeG-20261003; trio + env lore in the tag, image in rootless storage) |
dankserver-qwen38-fp8-expert-offload-tuning.md |
FreeToken PR #587 ROCm, Qwen3.8-Flash-Next-Uncensored-FP8, ONE R9700 (frank-primary) |
Dankserver | 2026-10-05 → 10-05 (rollback target — tag frank-primary-freetoken-pr587-20261005; trio + Dockerfile in the tag, image localhost/frank-primary-freetoken:pr587-77a7201 and orcarouter payload on disk) |
frank-primary-freetoken-pr587.md |
llama.cpp master MiMo-V2.6-Distill-Qwen-9B Q6_K 2×200,704 f16 KV (frank-secondary) |
Dankclaw | 2026-10-03 → 10-05 (rollback target — payload on disk; owns the ubatch-2048 A/B; the Ornith swap of 10-05 was committed but never deployed, so this was the LIVE payload Swift replaced) | frank-secondary-llama-mimo-q6k-2x200704.md |
llama.cpp Ornith-1.5-9B Q8_0, ONE 262,144 f16 KV (frank-secondary) |
Dankclaw | 2026-10-05 (committed 77decb5→380aafa, never deployed — superseded by Swift the same evening; payload on disk) | trail in frank-secondary-llama-swift15-unc-iq3xxs-mtp-131072.md |
ROCmFPX llama.cpp fork Qwen3.8-27B Q8_0_ROCMFPX_AGENT + MTP (frank-large) |
Dankclaw | 2026-10-02 → 10-03 (rollback target, payload on disk) | frank-large-rocmfpx-q8agent-mtp.md |
gufo v0.1.1 Qwen3.8-27B UD-Q8_K_XL/UD-Q4_K_XL + DFlash2 (frank-large) |
Dankclaw | 2026-09-28 → 10-01, again 10-01 → 10-02 (payloads removed from disk 2026-10-03; rollback = re-download) | frank-large-gufo-qwen38-27b.md |
vLLM TheRock MiMo-V2.6-Distill-Qwen-9B BF16 + cross-model MTP (frank-large) |
Dankclaw | 2026-10-01 (same-day rollback to gufo) | frank-large-vllm-mimo-v26-bf16.md |
llama.cpp master MiMo-V2.6-Distill-Qwen-9B Q6_K (frank-secondary) |
Dankclaw | 2026-10-01 → 10-02 (the rung returned ACTIVE 2026-10-03 at the 2×200,704 shape — frank-secondary-llama-mimo-q6k-2x200704.md) |
frank-secondary-llama-mimo-q6k.md |
llama.cpp master MiMo-V2.6-Distill-Qwen-9B Q5_K_M 2×200,704 f16 KV (frank-secondary) |
Dankclaw | 2026-10-02 → 10-03 (rollback target — one MODEL_FILE line, buys back 875 MiB + the −10 % rung tax; owns the boot-pair table) |
frank-secondary-llama-mimo-q5km.md |
SGLang MiMo-V2.6 INT8-W8A16-AutoRound (frank-secondary) |
Dankclaw | 2026-10-01 (same-day swap to the GGUF path) | frank-secondary-sglang-mimo-v26.md |
tcclaviger vLLM GLM-5.3-Flash W4A16 int4, +/- DFlash2 drafter (frank-primary) |
Dankserver | 2026-09-30 → 10-01 | frank-primary-glm53-flash-w4a16.md |
llama.cpp b11030 Qwen3.8-27B UD-Q8_K_XL + DFlash2 (frank-large) |
Dankclaw | 2026-09-21 → 09-28 | frank-large-unsloth-qwen38-27b-q8xl.md |
R9V radiance-vLLM Qwen3.8-Flash-Next-Uncensored IQ4_XS (frank-primary) |
Dankserver | 2026-09-27 (same-day swap to Q8_0) | frank-primary-r9v-radiance-qwen38-uncensored.md |
llama.cpp b11030 Qwen3.8-Flash-Next Q8_0 + shared MTP (frank-primary) |
Dankserver | 2026-09-26 → 09-27 | frank-primary-llamacpp-qwen38-flash-next-q8.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 |
vllm-radiance TP=2 MXFP4 + DFlash2 (frank-medium) |
Dankserver | 2026-09-20 → 09-26 | frank-medium-radiance-mxfp4.md |
Lucebox DS4.1 DeepSeek-V4.1-Flash ROCmFP23 (frank-primary) |
Dankserver | 2026-09-26 (same-day swap) | frank-primary-lucebox-ds4.md |
| kingjones STRIX Qwen3.8-Flash-Next ROCmFP4 | Dankclaw | 2026-08-30 → 09-11 | kingjones-strix-rocmfp4.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 |
unsloth llama.cpp b11030 Qwen3.8-Flash-Next UD-IQ4_XS (frank-large) |
Dankclaw | 2026-09-21 (same-day swap) | frank-large-unsloth-qwen38-flash-next.md |
Kairic Edge Qwen3.8-27B IU4 W4A4 (frank-large) |
Dankclaw | 2026-09-21 (same-day swap) | frank-large-kairic-edge-qwen38-27b.md |
ISTA-DASLab Qwen3.8-27B-GSQ-RCO IQ3_S (frank-secondary) |
Dankclaw | 2026-09-16 → 09-17 | frank-secondary-qwen38-gsq-rco.md |
vLLM Gemma4-12B w4a16 (frank-secondary) |
Dankclaw | 2026-09-19 (same-day revert) | frank-secondary-vllm-gemma4.md |
llama.cpp Gemma4-12B QAT Q4_K_M (frank-secondary) |
Dankclaw | 2026-09-17 → 10-01 | frank-secondary-gemma4-12b.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-secondary) |
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. |