The shared MTP head borrows the main model output head, which a -ts 1,1
layer split places on ROCm1. With tensor overrides set, n_copies==1 in the
draft's scheduler, and a borrowed output.weight in a ROCm1 buffer aborts the
draft graph (ggml-backend.cpp:941) when the draft context is on ROCm0 —
the unit crash-looped 4x at ~12 s per attempt during the 2026-09-26 cutover.
Probed live on the host: ROCm0 aborts identically, ROCm1 loads and serves.
Discovery, not guesswork: dump the GGUF v3 headers of the fetched parts
(scripts/dump-gguf.py, added — a dependency-free reader that never
touches tensor data, so a 50 GiB part scans in milliseconds) before
the first load.
What the dump says (parts 2-3, 2026-09-26):
- The 51B-param PLE n-gram table is ONE tensor: per_layer_token_embd.
weight, dims [160, 320001536], Q8_0, 54.4 GiB — exactly the whole of
part 3. It is the same tensor the shared MTP head borrows, so the
=CPU override is required for placement AND for the draft load
(GPU-resident borrow: "invalid vector subscript").
- The model is qwen4exp, 512 experts, top-10 routing
(qwen4exp.ple.ngram_size=3, heads_per_ngram=8).
- Part 1 is metadata-only (ntensors=0); parts 2-6 carry tensors.
The placeholder pattern ngram_embeddings matched nothing — dropped from
OT_OVERRIDES (env, serve-script default, seam, AGENTS.md, runbook,
LLM index) before it could masquerade as a working override at load
time. Deployed set: exps=CPU,per_layer_token_embd.weight=CPU.
Suite: 346 green.
The 2026-09-26 same-day cutover that ended the Lucebox DS4.1 detour:
Dankserver's :7770 endpoint is now unsloth llama.cpp (the b11030-mix
prebuilt, ROCm gfx120X, bundled runtime) serving
unsloth/Qwen3.8-Flash-Next-GGUF at Q8_0 — 175.30 GiB across six sha256-
verified split parts — on both Radeon AI PRO R9700s, as a ROOT unit (the
frank-large shape: no container, no generated unit).
The deployed contract:
- Placement law: layer split -ts 1,1 with -ngl 999; the routed experts
and the 51B-param n-gram (PLE) table are COMPUTED in host RAM via
-ot exps=CPU,ngram_embeddings=CPU (the x4-pair measurement: streaming
over PCIe loses at 3.7 t/s, computing in RAM does not care).
per_layer_token_embd.weight=CPU is required by the shared MTP head's
borrow path (a GPU-resident borrow crashes the draft load).
mmap stays on; --cache-ram 16384.
- Spec chain draft-mtp,ngram-mod: the shared Q8_0 MTP head
(mtp-...-shared-Q8_0.gguf, 2,786,568,256 B) at depth 2, with the
draftless ngram-mod matcher chained behind it — the only legal way to
layer two spec implementations in one process.
- Vision explicit: --mmproj names the BF16 projector (this build never
autoloads; a server without it comes up healthy and text-only).
- Reasoning: --reasoning-format deepseek → reasoning_content; the
Qwen3.8 template's {xhigh, medium, low} reasoning_effort gate folded
by reasoningEffortMap in models.yml.
- One stream, the model's full 262,144 context; greedy server default
with Qwen-recommended sampling riding compat.extraBody.
The deployer's deploy_llm_primary is rewritten for the root unit: it
gates every artifact at its declared byte count (stat -c %s, never wc -c
— which read the whole 377 GiB lucebox file for minutes on 2026-09-26),
retires the lucebox user quadlet to dated home trash, waits out port
7770, relinks/enables/restarts the root unit and waits up to 1800 s for
/health. The quadlet-era tree under dankserver/frank-primary/ is
archived (dankserver/.AGENTTRASH/20260926-llamacpp-cutover/ on this
box; git history everywhere else) and its planner mapping replaced by
the scripts/ trio.
Observability flips back to the llamacpp namespace: a frank-primary
Prometheus job at 192.168.0.235:7770 (cross-host LAN — the netavark
published-port quirk that forces host.containers.internal for the two
Dankclaw endpoints is same-host only), the LlmEndpointDown runbook
text, and the dashboard description for three llama.cpp endpoints.
Docs: the new runbook (frank-primary-llamacpp-qwen38-flash-next-q8.md),
RETIRED banners on the lucebox and radiance runbooks and their index
entries, the AGENTS.md fleet section rewritten for the root-unit shape,
and the homepage frank-medium card renamed to frank-primary with the
Q8_0 Flash-Next spec (docs.html #models and the modality note updated:
images on frank-primary and frank-small, audio on frank-small only).
models.yml: the dankserver provider is "llamacpp (dankserver)" serving
frank-primary, contextWindow 262144, maxTokens 65536 (compaction-gap
law: 183,501 + 65,536 <= 262,144), input [text, image].
Suite: 346 green (frank_primary_unit.bats rewritten for the root unit —
16 tests pinning the placement law, the shared-head requirement, the
explicit projector, HIP env hygiene (BIND_HOST, never bare HOST), and
the deployer's byte-count gates; the quadlet-era planner and
changed-tests mappings rewritten for the trio; the observability scrape
test asserts three llamacpp jobs again).
Rollback: the lucebox image (localhost/lucebox-rocm:gfx1201) and the
378 GiB payload stay on the host; the Qwen payload stays fetched, so a
re-swap in either direction is a redeploy, not a refetch.
Fetches into /home/dank/models/Qwen3.8-Flash-Next-GGUF/ keeping the Hub
layout: the six Q8_0 split parts (175.30 GiB — never concatenated, part
1's header advertises file_count=6), the shared Q8_0 MTP drafter head
(2.6 GiB — "shared" borrows the target's embeddings; unsloth's MTP guide
names it the recommended head), and the BF16 vision projector. Total
191,919,144,448 bytes.
Sizes and sha256s captured from the resolve endpoint's x-linked-etag/
x-linked-size on 2026-09-26; every artifact is checked for exact byte
count AND sha256, curl -f so an auth error fails instead of writing the
error body, resumable via -C -. The repo is public: no token machinery.
The frank-medium retirement tail the 2026-09-26 lucebox cutover left
uncommitted: the radiance quadlet tree, its swap/fetch tooling and its
seam test are deleted (archive copies live in dankserver/.AGENTTRASH/
20260926-frank-medium-radiance/ and scripts/.AGENTTRASH/20260926-
frank-medium-radiance/), the planner/allowlist/test-changed mappings
drop the service, and frank-large's chat template moves to scripts/
(its old home was the retired frank-medium dir).
Finished here:
- tests/frank_primary_unit.bats: the lucebox quadlet seam (boot
persistence, host-network bind, HIP_VISIBLE_DEVICES=0,1, HIP-reserved
env-name guard, checkout-mounted entrypoint/healthcheck, first-start
patience, deployer payload/port gates).
- test-changed.sh: explicit .AGENTTRASH/ case — retirement commits move
files to trash, and the wrapper refused those additions with "no
focused-test mapping".
- observability: the vllm: namespace left with the radiance runtime.
Rules keep only llamacpp:* series (prefix-cache reuse, spec-decode,
queueing, endpoint-down); the dashboard drops the vLLM KV/latency
panels; prometheus.yml documents that frank-primary (lucebox) has no
/metrics and therefore no scrape job. llm-fleet.json was left
corrupted mid-edit (missing opening brace) and is rewritten from HEAD.
Suite: 339 green (was 7 red).
The runtime's auto budget is gpu_free - kv - warm - safety (22.35 GiB), which
leaves only the 0.50 GiB safety margin free while the fit check demands the
1.50 GiB discrete headroom, so auto-sizing refuses on any 32 GiB target:
"device 0 memory: 30.97 of 31.86 GiB used, 0.89 GiB free (headroom 1.50
GiB): does not fit". 18000 MB is the value DS41.md measured its R9700 rows
at: ~1500 experts resident, ~5 GiB free on device 0.
--ds4-prefill dense made requires_monolithic_model() true, and a monolithic
load asks ggml for the entire 187 GiB expert set as one device-0 buffer:
"allocating 191932.25 MiB on device 0: cudaMalloc failed: out of memory",
followed by "monolithic HIP load required for dense prefill". Approximate
prefill (dense, sparse) is expressible only where the experts are resident
(in-process owners). exact feeds the prompt token by token, which is the
path the hybrid tier streams experts for. Chunk follows DS41.md's
cold-expert recipe (1024).
wc -c falls back to reading the whole stream when its fstat shortcut does
not apply, and this gate runs over a 377 GiB GGUF: the 2026-09-26 cutover
deploy sat in wc for minutes (30 s of CPU, NVMe-bound) before it could
reach the cutover at all. stat -c %s is metadata-only and equally exact.
The llama.cpp hunk (ggml_cuda_node_launches_nothing) was needed on main's
tree; the branch restructured that file and compiles clean, so only the
apt-list and cmake-3.31 hunks remain. Regenerated from the host clone.
The deepseek41 architecture exists only on Luce-Org/lucebox's
feat/ds41-engine branch; main rejects the checkpoint with
"unsupported model architecture 'deepseek41'". Re-aim the image build at
that branch and fix the launch shape, which had been copied from the V4
DS4.md recipe:
- drop --ds4-fused-decode and --ds4-fused-verify-f16-kv, and use
--ds4-prefill dense: V4.1's validate_model_features refuses the V4-only
prefill/fused paths (layer split and --mmproj too).
- --chunk 4096 (the V4.1 dense-prefill measurement point), --max-ctx
131072 (the V4.1 default window), --prefix/--prefill-cache-slots 0 as
the DS41.md bring-up recipe.
- drop --cache-type-k/v: the DeepSeek4 backend ignores them; the MLA
compressed caches are F16 by design.
- expose BOTH R9700s and set LUCE_EXPERT_STREAM_DEVICE=1, so hip:0 owns
the dense weights plus the hot expert stack while hip:1 holds the
streamed-expert slot cache instead of competing with it.
- quadlet: 384 routed experts per layer, Engram tables, 40 layers.
Replaces frank-medium (vllm-radiance TP=2) on :7770. The 377.2 GiB
43-layer MoE (256 routed experts, top-6) is mmapped: dense work and the
MLA KV cache on the R9700, routed experts computed on CPU from the
page cache (246 GiB RAM). The unit bypasses the image entrypoint
(Qwen/DFlash-only flag set) and execs luce_server with the DS4 launch
shape; --ds4-fused-decode's monolithic-load fallback IS the serving
mode here. deploy_llm_primary gates on image + model byte count,
stops/masks the radiance unit, waits for :7770, installs and starts.
Runbook: frank-primary-lucebox-ds4.md.
With a missing file, -C - sends Range: bytes=0-, which HF's xethub
CDN rejects with 400. Xet-backed repos (e.g. Lucebox/DeepSeek-V4.1-
Flash-ROCMFP23-GGUF) fail on the first fetch; the old LFS backend
tolerated the zero-offset range.
Dim the spec line (--dim) so the card reads pale role -> dim spec -> bright
spring-green inputs -> dim use. The inputs line now pops as the bright middle
tier and the spec/use are de-emphasized as reference detail.
Add --input: #00ff9d to the palette and point .desc-inputs at it, so the
Inputs line is visually distinct from the bright-green spec (--fg), the
pale-green role (--head), and the dim-green use (--dim).
Each LLM card now lists its accepted inputs as a line (Inputs: text · image ·
audio), sourced from the harness models.yml:
- frank-large: text (no vision projector)
- frank-medium: text, image (Gemma4 vision path)
- frank-small: text, image, audio (Gemma4 projector audio encoder; audio is
not in models.yml's input list only because OMP's schema rejects it, but the
endpoint accepts input_audio parts)
New .desc-inputs CSS + bare-mode reset; /docs model guide gains an Inputs line
per model. bats 30/30 + live render verified.
Each LLM card now carries a details object (role/spec/use) rendered as a
bold pale-green role, a bright-green spec line, and a dim 'Use:' line.
app.js descHTML() falls back to the plain description for non-LLM cards;
new .desc-role/.desc-spec/.desc-use CSS + bare-mode reset.
Roles made neutral (no nicknames): frank-large = deep reasoning,
frank-medium = primary model, frank-small = fast utility model.
The /docs model guide was fixed — it had drifted to retired model info
(frank-large as Qwen3.8-Flash-Next 87.3 GiB/200k, frank-medium as FP8
~31 GiB) — now Qwen3.8-27B UD-Q8_K_XL 31.5 GiB/262k and MXFP4/W4A8
19.4 GiB, reordered large->medium->small. bats 30/30 + live render.
frank-large: cybersecurity + debugging (requires Frank's permission)
frank-medium: primary intelligent model (surpasses Claude Sonnet 5 per
Artificial Analysis) — software engineering, sysadmin, instruction tasks
frank-small: fast/cheap utility model — agentic search, RAG, research
subagents, translation, roleplay, summarization, small utility tasks
Updated both the status cards (services.json) and the /docs model guide.
The auth works via the modern /Users/AuthenticateByName endpoint (what the
web UI uses). The 401 was a test artifact from probing the dead legacy route.
No config change needed; LDAP-Auth plugin + authentik 2026.8.3 outpost healthy.
The UserWriteStage writes prompt_data['password'] via user.set_password().
A PasswordStage only authenticates the current password. Document the
correct mechanism (password field on the default-user-settings prompt +
empty-password guard policy) and the throwaway-user verification.
The default-user-settings-flow was missing a PasswordStage, so users could
edit name/email/locale but not their password. Added a PasswordStage
(InbuiltBackend) bound at order 101. Documented the flow's stage table and
the two ORM gotchas (MTI through model, required backends array).
The local username/password path is retired (ENABLE_LOGIN_FORM +
ENABLE_PASSWORD_AUTH false, ui.enable_login_form DB override false) and
qa-e2e-admin is out of the authentik Admins group. Documented in the SSO
section and History.
The authentik OIDC round-trip is verified, so retire the local
username/password path. ENABLE_LOGIN_FORM hides the form and
ENABLE_PASSWORD_AUTH refuses password logins; the only way in is now
the OIDC flow, which folds into the local account by email. The
ui.enable_login_form config-DB override is flipped to false in the
same change (the DB wins over env, so both must agree).
Footer link opens the authentik default-user-settings-flow in a new tab,
giving users a self-service entry point to change their password and
manage MFA/credentials without admin intervention.
systemd splits unquoted Environment= values on whitespace, so the
quadlet quotes OAUTH_SCOPES to keep all four scopes; update the bats
assertion to expect the quoted form (it was checking the old
unquoted line and failing).
Records the LDAP-Auth plugin wiring: the Jellyfin LDAP provider +
outpost on Dankclaw, the svc-jellyfin-ldap service account, the
jellyfin_users/jellyfin_admins access groups, and the key gotcha that
the bind credential is a PASSWORD (set via Recovery), not an API/app
token — the default auth flow's standard-password backend rejects
tokens with 'flow error password: Invalid'. Verified end-to-end:
alex (in jellyfin_users) logs in with their authentik password and the
plugin creates the matching Jellyfin user.
systemd splits unquoted Environment= values on whitespace, so
'OAUTH_SCOPES=openid email profile roles' arrived as 'openid' and the
authorize request carried a single scope — the id_token then lacked the
email claim and the callback failed. Quoted, all four scopes flow.
Also: assign the default openid/email/profile ScopeMappings to the
provider (2026.x no longer auto-creates them; without them the token
grant is the intersection with the provider's mappings = roles only,
and userinfo 403s).
fill-verify-Enter with a single inputValue read per stage (identification
and password); the toHaveValue assertion hard-failed every attempt when the
re-render wipe landed inside its 5s window (00-auth.setup failure 2026-09-24)
Boot 2026-09-22 at 0.98 fill: KV pool auto-sized to 425,047 tokens (1.62x
the 262,144 window) with 14.42 GiB per card available for KV. The DFlash2
drafter on the Swift finetune measures mean acceptance length 7.00 / 85.7%
(easy) and 5.08 / 58.3% (varied) — it survives the base-model change.
Replaces the estimated ~420k / ~17.6 GiB figures with the measured values.
0.99 failed the vLLM startup memory check before weight load: the R9700
reports 31.86 GiB total but only 31.23 GiB free at device-init (the ROCm/HIP
context + NCCL + radiance custom all-reduce consume the 0.63 GiB gap), so
0.99 (31.54 GiB) exceeded free and the container crash-looped. 0.98 (31.22
GiB) is the ceiling and the prior production value.
Also fixed the runbook KV math that had shipped with the 0.99 change: the
~730k pool estimate was impossible (MXFP6's 25.16 GiB weights > MXFP4's
19.37 GiB, so the pool is smaller, not larger than MXFP4's 486k) and the
34.2 GiB/card figure was not the R9700 total. Recomputed ~420k tokens at 0.98
fill.
The Qwen-Image 2.1 VAE is a video VAE (5D convs, time_conv, depth-3).
ComfyUI detects it as WanVAE (latent_dim=3), but EmptyLatentImage produces
a 4D latent. The decode function's memory_used_decode lambda accesses
shape[4] which is out of range for 4D.
Fix: expand 4D latents to 5D in the decode function when latent_dim==3.
Added to the patch script for persistence across container recreations.
The serve script now passes --chat-template-file pointing at the
Qwen-Sharp v22.4.0 template. Without it the binary falls back to the
built-in peg-native template, which produces a ~73,600-token prompt for
a ~250-token request. With the sharp template wired in, the same request
produces a 62-175-token prompt.
The serve script only passed --chat-template-kwargs, so the binary fell
back to the built-in peg-native template. A 250-token request produced a
73,600-token prompt (280x the expected ~260). Wiring in --chat-template-file
drops the prompt to 62 tokens. Draft acceptance 0.79 (mean 4.14), model
answers correctly, reasoning lands in reasoning_content.
Frank
