The first no-redirect HEAD fix read X-Linked-Size on every 3xx, but
non-LFS files on a Xet-backed repo answer 307 to HF's own
/api/resolve-cache WITHOUT any X-Linked-Size header. The fallback to the
stub's Content-Length recorded the redirect page size (254-264 bytes)
instead of the file size, so hf-fetch.sh failed the size check on every
aux file it verified against the regenerated manifest (README.md
"65400 != 254", config.json "72514 != 258", 7 files on the FP8 repo).
Distinguish the two redirect shapes: 3xx WITH X-Linked-Size = LFS/Xet,
whose X-Linked-* headers are the truth and whose redirect must NOT be
followed (the Xet bridge ETag is the CAS hash, not the sha256); 3xx
WITHOUT = non-LFS, where the Location (followed once, via urljoin)
answers 200 with the real Content-Length and a git-blob-sha ETag that
the 64-hex gate correctly rejects (size-only check for those files).
Verified against Qwen/Qwen3.8-Flash-Next-FP8: all 7 previously-failing
aux files now record their on-disk byte counts exactly (README.md 65400,
config.json 72514, merges.txt 3353259, ...), shard shas unchanged
(model-00002 6841fe21...), total 172.82 GiB across 144 files.
On Xet-backed repos (Qwen/Qwen3.8-Flash-Next-FP8), the resolve endpoint 302s
to a CDN bridge whose final ETag is the Xet CAS chunk-dag hash, NOT the
content sha256. urllib follows redirects, so the manifest recorded the Xet
hash and every downloaded shard failed sha256 verification against a hash no
download could ever match (8/8 shards FAIL, all sizes correct, on-disk bytes
matching the Tree API's lfs.oid). Classic LFS CDNs serve ETag=sha256, which
is why this was invisible on prior fetches.
Fix: HEAD via http.client, which does not follow redirects. 200 = direct
answer (Content-Length + ETag, non-LFS); 302 = LFS/Xet redirect
(X-Linked-Size + X-Linked-ETag = content sha256). Verified against the FP8
repo: shard model-00002-of-00131 now records 6841fe21..., the sha256 of the
bytes already on disk (cross-checked against the Tree API lfs.oid).
Instrument the live server to answer "can -ot target the most active
layers": AMD IBS op sampling on llama-server during 4 mixed concurrent
generations, sampled load addresses mapped through /proc/<pid>/maps to
backing tensors with extents derived from consecutive GGUF header
offsets (no quant type-size tables - a wrong per-element size silently
mis-buckets tensor tails, first run lost 59% of expert samples to a
junk bucket).
Measured (75 s window, 2.7M expert-tensor samples): per-block read
volume is FLAT, 0.93x-1.08x of mean across all 40 CPU-resident blocks.
MoE top-k routing fires every block every token, so "most active
layers" do not exist at -ot granularity - any 8 GPU-resident blocks
are equivalent, the lever is COUNT, already at the 5/3 VRAM ceiling.
Real skew is per-EXPERT (top 10% of 48x512 cells carry 40.5% of
samples), below tensor-override granularity. No config change.
scripts/frank-primary-expert-activity.py: dump + sample + analyze in
one entry point; --analyze-only re-analyzes saved samples. Instruments
production serving in place; not a benchmark.
Blocks 0-4 on ROCm0 + 45-47 on ROCm1. This exact shape was probed and
battery-verified earlier the same session: card0 2.54 GiB free at boot,
2.11 GiB after the vision graph (steady under load), card1 unchanged
at ~3.3 GiB. Card1 cannot take another block (0.82 GiB would OOM the
vision graph + boot drift), so 5/3 is the physical limit at the
4x262144 / V-q8_0 shape. OT assertion pins the new value.
- CONTEXT_SIZE=1048576 / PARALLEL_SLOTS=4: four conversations, each the
full native 262144 window (per-slot window unchanged; slots divide
the pool, they never multiply it).
- CACHE_TYPE_V=q8_0 / CACHE_TYPE_K=f16: main KV drops 24,576 -> 18,816
B/token (-23.4%); the shared MTP drafter's KV ignores the V type
(measured: 2,048 MiB draft pool = the f16 law at 1,048,576 cells).
- OT_OVERRIDES: blocks 0-3 on ROCm0 and 45-47 on ROCm1 stay
GPU-resident (2.42/2.49 GiB per block, measured); the rest stay
CPU-computed. Measured free under load: ~4.9 GB card0 / ~3.4 GB
card1; a 5th block on card0 lands at 2.27 GB, under the 3 GB
checkpoint floor, so blocks are atomic and 4 is the safe fill.
- serve script: --cache-type-k/v env-wired tunables; ONE joined
--override-tensor flag (b11030 deprecates repeated flags, and the
loader is first-match-wins, so the specific patterns must precede
the broad exps=CPU sweep).
- seams: the window test asserts per-slot = 262144 at 4 slots; new
KV-type test; OT exact-value assertion pins the ordering law.
29,696 B/token ctx-scaled (12 of 48 layers carry KV - full_attention_interval=4;
indexer and draft KV included); weights/RS/compute are ctx-independent.
262k = 18.75 GiB total / 9.37 per card; 100k = 14.3 / 7.1. Parallel
slots split the pool rather than multiplying it.
Both b11030 serve scripts never passed --metrics, so /metrics answered
501 and Prometheus could not scrape frank-large (silently down since
its deploy) or frank-primary. frank-primary also gets -lv 4 (VERBOSITY
env tunable, default 4) for the full per-buffer load breakdown.
Battery 6/6: alias, reasoning_content, tool_calls, vision (probe image
described exactly), reasoning_effort high -> 200. Decode 11.8 t/s at
depth-0 prose (draft 109/accepted 72), 0.864 mean len 2.73 on tool
traffic. VRAM 29%/36% (output-head card carries the drafter). Also
records the ROCm1 drafter law in the runbook body (borrowed output.weight
+ n_copies==1 abort) and the two cutover traps: foreign-process health
false green, and llama-server SIGTERM cleanup hang.
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.
The qwen_image21 detection check and GGUF node arch list patch are
applied by a startup wrapper (comfyui-start.sh) that runs before
ComfyUI starts. The patch script and wrapper are baked into the image
so they survive container recreations. The quadlet's Exec now points
at the wrapper instead of main.py directly.
The hermesadmin.franksdank.cloud dashboard (9119 — config, API keys,
sessions) is a distinct admin surface from the web UI client. Add it as a
third AI-section card; probe 9119 (302 login redirect counts as up, verified
on Dankclaw).
The admin Infrastructure section carried the retired 'dnsmasq' (probe-only,
no link) — Pi-hole FTL (a dnsmasq fork) replaced it on 2026-08-24. Replace it
with a linked Pi-hole card (pihole.franksdank.cloud, probe 8083 — the 403
basicauth counts as up). The Hermes card was probe-only; add the web UI
client link (hermes.franksdank.cloud). Both probes verified up on Dankclaw.
Knowledge-base follow-up to a45f396. The runbook, both index one-liners, and
the AGENTS.md topology row all still declared FP8 active; flipped to
just1moremodel/Qwen3.8-27B-Uncensored-MXFP4-awq with unquantized bf16 KV (pool
486,464 tokens, full 262,144 window), and recorded the causal nuance: fp8 KV
was on both arms, so the FP8-vs-MXFP4 gap was weight precision, not KV - clean
KV is a quality hypothesis for W4A8, not a throughput one. No verdict yet.
The quadlet's "TEXT ONLY ... 400 here" comment was wrong: vision works on the
MXFP4 checkpoint (Qwen3_5ForConditionalGeneration carries the vision tower
through the Gemma4 merge path, unquantized) - verified by naming a solid red
48x48 PNG "Red". Comment corrected; harness models.yml input stays [text,image].
Docs-only; no re-deploy (the endpoint already serves vision).
Swap the serving checkpoint back to
just1moremodel/Qwen3.8-27B-Uncensored-MXFP4-awq (quark/W4A8) and serve it with
KV_DTYPE=auto (unquantized bf16 KV) instead of the hardcoded fp8. fp8 KV
stacked on MXFP4's already-quantized W4A8 weights compounds attention-path
precision loss; clean KV tests whether that was hurting output quality. The
freed MXFP4 weights (19.37 vs 30.9 GB) buy the KV pool back, so the full
262,144 native window fits unquantized - MAXLEN returns to 262144.
The entrypoint gains a KV_DTYPE tunable (default fp8, the historical behavior),
shared across both quantization paths; the quadlet sets auto. Rollback: SNAP
back to the FP8 checkpoint with KV_DTYPE=fp8 and MAXLEN=192000.
The LLM backends section said two ROCmFPX endpoints; the fleet now serves
three (frank-large/medium/small) with different runtimes. Rewrite it, fix the
gotcha that claimed host.containers.internal does not resolve on a bridge
(it does — verified end-to-end for both on-host endpoints), and add a History
entry for the 2026-09-21 model-picker rebuild.
The per-key config DB already pointed web search at SearXNG (engine=searxng,
query URL http://192.168.0.143:8081/search), but only inside the data volume.
The quadlet now carries the same values as seeding env vars, so a fresh data
dir comes up wired, and the doc records the access path: the internal
host-published port, not the search. vhost — the Anubis->Authentik guard
chain is browser-only, and the bridge egress sits in SearXNG's pass_ip, so
the 4-req/IP/hour JSON cap never applies.
The user page now orders Web Apps, Media Library Apps, AI — the models sit
at the bottom, below the apps people click. The AI card and /docs#models
descriptions drop the infrastructure (runtimes, GPUs, tensor parallelism,
draft heads) in favor of what users care about: the hosted model, its
size, the context/parallel capacity, and what it's good at.
The build default is 8192 MiB. dankclaw is memory-tight (frank-large's
70 GiB GTT plus the rest of the stack) and Gemma4 runs fully on the 3090
(-ngl 999), so the CPU-side cache is not the hot path. Cap it at 2048 to
give back ~6 GiB of LPDDR. Gemma4 is not a DeltaNet model, so the
>12.8 GiB CACHE_RAM floor does not apply.
Wired through frank-small.env (CACHE_RAM) -> serve-frank-small.sh
(--cache-ram), with a wiring seam so the cap cannot be silently unwired.
Each section's panels fill an auto-fill row (as many per row as the
viewport allows) and the sections stack vertically — the side-by-side
column layout was the wrong read of 'render the sections horizontally'.
The board rendered vertically for a user whose browser had cached the
pre-sectioning style.css: deploys overwrite /srv/homepage in place, and
nothing told the browser to revalidate. The @home handler on the post-auth
listener now sends Cache-Control: no-cache, so every load is an ETag
round-trip (a cheap 304 when unchanged) and a deploy is always visible on
the next navigation.
The first cutover crash-looped the unit with 'invalid split file name':
the fetch script concatenated the three split parts into a single GGUF,
but part 1's header carries ggml.file_count=3, so the byte-correct
concatenation still advertises itself as a split and the loader demands
a -NNNNN-of-NNNNN filename.
- serve-frank-large.sh: -m points at part 1; llama.cpp loads the split
natively (parts 2-3 auto-discovered in the same directory)
- deploy-remote.sh: LLM_LARGE_MODEL gate path follows
- download-frank-large-unsloth.sh: assembly removed; the parts ARE the
canonical payload, verified against live Hub LFS oids
- docs: runbook model section + troubleshooting note, AGENTS.md, log
- the redundant 87 GiB assembled file is staged on dankclaw at
~/.AGENTTRASH/20260921-frank-large-assembled/
Both pages now group their panels under section headings rendered by shared
renderSection()/renderPanel() components in app.js (SECTION_ORDER fixes each
page's order: user = AI, Web Apps, Media Library Apps; admin = Media Library
Apps, Observability, AI, Infrastructure). The WIP badge splits into WIP: OPEN
and WIP: CLOSED via the wip value ("open"/"closed"); the checker passes the
value through as wip-open/wip-closed. The frank-large card follows the
unsloth llama.cpp cutover, frank-medium follows the FP8 checkpoint, and the
/docs model guide matches. Tautulli (Plex statistics, 192.168.0.235:8181)
joins the admin page's Media Library Apps section with an open link.
Only the 8084 forward is exposed; the desktop GUI runs inside the
container netns and is internal-only. Drop the now-unneeded
CUSTOM_HTTPS_PORT (no host-port conflict exists inside the netns).
lscr.io/linuxserver/calibre:9.15.0 (desktop build) running calibre-server
as the s6 main service on internal 8090 -> host 8084, auth-gated with a
plaintext userdb (mode 600) bootstrapped once by the deploy handler.
The desktop GUI is kept on 8080/8182, basic-authed with the same
credential pair via the machine-local env file.
The verification looped over every LFS file under UD-IQ4_XS/ and MTP/ in
the live Hub tree — the five MTP head variants we do not fetch (BF16,
Q4_K_M, Q8_0, shared-BF16, shared-Q4_K_M) printed MISSING, set ok=False,
and set -e killed the script silently between verification and assembly
after a 3-hour download. Verify exactly the FILES set instead (passed to
python as argv), and report NOT IN HUB TREE when an expected file has
vanished upstream. Also fix the layout comment: the transport parts live
in UD-IQ4_XS/, not parts/.
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.
Replace the CIRU v4.4.1 Orca runtime with the unsloth llama.cpp prebuilt
(b11030-mix-5ff778e, ROCm gfx1151, bundles its own ROCm) serving
unsloth/Qwen3.8-Flash-Next-GGUF:UD-IQ4_XS (87.3 GiB, three HF split parts
concatenated) on the Strix Halo iGPU. One conversation, 200,000 ctx,
PARALLEL_SLOTS=1, MTP depth 2 via the explicit -md shared-Q8_0 head
(sidecar auto-discovery does not search the mtp/ subfolder), text-only.
Fleet contract unchanged: port 7770, alias frank-large.
- serve-frank-large.sh: unsloth binary, -m/-md, --spec-type draft-mtp
--spec-draft-n-max 2, --jinja, preserve_thinking; gates on binary,
GGUF, MTP head; conditional --mmproj on ENABLE_VISION=1
- download-frank-large-unsloth.sh: resumable fetch of 3 parts + MTP head
+ mmproj, each verified against its LFS sha256 fetched live from the
Hub tree API; concatenates parts, records/verifies SHA256SUMS
- deploy-remote.sh: LLM_LARGE_MODEL/LLM_LARGE_DRAFT paths, pkill pattern
on the model path (not the binary name), wait_port_free gate
- tests: seams for 200k/1-slot, explicit -md, text-only, handler gates,
sweep safety
Runbook deployed-flags table and AGENTS.md now name the template
(froggeric v22.4.0, repo-tracked, terse by default) and the rollback
target; the stale qwen-fixed-v22.3.jinja row and the long-gone
MM_MERGE_ENGINE note are gone.
The template was staged in the working tree (then stashed by a peer for the
prometheus deploy) but never committed, so the live container kept serving
/patches/qwen-fixed-v22.3.jinja. Commit the repo-tracked template and flip
the quadlet: CHAT_TEMPLATE now points at it, mounted read-only at
/templates/qwen-sharp-v22.4.0.jinja. The entrypoint already passes
--chat-template on the shared exec path, so this applies to the FP8 shape.
Rollback: one env flip back to /patches/qwen-fixed-v22.3.jinja.
node-exporter is net=host, so its 192.168.0.143:9100 bind is a host bind,
not a published port — the bridge-networked Prometheus container cannot
reach its own host's LAN IP there (netavark DNATs published ports only).
The node-dankclaw target has been red by construction since the
observability cutover while the container reported healthy. Point it at
host.containers.internal:9100 (netavark delivers that to the host LAN IP,
where node-exporter listens) — the same rule frank-large and frank-small
already use. node-dankserver is a different machine and keeps its LAN
address. Update the cross-file contract test and the Targets table.
DFlash2 (100.0 t/s decode, 287.1 t/s burst-4) beats MTP self-speculation
(85.9 t/s, 179.7 t/s) despite a lower accept length (4.24 vs 5.66): the
small separate drafter steps faster than the target's own MTP layer applied
autoregressively. DFlash2 is the deployed shape; both swap-script paths now
default to dflash/7. Docs updated.
The entrypoint now reads the model's weight quantization from config.json
and serves the plain FP8 path (no MXFP4 patches, --quantization=fp8, MTP
self-speculation, ROCM_AITER unified attention with the R4D all-reduce)
or the MXFP4 patch-and-serve path. A model swap is now: change SNAP
(+ SPEC_METHOD/SPEC), restart.
- radiance-entrypoint.sh: quantization detection, gated MXFP4 env vars
and patch block, --quantization fp8 flag
- quadlet: SNAP -> Qwen3.8-27B-Uncensored-FP8, SPEC_METHOD=mtp, SPEC=8,
KV_MEM=0 (profile the shape, the documented plain-FP8 default)
- deploy-remote.sh: model-aware gates (read SNAP/SPEC_METHOD from the
quadlet; drafter gate only for dflash, r4d.so gate only for mxfp4)
- tests: quantization-aware drafter/spec and KV-pool tests
- hf-fetch.sh: generic, resumable, verified, idempotent HF fetch tool
- frank-medium-fp8.manifest: 17 files (10 config + 7 shards) with sizes
and LFS sha256
- shared/prometheus/rules/llm-fleet.yml: the llamacpp reuse recording rule
divided cached by prompt, but llama.cpp's prompt_tokens_total EXCLUDES
cached tokens (its own HELP line), so the ratio was unbounded — measured
77 on a fully-warm frank-large, meaning LlmPrefixCacheCollapse could never
fire on that side. Now cached / (cached + prompt), with the traffic floor
counting both terms too; the header documents the unit trap. Also fixed the
LlmEndpointDown description: frank-large's CIRU llama.cpp build DOES export
the llamacpp:* family (verified live), so the alert covers all three
endpoints.
- shared/grafana/provisioning/dashboards/llm-fleet.json: re-cut for two
namespaces. Every panel reads both (the endpoint picker selects); the
KV-pool-fill panel retired 2026-09-16 returned with
vllm:kv_cache_usage_perc; the latency p95 panel returned with the vLLM
histograms (TTFT/ITL/e2e); the alerts panel is scoped to the fleet's
Llm.* rules; the stale halogen-era description is gone. All 21 panel
expressions validated against the live endpoints.
- runbook + log + Observability: prefix caching measured, not inferred —
reuse happens at 1,648-token block granularity (attention block size padded
to the mamba page size); an identical 13,021-token prompt went 2.30 s cold
to 0.68 s warm with 9,888 tokens (76 %) reused, while a 2,521-token prompt
registered zero hits. Rule counts corrected to 6 alerts + 3 recording rules.
./tests/run.sh: 325 pass.
The radiance TP=2 cutover changed the metric namespace frank-medium exports
(llamacpp:* -> vllm:*) and left two scrape targets addressing host processes
by an address a container cannot reach.
- shared/prometheus/rules/llm-fleet.yml: two namespaces side by side. Added
LlmRequestsWaiting, LlmKvCacheSaturated (vllm-only gauges llama.cpp never
had), the job:llm_vllm_prefix_cache_reuse:rate5m and
job:llm_spec_accept_length:rate5m recording rules, and re-cut
LlmPrefixCacheCollapse / LlmSpecDecodeOff to OR both families with
per-family traffic floors so an idle endpoint cannot fire them. Every
expression validated against live Prometheus.
- shared/prometheus/prometheus.yml: frank-small -> host.containers.internal:7771
and frank-large scraped at host.containers.internal:7770. Both are HOST
processes on Dankclaw and netavark DNATs published container ports only, so
the LAN-IP targets were red by construction; frank-large's CIRU llama.cpp
build does export the llamacpp:* family, contra the old comment.
- tests/observability_quadlet.bats: the two seams now encode the new contract
(per-endpoint reachability by process type; every named series must be on the
measured list for its engine; engine-independent rules must name both).
- homepage docs.html/services.json: frank-medium sees pictures, frank-large is
CIRU Orca with a single seat (was halogen w4b, two seats, 200k).
- docs: radiance runbook is ACTIVE (deployed flags, three-arm battery, verified
capabilities, rollback, replica-era sections labelled); llama.cpp runbook
carries the SUPERSEDED banner; Dual-R9700-Cooperation states the measured
verdict; Observability records the namespace split and the DNAT lesson;
AGENTS.md topology/frank-medium/Model Config/Benchmarking Policy/runbook
index flipped; both indexes updated; work-log entry added.
Also repaired agent-pass damage: prose prepended above frontmatter openers,
duplicated runbook bodies, a literal tool-call token pasted into a runbook, and
an index destroyed by diff artifacts (restored from HEAD, flips re-applied).
Vault link check: 128 pages, 0 unresolved. ./tests/run.sh: 325 pass.
The conversation battery (scripts/bench-conversation.py, salted, same 10
prompts, 2026-09-20) measured three arms on the two R9700s:
arm I llama.cpp layer split 32:33 + DFlash2, Q8_0 geo decode 45.7 t/s, TTFT 0.72 s, burst-4 71.7 t/s
arm L llama.cpp tensor split 1:1 (RCCL), no drafter geo decode 30.5 t/s, TTFT 0.71 s, burst-4 54.3 t/s
arm R radiance vLLM TP=2 + DFlash2-FP8, MXFP4 geo decode 95.8 t/s, TTFT 0.21 s, burst-4 259.4 t/s
Radiance wins every axis, so it takes the alias. The board swap is what made
arm R possible: TP=2 was archived on 2026-09-16 because the second card sat
behind B650 chipset bridges with AtomicOpsCap: Routing-, and the ProArt
B850-Creator put both cards on CPU GPP root ports (Gen5 x8, Routing+, ReqEn+).
The R4D one-shot all-reduce needs no RCCL collective anyway.
- un-retire dankserver/frank-medium/: the TP=2 quadlet (banner rewritten —
it is the deployed shape now), radiance-entrypoint.sh, the healthcheck.
The replica pair and its affinity proxy stay archived; one process owns
both cards now.
- retire scripts/frank-medium.{service,env} + serve-frank-medium.sh and
bench-spec-ab.py to scripts/.AGENTTRASH/20260920-llama-layersplit/ as the
rollback path. build-llama-rdna4.sh and download-frank-medium-gguf.sh
stay: they are the tooling that rollback needs.
- deploy-remote.sh: deploy_llm_medium now gates on the image (pull once,
re-tag to the localhost name the quadlet resolves), the MXFP4 checkpoint,
the drafter, the pinned patch clone and the patched libr4d; retires the
llama root unit into the home trash instead of relinking it; then
install_quadlet + wait_container_healthy 1800s (first start compiles).
retire_vllm_medium_quadlets becomes retire_vllm_replica_quadlets — the
a/b/proxy trio only, since frank-medium is installed again.
- planner + test-changed map dankserver/frank-medium/** to frank-medium
and its seam; the scripts-trio mapping is gone with the files.
- tests/frank_medium_unit.bats rewritten for the container contract: boot
persistence of a GENERATED unit (no enable on this host's v1 generator),
TP=2 with the atomics-era NCCL workarounds kept out, the DFlash2 depth vs
the MXFP4 decode-kernel row band, the KV pin's coupling to the shape it
was calibrated at plus pool/VRAM arithmetic, the endpoint/tool/reasoning
contract, and the archive invariants.
- homepage card + docs updated, and they were stale twice over: they still
described the ajgazin Swift 35:30 / 393k payload, not the deployed shape.
Known regression, documented in the unit: vision. The MXFP4 checkpoint is
language_model_only and the launcher loads no projector, so images are a 400
here; the harness's vision role already routes to frank-small.
The warm-up request was a warm prefix-cache hit on the next run, so it
hid exactly what the arms were meant to differ on (prefill). Token
counts now come from the streamed usage of each job itself, and --salt
defeats cross-arm inheritance.
bench-conversation.py answers 'what does this endpoint feel like': ten real
jobs streamed once, TTFT split from decode tok/s, salted so no arm inherits a
warm cache, optional concurrent burst for capacity. Needed to compare the two
tensor-parallel runtimes the 2026-09-20 board swap unblocked.
dankserver-route-primary.sh pins eno1 (the fleet address, .235) as the
preferred default route after the board swap brought up eno2 with DHCP and a
lower metric; eno2 stays up as failover. nmcli device reapply, not connection
up, so the link this session rides is not torn down.
librccl DT_NEEDEDs librocm-core.so.1, so a GGML_HIP_RCCL=ON binary would not
exec from its bundled lib dir (measured: 'error while loading shared
libraries: librocm-core.so.1'). The layer-split build never pulled it in.
Frank
