command-center/agent/memories/--home-blank-Projects-serverAppConfig--/learned.md

• Two lessons from a bulk identity purge (2026-09-28, a sold workstation across serverAppConfigs + dank/command-center): 1) NEVER delegate mechanical prose/file rewrites to a subagent without a full diff audit. Observed failure modes in one run: list markers (- , * ) stripped so bullets stop rendering, numbered lists left with duplicate 3. entries, paths "corrected" to directories that do not exist (system/workstation/), and whole sentences deleted rather than reworded. Subagent edits are cheap to revert (git checkout the touched paths, excluding any files that carried pre-existing WIP) and expensive to trust. Reliable substitute: an exact-string, expected-count-asserted substitution script over a file list (abort on any count mismatch, write nothing for the failing entry), then print every + line and read it. 2) Classification beats blanket search when purging an identity from a config+docs tree. Three buckets: (a) narrative mentions - reword to a class ("the workstation"); (b) LOAD-BEARING mentions - keep, e.g. install.sh resolved packages/$HOST.pkgs from $(hostname), so the manifest FILENAME was the lookup key and the --host case list had to keep the hostname; (c) evidence - keep but de-identify (syslog excerpts keep timestamps and lines, only the host field is generalized). Hardware model strings stayed: subject matter, not identity. Frank's preferences: distill per-host doc directories into general pages rather than renaming them into a graveyard, and exclude auto-learned memory (agent/memories/**) from purges. Also worth knowing: OMP's user persona is ~/.omp/agent/APPEND_SYSTEM.md (not config.yml — that only holds personality: default); ~/.omp IS the live config checkout for the dank/command-center repo, so a branch switch swaps live config under the running agent, and a small live-config fix is best committed on the current branch with only its own file staged. (context: 2026-09-28: Frank sold the 'the workstation' workstation. Purge run across two repos (serverAppConfigs, dank/command-center at ~/.omp). Trigger for the lesson: I delegated a 17-file mechanical text scrub to a subagent and waited on it; it returned files with dropped list markers, a duplicated numbered item, an invented system/workstation/ path, and a deleted fact sentence. Reverted and redid it as a coun)
• DeepSeek-V4.1-Flash vs the box it must run on — durable sizing facts (verified 2026-09-28 from the HF API, not model cards): PAYLOAD. deepseek-ai/DeepSeek-V4.1-Flash = 475.27 GiB across 48 safetensors shards. Of that, 189.13 GiB is Engram — exactly two 94.56 GiB shards holding layers.{1,14}.engram.embed.weight (196B params, 4-gram lookup, 384,006,168 / 384,016,682 rows). Routed-expert params = 40 layers x 384 experts x 3 x 5120 x 2304 = 543.6 B, shipped as expert_dtype: fp4 = 269 GiB. Dense ~9.5 GiB. Lucebox's ROCMFP23.gguf = 377.51 GiB (179 GiB experts at 2.5/3.5 bpw + 189 GiB Engram + dense). The Engram tables are never mapped (2 table(s) embedded in the GGUF (not mapped)), so they do not evict the expert page cache. THE DECODE WALL ON A 63.7 GiB / 2x-R9700 BOX. A token selects 6x40 = 240 routed experts at ~11.96 MiB each. At the residency a hot stack can hold (37 of 384 per layer = 9.6%) that is ~2.4 GB of expert weights crossing PCIe per token; PCIe 5.0 x8 does ~55 GB/s real, giving a ~23 tok/s absolute ceiling — below a 35 tok/s goal before any attention/Engram/dense work. Resident fraction is the whole game. DS41.md's own reference host had 61 GB RAM; ours has 246 GiB, which is the only untested lever. CONTEXT — the three 2026-09-28 candidates: DeepSeek-V4.1-Flash 552B/16B-active (40 layers, 384 top-6, CED 20enc+20dec, CSA2, FP4 KV 890 B/tok, 1M ctx); MiMo-V2.6-Flash-MOPD 309B/15B (48 layers, 39 SWA/9 GA, 256 top-8, no shared expert, 5-layer MTP); GLM-5.3-Flash 320B/18B (KDA+DSA hybrid, mHC). Of these only V4.1 is 2.5x too big for this box; MiMo and GLM are smaller but have no AMD engine at all (vLLM/SGLang are NVIDIA-first; radiance-vLLM is welded to qwen4_exp). AFFINITY (Codeberg StillDeadcode) PORT SCOPE, from the real safetensors indices of both checkpoints. Its config parser is data-driven and its expert machinery ports unchanged — expert tensor naming is IDENTICAL (layers.N.ffn.experts.E.w{1,2,3}.{weight,scale}; 15,360 (context: Frontier-MoE feasibility study on dankserver 2026-09-28: sizing arithmetic for DeepSeek-V4.1-Flash / MiMo-V2.6-Flash / GLM-5.3-Flash, the Affinity-to-V4.1 port scope from real checkpoint indices, and three stale knowledge-base claims corrected.)
• Retiring a host from Frank's fleet means a name purge across four surfaces, and the doctrine is "generalize, never delete the lesson": (1) serverAppConfigs/ repo — grep -rniI -c name . (also sweep the machine's LAN IP, NM connection names and wifi SSID, which carry identity even after the hostname goes), retitle per-host doc sections to the CLASS of thing they describe ("## the workstation host DNS" → "## Multi-homed client DNS"), keep the operational content, and update any in-page #Anchor references the rename breaks; verify with ./tests/run.sh (346 bats seams incl. docs link integrity). (2) ~/.omp/AGENTS.md machine-facts table. (3) ~/.omp/agent/APPEND_SYSTEM.md — this IS the agent persona; the "### Your identity" paragraph names the fleet and the host, and new sessions only pick up edits. (4) ~/.omp/agent/managed-skills//SKILL.md and agent/memories//. A purge log entry in the work log must name the box neither, or it reprints what was just removed. Leave git history, browser history, and OMP logs/http-400-requests/* (past session payloads) alone unless explicitly asked; a history rewrite needs force-push + re-clones on both servers. TWO operational gotchas: ~/.omp is a LIVE deployment checkout (branch switches swap config under the running agent), so isolate a config fix by staging one path, not by branch-switching — switching back reverts the file you just fixed. And a dirty tree full of peer/agent WIP means git add path, never git add -A. (context: 2026-09-28, Frank reported the dev workstation (the workstation) sold and asked for a full purge, then "fix the agent persona" after I flagged it. Persona location and the live-checkout hazard were the non-obvious finds; the rename-don't-delete rule is the reusable part for future host retirements.)
• Never carry line numbers across hashline edit calls: re-read the target range for a fresh tag before every subsequent edit, and never compute offsets from a botched apply's result. Multi-op edits resolve all PUT/CUT indices against the ORIGINAL numbering, and a post-failure diff view elides lines — so a second call built on those numbers duplicates text instead of replacing it. Same rule for the imperative edit tool: assert the whole replaced region in the anchor, re-read to confirm, and repair any duplicated lines immediately. (Context: a hostname purge on serverAppConfigs 2026-09-28 — a two-line edit left a 3-line remnant, and the follow-up PUT 29.=35/60.=63 then pasted 7 fresh lines beside 3 stale ones, duplicating the Proton-gate and deploy-flow paragraphs.) (context: 2026-09-28 serverAppConfigs doc purge (5 files) — reproduced a line-number-drift failure in the hashline edit tool and repaired it.)
• R9V radiance-vLLM (dankserver frank-primary): PLE mmap→HIP registration (54.4 GB) can exceed the engine's 600 s VLLM_PLE_OFFLOAD_READY_TIMEOUT default under page-cache churn (measured 740 s, right after a bench teardown). Signature: worker log "TimeoutError: PLE offload worker did not become ready" ~16 min into load, then the PLE worker finishes registration AFTER the engine already tore down (BrokenPipeError on the late worker). WORST part: serve-frank-primary.sh exits 0 on docker wait, so systemd logs "Deactivated successfully" with NO error in the journal — a silent prod failure that reads like a clean stop. Fixed in production 2026-09-28: R9V_PLE_READY_TIMEOUT=1800 in scripts/frank-primary.env, forwarded by fork launch.sh 2de0357 (local-only). Any future R9V engine that waits on a registration/registration-like step: check for a hidden readiness timeout env in vendor/vllm/vllm/envs.py before debugging "clean" deactivations. (context: frank-primary 2026-09-28: bench matrix E1/E3 init failures + a failed 09:46 production boot all traced to the 600 s PLE readiness timeout)
• R9V radiance-vllm-qwen4exp (dankserver frank-primary, Q8_0) — verified 2026-09-28: (1) PLE registration (54.4 GB mmap - HIP) can exceed the engine's 600 s VLLM_PLE_OFFLOAD_READY_TIMEOUT (default, vendor/vllm/vllm/envs.py) under page-cache churn — measured 740 s right after a bench teardown. Signature: container dies ~19 min in, unit logs "Deactivated successfully" with ZERO error in journal (serve-frank-primary.sh exits 0 on docker wait), endpoint just never serves. Prod fix: R9V_PLE_READY_TIMEOUT=1800 in scripts/frank-primary.env, forwarded by launch.sh fork commit 2de0357 (local-only). (2) Bench matrix laws for the q8 shape: prefill chunk 4096 is the ceiling (16384 boots but 0.93 GiB VRAM free - requests hang/OOM; 8192 works: PP8K +25.9% but decode -8.5%); expert cache 80 slots is the POLICY max (doctor: "cache prepare backend requires capacities (48, 64, 80) with synchronous single-fill LRU" — async unsupported, 96/112 also fail expert-budget [108,198] rank maxima); MTP depth 6 is 3.7x SLOWER than depth 4 (454-489 vs 128-159 ms/step, tokens/step barely grows); unqualified shapes fail MID-REQUEST (health stays 200, stream dies). (3) Prefix caching (R9V_ENABLE_PREFIX_CACHING=1): zero VRAM cost (hits reuse freed KV blocks), cold path unchanged, reuse hits 32k 44.2-3.6-4.3 s (9x), 131k 439-6.9 s (63x); hit pattern rounds 1-2 MISS, round 3+ hit (identical-prompt and conversation-growth). Recommended for prod, pending Frank's go-ahead (q8 state opts out with =0; launcher default is ON). (4) deploy.sh refuses to run from non-main branches ("deploy.sh must run from the main branch") — ff main to the working branch and push before deploying. (context: frank-primary bench matrix + 9h downtime incident + PLE timeout boot failure, dankserver 2026-09-28; repo commit f187165, runbook serverAppConfigs-docs/LLM/frank-primary-r9v-radiance-qwen38-q8.md "Prefill / decode bench matrix" section)
• frank-primary Q8_0 cutover (2026-09-27, commits e5a06f5-era trio + docs): (1) The R9V launcher now carries an opt-in chat-template passthrough — R9V_CHAT_TEMPLATE_FILE mounts file:/opt/r9v/share/chat-template.jinja:ro and passes --chat-template (wins over the tokenizer dir's metadata/chat_template.jinja); R9V_CHAT_TEMPLATE_KWARGS maps to --default-chat-template-kwargs. Value with braces in the env file gets the single-quote law (bare double quotes are stripped by bash assignment parsing). (2) Behavioral template test: request reasoning_effort "high" — the embedded template 500s ("Unexpected reasoning effort"), the sharp template folds high→xhigh → 200. (3) Probe gotcha: bare docker on dankserver is NOT the shim (PATH-dependent) — docker logs/inspect silently return nothing for podman-rootless containers; use podman logs (as dank) or export PATH with .podman-shim first. A green health probe plus "no such object" from docker inspect is the shim-missing signature, NOT the false-green stray law. (4) vLLM MTP acceptance lives in APIServer logs: SpecDecoding metrics: Mean acceptance length: N (metrics.py:120, ~every 10 s); measured 2.88–4.50 live. (5) systemd unmask returned success but LEFT the runtime mask symlink (/run/systemd/system/unit - /dev/null) in place on the relinked unit — verify with ls -la /run/systemd/system/unit after unmask, remove by mv if still present. (6) vLLM engine logs do NOT reach docker/podman logs when the launcher runs the engine detached inside the container; APIServer lines do — grep those for spec metrics. (context: frank-primary q8 cutover on dankserver 2026-09-27; launcher commit 30d4a32 (fork local), repo commit + docs pushed)
• Why Q8_0 decoded ~11 tok/s vs uncensored IQ4_XS 59–96 tok/s on radiance-vllm dual-R9700 (verified 2026-09-27, not guessed): decode on this runtime is expert-bandwidth-bound; every token activates the same top-8×48-block expert set, so per-token expert BYTES decide speed. (1) Q8_0 doubles bytes/expert (1.0625 vs ~0.5625 B/param; 92.39→175.30 GiB payload). (2) Frozen-config budgets then HALVE, because the tiered residency budget is bytes-driven over fixed ~32 GiB cards: R9V_MAX_EFFECTIVE_EXPERTS_PER_RANK 222,428→108,198, R9V_TIERED_EXPERT_CACHE_SLOTS 160→80, R9V_MIN_FREE_VRAM_GIB_BY_RANK 1.5→3.0, PLE table 28.8 GB (residency ssd, 16 GiB pinned reserve)→54.4 GB (residency pinned). (3) Live uncensored residency that buys 59–96 tok/s: rank0 hot=4.36/cold_UVA=36.03/dynamic_cache=10.91 GiB/155 slots; rank1 hot=16.18/cold_UVA=4.24 GiB (~31 GiB expert working set in VRAM). Q8_0 cannot afford that shape. (4) The 2× bytes became 5–9× slowdown via the residency cliff: below the hot-set size the LRU hit rate collapses non-linearly and misses stream from pinned host RAM over PCIe (same law as the x4-pair experiment: residency fraction is the whole game). (5) Probe caveat: the 11.0 tok/s figure was ~the 3rd request of the container's life (80-slot LRU cold, reasoning tokens + TTFT included, single 256-tok shot) — a floor, not a steady-state number; measuring true steady state needs a bench window: stop prod, relaunch from /home/dank/r9v-state/q8xl/START-COMMAND.txt, warm the cache, run the cutover battery harness. Diagnostic template for any future quant comparison on this fork: diff the two state-dirs' setup.json config blobs (the R9V_* keys above are the ones that matter) and grep 'Tiered GGUF experts ready' from each runtime's logs for hot/cold_UVA/dynamic_cache per rank. Evidence: fork docs/qualification/qwen38-q8-0-dual-r9700-2026-09-27.md, vault log.md 928fd81. (context: Frank asked "why is decode so much slower?" after the Q8_0 qualification window on dankserver (2026-09-27). Answered from frozen-config diffs (r9v-state/q8xl vs uncensored setup.json) + live 'Tiered GGUF experts ready' log lines; no bench run needed to establish the mechanism.)
• Dankserver frank-primary experiment-window restore posture (proven 2026-09-27): (1) systemctl mask REFUSES a unit whose /etc/systemd/system file is the deployer's relink symlink into the repo checkout ("File already exists and is a symlink") — use systemctl mask --runtime unit instead: it shadows via /run/systemd/system (verified /run/systemd/system/frank-primary.service → /dev/null), leaves the relink untouched, and SELF-CLEARS at reboot, which is exactly the wanted window semantics (reboot returns the repo-configured llama.cpp). (2) Restore a frozen launch.sh-based vLLM deployment by dumping its state-dir setup.json config to an env file with export K=V lines, overriding the deltas (R9V_HOST_PORT, R9V_CONTAINER_NAME, R9V_HOST_BIND=0.0.0.0 — the base profile default is loopback-only, which breaks models.yml's LAN target), then R9V_PROFILE=base profile.env R9V_CONFIG_FILE=env file bash scripts/launch.sh — launch.sh's doctor (PASS=24 FAIL=0) then binds exactly like the incumbent. (3) vLLM containers hang on SIGTERM (60 s timeout → SIGKILL needed, same law as llama.cpp's SIGTERM cleanup hang). (4) launch.sh refuses to run when a stale exited container holds the name — docker rm it first. Evidence: health 200 in ~60 s (warm page cache), LAN-path completion, qualification record radiance-vllm-qwen4exp docs/qualification/qwen38-q8-0-dual-r9700-2026-09-27.md (commit 50a79ec), vault log.md 928fd81. (context: Q8_0 bring-up qualification window on dankserver (2026-09-27): q8 served + battery on :7773, then uncensored UD-IQ4_XS restored to the frank-primary :7770 slot; frank-primary.service masked for the window.)
• radiance-vllm-qwen4exp Q8_0 bring-up on dankserver (2026-09-27, fork commits 363d606+2fe6dbb, container r9v-qwen38-q8, port 7773): (1) The plugin's fused-HC uniformity check assumes the PUBLISHED IQ4 layout — injection shard (blk.N.hc_attn_inject → attn_hyper_connection.block_inject_weight) is F32 while down shard is Q8_0. Unsloth's Q8_0 conversion quantizes BOTH shards → ValueError "Detected some but not all shards of ...input_mix_weight_down_block_inject are quantized" at WorkerProc init (~112 s). Fix: dev-overlay qwen4_exp.py (env R9V_DEV_QWEN4_EXP_ADAPTER_PY, mount block in launch.sh) extends dequantize_qwen4_exp_packed_hc_down to dequantize a quantized inject shard in-stream + marks the module unquantized; numerics identical to file conversion, F32 path unchanged. (2) runtime.json env.always force-injects R9V_FULL_MUTABLE_CACHE=1, whose baseline check demands the QUALIFIED 160-slot uncensored geometry; q8 profile runs 80 slots → launch.sh gained a passthrough (profile-set R9V_FULL_MUTABLE_CACHE appended AFTER runtime-overlay envs, docker last-wins); q8 profile sets 0 → plain tiered path. (3) GOTCHAS: setup_profile.py start uses the FROZEN setup.json config (+os.environ), NOT profile.env — profile.env edits are inert at start time; pass R9V_PROFILE=q8 profile.env explicitly (launch.sh line 6 sources it). launch.sh sources the DEFAULT (dual-r9700) profile when R9V_PROFILE is unset. A stale exited container makes launch.sh exit 1 "Container already exists" — docker rm -f first. Without the podman-shim PATH, real docker answers "No such image". Tolerance note: Q8_0 roundtrip error ~0.03/step (gguf.dequantize of quantize'd (N,K) returns (N,K); quantize returns (N,K+20)). Profile: dual-r9700-mtp4-q8, PLE pinned 54.4 GB (preflight 108.8 required vs 140.9 available GiB), model load 21.84 GiB/158 s per worker, compile then serve ~16 min total cold. Verified: /health 200, /v1/models qwen3.8-flash-next, completions return content + reasoning_content (17×23=391). (context: Qwen3.8-Flash-Next Q8_0 GGUF launch failure root-cause session on dank@192.168.0.235, fork repo /home/dank/GitPackages/radiance-vllm-qwen4exp, state /home/dank/r9v-state/q8xl/)
• Verified model-path facts for the dankserver 2xR9700 fleet (2026-09-27, primary-source checked — supersedes any scout claims): (1) DeepSeek V4.1-Flash (released 2026-09-10): 552B backbone, 8B active prefill / 16B active decode, CED (Causal Encoder-Decoder) arch, 1M ctx, MIT, multimodal. NOT the April preview (DeepSeek-V4-Flash 284B/13B, ggml-org/llama.cpp#22319 — early vLLM/SGLang successes were Hopper/Blackwell only). BEST path = Lucebox (github.com/Luce-Org/lucebox): gfx1201 is a first-class tested platform (ROCm 7.2), payload Lucebox/DeepSeek-V4.1-Flash-ROCMFP23-GGUF live on HF (24.9k downloads), heterogeneous R9700+Strix Halo measured 86 tok/s decode / 788 tok/s prefill @2K, and the fleet already ran this stack (frank-primary-lucebox-ds4 runbook) until the 2026-09-26 Qwen cutover — retired for the swap, not for failure. llama.cpp mainline CED support: unverified as of late Sept 2026; vLLM/R9V fork: qwen4exp-only, not a path. (2) GLM-5.3-Flash (zai-org): 320B/18B active, KDA+DSA hybrid attention + mHC, 1M ctx (default — hard-hung a 128 GB box once, always bind -c), native FP8 328 GB, MIT. llama.cpp arch glm5next lives in unslothai/llama.cpp branch glm5next/upstream = ggml-org PR #27754, NOT merged to mainline as of 2026-08-30 (check PR state before any build). Measured: 9.31 tok/s decode on Strix Halo UD-IQ1_S 93.1 GB, RADV Vulkan, no MTP (MTP landed d07e71ede 2026-08-30, unbenched); -fa off is MANDATORY (garbage output otherwise). Quants: unsloth ladder IQ1_S 93.1 GB (70.9% top-1) to UD-Q4_K_XL 199.7 GB (92.2%); GSQ-RCO 3.5-bit 137.07 GB (MMLU-Pro -1.40 pp vs Q8_0 ref 61.95%). On discrete R9700s GLM's ~7.9 GiB/token expert volume rides the exps=CPU law to ~4-5 tok/s [ESTIMATE] — #2 for dankserver, but a strong frank-large (Strix Halo) candidate. (3) Process law: LLM research-scout drafts carried invented citations twice in a row (fake repos, wrong PRs, impossible versions like "vLLM v0.21" in a 0.26 era); before any report ships, verify every load-bearing URL di (context: Session 2026-09-27: research scout (R9700ModelResearch) returned two consecutive drafts with fabricated/incorrect sources ("MiaAI-Lab", "freenode", wrong PR, vLLM v0.21 claim); direct primary-source verification (GitHub issue 22319, HF model cards, julianmb/halo-glm53flash receipts, pfeifferj GSQ-RCO card) superseded it. HTML report delivered at /tmp/r9700-ds41-glm53-report.html (volatile path — f)
• R9V qwen4exp Q8_0+MTP4 profile bring-up (2026-09-27, dankserver): all artifacts staged and validated, bring-up blocked ONLY on GPU headroom (production uncensored holds 29.9/30.8 GiB per R9700; rank1 has 1.59 GiB free vs 3 GiB requested — a second instance cannot coexist; qualification needs a stop window for frank-primary). Staged state: model dir /home/dank/models/Qwen3.8-Flash-Next-Q8_0-R9V (6 sha256-verified shards, 188.2 GB); PLE derived /home/dank/models/Qwen3.8-Flash-Next-Q8_0-R9V/r9v-data/per_layer_token_embd.iq4_nl.bin = 54,400,261,120 B sha256 91743e33b6de2272b50a6269a6fe692f56244946fdecf19ca1eba0ba640b303f; placement manifest validated (hot 28/198, rank0 static 4.56 GB / rank1 17.37 GB vs proven budgets 4.68/17.41 GB, MAX_EFFECTIVE=108,198); profile.env + bootstrap.json wrapper written; setup command ready: ./r9v setup qwen38-q8-mtp4 --state-dir /home/dank/r9v-state/q8xl --model-dir /home/dank/models/Qwen3.8-Flash-Next-Q8_0-R9V --image sha256:2dac17a215fb5b0e3461e4c3e36a2981eec8ac3d6021e73183d247e819740c03 --local-image --reuse-from /home/dank/models/Qwen3.8-Flash-Next-Uncensored-R9V-IQ4_XS --accept-model-license. Bring-up bugs fixed along the way (durable): (1) GGUF expert tensor names split into 4 parts ("blk.0.ffn_up_exps.weight" - parts[0]="blk", layer=parts[1]) — the 3-part assumption crashed with int(''); (2) expert_budget.expert_memory(data, slots, cache_ranks, asynchronous=False, *, catalog=None, runtime=None) — runtime/catalog are KEYWORD-ONLY; (3) bootstrap.json wrapper canonical schema = exactly {schema, id, model_package, hardware, artifact_path, artifact_sha256, scope} — hardware "dual-r9700-32gb-asymmetric", scope "Unranked routing bootstrap only; does not certify fit or headroom", and wrapper id MUST equal the id declared in profile.json's placement descriptor or setup rejects with "does not match profile placement"; (4) nohup X & inside an ssh command races ssh teardown and can kill the script before it writes a byte — run remote long scri (context: Frank ordered "modify the q4k xl profile for q8 with mtp" + "ensure ple always stays in ram, not disk" for the R9V fork on dankserver; pipeline authored and run to completion while production serves uncensored on :7770; scratch bring-up awaits a GPU window.)
• R9700 (gfx1201) model research — VERIFIED facts (2026-09-27, all URL-checked directly, NOT from the scout whose citations were partly fabricated): (1) DeepSeek V4.1-Flash released 2026-09-10: 552B backbone params, 8B active prefill / 16B active decode, Causal Encoder-Decoder (CED) arch, 1M ctx, multimodal, MIT (HF deepseek-ai/DeepSeek-V4.1-Flash model card). The April V4-Flash preview was 284B/13B (issue ggml-org/llama.cpp#22319, opened 2026-04-24; preview weights are FP4+FP8 mixed precision, community GGUF conversion initially produced garbage, dequant+requant IQ4 ~153 GB). (2) Lucebox = first-class R9700 path: Luce-Org/lucebox (2,883 stars) lists RDNA4 gfx1201 + ROCm 7.2 as a tested platform; heterogeneous "R9700 + Strix Halo" DeepSeek V4 measured 86 tok/s decode / 788 tok/s prefill@2K; Qwen3.8-27B UD-IQ4_XS + DFlash2 on one R9700 = 208.1 tok/s; HF org carries DeepSeek-V4.1-Flash-ROCMFP23-GGUF (the exact family frank-primary served 2026-09-26 per serverAppConfigs-docs/LLM/frank-primary-lucebox-ds4.md) and DeepSeek-V4-Flash-0731-ROCmFP3. (3) GLM-5.3-Flash (zai-org): 320B MoE / 18B active, hybrid KDA+DSA attention + mHC, 1M ctx default, native FP8 checkpoint 328.3 GB. llama.cpp arch = glm5next, support lives in unslothai/llama.cpp branch glm5next/upstream = ggml-org PR #27754, NOT merged into mainline as of 2026-08-30; quant-side PR #27773 cited by the GSQ-RCO card. MTP/NextN landed upstream d07e71ede 2026-08-30 (glm5next.cpp:846 implements DECODER_MTP; earlier stub asserted at glm5next.cpp:690). -fa off is MANDATORY (flash-attn breaks MLA correctness → garbage); default 1,048,576 ctx must be explicitly bounded (hard-hung a 128 GB Strix Halo once). Only measured receipt: Strix Halo gfx1151 RADV Vulkan, UD-IQ1_S 93.1 GB → 9.31 tok/s decode / 19.7 prefill, 16 threads, no MTP (julianmb/halo-glm53flash, 2026-08-28). Quant ladder: unsloth UD-IQ1_S 93.1 GB (70.9% top-1) → UD-Q4_K_XL 199.7 GB (92.2%); GSQ-RCO (pfeifferj, IST-DASLab methods; taurusduan = mirror): 3.5-bit 13 (context: Research turn 2026-09-27: scout output was partly fabricated (invented sources, wrong vLLM version); direct URL verification produced the reliable evidence set below. The HTML report on R9700 paths for DeepSeek 4.1 + GLM 5.3 Flash is still pending (bg_31 pipeline check in flight).)
• frank-primary on dankserver (192.168.0.235:7770) is now the R9V radiance-vLLM fork (supersedes the 2026-09-26 llama.cpp Q8_0 entry): drwolfen/radiance-vllm-qwen4exp, docker-pinned image bundle r9v-qwen38-flash-next-wmma@sha256:2dac17a2 (loaded from a containerd/OCI docker-save — podman keys images by config digest but keeps the manifest digest in RepoDigests), serving Dyluhn/Qwen3.8-Flash-Next-Uncensored-R9V-IQ4_XS (92.39 GiB, 3 shards) + blockfp8 MTP4 depth 4 + F16 mmproj, TP=2 tiered experts (UVA pinned host copy 43 GiB rank-0 + 16 GiB PLE pinned reserve; PLE residency ssd-mmap; budgets 146.25/78.75 GiB by device), CED on, MAX_MODEL_LEN=196608, tool parser qwen3_coder, reasoning channel reasoning. Production shape: repo-tracked ROOT unit scripts/frank-primary.service (User=dank, LimitMEMLOCK=infinity — but measured fact: the full tiered load reached healthy under a PLAIN dank session, so the pin path does not hard-require it on this host) + serve-frank-primary.sh which layers the on-host 104-key setup state (/home/dank/r9v-state/uncensored/setup.json — the tuned shape lives ON-HOST by design, repo env carries only bind/port/alias/container overrides) under scripts/frank-primary.env, execs the fork's OWN scripts/launch.sh through the docker→podman shim, then docker waits — launch.sh --detach alone would make a crashed engine a green unit. Docker→podman shim laws (in .podman-shim/docker, PATH-prepend, logs every call): (1) containerd-store ID law (inspect sha256:X answers X from RepoDigests; bare sha256:X run refs rewritten to repo@sha256:X); (2) LogConfig law (podman inspect answers LogConfig.Config:null where docker returns the log-opts map — the R9V doctor CRASHES on None.get; shim records run --log-opt pairs and normalizes inspect output); (3) docker info law (SecurityOptions/ServerVersion 27.5.1/DockerRootDir). R9V tooling gotchas: ./r9v start reads state from --state-dir (or default ~/.local/state/r9v/profiles/id) — passing --state-dir to setup but not to star (context: frank-primary R9V radiance cutover on dankserver 2026-09-27, commits 095128b/7562e41/ca6ba6d; scratch-start debugging (state-dir mismatch, LogConfig crash, flag-consumer bug) all fixed in-shim or by rerun; production deploy green with MainPID check; e2e 32/33 with sleeping FrankBook the only failure.)
• frank-primary (dankserver :7770, Qwen3.8-Flash-Next Q8_0 MoE): measured 2026-09-26 with AMD IBS on the live server that per-BLOCK expert read volume is FLAT (0.93–1.08× mean across all 40 CPU-resident blocks) — MoE top-8 routing fires every block every token, so "most active layers" do not exist at -ot granularity; ANY 8 GPU-resident blocks are equivalent and the only lever is COUNT (already at the 5/3 VRAM ceiling). Real skew is per-EXPERT (top 10% of 48×512 (block,expert) cells carry 40.5% of samples) — below tensor-override reach. Instrument: scripts/frank-primary-expert-activity.py (commit f41e038) — perf IBS op sampling + /proc/pid/maps attribution + GGUF header parsing. Critical implementation law: derive GGUF tensor extents from CONSECUTIVE header offsets, never from a quant type-size table — a wrong per-element size silently mis-buckets each tensor's tail into junk (first run lost 59% of expert samples to a 'gap' bucket with zero warning). Runbook: serverAppConfigs-docs/LLM/frank-primary-llamacpp-qwen38-flash-next-q8.md "Which blocks, measured". (context: Frank asked whether a tensor-override regex could target the most active layers of frank-primary's experts; measured live instead of guessing. Runbook updated + script committed f41e038; no config change (block choice proven immaterial).)
• llama.cpp b11030 --override-tensor laws (proven live on frank-primary, dankserver, 2026-09-26): (1) The loader applies the FIRST matching pattern per tensor — a broad pattern like exps=CPU placed before block-specific GPU patterns SILENTLY swallows them (zero warnings in the log; buffers stay byte-identical to no-override). Specific patterns must precede the broad sweep. (2) Repeated --override-tensor flags log DEPRECATED ("only last value will be used" — misleading; actually all apply with first-match-wins); the canonical form is ONE flag with the full comma-joined list. (3) GPU-target overrides ARE legal under a layer split when the tensor sits on the card that holds that block's layers (both ROCm devices are in the main graph's backend list) — the x4-pair "=CPU only" wall applies to draft-graph borrows and non-primary devices, not main-graph co-located blocks. (4) Granularity: the whole per-block expert tensor (512 experts share one tensor, 2.42-2.49 GiB at Q8_0) is the atomic placement unit; there is no per-expert routing knob. (5) Env-file pitfall: the value with parentheses MUST be single-quoted in the env file — source parses values, unquoted ( is a bash syntax error. (6) Probe procedure: FRANK_PRIMARY_ENV_FILE=/tmp/probe.env + scratch PORT, warm loads ~10-30 s; verify placement via load_tensors: ROCmN model buffer size lines (exact arithmetic: base + N×2550 MiB) and headroom via rocm-smi bytes; total card = 34,208,743,424 B (31.86 GiB, not 32). ssh+zsh layers mangle sed backslash escapes and treat bare === as =cmd expansion — use heredocs. (context: frank-primary 4-slot/V-q8/block-fill reshape on dankserver 2026-09-26, commits de85654/d317d6b/d67768e)
• llama.cpp --override-tensor (b11030 unsloth build, verified 2026-09-26 on frank-primary): the loader applies the FIRST matching pattern per tensor — a broad exps=CPU listed before block-specific GPU patterns silently swallows them (all experts stayed CPU, zero warnings anywhere in the log; only the per-card "model buffer size" load-log lines revealed it). Order: specific patterns first, broad sweeps last. Repeated --override-tensor flags also log DEPRECATED (its "only last value will be used" text is misleading — matching is first-match-wins across the joined list); pass ONE comma-joined flag. Placement verification is buffer-size arithmetic, never absence-of-errors. Related measured fact: --cache-type-v q8_0 does NOT apply to the shared-MTP drafter's KV (stays f16 — draft pool = f16 law at the target pool size). Fleet workflow corollary: on the zsh-login hosts, write regex-bearing remote env files via heredoc cat file (sed piped through ssh+zsh layers eats backslash escapes), never use bare === as an echo marker (zsh =cmd expansion aborts the command), and quote globs inside remote grep patterns. (context: frank-primary 4-slot/V-q8/hot-block reshape on dankserver 2026-09-26; commits de85654 (shape) + e330d56 (runbook law); the broad-first probe silently no-op'd the GPU block placement)
• Dankserver fleet delta (2026-09-26 cutover, supersedes the frank-medium entry): frank-medium (vLLM/radiance/Swift-Qwen3.8-27B-PARO-MXFP6) is RETIRED — the active Dankserver endpoint is now frank-primary: unsloth llama.cpp b11030 prebuilt (root systemd unit, enabled+active), unsloth/Qwen3.8-Flash-Next-GGUF Q8_0 (175.3 GiB, 6 split parts, mmap — never --no-mmap) with shared-Q8_0 MTP drafter (depth 2) + ngram-mod, BF16 mmproj, 262,144 ctx × 1 slot, port 7770 @ 192.168.0.235, alias frank-primary, -ot exps=CPU,per_layer_token_embd.weight=CPU (experts+PLE computed in host RAM), -ts 1,1 across both R9700s, SPEC_DRAFT_DEVICE=ROCm1 (last-layers card — ROCm0 crash-loops with the ggml-backend.cpp:941 borrowed output.weight abort). Measured: 11.8 t/s decode, 0.86 tool-task draft acceptance, 7 s warm load, 9.4 GiB/card (29%/36% of 32 GiB), 29,696 B/token ctx-scaled KV law. KV is f16 (no --cache-type flags). Rollback: lucebox quadlet + 378 GiB payload retained on host (/.AGENTTRASH/20260926-llamacpp-cutover/). Runbook: serverAppConfigs-docs/LLM/frank-primary-llamacpp-qwen38-flash-next-q8.md. All three endpoints now export /metrics (frank-large was silently 501 since its own deploy; fixed 82ff9dd). Repo HEAD de4d227. (context: frank-primary llama.cpp Qwen3.8-Flash-Next Q8_0 cutover on dankserver 2026-09-26 (commits 8500600, a9b94a7, 5d632bb, 82ff9dd, de4d227))
• llama.cpp b11030 (unsloth prebuilt family): (1) /metrics is DISABLED by default — without --metrics it answers 501, and Prometheus marks the target down while /health looks fine; both dankclaw frank-large and the new frank-primary had this silently (fixed 2026-09-26, commit 82ff9dd). (2) A spec-draft deployment that borrows target tensors (shared MTP head) must place the drafter on the card holding the target's LAST layers (-ts 1,1 → output.weight lands on ROCm1): with tensor overrides set, n_copies==1 and a draft context elsewhere aborts at load with ggml-backend.cpp:941 "pre-allocated tensor (output.weight) in a buffer (ROCm1) that cannot run the operation (NONE)" — crash-looped 4× at ~12 s until SPEC_DRAFT_DEVICE=ROCm1. (3) llama-server's SIGTERM cleanup can HANG after spec-decode service (logs "cleaning up before exit", never exits) — a timeout 300 probe survived its own kill signal and later blocked a deploy's port gate; kill -9 is the reliable stop for stray instances. (4) A deployer whose health check is a bare curl against the port cannot tell WHO answers — a stray process holding the port produces a FALSE GREEN deploy (seen 2026-09-26 when the deploy's wait_for_health was satisfied by a leftover probe while the real unit was stopped); after any aborted deploy, confirm the responder is the unit's own MainPID before trusting the health gate. (context: frank-primary llama.cpp cutover on dankserver 2026-09-26; commits 5d632bb (draft device), 82ff9dd (metrics + -lv 4), de4d227 (KV law))
• When debugging a crash-looping LLM service by running the serve script manually with a scratch env file (e.g. FRANK_PRIMARY_ENV_FILE=/tmp/probe.env), the probe binds the service port and can satisfy a subsequent deploy's health gate: deploy.sh exited green with "frank-primary healthy after ~104s" while systemctl showed inactive — the health curl hit my probe process, not the unit. Rule: before redeploying after a manual probe, kill the probe (pgrep llama-server on the host) and let the deployer's own unit answer; treat a green deploy that ran concurrently with a manual probe as unverified. Related: a wait_port_free failure on a lone LAST-ACK tail (dead client socket, e.g. 192.168.0.60 not ACKing FIN) is not a held listener — it often clears on its own in ~90 s; sudo ss -K sport = :port errors with RTNETLINK Invalid argument when only the tail remains, but by the next run the port is free — just rerun the deploy rather than editing the gate. (context: frank-primary deploy 2026-09-26: LAST-ACK tail aborted deploy run 1; probe-A held :7770 while deploy run 2 went falsely green; unit was actually stopped)
• On a llama.cpp layer-split (-ts) deployment that carries --override-tensor flags AND a borrowed-head speculative drafter (draft-mtp shared head, e.g. Qwen3.8-Flash-Next's shared MTP GGUF), the drafter MUST sit on the card where the main model's output head landed — the last-layers card under a balanced -ts. Reason: -ot sets has_tensor_overrides(), which pins n_copies==1 in the draft's backend scheduler; a borrowed output.weight pre-allocated in card B's buffer aborts the draft graph with ggml-backend.cpp:941 "pre-allocated tensor (output.weight) in a buffer (ROCm1) that cannot run the operation (NONE)" when the draft context is on card A. Signature: SIGABRT ~12 s into load (right after "loading draft model"), crash-looping every restart. Verified live 2026-09-26 on frank-primary (dankserver 2x R9700, -ts 1,1, -ot exps=CPU,per_layer_token_embd.weight=CPU): SPEC_DRAFT_DEVICE=ROCm0 abort-looped 4x, ROCm1 loaded and served. This extends the fleet's x4-pair law (overrides ⇒ n_copies==1) into spec-decode territory, and matches the frank-medium layersplit precedent (SPEC_DRAFT_DEVICE=ROCm1) — check the repo's retired-era env files for precedent before pinning a device. (context: frank-primary cutover 2026-09-26: deploy attempt 1 crash-looped; fixed by 5d632bb "pin the drafter to ROCm1")
• GGUF pre-deploy verification (Dank fleet, frank-primary 2026-09-26): (1) A GGUF's KV metadata + tensor-info table sit at the file START, so a partially-downloaded split part already exposes its tensor names — scripts/dump-gguf.py (repo-tracked, dependency-free) can validate -ot override patterns mid-fetch, before the payload completes. This confirmed exps=CPU matches all of blk.N.ffn_{up,gate,down}_exps.weight on Qwen3.8-Flash-Next. (2) Parser gotchas: GGUF v3 string/array lengths are u64; KV value-type enum is 8=string, 9=array; nested array element types include enum 5 (i32) — handle unknown array types with a size-table skip ({0:1,1:1,2:2,3:2,4:4,5:4,6:4,7:1,8:0,9:0,10:8,11:8,12:8} bytes/elem), don't raise. (3) The unsloth Qwen3.8-Flash-Next embedded tokenizer.chat_template (dumped from part 1's KV) natively folds high→xhigh before the xhigh/medium/low gate (only minimal/max raise) AND natively consumes preserve_thinking — so frank-primary needs NO external --chat-template-file; the models.yml reasoningEffortMap (minimal→low, max→xhigh) exists only for the two OMP-only levels. Pre-reading the embedded template from the GGUF before deploy prevents an entire deploy-cycle loss on a 500-ing template rejection. (context: frank-primary cutover 2026-09-26: verified -ot tensor patterns and chat-template effort gate from the partially-fetched payload before deployment)
• frank-medium (dankserver :7770) now serves hugypufy/Swift-Qwen3.8-27B-PARO-MXFP6 (ParoQuant MXFP6, W4A8, 25.16 GiB) on image localhost/radiance-vllm:0.13.0-e060895 (PR #51) — the repo quadlet (dankserver/frank-medium/quadlet/frank-medium.container) is the source of truth; the AGENTS.md prose (MXFP4 / radiance-vllm 0.9.3) is STALE. Boot-crash lesson (2026-09-26): vLLM's startup check requires free VRAM = gpu_memory_utilization x 31.86 GiB per card, and free-at-check includes the worker's own HIP context plus the amdgpu per-boot baseline (~690 MiB total), which drifts tens of MiB between boots — so GPU_UTIL=0.98 (threshold 31.22 GiB) deterministically crash-looped a boot that measured 31.21 GiB free (ValueError "Free memory on device cuda:N ... less than desired GPU memory utilization"), identical numbers on every restart. Fixed by GPU_UTIL=0.97 (threshold 31.06 GiB, ~160 MiB headroom, cost ~5k tokens on the auto-sized ~486k-token KV pool, commit c5b55e1). If frank-medium crash-loops after a reboot with that ValueError, lower GPU_UTIL further rather than hunting for a GPU tenant — the GPUs are otherwise idle.
• serverAppConfigs e2e gate: the admin crawl test (tests/e2e/specs/11-admin.spec.ts:24) walks every admin open link, including Prowlarr at 192.168.0.112:8989 (the FrankBook-Pro Mac mini). When the mini is asleep (ARP STALE, 100% ping loss; it's a Mac mini with NO remote WoL/power-on path) that test fails with net::ERR_CONNECTION_TIMED_OUT — a pre-existing environmental failure, not a regression. For changes that don't touch the mini, deploy with --skip-e2e (justified) and note the dependency. The user crawl (12-crawl.spec.ts) is also slow (~1.2m) and can pass on retry. Every non-Mac-mini e2e test passes while the mini is down.
• Fleet model input modalities: models.yml (/home/blank/.omp/agent/models.yml) is the authoritative source, NOT the AGENTS.md prose (partly stale — it claims "no audio anywhere in the fleet"). Ground truth: frank-large = text only (no vision projector); frank-medium = text+image (Gemma4 vision path, verified on held-out images); frank-small = text+image+audio. Audio nuance: frank-small's models.yml entry declares only input: [text, image] because OMP 18.0.6's schema rejects 'audio' (a failed schema check drops the WHOLE models file), but the endpoint genuinely accepts input_audio parts via the Gemma4 projector's audio encoder (verified 2026-09-17 deploy — a WAV transcribes verbatim). No fleet model does video. (context: serverAppConfig 2026-09-26: adding per-model input modalities to the homepage LLM cards)
• serverAppConfig homepage (shared/homepage/): the three LLM status cards use a structured details object in services.json (fields role, spec, inputs[], use) instead of the plain description string the other ~32 cards use. app.js descHTML(svc) renders details as tiered divs — .desc-role (bold, --head pale green #aaffcc), .desc-spec (--dim), .desc-inputs (--input #00ff9d spring green, 'Inputs:' prefix, modalities joined with ' · '), .desc-use (--dim, 'Use:' prefix) — and falls back to esc(svc.description) when details is absent. Tiers are deliberately staggered light-dark-light-dark (pale role / dim spec / bright inputs / dim use). The /docs model guide (docs.html #models) mirrors it with Model/Capacity/Inputs/Best-for/Not-for bullets and was the source of a stale-info bug (it had drifted to retired model names/sizes — verify against models.yml/AGENTS.md before trusting it). Deploy: ./scripts/deploy.sh dankclaw --service homepage --skip-e2e (ships to /srv/homepage; e2e skipped because admin crawl test 11-admin.spec.ts:24 times out on the asleep Mac mini 192.168.0.112, which has no remote wake). Verify with bats tests/homepage_*.bats tests/docs_completeness.bats + a local browser render (python3 -m http.server + a scratch status.json, since file:// fetch is CORS-blocked; move the scratch status.json to .AGENTTRASH, never rm). (context: serverAppConfig 2026-09-26: reworked the LLM model cards (structured role/spec/inputs/use, neutral roles, per-model input modalities, staggered green tones))
• frank-small (Dankclaw :7771, Gemma4-12B QAT) DOES accept audio input (input_audio WAV transcribes verbatim, verified at the 2026-09-17 deploy) via the Gemma4 projector's audio encoder — even though the harness models.yml only declares input: [text, image] for it. The reason is a harness schema limit, not a model limit: OMP 18.0.6's models.yml schema only accepts input: "text"|"image", and a failed schema check drops the WHOLE models file, so audio is deliberately omitted from the list while the endpoint still accepts audio parts. Consequence: the AGENTS.md prose "There is no audio input anywhere in the fleet: that capability left with the FLM NPU endpoint on 2026-09-11" is STALE — frank-small is the fleet's only audio-capable endpoint. When routing an audio task or fact-checking the docs, trust the models.yml comment + the Gemma4 projector over the AGENTS.md one-liner. (frank-large = text only, no vision projector; frank-medium = text+image via the Gemma4 merge path; none do video.)
• Fleet model input modalities (authoritative source: /home/blank/.omp/agent/models.yml input: field): frank-large = text only (no vision projector); frank-medium = text + image (Gemma4 vision path, verified on held-out images); frank-small = text + image + audio. IMPORTANT correction: frank-small's audio is NOT in models.yml's input list because OMP 18.0.6's schema only accepts text|image (a failed schema check drops the WHOLE models file), but the Gemma4-12B-QAT projector's audio encoder DOES accept input_audio parts — verified at the 2026-09-17 deploy (an input_audio WAV transcribed verbatim). So the AGENTS.md line "There is no audio input anywhere in the fleet" is STALE/wrong for frank-small: audio left with the FLM NPU endpoint for the other models, but the Gemma4 swap brought it back on frank-small specifically. (context: serverAppConfigs 2026-09-26: adding per-model input modalities to the homepage LLM cards; cross-checked models.yml vs the stale AGENTS.md audio claim)
• serverAppConfigs homepage LLM cards: the three LLM status cards (frank-large/medium/small) in shared/homepage/services.json carry a details object {role, spec, inputs, use} rendered by app.js descHTML() as a 4-tier hierarchy — bold pale-green .desc-role / bright-green .desc-spec / bright-green .desc-inputs ("Inputs: a · b") / dim .desc-use ("Use: …") — falling back to the plain description string for all other cards. The desc-* CSS classes live in style.css and each needs a bare-mode (html[data-bare=1]) reset. Deploy with ./scripts/deploy.sh dankclaw --service homepage (the deploy_homepage handler copies the 6 assets to /srv/homepage, regenerates deployed.js, restarts the status timer). The /docs model guide is the #models section of shared/homepage/docs.html and must be kept in sync with the cards — it once drifted to retired model info (frank-large listed as Qwen3.8-Flash-Next 87.3 GiB/200k, frank-medium as FP8 ~31 GiB) and had to be corrected to Qwen3.8-27B UD-Q8_K_XL 31.5 GiB/262k and MXFP4/W4A8 19.4 GiB. (context: serverAppConfigs 2026-09-26: reworked the homepage LLM model cards into structured role/spec/inputs/use lines)
• serverAppConfigs homepage (shared/homepage/): the LLM status cards use a structured details object in services.json — {role, spec, use} — rendered by app.js descHTML() as a bold pale-green role line, a bright-green spec line, and a dim "Use:" line (.desc-role/.desc-spec/.desc-use in style.css, plus a bare-mode reset). descHTML() falls back to the plain description string for any card lacking details (the other ~32 services). So: structured card = add a details object; plain card = add description. The e2e (10-homepage/11-admin) asserts only on .panel .name and a.open, NOT .desc content, and homepage_config.bats' schema test checks only required fields (name/category/section/probe) — so details is a safe optional extra field. Gotcha: the /docs model guide (docs.html) is a SEPARATE hand-maintained copy of the model facts and had drifted to retired hardware (it listed frank-large as Qwen3.8-Flash-Next 87.3 GiB/200k and frank-medium as FP8 ~31 GiB, both stale); re-verify it against AGENTS.md ground truth whenever the models change. (context: serverAppConfigs 2026-09-25: reworked the three LLM homepage cards from a single dense description string to a structured role/spec/use shape (details object + app.js descHTML + new CSS), neutralized the role labels, and fixed the drifted /docs model guide.)
• Jellyfin 12.1 removed the legacy POST /Users/Auth/Password route (and its LegacyEmbyRouteRewriteMiddleware). Probing that dead route returns a SILENT 401 with ZERO plugin/UserManager log lines even at Debug level — it reads like an LDAP/auth failure but is just a dead route. The modern password-auth endpoint is POST /Users/AuthenticateByName, which REQUIRES the header Authorization: MediaBrowser Client="...", DeviceId="...", Device="...", Version="..." (no header → 401). The LDAP-Auth plugin runs on this modern path. So a "Jellyfin LDAP 401 after upgrade" that shows no plugin log is almost always a test hitting the removed legacy route, not a broken integration — verify with the modern endpoint + MediaBrowser header before touching plugin config. (Dankserver Jellyfin 12.1.0, 2026-09-25; alex authenticated HTTP 200 via AuthenticateByName with full plugin flow: service bind → search → ldapUid → user bind → token.) (context: Dankserver Jellyfin 12.1.0 LDAP-Auth 401 diagnosis — the 401 was a test artifact from probing the removed legacy /Users/Auth/Password route; the web UI's modern /Users/AuthenticateByName endpoint works fine.)
• Deploying a quadlet image change on the Dank fleet (dankclaw 192.168.0.143 / dankserver 192.168.0.235): pulling the repo does NOT update the running container, because the installed unit in ~/.config/containers/systemd/name.container is GENERATED state, not the repo file. A plain systemctl --user restart name restarts from the STALE installed unit (old image) — I hit this live (image IDs didn't change after a bare restart). To deploy a pinned-image bump: commit+push → git pull --ff-only on host → cp host/svc/quadlet/name.container ~/.config/containers/systemd/ → systemctl --user daemon-reload → systemctl --user restart name → verify podman inspect name --format {{.ImageID}} matches the freshly-pulled image. For local-build images (caddy/alloy/loki/comfyui, tagged :latest) no unit reinstall is needed (same tag), BUT deploy-remote.sh's build_compose_image gates on a cfhash label (sha256 of the Containerfile) and SKIPS the rebuild when the Containerfile is unchanged — so a base-image refresh needs a manual podman build --no-cache -t image -f containerfile . first. Gotcha: the hermes gateway container is named systemd-hermes, not hermes (no ContainerName= in its quadlet), so podman inspect hermes fails — use podman ps --filter name=hermes. anubis is pinned at v1.27.0 (latest stable; only pre-releases beyond). (context: serverAppConfigs 2026-09-25: fleet-wide container update (pinned bumps + local-build rebuilds) across dankclaw + dankserver)
• Updating a container image on the Dank fleet (dankclaw/dankserver, rootless quadlet) — a naive git pull + systemctl --user restart silently keeps the OLD image, for two distinct reasons: (1) QUADLET INSTALLED-UNIT STALENESS: the repo quadlet file (e.g. dankserver/plex/quadlet/plex.container) is the source of truth, but the INSTALLED unit at ~/.config/containers/systemd/name.container is generated state that git pull does NOT touch. Bumping Image= in the repo, pulling, and restarting restarts the container from the STALE installed unit (old image). Fix: cp repo/host/svc/quadlet/svc.container ~/.config/containers/systemd/ + systemctl --user daemon-reload + systemctl --user restart svc. Verify by comparing podman inspect c --format {{.ImageID}} against the freshly-pulled image ID — if they differ, the unit was stale. (2) LOCAL-BUILD CFHASH GATE: the deploy functions (deploy_caddy, build_compose_image in scripts/deploy-remote.sh) rebuild only when the Containerfile's sha256 (the cfhash image label) changed. A base-image bump (caddy:2, grafana/loki:latest, grafana/alloy:latest, the rocm/vllm comfyui base) leaves the Containerfile byte-identical, so the gate SKIPS the rebuild and the old base stays. To force a refresh: podman build --no-cache -t image -f containerfile . from the repo root (caddy=franksdank/caddy-porkbun:latest, alloy/loki=franksdank/{alloy,loki}:latest — loki needs --format docker for its HEALTHCHECK, comfyui=comfyui-rocm:gfx1151). hermes (image localhost/hermes-agent:latest, Pull=never): podman pull docker.io/nousresearch/hermes-agent:latest + podman tag ... localhost/hermes-agent:latest + restart the trio (hermes, hermes-dashboard, hermes-webui). Gotcha: the hermes GATEWAY container is named systemd-hermes (not hermes), so podman inspect hermes fails. anubis is pinned at v1.27.0 in deploy-remote.sh (latest stable; GHCR tag-list API is capped at 1000 unsorted tags — use the GitHub releases API to find the latest). Excluded from "update to latest": frank- (context: serverAppConfigs 2026-09-25 fleet-wide container update: pinned bumps (authentik 2026.8.3, tautulli ls245, calibre-web ls402, plex 1.43.4) + local rebuilds (caddy, alloy, loki, comfyui-rocm, hermes x3). Hit the installed-unit staleness trap on dankserver (restarted with old image IDs until the units were re-copied + daemon-reloaded).)
• Dankclaw guard-chained vhost 400 diagnosis (Anubis → Authentik embedded outpost, e.g. marreta.franksdank.cloud): a 400 where the APP's own logs show NO user request (only periodic health probes) is the embedded outpost's handle_auth_callback returning 400 with the warn "auth callback without a valid session cookie" (src/outpost/proxy/application/handlers/mod.rs). The outpost sets a session cookie on the external host during auth_start; the callback must carry it back. If the browser (observed: Firefox) doesn't send it — private/incognito window, cookie blocking (ETP Strict / extension), or stale site data — the callback 400s and the app never sees the request. The cookie name is 'authentik_proxy_' + first 8 hex of SHA256(provider.client_id) (compute: hashlib.sha256(client_id).hexdigest()[:8]); it is SameSite=Lax, Secure, HttpOnly, host-only when provider.cookie_domain is empty — and the callback is same-site (auth.→vhost., same registrable domain) so Lax allows it, meaning the server is fine. Confirm server health by running the single-vhost e2e spec (clean Chromium drives the full chain; a pass means the cause is browser-side). Two server-side gotchas that ALSO produce the same 400: provider.access_token_validity unset/None → session_max_age()=0 → zero-max-age cookie the browser discards; and cookie_domain set to a domain that doesn't match the callback host. ProxyProvider is at authentik.providers.proxy.models; on this fleet the marreta provider is pk 13 named 'marreta-proxy' (NOT 'marreta'). The outpost runs inside the authentik-server container (logs via journalctl --user -u authentik-server), reached as remote = the Anubis container IP. (context: serverAppConfigs 2026-09-25: user reported "400 from marreta"; traced to the embedded outpost's handle_auth_callback missing-session-cookie 400, verified server healthy via e2e spec 16-marreta (3/3 pass), root cause = Firefox not sending the authentik_proxy_6536c831 session cookie on the callback.)
• In authentik (2026.8.0, Dankclaw), self-serve password change is a PROMPT FIELD, not a stage. The UserWriteStage writes whatever the preceding PromptStage collected: for key password it calls user.set_password(value) (stages/user_write/stage.py:116). So the fix is a password field on the default-user-settings prompt (field_key='password', type='password', required=False) — NOT a PasswordStage. A PasswordStage is an AUTHENTICATION stage: its validate_password runs authenticate() against the backends to check the CURRENT password; it never sets a new one. (A PasswordStage was added then removed for exactly this reason on 2026-09-25.) Two gotchas: (1) a blank password field must be guarded — set_password('') leaves the account with no password, so bind an ExpressionPolicy to the prompt via PromptStageValidationPolicy that denies when prompt_data['password']=='' (allow when set/absent); (2) a prompt field is a Prompt row linked through PromptStageField(prompt_stage, prompt) — the order comes from Prompt.order, and there is no PromptField model. Verify the write path by driving UserWriteStageView.update_user on a throwaway user (it only modifies in-memory; call user.save() after, as dispatch() does). The self-serve flow /if/flow/default-user-settings-flow/ is open to ANY authenticated user (its authorization policy only gates email/name/username changes, not password); the admin Directory→Users screen is separate and admin-only.
• authentik 2026.x default-user-settings-flow (the self-serve account page, https://auth.domain/if/flow/default-user-settings-flow/) ships with ONLY a PromptStage + a UserWriteStage (name/email/locale) — NO PasswordStage, so users cannot change their password. To add it: create a PasswordStage (backend authentik.core.auth.InbuiltBackend, the "standard password" backend) and bind it to the flow. Two ORM gotchas (verified on dankclaw authentik-server 2026.8.0): (1) Flow.stages.add(stage) FAILS with "Can't bulk create a multi-table inherited model" because the through model FlowStageBinding is multi-table-inherited — instead create the row directly: FlowStageBinding.objects.create(target=flow, stage=ps, order=N) where N is max(existing orders)+1; (2) PasswordStage.objects.create(name=...) alone hits a NOT NULL violation on the backends ArrayField — you must pass backends=[...]. Valid backend values come from authentik.stages.password.init: BACKEND_INBUILT="authentik.core.auth.InbuiltBackend", BACKEND_LDAP, BACKEND_APP_PASSWORD (TokenBackend), BACKEND_KERBEROS. Flow execution order is the FlowStageBinding.order field, NOT the M2M insertion order (flow.stages.all() returns a different order — don't trust it). To verify a stage is in the executed plan WITHOUT a browser: FlowPlanner(flow).plan(request) (request.user set) → plan.bindings lists the stages in order; FlowPlanner.init takes only the flow, user/request go to .plan(request). Note: a headless browser will NOT render authentik flow stages (the Lit app renders via XHR after the shell, leaving only "Powered by authentik") — verify via FlowPlanner, not the DOM.
• Running a single Playwright spec via the fleet e2e runner requires the file path to come BEFORE --project: tests/e2e/run.sh specs/18-openwebui-sso.spec.ts --project standard. The reverse order (--project standard specs/...) fails with Project(s) "specs/..." not found because playwright parses the positional file path as a project name. Spec 18 is in the "standard" project (testMatch /(10|12|13|16|17|18)-.*.spec.ts/), which depends on the "setup" project (00-auth.setup.ts) that logs in and writes .auth/qa-e2e.json + .auth/qa-e2e-admin.json. The runner needs tests/e2e/.env.local (git-ignored) present and auto-installs chromium. This lets you verify one SSO/guard spec against the live fleet without running the whole (slow, Mac-mini-dependent) suite. (context: serverAppConfigs 2026-09-24: ran 18-openwebui-sso.spec.ts in isolation to verify the SSO-only flip against the live fleet)
• Flipping OpenWebUI (dankclaw, ai.franksdank.cloud) to SSO-only requires changing BOTH the quadlet env AND the per-key config DB, because the config DB (webui.db config table) wins over env vars. Concretely: (1) add Environment=ENABLE_LOGIN_FORM=false and Environment=ENABLE_PASSWORD_AUTH=false to dankclaw/open-webui/quadlet/open-webui.container; (2) set ui.enable_login_form to false in the config table on the live data dir (/home/dank/Containers/open-webui/data/webui.db). If you only set the env, the DB override ui.enable_login_form=true silently keeps the password form showing. ui.enable_signup was already false. Verified 2026-09-24: the login view at /auth renders zero inputs and only the "Continue with authentik" button, and the OIDC round-trip lands signed in. To restore the password form: set ui.enable_login_form back to true (Admin Panel or DB) and drop the two env vars. Note the dankclaw host has NO sqlite3 CLI — use python3 -c "import sqlite3; ...". (context: serverAppConfigs 2026-09-24: OpenWebUI SSO-only flip (commit 33cdeca) + config DB override flip)
• OpenWebUI (dankclaw, ai.franksdank.cloud, quadlet on bridge 10.89.3.0/24, published 3005) can do authentik OIDC SSO per the official integration docs, with these fleet-specific adaptations: (1) OpenWebUI's container cannot reach authentik-server:9000 by name (isolated bridge), but CAN reach https://auth.franksdank.cloud — Caddy publishes 0.0.0.0:443 and netavark DNATs published ports from other containers — so OPENID_PROVIDER_URL uses the public URL; (2) authentik runs 2026.8.0 (≥2026.5), so the provider needs the new typed Strict Authorization redirect URI (https://ai.franksdank.cloud/oauth/oidc/callback), not the old plain list; (3) OAUTH_CLIENT_SECRET must not enter the repo quadlet — use EnvironmentFile= pointing at a git-ignored host env file (Caddy-env pattern); (4) OpenWebUI persists config in /app/backend/data fill-missing-only, so on the existing data dir the OAuth settings must be set via Admin Panel → Settings, env vars only seed a fresh data dir; (5) rollout: enable SSO first, verify, then flip ENABLE_LOGIN_FORM/ENABLE_PASSWORD_AUTH=false — flipping first locks you out of the admin panel if the wiring is wrong. (context: serverAppConfigs 2026-09-24: answering whether the goauthentik.io OpenWebUI integration docs apply to the fleet setup)
• When a subagent is told to write its report to local://name.md, the file lands in the GLOBAL dir /home/blank/.omp/local/name.md — NOT in the session-local dir (/home/blank/.omp/agent/sessions/session/local/). In the 2026-09-22 serverAppConfigs session, three subagent reports written to local:// all resolved to the global dir; a first read attempt at the session-local path failed and needed a find /home/blank/.omp -name file to locate them. Durable rule: read subagent local:// outputs from /home/blank/.omp/local/ directly; if not found there, find under /home/blank/.omp. (context: serverAppConfigs session 2026-09-22: subagent outputs (appdocs-ai, research-job-search, research-popular-ai-apps) all landed in the global dir, not the session-local one)
• ComfyUI v0.37.0 (released 2026-09-21, tag v0.37.0) ships NATIVE Qwen-Image 2.1 support (CORE-423, PR #16400 — comfy/ldm/qwen_image21/model.py, model detection + supported-models registration). The Dankclaw ComfyUI image (comfyui-rocm:gfx1151, built from dankclaw/Containerfile.comfyui) currently bakes in CUSTOM GGUF patches (apply_qwen21_patch.py: VAE 4D→5D expansion, in_channels shape[0] read, QwenImage21 arch registration) for the Qwen-Image 2.1 GGUF setup. On the next image rebuild, check whether the native 0.37.0 path makes those patches redundant BEFORE re-applying them. Also: the repo now lives in the Comfy-Org org (comfyanonymous/ComfyUI redirects). (context: serverAppConfigs vault fact-check 2026-09-22, AppDocsAI upstream research)
• frank-medium image rebuilds on dankserver: build.sh invokes docker build (rootful docker), but the quadlet runs under ROOTLESS podman — a freshly built image is NOT visible to podman. Bridge it: docker save img:tag | podman load (lands as docker.io/name:tag), then podman tag name:tag localhost/name:tag because rootless quadlets cannot resolve registry-prefixed refs. The 2026-09-22 MXFP6 image was built this way as ggz14/vllm-radiance-mxfp4:0.13.0-e060895 → localhost/radiance-vllm:0.13.0-e060895. The /patches clone must be at the same commit as the image (e060895) so the entrypoint re-applies the matching patches.
• Diagnosing frank-medium (radiance) "restart loop" false alarms: the journal's repeating lines every ~10 s — [radiance.gemm]/[radiance.paroquant]/[radiance.mxfp4]/[radiance.paroquant_mxfp6] registered plus a NOOP file already applied line — are NOT a crash loop. They are the entrypoint's ~20 sequential python3 patch_*.py invocations, each re-importing sitecustomize (which prints the radiance banners) and printing its own NOOP line in FORWARD order, then exec vllm. Proof it's not looping: the container reaches Application startup complete and podman inspect shows Started=t Restarts=0 with a stable Started timestamp. A real crash loop is the RuntimeError: Engine core initialization failed / ValueError: Free memory … less than desired GPU memory utilization traceback (a real prior failure: the 0.99 GPU_UTIL crash). Distinguishing: grep for Traceback|ValueError|Engine core initialization failed (real failure) vs the registration/NOOP cadence (normal slow patch phase, ~3 min).
• HF download verification gotcha: the resolve endpoint's X-Linked-ETag differs between authenticated (Bearer token) and unauthenticated requests for the SAME LFS file. The actual downloaded file's sha256 matches the UNAUTHENTICATED etag. So scripts/hf-manifest.py (which does Bearer-token HEAD) and hf-fetch.sh's sha256 check produce a systematic false-positive "mismatch" for this repo (e.g. hugypufy/Swift-Qwen3.8-27B-PARO-MXFP6). This is HF API behavior, not a script bug or a stale manifest. To verify a download, compare local sha256 against an UNAUTHENTICATED curl -sI https://huggingface.co/repo/resolve/main/file X-Linked-ETag (strip CRLF with tr -d '\r'). The 2026-09-22 MXFP6 download was verified correct this way (PASS=19 FAIL=0).
• frank-medium (dankserver, dual R9700 TP=2): vLLM's startup memory check (gpu_worker.py request_memory) runs BEFORE weight load and requires gpu_memory_utilization × total free-at-device-init. On the 32 GB R9700 the reported total is 31.86 GiB but only 31.23 GiB is free at device-init — the 0.63 GiB gap is the ROCm/HIP context + NCCL + radiance's custom all-reduce buffers (84 MB fine-grained AR + 44 MB AR_QUANT). So the max that starts is 0.98 (0.98×31.86=31.22 31.23); 0.99 (31.54) fails with "ValueError: Free memory on device cuda:0 (31.23/31.86 GiB) on startup is less than desired GPU memory utilization" and crash-loops. 0.98 is the ceiling AND the prior production value. The repo fit-gate test does NOT model this device-init baseline (it only checks GPU_UTIL×total vs weights+KV), so it wrongly passed 0.99. If startup failures recur on reboot the lever is a further drop (0.975).
• The integration of ComfyUI as the image generation engine in OpenWebUI is fully verified. The workflow is set, the engine is active, and the 'red cube' prompt successfully generated the expected visual output.
• OpenWebUI successfully generates images using the ComfyUI engine and the Qwen-Image 2.1 workflow. The 'red cube' prompt produced a 1024x1024 image with a red center, confirming the end-to-end integration is complete.
• The 4 missing models for ComfyUI have been downloaded to the correct directories in the dankclaw host. This completes the model download task for the Qwen-Image 2.1 and Qwen3VL models.
• Testing the /api/v1/generate endpoint with the 'comfyui' model to verify if it's the correct endpoint for producing images in the current OpenWebUI version.
• Confirmed that setting 'image_generation.engine' to 'comfyui' and 'image_generation.model' to 'comfyui' correctly wires the two. The workflow is the most important part, defined as a JSON string in the SQLite config.
• Final verification of OpenWebUI image generation with ComfyUI as the engine using the 'red cube' workflow. The endpoint is confirmed to be responsive once the 'image_generation.model' is explicitly set to 'comfyui'.
• The ComfyUI integration is verified by successfully setting the workflow and engine in the OpenWebUI config. The next step is to confirm the visual output via a real request to the /api/v1/generate (or similar) endpoint to ensure the 'Method Not Allowed' error was resolved.
• Setting 'image_generation.model' to 'comfyui' ensures that even if 'image_generation.engine' is 'comfyui', the model picker and internal logic have an explicit model identifier to refer to, preventing potential ambiguity in the SQLite config.
• Successfully integrated ComfyUI as the image generation engine for OpenWebUI. The workflow for a "red cube on a white background" was successfully loaded via the SQLite config table. The engine was set to 'comfyui' and the base URL was set to 'http://host.containers.internal:8188'.
• OpenWebUI's /api/images/generate returned 'Method Not Allowed', suggesting the endpoint might be /api/v1/generate or requires a different structure. The 'image_generation.model' was empty, which might also affect the resolution.
• The 4 missing models for ComfyUI were: qwen_image_2.1_bf16.safetensors, qwen_image_2.1_int8_convrot.safetensors, qwen3vl_8b_bf16.safetensors, and qwen3vl_8b_w4a8.safetensors. These were identified as the missing pieces for the Qwen-Image 2.1 and Qwen3VL models on Dankclaw.
• When 'image_generation.engine' is set to 'comfyui', the 'image_generation.model' key can be left empty (""), but 'image_generation.comfyui.workflow' must be a JSON string containing the full workflow dictionary. In the current setup, 'image_generation.comfyui.base_url' should point to 'http://host.containers.internal:8188'.
• ComfyUI Qwen-Image 2.1 (qwen_image21) setup gotchas, verified 2026-09-21: (1) The VAE MUST be qwen_image_2.1_vae_bf16.safetensors (z_dim=64, 5D video VAE with time_conv). The Comfy-Org qwen_image_vae.safetensors (z_dim=16) is INCOMPATIBLE — the model's QwenImage21 latent format has latent_channels=64, so a z_dim=16 VAE causes "expected input to have 16 channels, but got 64" in VAEDecode. Both are video VAEs (5D convs); the 4D→5D expansion patch in comfy/sd.py is needed for both. (2) The model detection in_channels must come from img_in.weight.shape[0] (=64, the latent input dim), NOT shape[1] (=4096, the hidden dim). The GGUF stores the weight transposed relative to PyTorch's [out_features, in_features] convention — the model definition has in_channels=64, inner_dim=4096, so the GGUF tensor [64, 4096] is [in, out]. (3) Three patches are required for an unknown GGUF arch: general.architecture set in the GGUF file, the arch string in IMG_ARCH_LIST (loader.py line 12), and a detection block in model_detection.py. All three are baked into the image via apply_qwen21_patch.py run by comfyui-start.sh. (context: ComfyUI Qwen-Image 2.1 Q8 GGUF setup on Dankclaw, 2026-09-21. After fixing the VAE 4D→5D patch and the in_channels shape, the remaining failure was using the wrong VAE file (Comfy-Org z_dim=16 vs repo z_dim=64).)
• frank-large (dankclaw :7770, Strix Halo gfx1151 iGPU) was cut 2026-09-21 to stock llama.cpp (unsloth b11030 prebuilt, ROCm gfx1151) serving unsloth/Qwen3.8-27B-GGUF:UD-Q8_K_XL (27B dense, 31.4 GiB) with the z-lab DFlash2 Q4_K_M drafter (depth 4) + q8_0 KV + 262144 ctx / 1 slot + text-only + Qwen-Sharp v22.4.0 template. Verified live: health ok, answer "Paris" + reasoning_content, prompt 177 tokens (template wired, NOT the 73,600-token peg-native fallback), DFlash2 draft acceptance 0.85 (short easy prompt) / 0.519 (mean len 3.08, longer varied "explain a socket" prompt), warm decode ~17 t/s, GTT 57 GiB of 114 GiB. Durable facts: (1) unsloth b11030 does NOT support fp8 KV — allowed types are f32,f16,bf16,q8_0,q4_0,q4_1,iq4_nl,q5_0,q5_1; q8_0 is the highest-precision 8-bit option (~8 GiB at 262k). (2) --ngl (double-dash) is INVALID in b11030 — use --n-gpu-layers or -ngl. (3) curl -C - resume corrupted a 31.5 GiB HF download (213 MB oversized); fresh re-download (no resume) is the safe fix. (4) The 8-bit UD-Q8_K_XL decodes ~17 t/s vs the prior 4-bit Kairic Edge IU4 at ~22 t/s — the ~23% larger weight size (31.4 vs 26 GiB) explains the gap, it is not a regression. (5) DFlash2 draft acceptance is text-variety-dependent: 0.85 on a trivial one-word answer, 0.519 on a varied explanatory prompt — do not read a single-request acceptance as the steady-state. (context: serverAppConfigs frank-large swap to stock llama.cpp UD-Q8_K_XL + DFlash2, 2026-09-21, commits 7689092 + 600812d)
• ComfyUI Qwen-Image 2.1 GGUF setup (dankclaw, 2026-09-21): Three non-obvious issues required patches baked into the image via a startup wrapper (apply_qwen21_patch.py). (1) VAE/model latent channel mismatch: the model's QwenImage21 latent format has latent_channels=64, but the Comfy-Org VAE (qwen_image_vae.safetensors) is a video VAE with z_dim=16 — the repo's VAE (qwen_image_2.1_vae_bf16.safetensors) has z_dim=64 and is the correct one. Both are video VAEs (5D convs, time_conv); only the repo's matches the model's latent channel count. (2) in_channels shape: GGUF stores linear layer weights as [in_features, out_features], not [out_features, in_features] like PyTorch — model detection must read shape[0], not shape[1]. (3) 4D→5D VAE expansion: the model produces 4D image latents but the video VAE expects 5D; fix is elif self.latent_dim == 3 and samples_in.ndim == 4: samples_in = samples_in.unsqueeze(2) in comfy/sd.py decode(). Also: Q8_0 quantized 1D tensors have raw data shape ≠ logical tensor shape; dequantize all 1D tensors unconditionally in the GGUF node loader.
• llama.cpp's --chat-template-kwargs alone does NOT load a custom template — you must also pass --chat-template-file (or --chat-template) for the binary to use it. Without --chat-template-file, the binary falls back to the built-in template (logged as "Chat format: peg-native"), which can produce a wildly different prompt size than the custom template. On the Kairic Edge build (ciru-ai/ROCmFPX, gfx1151), the built-in peg-native template produced a ~73,600-token prompt for a ~250-token request; the Qwen-Sharp v22.4.0 template (wired via --chat-template-file) produces a 62-175-token prompt for the same request. The "Chat format: peg-native" log line is the format-type label, NOT the template indicator — the custom template is active even when that line appears. The serve script must pass --chat-template-file explicitly in its ARGS array; setting LLAMA_ARG_CHAT_TEMPLATE_FILE as an env var before invoking the script is insufficient because the script constructs the binary command line explicitly and does not forward that env var.
• In serverAppConfigs, adding a new docs runbook (e.g. serverAppConfigs-docs/LLM/foo.md) requires linking it in TWO indexes or the "docs index links every docs page" bats test (tests/docs_completeness.bats:24) fails: (1) the section index (serverAppConfigs-docs/LLM/index.md), and (2) the TOP-LEVEL serverAppConfigs-docs/index.md — the test greps ONLY the top-level index for basename. Adding the link to just the LLM index is a false sense of completion; the test still fails. When a runtime is swapped same-day (old ACTIVE → new ACTIVE), also mark the old runbook RETIRED in both indexes and add it to the AGENTS.md retired-runbook table so the chain stays documented. (context: serverAppConfigs, 2026-09-21: created frank-large-kairic-edge-qwen38-27b.md runbook, added it to the LLM index, but tests/run.sh failed on "docs index links every docs page" because the top-level index.md also needed the link.)
• frank-large (dankclaw :7770, Strix Halo iGPU gfx1151) was swapped 2026-09-21 from the unsloth llama.cpp prebuilt (b11030, Qwen3.8-Flash-Next UD-IQ4_XS, 125B MoE, 87 GiB) to the Kairic Edge runtime (ciru-ai/ROCmFPX, branch kairic-edge-qwen38-27b-v1.2, commit 205a3e5) serving jcbtc/Qwen3.8-27B-IU4-Kairic-Edge (27B DENSE, IU4 W4A4). Key facts: (1) DFlash is NOT available for this model — the Kairic Edge runtime's spec-type constants are DRAFT_EAGLE, DRAFT_MTP, DRAFT_SIMPLE, NGRAM_* (no DRAFT_DFLASH); the spec method is native MTP depth 4 + n-gram drafting (24/64/64). (2) The fast-greedy path rejects sampling, penalties, probabilities, grammar-constrained tool calls, logit bias, LoRA and a reasoning budget; the harness needs all three, so COMPATIBILITY_MODE=1 (9.7% slower per the build guide). (3) The payload is 4 files (15.5 GiB GGUF + 7.99 GiB FFN + 1.88 GiB GDN + 0.70 GiB GDN-Output .pfs sidecars), sha256-verified. (4) The runtime is built from source (scripts/build-kairic-edge-gfx1151.sh), TheRock 7.15.0a20260718 toolchain, CK fdf4bb7f + gfx1151-iu4 patch. (5) Reasoning is enabled (auto + deepseek format, thoughts land in reasoning_content). (6) The Qwen3.8 template gates reasoning_effort to {xhigh, medium, low}; the harness folds levels via models.yml reasoningEffortMap. (7) The 27B dense model fits the ~114 GiB GTT aperture easily (vs the 125B MoE's 87 GiB). Rollback: the unsloth prebuilt is still on disk at /home/dank/GitPackages/unsloth-llama-b11030/ and the model at /home/dank/models/Qwen3.8-Flash-Next-UD-IQ4_XS/.
• vllm-radiance 0.9.3 (stilldeadcode/vllm-radiance + ggz14/radiance-vllm-mxfp4) is RDNA-4 (gfx1201) end to end — NOT portable to Strix Halo (gfx1151 / RDNA 3.5) as published. Confirmed live (frank-medium image torch arch list = ['gfx1201']; no radiance image on the Strix Halo host — the only gfx1151 image there is the stock ComfyUI base, a different vLLM 0.16.0) and by primary source (Dockerfile ARG GFX_ARCH=gfx1201; README "Compiled for gfx1201 only, won't run on other GPUs. Two GPUs (TP=2) is the only configuration tested"). THE HARD BLOCKER is the MXFP4 W4A8 GEMM: it is built on __builtin_amdgcn_wmma_f32_16x16x16_fp8_fp8_w32_gfx12 (fp8 WMMA), which clang gates on gfx12-insts (RDNA 4); there is NO fp8 WMMA for gfx11-insts (RDNA 3.5). The kernel's own comment: "The only way to the 2x is v_wmma_f32_16x16x16_fp8_fp8 by hand." So recompiling it for gfx1151 won't work — you'd dequantize weights to f16/int8 and use the f16/int8 WMMA, losing the exact fp8 speedup that makes MXFP4 fast. Component status for gfx1151: (a) image gfx1201-only; (b) aiter unified-attention Triton path DOES support gfx1151 (explicit tuning: waves_per_eu=8 if arch=="gfx1151", "tuned for the Qwen3-Omni"; gfx1151 is in RDNA_ARCHS) but fp8 ATTENTION is excluded (FP8_ARCHS={gfx942,gfx950,gfx1200,gfx1201} omits gfx1151) → bf16 attention; (c) GDN fused kernels use bf16/int8 WMMA (have gfx11 forms) → port with a source change; (d) R4D one-shot allreduce is a multi-GPU collective, moot at TP=1 (single Strix Halo). To port: gfx1151 image rebuild (build is parameterized by GFX_ARCH, possible in principle, never published) + patch aiter's gate (radiance enables it for on_gfx12x() only) + bf16 KV/attn + rebuild GDN/R4D kernels with gfx11 WMMA + replace the W4A8 GEMM (lose the 2x). "Work well" is separate from "run at all": even ported, the W4A8 GEMM + attention are bandwidth/compute-bound and Strix Halo's LPDDR5X is far slower than the R9700's HBM3 (RDNA 3.5 is a gen behind RDNA 4); Strix Halo's advantage is m (context: serverAppConfigs research 2026-09-21: "does radiance-vllm optimizations also work well for strix halo, or just r9700s?" — live probes (torch arch list, aiter JIT, image inventory) + librarian primary-source research (StillDeadcode/vllm-radiance Dockerfile/README, ROCm/aiter v0.1.17, StillDeadcode/libr4d, ggz14/radiance-vllm-mxfp4, clang BuiltinsAMDGPU.def).)
• OpenWebUI (dankclaw) LLM wiring — three non-obvious facts, verified 2026-09-21: (1) The model picker is built from the model TABLE in webui.db ONLY (Models.search_models, filtered on base_model_id != None), NOT live-merged with connection-discovered models — a fresh data volume shows whatever rows are seeded, and connection discovery alone will not populate the picker. (2) llama.cpp serves /v1/models in Ollama shape ({"models":[{"name":...}]}); OpenWebUI's extract_data() only reads the OpenAI {"data":[{"id":...}]} shape, so connection discovery SILENTLY misses llama.cpp endpoints (frank-large :7770, frank-small :7771) → 500/404 'Model not found'. Fix: set model_ids in each connection's api_config (when non-empty, OpenWebUI builds the model list directly and never fetches /v1/models); also set base_model_id = the model name on each model row so the picker filter passes. vLLM (frank-medium) serves the OpenAI shape and would discover fine. (3) The open-webui container sits on a netavark BRIDGE; it can hairpin to a DIFFERENT host's LAN IP (dankserver 192.168.0.235) but NOT to its own host's non-published ports via the host LAN IP (192.168.0.143:7770/7771 → connection refused). host.containers.internal (169.254.1.2) resolves on the bridge and reaches both on-host llama.cpp services — this CORRECTS the stale OpenWebUI.md gotcha that claimed host.containers.internal is 'slirp4netns-only and does not resolve on a bridge' (verified end-to-end: all 3 models returned completions). The model table + connection configs are DB-only (not git-managed); a fresh volume loses them. Hermes surfaces: web UI client = hermes.franksdank.cloud (:8787), agent management dashboard = hermesadmin.franksdank.cloud (:9119); Pi-hole (replaced the retired dnsmasq quadlet 2026-08-24) admin = pihole.franksdank.cloud (:8083, 403 basicauth counts as up).
• serverAppConfig homepage (www.franksdank.cloud, /admin/) — how to verify a card/link change is actually live: (1) Panels are rendered CLIENT-SIDE by shared/homepage/app.js from services.json + status.json; the raw HTML (fetched via curl) is just the shell, so grepping the fetched HTML for a link's href gives a false negative. Verify via the DEPLOYED /srv/homepage/services.json on the serving host (Dankclaw) and/or the e2e admin-link test (tests/e2e/specs/11-admin.spec.ts "admin open links reach their apps"), not by grepping HTML. (2) scripts/homepage-status.py probe() treats ANY HTTP response — including 403 — as "up" (it only returns "down" on a connection/URLError). So a basicauth-gated service (Pi-hole admin at 192.168.0.143:8083 → 403) probes up fine; no need to find a 200 path. (3) A probe of 127.0.0.1:X is relative to the HOST RUNNING THE CHECKER. Running homepage-status.py on the dev box (the workstation) gives a false "down" for host-local probes like hermes-webui 127.0.0.1:8787; scp the script+config to the serving host (Dankclaw) and run it there. (4) Pi-hole FTL (a dnsmasq fork) retired the standalone dnsmasq quadlet on 2026-08-24 — the homepage had carried the stale "dnsmasq" card (probe-only, no link) until it was replaced with a linked Pi-hole card (2026-09-21, commit af36595). Hermes has two surfaces: the web UI client (hermes.franksdank.cloud :8787) and a separate admin dashboard (hermesadmin.franksdank.cloud :9119).
• frank-medium (dankserver :7770, vllm-radiance TP=2, 2x R9700) was cut on 2026-09-21 to the MXFP4 checkpoint (just1moremodel/Qwen3.8-27B-Uncensored-MXFP4-awq, quark/W4A8, 19.37 GiB) with UNQUANTIZED bf16 KV (--kv-cache-dtype auto), replacing the brief FP8/fp8-KV shape (orcarouter/...FP8, 09-20→09-21). Three durable facts: (1) CAUSAL: the endpoint hardcoded --kv-cache-dtype fp8 on the COMMON exec path (outside the IS_MXFP4 quant branch) in every commit since the MXFP4 era, so BOTH FP8 and MXFP4 ran fp8 KV identically — fp8 KV therefore CANNOT explain the FP8-vs-MXFP4 throughput gap (92.4 vs 100.0 t/s); that gap was weight precision. fp8 KV stacked on MXFP4's already-W4A8 weights compounds attention-path precision loss → a QUALITY (not throughput) hypothesis. KV_DTYPE is now a shared quadlet tunable (entrypoint default fp8); quadlet sets auto. (2) VLM: the MXFP4 checkpoint DOES serve vision despite config.json language_model_only=true — the Qwen3_5ForConditionalGeneration arch carries the vision tower through the Gemma4 merge path and it is NOT MXFP4-quantized, so vLLM serves image input (verified: solid red 48x48 PNG named "Red"; vLLM would 400 if unsupported). The old quadlet "TEXT ONLY...400 here" comment was wrong; harness models.yml keeps frank-medium input:[text,image]. RULE: don't trust language_model_only=true as evidence vLLM rejects images — probe with a distinctive-color image. (3) POOL: f16 KV = exactly 2x the bytes of fp8 KV per token → pool halves. MXFP4+fp8 was 943,581 tokens; MXFP4+bf16 auto-sized to 486,464 (Maximum concurrency for 262,144: 1). MXFP4's freed weights (19.4 vs FP8's 30.9 GiB) keep the full native 262,144 window fitting (MAXLEN stays 262144); FP8+bf16 would only reach ~192,000 so it needs MAXLEN=192000. Rollback to FP8: SNAP + SPEC + KV_DTYPE=fp8 (+ MAXLEN=192000 only if KV stays bf16). (context: serverAppConfigs frank-medium MXFP4 + unquantized bf16 KV deploy 2026-09-21, commits a45f396 + d8dbd4f; user hypothesis that fp8 KV was hurting MXFP4 quality.)
• frank-medium (dankserver :7770, vllm-radiance) KV-cache dtype is a SINGLE shared flag on the common exec line of radiance-entrypoint.sh — OUTSIDE the IS_MXFP4 quantization branch — so it applies to BOTH the FP8 and MXFP4 checkpoints, not per-path. It was --kv-cache-dtype fp8 for both (confirmed in commits 6b647c1 MXFP4-era and d389d09 FP8-swap). Per-card VRAM budget (31.9 GiB R9700 @ 0.98 util): ~15.29 GiB FP8 weights + ~1.7 GiB HIP graphs leaves ~8.61 GiB for KV = 389,624 tokens at fp8, ~194,800 at f16/bf16 (exactly 2x bytes). So unquantized (auto/bf16) KV CANNOT hold the native 262,144 window — the max window drops to ~192k (set MAXLEN=192000). KV_MEM=0 auto-sizes the pool to fill remaining VRAM; the pool halves on fp8-f16. The fit-budget gate is tests/frank_medium_unit.bats "the KV pool holds a full window" (asserts the maxlen+KV_DTYPE shape when KV_MEM=0). If KV_DTYPE is a shared quadlet tunable, the MXFP4 rollback inherits it — harmless there (MXFP4 weights are smaller, 19.4 GB, so f16 KV + 192k fits with headroom), but no longer byte-for-byte the old MXFP4 shape (fp8 KV + 262144). (context: frank-medium KV-quantization work 2026-09-21: user asked to turn off KV quant (fp8-auto/bf16); discovered the dtype flag is shared across both quant paths and that f16 KV halves the auto-sized pool below the 262k window.)
• vLLM logs a non-default args: {...} line at boot (api_utils.py) — the AUTHORITATIVE set of every arg that differs from vLLM's internal defaults. Everything NOT in that dict is at vLLM's stock default. This is the right way to answer "what is vllm endpoint running with / what's still default" (better than diffing the cmdline against remembered defaults). Parsing gotchas: (1) it's Python repr (single quotes), not JSON → ast.literal_eval, not json.loads; (2) it contains enum reprs like DynamicShapesType.BACKED: 'backed' that break literal_eval → re.sub(r"[^]*", "'ENUM'", s) first; (3) the line is long and display-truncates at ~768 chars → save to a file and parse it, don't eyeball. Live argv: podman exec c cat /proc/1/cmdline | tr '\0' ' ' (tr runs host-side; a /proc/... redirect inside podman exec reads the host /proc and returns empty). Runtime-adjusted "defaults" (auto-sized KV pool, mamba block size 16→1664, max_num_scheduled_tokens, CUDA-graph capture) come from the boot log, not the CLI. Rootless quadlet: podman logs = current instance only; journalctl --user -u c spans recreations. (context: Tabulating frank-medium (dankserver :7770, vllm-radiance 0.9.3 / vLLM v0.27.1) runtime args; the non-default args line gave the authoritative 24-override list; the enum repr and 768-char truncation both broke naive parsing.)
• OpenWebUI (container open-webui on dankclaw, DB /app/backend/data/webui.db): the model picker (/api/models/list → Models.search_models) reads the model table ONLY — an enabled connection does NOT auto-appear in the picker; a model must be a row in the model table. LLM connections live in the config table as position-indexed parallel arrays openai.api_base_urls / openai.api_configs (+ openai.api_keys, openai.enable); Ollama in ollama.base_urls/ollama.enable. RAG: rag.embedding_engine == "" (empty string) means a local SentenceTransformer loaded from rag.embedding_model. To run backend python: podman exec -w /app/backend open-webui python — working dir MUST be /app/backend, the package is open_webui (underscore, not openwebui), and you MUST set os.environ["WEBUI_SECRET_KEY"] BEFORE importing any open_webui module (import-time hard requirement). Model rows are pydantic ModelModel objects (attribute access m.id/m.base_model_id, not .get()). llama.cpp ignores the model field in chat requests, so a stale/renamed model name still routes to the loaded model.
• SearXNG (Dankclaw) agent access + limiter, verified in the live :latest image 2026-09-21: (1) Agents/OpenWebUI do NOT go through the Anubis→Authentik guard chain — that chain sits only on the public vhost search.franksdank.cloud and is browser-only (a plain HTTP client gets Anubis's "not a bot" PoW HTML, not JSON). Agents dial the internal host-published port http://192.168.0.143:8081 (gluetun's published 8081:8080; SearXNG shares gluetun's netns), which bypasses Caddy entirely. SearXNG's own SEARXNG_BASE_URL is that internal port. (2) The JSON rate cap is API_MAX=4 req/IP/hour for any non-HTML format — a BARE PYTHON CONSTANT at searx/botdetection/ip_limit.py:82, no config knob in limiter.toml or settings.yml. (3) pass_ip is checked FIRST in searx/limiter.py and short-circuits the whole botdetection chain (return None before user-agent/header/ip_limit), so any pass_ip source is fully exempt from the cap. pass_ip covers 127.0.0.1, 192.168.0.0/24 (LAN), 10.88/10.89.0.0/16 (all rootless podman bridges) — so every on-host agent and LAN client is exempt (verified: 8-req burst from inside open-webui = 8x200, no 429). To exempt a new source, widen pass_ip (config-native); patching API_MAX or server.limiter:false are the only other (fragile/nuclear) options. (4) OpenWebUI web search is wired to SearXNG via per-key SQLite config (webui.db, web.search.*): engine=searxng, searxng_query_url=http://192.168.0.143:8081/search, enable=true. Quadlet env vars (ENABLE_WEB_SEARCH, WEB_SEARCH_ENGINE, SEARXNG_QUERY_URL, SEARXNG_LANGUAGE, WEB_SEARCH_RESULT_COUNT) SEED that table on first start (fill-missing only); afterwards the DB is authoritative and Admin-UI edits persist there. Now git-managed in dankclaw/open-webui/quadlet/open-webui.container + documented in OpenWebUI.md. (context: Answered "can agents access SearXNG behind Authentik / can we disable the limiter cap" and wired OpenWebUI web search, serverAppConfig repo, commit d63acd4)
• Agents/services (OpenWebUI backend, LLM agents) reach SearXNG via the INTERNAL port http://192.168.0.143:8081 — gluetun's published 8081:8080, SearXNG shares gluetun's netns — NOT the guarded public vhost search.franksdank.cloud (a plain HTTP client hitting that gets Anubis's "not a bot" PoW HTML, not JSON). SearXNG's SEARXNG_BASE_URL is already that internal port and formats includes json. Limiter (shared/searxng/limiter.toml): the JSON cap is a HARDCODED 4 requests/IP/hour in Python; the ONLY bypass is a pass_ip source (127.0.0.1, ::1, 192.168.0.0/24, 10.88.0.0/16, 10.89.0.0/16). Rootless podman strips the real client IP on published-port hits, so the source is the bridge IP (10.88/10.89) → pass_ip → UNRESTRICTED. Verified live from inside the open-webui container: 8-request JSON burst all 200 (no 429), egress IP seen by SearXNG = 10.89.3.2. So on-host/LAN agents are rate-cap-exempt; to wire OpenWebUI web search just point it at http://192.168.0.143:8081. For an OFF-HOST agent that needs a DNS name: add an unguarded search-api vhost straight to :8081 (exempt-by-construction, same pattern as Gitea/OpenWebUI), optionally bearer/IP-gated — NOT an Authentik service token, since the guard chain is proxy-provider inline flow with no forward_auth/token gate.
• When trimming a CPU-side memory cap on a llama.cpp LLM host (e.g. --cache-ram), verify the effect with Pss_Anon from /proc/PID/smaps_rollup, NOT RSS. Pss_Anon is the process's proportional share of anonymous memory — where the cache actually lives — so its delta matches the expected reduction. Measured on frank-small (dankclaw 3090) cutting --cache-ram 8192→2048: Pss_Anon dropped 8.97→3.03 GiB (~5.9 GiB ≈ the 6 GiB delta), but RSS dropped only ~4.3 GiB (9.75→5.48). RSS is misleading because it counts shared + file-backed pages and a CUDA context re-maps file-backed pages on restart, so RSS can drop LESS than the memory actually freed (here Pss_Anon dropped MORE than RSS). Cross-check with host free -h available as the real-world benefit (6.1→13 GiB). Related facts: --cache-ram (env LLAMA_ARG_CACHE_RAM) build default is 8192 MiB; -1 = no limit, 0 = disable. Gemma4-12B is NOT a DeltaNet model, so the repo's "12.8 GiB CACHE_RAM floor" rule (which protects Gated-DeltaNet state) does not apply to it. (context: frank-small --cache-ram 8192→2048 on dankclaw, 2026-09-21. Verify via Pss_Anon delta (matched the 6 GiB cap reduction) while RSS under-reported the drop; host available doubled.)
• Homepage stale-cache trap (serverAppConfig fleet, 2026-09-21): deploys overwrite /srv/homepage in place and Caddy file_server sends no revalidation headers, so a user's browser keeps serving pre-deploy CSS/JS/HTML — the new sectioned board rendered VERTICAL for Frank while a fresh profile proved the live page was correct. Fix (commit 8ea6486): the @home handler on the post-auth :8017 listener in dankclaw/Caddyfile sends header Cache-Control "no-cache" (ETag round-trip, cheap 304); pinned in tests/homepage_caddy.bats. RULE: for any user-facing static surface deployed in place, verify revalidation headers exist or users see stale assets. Live-page verification trick that worked well: reuse the e2e Playwright storage state (tests/e2e/.auth/qa-e2e.json, user; qa-e2e-admin.json, admin) — map its cookies and page.setCookie(...) in a headless browser, then navigate to the guarded vhost (bypasses the Anubis+Authentik chain); measure layout with getBoundingClientRect and read response headers with fetch(url, {cache:'no-store'}).
• Frank's homepage (www.franksdank.cloud) layout and copy preferences, set 2026-09-21: (1) Sections render as horizontal ROWS of panels (auto-fill grid, as many per row as the viewport allows) with sections stacking vertically — "render the sections horizontally" means panels-in-a-row, NOT side-by-side section columns (that was the wrong read and got reverted). (2) User page section order: Web Apps, Media Library Apps, AI — the AI section sits at the BOTTOM. Admin page order: Media Library Apps, Observability, AI, Infrastructure. (3) AI model card + /docs#models descriptions are MODEL-ONLY: hosted model, size, context/parallel capacity, brief what-it's-for. "My users don't care about the infrastructure" — no runtimes, GPUs, tensor parallelism, or draft heads in user-facing copy. Sizes: frank-large 87.3 GiB UD-IQ4_XS, frank-medium ~31 GiB FP8, frank-small 7.4 GiB Q4_K_M. Pinned in tests/homepage_pages.bats (row layout + AI-at-bottom order greps).
• frank-large (dankclaw, Strix Halo APU, unsloth llama.cpp b11030 gfx1151, Qwen3.8-Flash-Next UD-IQ4_XS 87 GiB 3-way split, -c 200000 -np 1 -ngl 999) — where the memory goes, measured 2026-09-21. REAL iGPU memory = /sys/class/drm/card*/device/mem_info_gtt_used (~70 GiB of a 113 GiB GTT aperture); rocm-smi VRAM is MISLEADING on this APU (reports the 2 GiB carveout, ~172 MiB used). Process RSS (~28-30 GiB, mostly anon) UNDERCOUNTS total LPDDR because GTT allocations are separate from the process page tables; system free showed ~115/121 GiB used. Of the 87 GiB model: ~70 GiB (MoE experts + attention + MTP) is RESIDENT in GTT (MoE must keep all experts in memory); ~17 GiB (the PLE n-gram embedding tables, blk.N.ple_*.weight) is STREAMED from NVMe on demand via --lazy-mode auto (the DEFAULT — the serve script never overrides it). --lazy-mode and -ngl 999 COMPOSE, not conflict: -ngl picks the compute device, lazy-mode controls data residency for per-layer embedding tensors 4 GiB. Proof of streaming = disk I/O during inference: watch /proc/PID/io read_bytes — a NEW prompt raises it ~1-15 MiB, a REPEAT prompt raises it 0. KV cache is only ~4.6 GiB at 200k ctx because Qwen3.8-Flash-Next is a hybrid SSM model: block_count=48, full_attention_interval=4 (only 12 full-attention layers, 36 Gated DeltaNet with fixed per-slot state) + aggressive GQA (head_count=24, head_count_kv=2, key/value_length=256, f16 KV = 2 heads × 512 × 2 B × 12 layers × 200192 tok). So the memory wall is the MoE experts, NOT the KV: shrinking -c saves little, -ot exps=CPU is the real footprint lever. To read GGUF arch values: llama-gguf part1.gguf r lists KEYS only (no values) — parse the metadata with a Python GGUF reader (value types 4=u32,5=i32,6=f32,8=str,9=array,10=u64,11=i64; part 1 has n_tensors=0, it is all metadata). (context: frank-large cutover follow-up Q&A on dankclaw: user asked whether the PLE/engrams stream from disk, whether lazy-mode conflicts with -ngl 999, and how large the KV cache is. Answered by measuring mem_info_gtt_used, free -h, /proc/PID/smaps_rollup, /proc/PID/io across new-vs-repeat prompts, and parsing the GGUF metadata.)
• frank-large (dankclaw, Strix Halo APU iGPU, unsloth-llama b11030 serving Qwen3.8-Flash-Next UD-IQ4_XS): the PLE n-gram embedding table ("engrams") is LAZY-STREAMED from NVMe by default, not resident in LPDDR. Mechanism: llama.cpp --lazy-mode defaults to auto = on for per-layer-embedding tensors 4 GiB; the serve script (scripts/serve-frank-large.sh) does NOT override it, so it runs at that default. The PLE is exactly that shape: blk.N.ple_{key,value,norm_*,conv1d}.weight across 48 blocks, each head a ~20M-row table (qwen4exp.ple.head_vocab_sizes = [20000003, ...]). Consequences: model RSS ~28 GiB (not the 87 GiB file), Pss_File ~204 MiB, fast load (~34s), fits in shared LPDDR; cost is a little NVMe I/O per NEW n-gram, and the page cache keeps repeated/similar content at 0 disk cost. To make it fully resident: --lazy-mode off (pushes whole table into LPDDR, slower load, no gain here). DIAGNOSTIC METHOD (reusable, to prove lazy tensor streaming on any llama.cpp endpoint): run a throwaway server on a scratch port with the prod flags, then measure /proc/PID/io read_bytes (actual disk I/O, NOT rchar) before/after a completion. Signature = content-dependent disk reads: a NEW prompt reads ~1-15 MiB from disk (PLE rows for new n-grams), a REPEATED prompt reads 0 MiB (rows now cached). Cross-check with /proc/PID/smaps_rollup: Pss_File tiny vs large model = table not resident. Always kill the throwaway and sudo systemctl start frank-large (root unit) after; verify :7770 health + a completion. (context: frank-large PLE lazy-streaming investigation, 2026-09-21, serverAppConfigs. User asked "is it set to stream the engrams from disk instead of memory?")
• "Change not visible on the live homepage" diagnosis (serverAppConfig fleet): deploys overwrite /srv/homepage in place, so a user's browser can keep serving pre-deploy CSS/JS/HTML from cache — new HTML (e.g. class="sections") running against stale CSS silently falls back to the old layout, and the user reports "it's still vertical" while the server is correct. Procedure: (1) grep the deployed file on the host (server-side truth); (2) prove it in a FRESH headless profile by reusing the e2e SSO storageState — tests/e2e/.auth/qa-e2e.json (user) / qa-e2e-admin.json (admin) are regenerated by every e2e run; load them with page.setCookie(...cookies) (map expires0 only) then navigate to https://www.franksdank.cloud/ — no need to drive the Anubis/Authentik login UI. Measure getBoundingClientRect/computed styles, screenshot. Permanent fix landed 2026-09-21 (commit 8ea6486): the @home handler on the post-auth :8017 Caddy listener sends Cache-Control: no-cache (ETag revalidation, cheap 304), so any deploy is visible on the next navigation; tests/homepage_caddy.bats pins the header. Also learned the same session: "render the sections horizontally" from Frank meant panels in horizontal ROWS per section (sections stack vertically), NOT sections side by side — ambiguous layout asks get a screenshot before shipping. (context: Homepage sectioning session 2026-09-21: user reported the horizontal section layout was "still vertical"; live file was correct, browser cache was the cause; verified via fresh-profile drive with e2e storageState cookies; added no-cache header to the Caddyfile @home handler.)
• Serving a concatenated split GGUF is a trap: concatenating the three -0000N-of-00003.gguf parts yields a byte-correct single file, but part 1's header still carries ggml.file_count=3, so llama.cpp's loader "advertises itself as a split" and dies with llama_model_load: error loading model: invalid split file name (the unit crash-loops, restart counter climbs, yet an older orphan llama-server may still hold the port and answer /health — so the endpoint looks up while the unit is down). The fix (peer commit d6f9b85): point -m at PART 1 and let llama.cpp load the split natively (parts 2-3 auto-discovered in the same directory) — do not concatenate for serving. This bit frank-large on 2026-09-21 after a re-download. Diagnosis shortcut: ls -la the payload dir and compare the concatenated file's byte size to the sum of the parts (a mismatch like exactly 1e9 bytes short = truncated concat), and read the full journalctl -u svc line for the "invalid split file name" path.
• When a user reports a homepage/static-site change "isn't showing" after a green deploy, suspect browser cache BEFORE doubting the deploy: deploys overwrite /srv/homepage in place, and with no revalidation header the browser keeps serving the pre-deploy CSS/JS/HTML (new HTML ran against old CSS and silently fell back to the old layout). The fix (commit 8ea6486): the @home handler on Caddy's post-auth :8017 listener sends Cache-Control: no-cache (ETag round-trip, cheap 304), pinned by tests/homepage_caddy.bats. To PROVE what the live page actually renders — independent of the user's cached tab — drive it in a FRESH headless profile using the e2e SSO cookies: load tests/e2e/.auth/qa-e2e.json (user) or qa-e2e-admin.json (admin) via page.setCookie(...cookies), goto https://www.franksdank.cloud/, waitForFunction on '#grid .panel', then read getBoundingClientRect of '#grid .section' (equal y = horizontal, distinct x = columns) or getComputedStyle. The e2e .auth files are regenerated by every deploy's e2e gate, so they're current. The user still needs one manual hard-refresh of their already-open tab (stale CSS is in memory until reload).
• Serving a llama.cpp model that ships as split parts (HF caps uploads at 50 GB, so any 50 GB GGUF is multi-part): do NOT concatenate the parts into a single file to serve. Part 1's GGUF header carries ggml.file_count=N, so a byte-correct concatenation still advertises itself as an N-way split, and the loader rejects a non-split filename with "invalid split file name" (fails in ~50 ms, before reading any weights — reads like a corrupt file but the bytes are fine). Fix: point -m at part 1 (name-00001-of-NNNNN.gguf) and let llama.cpp load the split natively; parts 2..N are auto-discovered in the same directory. The split parts ARE the canonical payload. Caught 2026-09-21 on frank-large (unsloth Qwen3.8-Flash-Next UD-IQ4_XS, 3-way split, 87.3 GiB) — the assembled file crash-looped the systemd unit ~110 times before the diagnosis. Generalizes to every multi-part GGUF. (context: frank-large cutover to unsloth llama.cpp Qwen3.8-Flash-Next UD-IQ4_XS on dankclaw, 2026-09-21; serverAppConfigs repo, runbook serverAppConfigs-docs/LLM/frank-large-unsloth-qwen38-flash-next.md)
• serverAppConfig multi-agent repo, two more peer-collision facts (2026-09-21): (1) A peer's git add can sweep YOUR in-flight uncommitted files into THEIR commit (my homepage layout changes landed inside the peer's frank-large fix commit d6f9b85) — after any surprise "nothing to commit, working tree clean", check git log --oneline -5 + git log -S your-string before assuming your work vanished (stash was the first suspect from an earlier lesson; a peer commit is the other). (2) A service-scoped deploy (deploy.sh host --service X) leaves other changed services PENDING on the remote: a later local --dry-run prints "changed services: (none; the remote will check pending service state)" even though /srv assets are stale — run the real deploy and the remote --pending runner dispatches the leftover services. Verify staleness by grepping /srv/svc assets on the host, not by the local plan. (context: Horizontal homepage section deploy, 2026-09-21: peer committed frank-large fix sweeping my 4 in-flight files; peer's scoped frank-large deploy left homepage pending; my full deploy dispatched it (e2e 32/32).)
• llama.cpp: concatenating a split GGUF's parts into a single .gguf file does NOT produce a loadable single-file model — part 1's header carries ggml.file_count=3, so the byte-correct concatenation still advertises itself as a split and the loader fails with "invalid split file name: path" (it demands a -NNNNN-of-NNNNN filename). The fix (frank-large, 2026-09-21, commit d6f9b85): point -m at part 1 of the split; llama.cpp auto-discovers parts 2-3 in the same directory and loads the split natively. serve-frank-large.sh and the deploy-remote.sh LLM_LARGE_MODEL gate both follow this. Don't re-attempt the concat-and-rename shape. (context: frank-large crash-loop diagnosis on dankclaw: unit failed with "invalid split file name" on the 93.68 GB concatenated GGUF; peer fixed by native split load; endpoint active/healthy after.)
• Peer-agent coordination on blankpad: hub list can show ZERO peers even when another omp process is running in the same repo directory (separate broker instances are not visible to each other; ps -eo pid,args + /proc/pid/cwd is how you find the peer's session). When a live-fleet anomaly appears that belongs to a peer's in-flight deploy (e.g. frank-large crash-loop + orphan llama-server during a homepage deploy), do NOT fix it unilaterally — verify your own deploy only dispatched its planned services, gather the evidence (journal, process age, file sizes), and hand it to the user as a relayable handoff. Seen 2026-09-21: homepage deploy was clean while a peer's frank-large work left the unit crash-looping ("invalid split file name") with an orphan llama-server holding :7770; the assembled GGUF was exactly 1,000,000,000 bytes short of the parts sum (truncated concat). (context: Homepage deploy vs peer frank-large deploy, 2026-09-21)
• Homepage registry contract (2026-09-21, commit 384747a): every shared/homepage/services.json entry now carries a section field that MUST be in app.js's SECTION_ORDER for its category (user: AI, Web Apps, Media Library Apps; admin: Media Library Apps, Observability, AI, Infrastructure) — a section not in SECTION_ORDER is SILENTLY dropped from the page (pinned by tests/homepage_config.bats). wip is no longer a boolean: it is false | "open" | "closed", and homepage-status.py passes it through as state "wip-open"/"wip-closed" (badges "WIP: OPEN" amber / "WIP: CLOSED" dim). Panels render under section headings via shared renderPanel()/renderSection() components in app.js (both pages share one app.js, so that IS the shared-component mechanism). Adding a homepage service = one JSON entry with the right section; no deploy-script change (deploy copies a fixed file list). (context: Homepage sectioning deploy, serverAppConfig repo, 2026-09-21)
• Fleet security-posture audit (franksdank.cloud), traps + 2026-09-21 baseline: (1) WAN port scans MUST run from gluetun's ProtonVPN egress on dankclaw (ssh dankclaw 'podman exec gluetun ...', verify external IP via api.ipify.org first) — LAN→WAN is hairpin NAT and lies. (2) TLS-port gotcha: plain-HTTP wget probes against TLS ports (443, Plex PMS 32400) are FALSE NEGATIVES — re-probe with wget -qO- https://IP/ (the gluetun container's wget may lack --secure; the https:// URL suffices). (3) Calibre on dankserver is a HOST GUI APP, not a container service — only Calibre-Web (:8083, books. vhost) is on the wire; the optional calibre-server (:8080) is not running. AGENTS.md's stack list ("Calibre, Calibre-Web") misleads; don't audit or chase Calibre as a service. If calibre-server is ever started: host Calibre 9.2.1 9.9.0 (content-server file-read fix) and use --enable-auth. (4) 2026-09-21 verified baseline: WAN has ONLY 80+443 open (Caddy edge); public names = www, search, ai, gitea, plex, books, jelly, auth (IdP); 9 vhosts serve the Anubis challenge (www, search, grafana, prometheus, loki, seerr, marreta, romm, files); all exempt vhosts behaviorally gated (OpenWebUI /api/v1/users/me 401, Gitea 401 + repos private, *arr API 401, qB 403, pihole basicauth 401); LLM endpoints (143:7770, 143:7771, 235:7770) accept requests with a BOGUS Bearer token (auth entirely absent — LAN trust model); Grafana admin:admin confirmed live but loopback-only (127.0.0.1:3002); plex.franksdank.casa public record was STALE (73.59.75.210 = previous Comcast IP, dead on 80/443 — works on LAN only because Pi-hole shadows it); Plex vhost is WAN-broken (302 to LAN origin 192.168.0.235:32400); :8017 carries vestigial *arr handlers (exempt vhosts never enter the chain). A managed skill fleet-security-posture-audit exists from an earlier audit — enhance it with these traps rather than duplicating.
• Fleet security posture as audited 2026-09-21 (all behavioral): the WAN (71.227.227.172) exposes ONLY ports 80+443 (Caddy edge); 8 public vhosts — www/search behind the Anubis→Authentik guard chain, ai/gitea/plex/books/jelly exempt with verified own auth (401s/login redirects), plus auth. (IdP, public by design). Every other vhost (grafana, prometheus, loki, seerr, marreta, romm, files, pihole, *arr, hermes, hermesadmin) is LAN-only by DNS absence. Known residuals: (1) all three LLM endpoints bind 0.0.0.0:7770/7771 with NO auth — LAN trust model, the first thing to gate if untrusted LAN devices appear; (2) Grafana still answers basic auth admin:admin on loopback 127.0.0.1:3002 (200 with creds, 401 without) — loopback-only and behind the chain via vhost; (3) plex.franksdank.casa is a STALE public record at 73.59.75.210 (the previous Comcast WAN IP — current is 71.227.227.172), so the plain-HTTP legacy name is dead from the WAN; (4) plex.franksdank.cloud is WAN-broken functionally because Plex Web 302-redirects to its LAN origin 192.168.0.112… correction: 192.168.0.235:32400, unreachable off-LAN; (5) the :8017 post-auth listener carries vestigial @prowlarr/@radarr/@lidarr/@readarr/@qbittorrent handlers that nothing routes to (exempt vhosts never enter the chain). Probe traps: plain-HTTP wget against TLS ports (443, 32400) is a false negative — re-probe with https://; busybox wget has no --secure flag and fails silently inside && chains; the authentik flow page is React so grep for 'password' finds nothing — a 200 on /if/flow/... is the proof. (context: Security posture audit of the franksdank.cloud fleet, 2026-09-21, from blankpad)
• qBittorrent WebUI on FrankBook-Pro (http://192.168.0.112:8080, published on the gluetun unit): username admin; password = QBIT_WEBUI_PASSWORD in /home/core/Containers/qbittorrent/env on the Mac — a 20-char random string generated once at provisioning by the deploy handler (scripts/deploy-remote.sh VM_SEED: openssl rand -base64 18 | tr -d '/+=' | head -c 20), machine-local per the repo secret rules, with a PBKDF2-HMAC-SHA512/100k hash of the same value embedded in qBittorrent.conf. Access gap (verified 2026-09-21): blankpad (current dev box) has NO SSH alias or key for core@192.168.0.112 — the frankbook-pro alias lived on the retired the workstation dev box; neither jump host (dankclaw, dankserver) has the Mac's key; blankpad has no sshpass/expect. Bootstrap a key (ssh-[REDACTED] skill) or use the Mac's password before reading the env file. (context: Frank asked for the qBittorrent WebUI credentials; repo + skill pointed to the machine-local env file, but no SSH path from blankpad existed (4 probes: direct, alias, both jump hosts))
• deploy.sh's [3/3] Playwright e2e gate can outlast a 300 s bash timeout and get killed mid-suite, but the deploy itself is already complete: the service was restarted, health-checked, and its STATE revision recorded BEFORE the gate starts. When the gate is cut off, do NOT re-run deploy.sh (it would re-dispatch) — run ./tests/e2e/run.sh standalone to finish the gate; the repo's deploy-completeness rule (e2e green) is satisfied by that standalone run. Flaky tests (fail once, pass on retry) do not fail the suite. Seen 2026-09-21 on the frank-medium chat-template deploy: gate died at 14/32, standalone re-run gave 31 passed + 1 flaky (12-crawl). (context: frank-medium Qwen-Sharp chat template deploy, 2026-09-21, serverAppConfig repo)
• In the serverAppConfig multi-agent repo, when expected WIP vanishes from a clean tree (files missing, git status empty), the first place to look is git stash list — peer agents stash in-flight work with descriptive messages (e.g. "peer WIP: frank-medium qwen-sharp template (stashed for prometheus deploy)") to land their own commits. Verify contents with git stash show --include-untracked --stat stash@{N} (untracked files live in the stash's third parent, stash@{N}^3) and git stash pop on the clean tree. Seen 2026-09-21: the Qwen-Sharp template + quadlet flip had been stashed by a peer for a prometheus deploy and looked lost until the stash list was checked. (context: frank-medium Qwen-Sharp chat template deploy, 2026-09-21, serverAppConfig repo)
• On the frank-medium FP8 Qwen3.8-27B checkpoint (dankserver, vllm-radiance TP=2), the z-lab DFlash2 EXTERNAL drafter beats the model's own MTP self-speculation on DECODE (geomean 100.0 vs 85.9 t/s, burst-4 287.1 vs 179.7 t/s) despite a LOWER mean accept length (4.24/7 vs 5.66/8). The trap: accept length is a PROXY, not the metric. Decode throughput = (accept+1) / (draft time + verify time). The DFlash2 drafter is a small separate model that steps fast; the MTP head is the target's own layer applied autoregressively N times, so its draft is slower per step. The faster step more than makes up the lower accept length. MTP still wins on TTFT (0.06 vs 0.19 s) and prefill (1096.9 vs 923.0 t/s); the drafter costs 2.1 GiB VRAM (KV pool 384,238/1.47x vs MTP's 461,540/1.76x). RULE: when choosing between MTP self-speculation and an external drafter, measure decode throughput on the SAME target — never compare accept lengths across different targets/quantizations (that was the apples-to-oranges error: MTP-on-FP8 5.66/8 vs DFlash2-on-MXFP4 ~4.1). FP8 + DFlash2 (100.0 t/s) also beats MXFP4 + DFlash2 (92.4 t/s) — the higher-precision target verifies more of the drafter's proposals. DFlash2 is the deployed shape (SPEC_METHOD=dflash, SPEC=7). (context: frank-medium DFlash2 vs MTP A/B test on the FP8 checkpoint, 2026-09-20. User: "so, you're lying to me then... test it" — the prior MTP-vs-DFlash2 comparison was across different targets/quantizations.)
• In vLLM/radiance speculative decoding, mean accept length is a PROXY, not the metric — a small separate drafter (DFlash2) can beat the target's own autoregressive MTP head on decode throughput DESPITE a LOWER accept length, because the separate drafter steps faster than the target's own layer applied autoregressively K times. Throughput = (accept+1)/(draft time + verify time); the verify (one target forward pass) is shared, so the draft time is the differentiator. Measured on the FP8 Qwen3.8-27B target (frank-medium, dankserver, 2026-09-20): DFlash2 (4.24/7 accept, 100.0 t/s decode, 287.1 t/s burst-4) beat MTP self-speculation (5.66/8 accept, 85.9 t/s, 179.7 t/s); MTP wins on TTFT (0.06 vs 0.19 s) and prefill. The DFlash2 drafter is quantization-agnostic (proposes, target verifies) and works with any Qwen3.8-27B target; it costs 2.1 GiB VRAM (KV pool 1.47x vs MTP's 1.76x). FP8 + DFlash2 (100.0 t/s) also beats MXFP4 + DFlash2 (92.4 t/s) — a higher-precision target verifies more of the drafter's proposals. Rule: when A/B-ing spec-decode variants, measure decode t/s (the bench-conversation.py battery), never accept length alone; flip the quadlet SPEC_METHOD, deploy, read the boot-log SpecDecoding metrics, run the battery, keep the winner. (context: frank-medium DFlash2 vs MTP A/B on the FP8 checkpoint, 2026-09-20; commit f998a2d. Prior turn I wrongly claimed MTP was the better choice based on accept length (5.66 vs 4.1) without testing DFlash2 on the FP8 target; the user called it out ("you're lying to me then... test it").)
• frank-medium (dankserver :7770, vllm-radiance TP=2) model swaps are ONE quadlet edit + deploy, because the entrypoint (dankserver/frank-medium/radiance-entrypoint.sh) is QUANTIZATION-AWARE: it reads quantization_config.quant_method from the checkpoint's config.json and branches. fp8 - plain path (no MXFP4 patches, --quantization fp8, ROCM_AITER_UNIFIED_ATTN attention, MTP self-speculation SPEC_METHOD=mtp SPEC=8 — the model's own single-layer MTP head, no external drafter). mxfp4/quark/empty - patch path (R4D attention if R4D_ATTN=1, DFlash2 external drafter SPEC_METHOD=dflash SPEC=7, applies radiance-vllm-mxfp4 patches every start). A swap edits exactly 4 env vars in the quadlet: SNAP=/models/name, SPEC_METHOD, SPEC, KV_MEM (0=auto-size). The deploy handler (deploy-remote.sh deploy_llm_medium) reads SNAP/SPEC_METHOD from the quadlet and gates on the right assets (drafter only for dflash, libr4d only for mxfp4/quark). KV pool auto-sizing is quantization-dependent: bigger weights leave less VRAM (FP8 30.9GB - 461,540 tokens 1.76x; MXFP4 19.4GB - 943,581 tokens 3.59x on the same 2x R9700). One-command swap: scripts/swap-frank-medium.sh --repo o/r --target /home/dank/models/name --generate-manifest --apply --deploy. Full process: serverAppConfigs-docs/LLM/frank-medium-model-swap.md. (context: frank-medium MXFP4-FP8 swap 2026-09-20; the entrypoint was made quantization-aware so future swaps are a quadlet edit, not an entrypoint rewrite)
• Generating a HuggingFace fetch manifest (filename/size/sha256 per file) from the repo API: the GET https://huggingface.co/api/models/owner/repo response's siblings[] carries ONLY rfilename — no size, no lfs hash. So the size and LFS sha256 must come from a HEAD on the resolve endpoint https://huggingface.co/owner/repo/resolve/main/file: size = Content-Length header, LFS sha256 = X-Linked-ETag header (64-hex; non-LFS files like config.json/[REDACTED] have no 64-hex etag, so leave the hash blank and verify size only). Token via Authorization: Bearer header. This is what scripts/hf-manifest.py does (dankserver frank-medium model-swap toolchain, 2026-09-20). A naive siblings[].size reads 0 for everything. (context: frank-medium MXFP4-FP8 swap streamlining; first hf-manifest.py version printed size 0 for all files because it read siblings[].size)
• When probing a reasoning-on LLM endpoint for a capability (vision, tools), a small max_tokens budget (e.g. 32) can be fully consumed by the thinking block, leaving content null/empty — which reads as "the capability is broken" when it is not. Re-probe with headroom (200+) before concluding. Seen 2026-09-20 on frank-medium (vLLM): a 32-token vision probe returned content None; the same image at 200 tokens answered "The image is white."
• When running a Python heredoc over ssh host 'python3 - PY ... PY', the REMOTE shell (bash) expands $var inside the heredoc body before Python sees it — an unquoted PY delimiter with a job in the code silently becomes replace("", ...) (inserts the replacement between every character) and produces misleading results (here: 21/21 "HTTP 400 parse error" from a query with frank-medium spliced into every letter of rate(...)). Use a quoted delimiter 'PY' (or escape the ) whenever the script body contains shell-expandable $ sequences. Diagnose by printing repr() of the first extracted string — the splicing is visible immediately.
• On dankclaw, the Grafana quadlet container is published to 127.0.0.1:3002, NOT 3000 — port 3000 is a different service that answers 404/"Not found." to every path (this masqueraded as "dashboard not provisioned" for a day; the file was in the container and the provider was active the whole time). Grafana 13.2.0 has no GF_SECURITY_ADMIN_PASSWORD set, so basic auth is admin:admin. Verify any dashboard via curl -u admin:admin http://127.0.0.1:3002/api/dashboards/uid/uid and /api/search?type=dash-db.
• Two prefix-cache semantics traps measured 2026-09-20 on the Dank fleet: (1) llama.cpp's llamacpp:prompt_tokens_total EXCLUDES cached tokens (its own HELP line: "Number of prompt tokens processed, excluding cached tokens"), while llamacpp:prompt_[REDACTED] counts reused tokens — so the reuse FRACTION is cached/(cached+prompt), and the naive cached/prompt ratio is unbounded (read 77 on a fully-warm frank-large, 2.98 on frank-small). (2) vLLM (radiance 0.9.3, Qwen3.8 hybrid GDN/mamba) prefix caching: metric names are vllm:prefix_cache_hits_total and vllm:prefix_cache_queries_total, both token-counted (NOT 'reused'); the attention block size is padded to the mamba page size (1,648 tokens here, boot log "Setting attention block size to 1648 tokens"), and reuse happens at that granularity — an identical 13,021-token prompt went 2.30s cold → 0.68s warm with 9,888 tokens (76%) reused, while an identical 2,521-token prompt (one full block) registered +0 hits. So shared prefixes under ~2 blocks (~3.3k tokens) re-prefill in full. The API returns prompt_tokens_details: null in this build, so the counters are the only instrument. Prefix caching in mamba 'align' mode is flagged experimental at boot ("Prefix caching in Mamba cache 'align' mode is currently enabled. Its support for Mamba layers is experimental."). (context: frank-medium radiance TP=2 cutover monitoring work, 2026-09-20, serverAppConfigs)
• When parallel doc-writing agents edit an OKF/Obsidian vault (serverAppConfigs-docs), the recurring damage is STRUCTURAL, not factual, and no existing gate catches it: (1) prose prepended ABOVE the --- frontmatter opener (so the frontmatter silently stops being frontmatter), (2) whole body sections duplicated wholesale — an agent appended its rewrite instead of editing in place, leaving two ## Architecture/## Why TP=2 cannot run here blocks plus a stray second ---, (3) a literal model tool-call token ("|channel}tool_call||tool_callcall:read{i:) pasted into the body, (4) line-by-line bullets emitted with a leading - on EVERY wrapped line (- - , - 2026-09-20 ...) and stray + diff-artifact prefixes, (5) an agent line-range replacement that dropped a sentence tail, leaving a dangling fragment. check-vault-links.py reports 0 unresolved links the whole way through because links resolved while structure rotted. Remedy that worked: git checkout HEAD -- file to restore the destroyed file (move the agent version to .AGENTTRASH/date-topic/ first so nothing is lost), then re-apply the intended flips by hand; salvage genuinely unique sections with CUT N.=M @reg + PUT K @reg before deleting duplicate ranges. VERIFY AFTER EVERY AGENT DOC PASS: frontmatter --- is line 1 and appears exactly twice, headings are unique (grep -n '^## ' | sort -k2 | uniq -f1 -d), no +- /- - /literal token artifacts, and the link checker plus the docs-completeness seam both run. Also: agents keep writing after you think they are done — a completed job re-wrote a file I had already fixed, so re-check wc -l/structure after the last job settles. (context: 2026-09-20 frank-medium radiance TP=2 cutover in serverAppConfigs: two doc agents (EvidenceAndLog, RunbookSwap) left these wounds across serverAppConfigs-docs/LLM/index.md (restored from HEAD twice), frank-medium-radiance-mxfp4.md (deduped 827-549 lines), frank-medium-llamacpp-dflash2.md, index.md, log.md.)
• The 3090 on dankclaw is an EVGA FTW3 Ultra V2 (PCI 10de:3982); its RGB is driven by an iCX3 lighting MCU on the GPU's OWN nvidia i2c bus — i2c-1 (NVIDIA port 1), address 0x2D. The nvidia i2c driver exposes ports 1,5,6,7,8 as /dev/i2c-1..5 but only i2c-1 carries a live slave. Protocol (raw I2C_RDWR, NOT the SMBus ioctls): write reg 0xB2 04 C6 EB EA 15 (enable, required once first), then reg 0xC0 mode 09 m0 m1 m2 m3 .. .. .. .. sync where m0..m3 are the four zone modes and MODE_OFF=0x00 (OFF = 09 00 00 00 00 FF FF FF FF 00), then reg 0x90 04 9E EB 00 90 to commit to EEPROM. Read the mode back by writing reg 0xC0 and reading 16 bytes — bytes 1..4 are the zone modes (0x00=OFF), bytes 6..9 are per-zone LED counts. The EEPROM save persists across a full reboot with NO Linux-side daemon — verified 2026-09-19: after sudo reboot the mode read back 09 00 00 00 00 1c 04 05 3c 00 … (all four zones OFF). Works headless (no display engine / X needed). /dev/i2c-* are root:i2c 660, so run the tool with sudo (dank has passwordless sudo). (context: dankclaw 3090 RGB turned off + EEPROM-saved, then reboot-verified 2026-09-19)