Captures the full pipeline recipe (graft->quant->splice->config->serve) with every
gotcha found this session, the 3 gibberish suspects, and the diagnostic ladder
(validate native-config no-MTP coherence FIRST) for a fresh session to finish the
chase. Also stages the NVFP4 scripts + 512-row calib. Recent decisions: NEO-CODE
seat swap (R36), webhook ALLOWED_HOST_LIST fix. Lessons: validate-tracer-bullet-first,
mtp-graft-dropped-at-load, gitea-204-red-herring.
The ufw fix (prior commit) was necessary but insufficient. The DECISIVE blocker
was gitea webhook.ALLOWED_HOST_LIST = 'external, 10.100.0.0/16' (NH3 only) —
corviduo-dev is 10.250.50.152 (Anaheim), so gitea refused to deliver ('deny
10.250.50.152') and never opened the TCP connection. Fixed to 'external,
10.0.0.0/8' (whole fleet, matches the ufw choice) + gitea restart.
Listener now logs every delivery (source-IP/hmac_ok/ref/action) — the old
log_message=pass silence hid the whole failure. Proven end-to-end: real gitea
delivery -> hmac_ok=True, ref=main, 202 deploying -> green deploy.
render-verify caught it: Dvalin's calib tool_calls carry OpenAI wire-form JSON
string arguments, but the Qwen3.6 chat template does .items() on arguments (needs
a dict) → jinja TypeError. Parse string->dict in render_verify + the quant's
load_calib_chat. Confirmed: renders the exact qwen3_coder XML the seat emits
(prefixed bifrost.soong-lab.*, v0.3.13 generate_portrait, <think>, <tool_response>).
Extracted from the deployed backend (bifrost/tools.py) via the venv with a
capturing mock register_tool — the LIVE schema, not a stale copy. OpenAI-function
form for brokkr/Dvalin's ~128-row tool-call-XML calib slice (R36 #355 anchor).
The auto-deploy silently never worked: corviduo-dev's ufw is default-deny and
port 9010 was never allowed, so gitea's webhook deliveries timed out (DROP).
v0.3.6 was a manual deploy; v0.3.7-v0.3.13 never auto-deployed. The setup-time
'test-delivery 204' was gitea queuing, not the listener receiving. Fixed by
'ufw allow from 10.0.0.0/8' (operator-directed). Confirmed end-to-end.
R36 gate (2026-07-14) validated NEO-CODE ships on all axes: tool-calling 0.967
(attach_tool 1.00, 0 runaways — #355 eliminated), prose genre-artifact-fine
(less clichéd than gen), refusal uncensored-as-spec + CSAM-clean.
#355 root cause was MODEL-level, not the reasoning-budget-forcing bug: Deckard
emitted Qwen's native qwen3_coder XML tool format malformed -> llama.cpp leaked
the closing tags into the arg value -> Bifrost attach_tool schema error -> retry
-> reasoning runaway to max_tokens. NEO-CODE emits the same native format cleanly
on the same seat/parser -> no schema error -> no runaway. The fix was the model
swap; there was never a wrong parser (the XML is Qwen3.5/3.6-native).
- reasoning seat: Deckard-PKD (Qwen3.5) -> NEO-CODE=Heretic2-Thinking (Qwen3.6-27B) Q5
- samplers: card defaults (temp 1.0 / top_p 0.95 / top_k 20 / min_p 0.0), DRY dropped
- ctx: 256K max; custom llama.cpp kept (qwen3_coder parse + PR#25544 belt-and-suspenders)
- persistent-memory ACTIVE 1 marked resolved
soong-dev found the studio serving a stale web/ (52015 vs 55025 bytes — missing the
01-Role section, favicon, thinking-status): the deploy rsynced backend/ but never web/,
so SOONG_LAB_WEB_DIR stayed pinned to the initial manual copy while the backend updated.
Deploy now rsyncs BOTH backend/->studio AND web/->SOONG_LAB_WEB_DIR (read from the env)
on every green run. Verified: served frontend now 55025 bytes, current.
Per operator call (no gitea write token on the Worldtree-team VM): a 2-min systemd
--user timer on nh3-dev polls corviduo's last-deploy.json and pings soong-dev via
althing on a NEW red deploy (green stays silent). Delivers soong-dev's red-run
visibility without a credential on corviduo. Tested (red detect+format DRY, green quiet).
The char-rp-reasoning (Deckard) seat now runs llamacpp-charrp:custom-latest via a
new LLAMA_REASONING_IMAGE var (Magidonia char-rp stays on stock — no reasoning bug).
Fixes Worldtree #355 at the source (budget multi-terminator handles Qwen3.5's
<tool_call> reasoning end-tag). Live 2026-07-13: Deckard loads on Blackwell, serves
coherent, reasoning bounds at the 400 budget. Rollback via .env LLAMA_REASONING_IMAGE.
Durable record of the custom llama.cpp the char-rp-reasoning seat will run to
fix Worldtree #355 (reasoning-budget forcing broken in stock b8840 — single
end-tag </think> can't match Qwen3.5's <tool_call> reasoning terminator, so the
budget never force-closes and reasoning runs away to max_tokens). PR #25544
adds multiple terminating sequences; unmerged upstream, so we build it.
- build.sh: reproducible recipe (clone master@6eddde0 + merge PR #25544 +
resolve the 1 server-common.cpp conflict + CUDA build for Blackwell sm_120)
- README.md: why + acceptance test + rollback + REMOVE-WHEN-MERGED tracking
Image llamacpp-charrp:6eddde0-pr25544 BUILT + smoke-tested on ana-ml2; seat
swap pending. See also auto-memory reference_charrp_custom_llamacpp_pr25544.
Adds the rsync --link-dest hourly snapshot job (nh3-dev:~/development ->
nh3-nas, 48-snapshot retention, secrets/build-dirs excluded) that closes the
no-off-box-backup gap exposed by the 2026-07-12 working-dir clobber. Script
mirrors the live ~/.config/dev-backup/dev-backup.sh; runbook covers restore.
Point the in-page TTS at the zonos-gateway wrapper on irv-ml1:8890 (direct,
so streaming isn't buffered by LiteLLM): OpenAI-shape body (model: ext-tts,
input, voice), Cora default voice, float32@44.1kHz PCM decode. Quotes are
joined into a single stream call (prosody — no per-sentence chunking).
Migration regex rewrites stale saved endpoints (:8299/:8210, /tts[/stream],
:4000) to the new one.
New TTS service entry + reproducibility_audit row for the zonos-gateway
wrapper (irv-ml1:8890) — the ext-tts-aliased OpenAI facade over Zonos.
23 fields across Text&voice / Expression / Prosody / Quality / Sampling /
Output section groups; live voice dropdown from /v1/voices; response
format pcm|wav (audition UI forces wav). Distinct from the older down
zonos :8203 entry. jsonschema-validated.
The live gateway config has served char-rp-reasoning as deckard-pkd-27b (:8018)
since the 2026-07-08 A/B; the standalone doc had frozen on QwQ-RpR-v4. Corrects
seat 4 (backend + samplers + server-side DRY/reasoning-budget notes).
Also snapshots session state in persistent-memory.md: phantom-qwen verified
already-clean, ana-docker docker log-cap (logrotate copytruncate, no bounce),
and the granite→gen memory_extractor bind live on demo+personal.
Drop-in system prompt for an agent whose quoted output is voiced by mOrpheus: speak in
double quotes (only quoted text is voiced), phrase each quoted line as one coherent
utterance (per-quote prosody), and the sparse/boundary/no-stack tag rules (measured
stability on the early checkpoint). Lists the honored tag set.
Per-sentence chunking generated each sentence cold, flattening intonation/prosody that
spans the whole quoted line. Chunk by QUOTED SECTION instead — each contiguous quote is
generated whole (max_tokens 2400) so its prosody stays intact; multiple quotes in a reply
still play serially on the shared clock. extractQuotes already returns exactly these spans;
dropped splitSentences.
Split the quoted dialogue into sentences and stream each as its own short /tts/stream
request (max_tokens 900), queued back-to-back on one shared AudioContext clock (speechHead)
so playback is gapless and in order. First sentence starts fast; each chunk is short so it
generates cleanly (no ramble/cap risk); the next sentence generates while the current plays.
A newer reply supersedes via the ttsGen counter; 🔊 replays.
Browsers suspend the Web Audio AudioContext until a user gesture; speakQuotes fires on
reply-complete (no active gesture), so a suspended context played silently. Prime/resume
the context on any click or keydown (capture phase) so it's running before playback.
Server side was fine throughout (/tts + /tts/stream both 200 with valid audio).
- max_tokens default 2400->3500 (~42s) in wrapper + gateway-chat client, with a _cap()
clamp so prompt+gen never exceeds MAX_CTX (4096) — a cloning ref block is ~1100 tokens,
so an unclamped 3500 would overflow context on the clone path.
- Staged clone voices: /voices dir of <name>.wav + <name>.txt, each encoded to its Orpheus
reference block at startup; voice="<name>" zero-shot clones it. Beatrice (a chatterbox
reference) staged as the first normal-voice clone. GET /voices lists baddy + clones.
- compose: mount voices dir + pass MORPHEUS_MAX_LEN to the wrapper (clamp must match engine).
vLLM concurrency (measured, --max-num-seqs 8, 250-tok reqs): near-linear batching — 8
concurrent finish in the same ~2.8s as 1 (707 tok/s, 8.1x single, flat per-req latency).
Chunked-sentence production can fan out for ~8x throughput; CPU SNAC decode is the scale
bottleneck, not generation.
Cut-offs were the max_tokens=1200 ceiling (~14.6s of audio), not memory (~1250 tokens
<< 4096 context). Diagnosis: the repetition penalty is load-bearing for clean stops —
rep 1.0 => the model never emits end-of-speech and rambles to the cap; rep 1.1 (the
wrapper default) => clean natural stop. So normal lines already complete; only genuinely
long dialogue (>~14.6s, ~25+ words) hit the cap. Raised default + client max_tokens to
2400 (~29s), still within the 4096 context (no memory cost). Verified: a 49-word line
now finishes at 16.73s (was clipped at 14.6s).
Wrapper gains POST /tts/stream: reads the vLLM token stream, decodes SNAC in WINDOWED
CHUNKS (every 6 frames, decode [2 ctx | 6 | 2 ctx] and emit only the middle 6 — context
both sides => seamless), and streams raw PCM16 (24kHz mono) as it generates. Windowed
(not per-frame) because per-frame CPU decode's per-call overhead x ~60 frames serialized
to ~7s (RTF 2.2); windowed keeps up (RTF ~0.97). Whole-clip /tts kept for non-browser use.
gateway-chat plays the stream via the Web Audio API (fetch reader -> int16->float32 ->
scheduled AudioBufferSourceNodes on a running clock; a new reply supersedes the prior
stream via a generation counter; 🔊 replays). Measured: TTFA 0.80s (was ~4.5s whole-clip),
RTF 0.97, full-duration match. CORS already covers the new route.
Deployed: tts rebuilt on irv-ml1, page pushed to ana-docker.
Gateway-chat now auto-plays quoted text from each assistant reply through the mOrpheus
TTS endpoint. Sidebar gains a 🔊 toggle + endpoint/voice fields (persist in localStorage,
prefilled to irv-ml1:8299 / baddy). On reply-complete, straight and typographic double
quotes are extracted, joined, POSTed to /tts, and the returned WAV plays (click 🔊 to
replay; a new reply interrupts the prior clip).
Requires CORS on the wrapper (page served from ana-docker:8091 fetches irv-ml1:8299
cross-origin) — added CORSMiddleware(allow_origins=[*]) to the mOrpheus tts app (internal-
only endpoint). Verified end-to-end: preflight + POST return ACAO=*, valid 24kHz WAV.
Deployed: tts container rebuilt/recreated on irv-ml1; page pushed to ana-docker conf
(bind-mounted, live on next request).
The gen seat's vLLM served-name was still qwen3.6-27b-aeon, a stale skin
left over from the AEON-27B → 35B-A3B-heretic swap — it named neither the
right family (aeon) nor size (27b vs 35B-A3B). Renamed the served-name to
qwen3.6-35b-a3b-heretic (+ -thinking) on ana-ml2 :8015 via the stack .env,
and repointed litellm's gen / gen-reasoning / summarizer-large model refs +
comments to match, so /v1/models, the gateway config, and spend-logs all
reveal the actual model in the request path.
Verified end-to-end: gen -> 'PIPELINE OK', gen-reasoning -> content + reasoning
surfaced, all three aliases healthy. char-rp / char-rp-reasoning untouched.
dvalin confirmed the live A/B-proven set IS canonical for Deckard as a dark-RP reasoning seat:
temp 1.0/top_p 0.95/top_k 40/min_p 0.05, no presence/rep penalty, DRY 0.8 server-side. Endorsed
over the card's base-thinking (top_k 20/min_p 0/presence 1.5). No value change; comment + memory
record the confirmation + tuning ladder (flat->min_p 0.08, loops->DRY 0.9, over-damped->DRY 0.6/off).
Operator wanted a reasoning-RP model that tolerates DRY (RpR-v4 forbids rep/DRY -> a
1/30 loop tail). Ran the full A/B on brokkr's 30-prompt D1 suite (content-only, slop-scored):
- Deckard-PKD (Qwen3.5-27B, DavidAU creative tune) WON: 0/30 loops, 0/30 refusals, clean
managed reasoning (native Qwen3.5 <think>/enable_thinking), DRY-tolerant, ~57 tok/s,
runs on the base llama-swap b8840 image. -> now the char-rp-reasoning seat (:8018).
- RpR-v4: 0 refusals but 1/30 loop (no-DRY). Pantheon-27B: clean slop but 7/30 explicit
refusals + needs the newer ggml-org/llama.cpp image (Qwen3.6 won't load on b8840).
Snowdrop + Gembrain (Gemma-4): floored (llama.cpp can't manage their reasoning without
the vetoed template hacks). Losers kept on disk as alternates.
- char-rp (Magidonia) unchanged; gen unchanged. gateway char-rp-reasoning -> Deckard
sampler (temp 1.0/top_p 0.95/top_k 40/min_p 0.05; DRY server-side).
dvalin-smithy offered a follow-up sampler pass for char-rp / char-rp-reasoning after
they accumulate real Worldtree/SillyTavern character-role traffic. Parked as a future
option (thread 01KX1DS6...) — nothing to tune until there's live-session data.
char-rp -> TheDrummer Magidonia-24B-v4.3 Q6_K (Magistral prose, ~65 tok/s,
zero refusal, tight POV) via llama.cpp (:8016).
char-rp-reasoning -> ArliAI QwQ-32B-RpR-v4 Q5_K_M (abliterated managed reasoning,
~52 tok/s, reasoning surfaces in reasoning_content) via llama.cpp (:8018).
- New canonical stack stacks/char-rp-gguf/ (llama-server x2, GPU0-pinned, ~86/97G
co-resident with gen). GGUF sidesteps the vLLM-NVFP4 + Mistral-tokenizer traps that
killed the Angel serve. Never Ollama.
- Best-of-breed per seat: no single dense 24-32B is both an elite non-thinking prose
seat AND a clean managed-reasoning seat on llama.cpp (Magidonia [THINK] boundary is
loose; Cydonia-R1 <think> runs away; QwQ is template-managed). Pantheon-Reasoning-27B
stays rejected (re-censors in <think>; RpR-v4 abliterated reasoning is the fix).
- Gateway rewired: char-rp->:8016, char-rp-reasoning->:8018, Mistral/QwQ samplers,
dropped the Qwen enable_thinking kwarg. One-model Magidonia fallback documented.
- Retired the ms32-24b-angel stack.
comfy-dev's explicit-over-implicit call: arbo now sends train_id, so the
worker no longer derives the loras/trained/{train_id}/ namespace from
output_dir.parent (which coupled it to arbo's handoff layout). train_id is
optional + path-safe-validated; when present it wins, else the path
derivation remains as the fallback. Wired through TrainRequest ->
validate_request -> published_relative_path -> _publish_lora. 18 tests green.
On a train reaching succeeded, IN ADDITION to output/{name}.safetensors
(unchanged download source), COPY it into ComfyUI's loras search path at
/storetank/arbo/models/loras/trained/{train_id}/{name}.safetensors and
return published_lora_name (the ComfyUI-relative LoraLoader string) in the
terminal GET /train/{id} payload (arbo Phase 2 auto-registration, §4.1/§7).
- Copy not move; a publish failure NEVER fails the train (keeps succeeded,
omits published_lora_name, logs the reason to the tailable run log).
- INV-T7-safe: a copy to a fixed computed path, no new free-form args.
- train_id derived from the handoff layout (output_dir.parent.name).
- Provisions loras/trained/ (arbotrain 2775, group-write per the Phase-1
lesson; world-readable/traversable for ComfyUI) via the deploy playbook.
- ComfyUI verified to resolve nested loras subfolders (no flat fallback).
- Pure path helper unit-tested; 16 tests green.
The first real arbo train 422'd: SDXL checkpoints live at
/storetank/arbo/models/checkpoints/ (the 2026-06-13 move to the 1.8TB
/storetank volume), which wasn't in ALLOWED_MODEL_ROOTS — the old roots
predated the move (/worktank/models is gone, /worktank/comfyui host path
is empty; ComfyUI mounts /storetank/arbo/models -> /basedir/models inside
its container). Allowlist /storetank/arbo/models (llmuser-readable,
world-readable tree), drop the two stale roots. Regression test added (15 green).
comfy-dev cross-check: Sindra v1/v2 used alpha=dim/2 (0.5 LoRA scaling),
which produced the validated likeness; the initial alpha=dim (1.0) was a
stronger, unvalidated default. Align the default to the proven value
(operator/per-request can still override). Tests updated (14 green).
Host service (runs as llmuser, owns /opt/fluxgym + GPU access) that runs
sd-scripts SDXL LoRA training on demand for arbo — the infra-ops half of the
in-arbo LoRA training Phase 1 ownership split (vh/arbo
docs/contracts/in-arbo-lora-training-phase1.contract.md §4.1/§2).
- Fixed-invocation only (INV-T7): bounded params -> one sd-scripts command
shape; every param range/allowlist/path-containment checked before spawn;
bad request = 422, never a silent downgrade. 14 unit tests green.
- Thin supervisor: never imports torch; subprocesses the fluxgym venv's
accelerate. 1-job-at-a-time (arbo lease is the serializer, 409 is backstop).
Durable job records + boot reconciliation (§4.3).
- API: POST /train, GET /train/{id}[/log], POST /train/{id}/cancel,
GET /gpu-status (per-device VRAM + tts_on_3090 co-OOM signal), GET /healthz.
- Wire-shape (§7 resolved with comfy-dev): shared /worktank/arbo/train handoff
(group arbotrain, setgid 2770); worker binds 0.0.0.0:8203, arbo reaches via
host.docker.internal:host-gateway (reachability proven on 172.20.0.1:8203);
device-aware TTS steering via /gpu-status.
Deployed to irv-ml1 via playbooks/deploy-lora-training-worker.yaml (elway,
idempotent); systemd unit active; /healthz + /gpu-status verified live.
- gen := AEON dual NVFP4 serves (vLLM 0.24 + LiteLLM v1.91.0); reasoning-trace bug
was the LiteLLM shared-config mutation, fixed durably via distinct -thinking served-names.
- Worldtree personal character/thoughtful-character repointed to char-rp/char-rp-reasoning.
- LitBench-RM torn down, comfyui restored on irv-ml1.
New stacks/qwen36-27b-aeon: two co-located vLLM serves on ana-ml2 GPU0 —
gen (:8015, MTP off) and an RP seat (:8016, native MTP) — dense Qwen3.6-27B
(qwen3_5 GDN-hybrid, uncensored/abliterated), ModelOpt-NVFP4, multimodal,
256K context, depends_on-sequenced util split (~0.50/0.45). Each serve
carries a base + `-thinking` served-name so the `-reasoning` gateway records
target distinct LiteLLM deployments — otherwise a thinking-off request mutates
the shared litellm_params and clobbers enable_thinking (the shared-config
footgun that silently disabled char-rp-reasoning).
Gateway (stacks/litellm/conf/config.yaml): gen / gen-reasoning /
summarizer-large -> AEON :8015; char-rp / char-rp-reasoning added -> RP seat
:8016 (Qwen-RP sampler recs); gen-reasoning -> `-thinking`, char-rp-reasoning
-> `-rp-thinking`. Retired qwen3.5-122-a10b[-reasoning] + qwen-large[-reasoning]
(qwopus displaced; those named a 122B that no longer serves gen).
Probed live vs z.ai 2026-07-05: glm-5.2 = 1,048,576-token (1M) input context,
131,072 (128K) max output; no gateway-side cap (pure z.ai passthrough). Comment-only,
no runtime effect.
R30 b15-b17 removed mood.decay_rate/mood.stale_hours from canonical (OCEAN
wall-clock OU replaced per-turn decay); deployed /opt/worldtree*/config
bind-mounts still carry them, harmless (CharacterSchema.mood is dict[str,Any]).
Tracked as an opportunistic edit-only/no-restart cleanup to restore byte-identity;
noted new optional mood.tau_base (unset->derived). Config-delta acked to worldtree-dev.
Records Vuong's 2026-07-02 call closing the granite-efficacy thread: no
intermediate real-efficacy granite spike (uninterpretable proxy — arch
gap + abliteration axis), efficacy validated on the real T1 run. Notes
the LitBench-less data/judge WIRING check as the correct pre-T1 de-risk
IF one is ever wanted, and that infra's remaining owed item is the queued
swappable-LoRA-on-NVFP4 load test (gated on the first T1 adapter).
The granite-8b harness spike proved the TRL SFT->DPO->eval seam (incl. the
in-loop HoldoutEvaluator base-vs-adapter leg) runs end-to-end, but used a
12-row/12-pair synthetic writing fixture — NOT the E-RP corpus — so the
~0 anti-slop delta (-0.002) is the expected null, not an efficacy signal.
Adapter reaped; nothing to A/B. Real behaviour-shift efficacy is a T1-run
question. Sharpen both the T1 in-flight bullet and the Recent-decisions
entry so 'green' no longer reads as efficacy-validated.
Displaced qwopus-122B on ana-ml2 GPU0:8013 with robbatt/Qwen3.6-40B-Deckard-NVFP4
(stock vLLM 0.23.0, loaded clean: hybrid attn + multimodal + fp4_gemm all green).
Repointed the 5 role aliases (gen, gen-reasoning, qwen-large, qwen-large-reasoning,
summarizer-large); added the qwen3.6-40b-deckard true-name record; left the true
names qwen3.5-122-a10b[-reasoning] to 404 (no-false-alias). Operator-directed
trial-by-fleet-traffic; revert path in the config banner + live backup
config.yaml.bak-pre-deckard-20260701-001036.
Add §9 "PFI LiteLLM Gateway — Deployed Sampling Defaults": the live fleet
sampling table (granite/qwen/judges/GLM) with provenance, overrideable-default
semantics, the GLM API-accepted-subset caveat, and the research-confirmed temp-0
rationale for granite + image-judge. Accepts the dvalin-smithy-dev recommendations
as deployed. §§1-8 vendor reference left intact.
dvalin evidence pass: IBM canonical is temp 0; greedy-loop risk is an
open-ended-generation phenomenon, not summ/classify; temp 0.1 reduces
classification reproducibility without fixing loops (use repetition/presence
penalty if loops appear). image-judge stays 0 (Qwen judge card + W&B judge
practice = temp 0 for reproducibility; NVFP4-needs-0.1 unsupported). Both
gateway temps now 0, vendor-canonical.
Operator call: avoid pure-greedy rigidity/loop-risk on granite summ/classify
while staying near-deterministic; matches the house nonzero-temp-floor lean.
image-judge held at temp 0 (scoring reproducibility) pending operator review.
- granite-4.1-8b (+ summarizer/classifier): temperature 0 (IBM vendor-canonical
"temp 0 for inferencing"; top_p/top_k no-ops at temp 0, omitted). Deterministic
baseline for summ/classify; creative callers override.
- GLM family (z.ai cloud): temperature + top_p 0.95 only (the ONLY params z.ai
chat API accepts per its OpenAPI schema; top_k/min_p/penalties absent -> not set).
temp 1.0 for glm-5.1/5.2/5-turbo/4.7 + gen-frontier; temp 0.6 for glm-4.5-air.
Matches z.ai API defaults -> explicit-over-implicit, future-proofs vs vendor drift.
Round-2 dvalin-researched (provenance-labeled), verified live, granite+glm smoked 200.
Embeddings/rerankers excluded (no sampling). Fleet-wide canonical-defaults sweep complete.
The abliterated/NVFP4 Qwopus 122B "gen" model (+ qwen-large / summarizer-large
aliases) had no repetition control in its sampling defaults, causing degenerate
repetition loops. Add presence_penalty: 1.0 (Qwen-documented anti-repetition
lever, range 0-2) to all 7 qwen3.5-122-a10b gateway records. Overrideable
default; bake into the vLLM serving def once the value is validated.
Native-allocator expandable segments to cut Qwen-Image-Edit fragmentation
OOMs on the A6000 (a ~2 GB alloc failing with 1.75 GB free while 45 GB sat
allocated + reserved-but-unallocated). Cache-preserving — packs better
without unloading the checkpoint, so no edit-latency hit. Paired with the
existing --disable-cuda-malloc (incompatible with cudaMallocAsync).
Deployed + recreated on irv-ml1; verified env present, PyTorch reads it,
container healthy. comfy-dev request 2026-06-25.
Langfuse's ClickHouse member spewed ~94 GB of unrotated logs and filled ana-docker's
root disk (took the fleet host to 100%, 28/48 containers unhealthy). Its trace UI was
redundant with LiteLLM's native logging — store_prompts_in_spend_logs:true already
captures full prompts/responses/tokens/cost/latency at :4000/ui — and nothing used its
unique trace-grouping/eval features (it only received flat gateway success_callbacks).
Removed the callbacks (gateway observability stays fully native) and tore down the
6-container langfuse stack + volumes on ana-docker. Re-add the callbacks if it returns.
Capability aliases for the PAID frontier tier, mirroring glm-5.2 / glm-5.2-
reasoning (thinking off / on) → openai/glm-5.2 @ z.ai. Worldtree binds these for
a frontier-grade generation/reasoning capability so the backing frontier model
can be swapped gateway-side (operator jump-started WT's request). PAID: only
all-proxy-models / explicitly-scoped keys reach them; the free all-agents-local
key stays fenced off z.ai spend. Verified both resolve + route to GLM 5.2.
llama-swap (ana-ml2:9292) is decommissioned (:9292 confirmed down), so the
catch-all wildcard routed every unmatched / typo'd / stale model name to a DEAD
backend, surfacing a misleading "Connection error" instead of a clean
"model not found". This is the exact footgun that silently swallowed Worldtree's
defunct model names (mistral-small-4 etc.) instead of erroring. Removed (operator
call) so unknown models now 404 loudly. Verified: gateway healthy post-restart,
a bogus model name now returns a clean not-found error, real aliases (gen) still
serve. Re-add explicit per-model entries if a swappable zoo ever returns.
Stand up the gateway-side capability aliases for the role→capability model
indirection (worldtree-dev's transparent-swap direction; operator: no wt-
prefix, reuse the existing summarizer/classifier/gen alias convention).
- chat-judge -> selene-1-mini-8b (mode chat) — WT selene-judgment role.
- reranker -> qwen3-reranker (mode rerank) — generic name for the cap.
- scalar-judge -> Skywork-Reward-V2 via a pass_through_endpoint to ana-ml2:8003
(LiteLLM has no reward/pooling MODE, so it's a passthrough, gateway-key-gated;
consumers hit /scalar-judge/<route> e.g. /score|/pooling|/classify).
Deliberately NO generic `embedding` alias: embedding vectors are model-specific
(not swap-transparent), so that capability stays `qwen3-embedding` — the model-
specific name is the guardrail against treating it as freely swappable. Verified
all three live (chat-judge 200, reranker present, scalar-judge passthrough 200
returning a Skywork reward). Deployed + gateway health-gated.
Empirical follow-up to the streaming /tts smoke test on the 3090. OmniVoice
is diffusion: a ~fixed per-call overhead (~1.5s at 32 steps, ~0.7s at 16)
dominates regardless of chunk length, so the upstream-claimed 40x RTF does
NOT hold here (measured ~2.8x/32-step, ~5.6x/16-step) and the chatterbox-
tuned scheduler over-chunks and starves.
- Streaming /tts defaults to num_step=16 (TTFA ~1.5s -> ~0.7s); batch
/v1/audio/speech stays num_step=32 for quality. Per-request override intact.
- Scheduler prior raised to rtf_prior=20 (env OMNIVOICE_STREAM_RTF_PRIOR,
wired through compose + .env.example) so it packs whole-text-minus-first-
sentence into a few chunks: validated ~3 chunks, no starvation, total wall
~= one-shot, less per-chunk silence padding.
- Docs corrected: the "sub-second / 40x" claims were wrong; streaming has a
diffusion TTFA floor (~0.7s) and wins mainly on long replies. chatterbox-
fast (autoregressive, ~0.5s TTFA) stays the lowest-latency front-end;
OmniVoice is the multilingual / voice-design complement.
Add a live-consumer streaming path and text sanitation to the OmniVoice
wrapper, so it can front speech-to-speech chat engines (not just the
asset-engine's batch WAV use).
- POST /tts: chunked 24 kHz mono s16le PCM (or open-ended WAV), driven by
the adaptive buffer-ratchet scheduler. Emits the first sentence
immediately, then ratchets chunk size up on OmniVoice's ~40x realtime
headroom -> sub-second time-to-first-audio. Wire-compatible with
chatterbox-fast /tts (both 24 kHz mono PCM). Batch /v1/audio/speech is
unchanged for asset/file callers.
- scheduler.py: VENDORED byte-faithful copy of chatterbox-fast's pure-
Python (torch-free) scheduler, pinned to commit 7631462 (v0.1.0/v0.1.1).
Vendor-copy over a shared package (operator call 2026-06-19): the module
has no GPU deps, so reuse it without dragging chatterbox-fast's torch
tree into this image. Promote to a shared package only on a 3rd consumer
or real drift.
- sanitize.py: language-safe TTS sanitizer run on both endpoints. Strips
markdown, <think> blocks, HTML, and model control tokens; deliberately
SKIPS the fork's English-only number/phone normalization that would
corrupt OmniVoice's 600-language input. Preserves [laughter]-style tags.
- Refactor: shared GenParams base for SpeechRequest + TTSStreamRequest;
single GEN_LOCK serializes generation (single-stream interactive).
- Dockerfile/playbook: copy + upload the two new modules; build-time
`import app` smoke; correct stale "Gradio demo / no FastAPI" comments.
9 Recent decisions + 6 Tried-and-abandoned (dates [2026-06-14]/[2026-06-15]) moved
non-destructively to archival-memory.md, each stamped _Archived 2026-06-19._. Kept
the active [2026-06-14] 'migrate ALL infra access to Claude-specific credentials'
standing directive. Back-ref counts: Recent decisions 79->88, Tried-and-abandoned
70->76. persistent-memory.md 397->363 lines.
Stands up tools/gateway-chat.html as a permanent URL on ana-docker (http://10.250.50.70:8091)
via a tiny nginx:alpine static container (no GPU, no DB). conf/index.html is a deployed
mirror of tools/gateway-chat.html (re-sync one-liner in README). Homepage tile + tnet per
convention. The enhanced tool (auto-discovers /v1/models, system prompts, streaming +
reasoning, image upload for vision) is now always-on for smoking new gateway models.
Duplicate-entry aliases. classifier -> granite-4.1-8b (:8004, same backend as the
existing summarizer alias). summarizer-large -> gen/qwen3.5-122-a10b (:8013, thinking
off) for heavier summarization on the 122B Qwopus. summarizer -> granite already
existed (no-op). Config-staged + deployed without bouncing the gateway; like any
config-add these activate on the next restart (no live-add performed).
Model field now pulls /v1/models (the ↻ control; new gateway models just appear)
instead of a hardcoded stale list; 📎 attaches an image (base64 data: URL in
image_url content) so the multimodal models (Qwopus, image-judge) can be smoked.
Static-verified (JS syntax + element-id consistency); headless smoke was blocked
by a shared-browser version skew in /opt/ms-playwright, not a tool defect.
Source + deployed config cleaned without bouncing the gateway. NOTE: these were
config-loaded models, which the /model/delete API can't remove (DB-only -> 'not
found in db'), so the LIVE gateway still serves them until its next restart, at
which point the cleaned config drops them. No bounce performed.
Same Qwopus gen model as gen / gen-reasoning (served-name qwen3.5-122-a10b @
:8013, thinking off/on respectively), but each bakes a dummy 'noop' function tool
+ tool_choice:none into litellm_params so a NON-EMPTY tools array always reaches
vLLM — for consumers where the global strip_empty_tools hook isn't the right fix
(they need a valid tools structure present, not stripped). tool_choice:none means
the noop is never called. api_base = the real LAN endpoint http://10.250.50.54:8013
(the requested http://vllm:8000 template wouldn't resolve from the ana-docker
litellm container). Verified: gen-nt + gen-reasoning-nt both survive a client
tools:[] send; noop never invoked; reasoning split intact.
Replaces the bjk110 text-only qwen3.5-122b as the `gen` model on ana-ml2 GPU 0.
OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destilled-abliterated-NVFP4 — Kimi-
distilled, abliterated, NVFP4, and crucially VISION-INTACT (serves as plain
multimodal, no text-only patch). Served as qwen3.5-122-a10b so the litellm
gen / gen-reasoning / qwen-large records route here unchanged.
Tuned for full native context on the 96GB Blackwell:
- stable vLLM image + fp8 KV → 11GB pool = 870,014 tokens = 3.32x concurrency
at the full 262144 (256K) window. Nightly+turboquant-4bit was unnecessary.
- CUDA graphs ON (no --enforce-eager) → 92.7 tok/s warm single-stream.
- util 0.95 + PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True — 0.96 OOM'd by
0.1GB on the 3.09GB FusedMoE transient workspace (the hard floor; defrag
reclaims the 4.2GB fragmentation, 0.95 adds margin).
- max-num-seqs 16 (short reqs fan out ~16x32k; 256K reqs pool-limit to 3.32x).
- text + image + video all enabled; tool-calling via qwen3_coder (XML), verified.
gen/gen-reasoning tool-calling 400'd (operator + brokkr's capability battery both caught it):
the bjk110 serve command shipped --reasoning-parser qwen3 but no tool flags. Qwen3.5 emits XML
tool calls (<tool_call><function=NAME><parameter=K>V</parameter></function></tool_call>), NOT
Hermes JSON — so `hermes` mis-parsed to raw text; `qwen3_xml` is the correct parser. Reasoning +
tools coexist (gen-reasoning keeps its thinking split). Verified live: a get_weather request
returns tool_calls=[get_weather {"city":"Paris"}].
vh