ext-tts / tts-1 / tts-1-hd / gpt-4o-mini-tts (all openai/zonos) were pinned to
irv-ml1's pre-move address 10.100.79.3:8198, dead since the 2026-09-06 headscale
cutover to 10.6.110.50 — so ext-tts through the gateway hung. Reported by
tts-dev/svos-dev.
The 4 aliases are DB-backed (store_model_in_db), so their api_base was updated
via the admin API to the DNS name http://irv-ml1.nh3.internal:8198/v1 (not a
fresh IP — that just re-arms the trap on the next move). The container cannot
resolve *.nh3.internal via split-horizon DNS, so this adds an extra_hosts entry
mapping the name to 10.6.110.50. Verified: container resolves the name and a
live ext-tts/sindra call returns 200 + valid MP3.
The gen-reasoning seat accepts only xhigh/medium/low and 400s on anything
else — including `high`, which is the default of several clients, so the
seat presented as broken rather than as one enum value out of step. The
DeepSeek Harness failed every request on its default setting, and the only
working client value was `low`: the seat's WEAKEST reasoning tier, while
its own default is xhigh.
conf/reasoning_effort_map.py is a pre-call hook in the same shape as the
existing strip_empty_tools hook. It is scoped to one model group, measured
rather than assumed: gen-reasoning rejects `high`; gen, sec,
char-rp-reasoning and summarizer all accept it and are left alone. Paid
passthroughs were not probed, because probing them spends vendor credits,
and are not mapped.
Verified after deploy: high and max now succeed on gen-reasoning, low and
xhigh still work, a request with no effort param still works, `gen` with
`high` still passes through unmapped, and the harness completes a real
file-edit task at full reasoning.
Needed a compose change as well as a conf push — callbacks are bind-mounted
per file, so the volume only attaches on container create. Recreated the
litellm service by name so the DB was not bounced with it.
The Heid panel plan uses Kimi's coding endpoint, not the general Moonshot API.
kimi-k3 now → openai/k3 @ https://api.kimi.com/coding/v1 (KIMI_CODE_API_KEY,
Vivace); the original general-endpoint entry is kept as kimi-k3-gen-api
(api.moonshot.ai, MOONSHOT_API_KEY). Both verified live through the gateway.
Same k3 constraints on both: temperature MUST be 1 (else 400), reasoning model
(reasoning_content vs content, needs adequate max_tokens).
Adds model_name kimi-k3 → openai/kimi-k3 @ https://api.moonshot.ai/v1
(OpenAI-compatible), keyed by MOONSHOT_API_KEY (compose env + .env.example
placeholder; real key on server only). Verified live through the gateway.
Two Moonshot constraints captured in the config comment + pinned: K3 accepts
ONLY temperature=1 (else 400), and it is a reasoning model (CoT in
reasoning_content, answer in content — needs adequate max_tokens or content
returns empty). Model id confirmed via /v1/models.
Move the ~22-service flat "AI Systems" group off the Main tab into a new
four-tab layout (Main / AI / Infrastructure / Toolchain). The AI tab sorts
the inference fleet by function into seven groups:
AI - Inference gen, char-rp, char-rp-reasoning, Granite summarizer
AI - Eval & Retrieval Selene, Skywork Reward, Qwen3 rerank/embed, image-bench
AI - Gateways & Chat LiteLLM, Asset Engine, Gateway Chat, Open WebUI, ...
AI - Speech (TTS) Chatterbox Fast, Kokoro, mOrpheus
AI - Audio Tools Parakeet ASR, YT Voice Clipper
AI - Image & Media ComfyUI, Arbo
AI - Dormant stopped rollback seats + retired auditions
Relabel each stack's homepage.group so canonical stacks/ matches the live
containers on ana-ml2, ana-docker, and irv-ml1. Dormant stacks were refreshed
with `docker compose up --no-start` so they carry the new label while staying
stopped (compose-start rollback preserved). settings.yaml drives tab/order/
columns; services.yaml and README updated to the new scheme.
vLLM's OpenAI server 400s on an empty tools array ("tools must not be an
empty array"), which broke every gateway call carrying tools:[] (clients
that send it to mean "no tools" -- OpenAI tolerates it, vLLM does not).
drop_params doesn't help: it drops unsupported PARAMS, not empty VALUES.
Add a CustomLogger async_pre_call_hook (conf/strip_empty_tools.py) that
pops an empty/None tools field (+ orphaned tool_choice) before forwarding,
registered globally via litellm_settings.callbacks so it covers every
vLLM-backed model, not just mistral-small-4. Mounted at
/app/strip_empty_tools.py beside config.yaml (LiteLLM resolves callbacks
relative to the config dir). Surgical: only fires when tools is present
and empty; real tools pass through untouched.
Verified on live gateway (1.87.0): mistral-small-4 and granite-4.1-8b
with tools:[] now 200 (were 400); no-tools baseline unchanged; a real
tool still passes through.
Adds explicit gateway entries for the four z.ai GLM models (glm-5.1,
glm-5-turbo, glm-4.7, glm-4.5-air) routed to api.z.ai with Z_AI_API_KEY,
plus the compose env passthrough + .env.example doc. Explicit entries
win over the llama-swap wildcard (distinct IDs, no collision). Extends
the gateway's unified logging to cloud inference, not just local
vLLM/llama-swap.
Cost note: paid API — only gateway-keyed callers reach these, but calls
spend z.ai credits (documented in config + compose comments).
LiteLLM proxy fronting the vLLM services on ana-ml2 so every request +
response is captured and inspectable in a browser Logs UI — the
visibility vLLM itself lacks (Dozzle shows only connection metadata).
- compose: litellm (proxy + /ui Logs) + litellm-db (Postgres store)
- conf/config.yaml: routes phi4-mini (chat, :8004), qwen3-embedding
(:8001), qwen3-reranker (:8002); store_prompts_in_spend_logs persists
full prompt/completion text. reward classifier (:8003) stays direct
(no first-class LiteLLM route).
- Langfuse-ready: lean first cut intentionally skips Langfuse's heavy v3
stack; graduating is one env-var + callback step, no re-architecture.
- roadmap: mark the vLLM-observability item's first cut as shipped.
Lean first cut of docs/roadmap.md "Observability for the vLLM stack".
vh