vh
3132a16ca0
Every fv-ml1 link on the Homepage dashboard was broken. Measured against the
live dashboard API before the fix: 16 entries pointing at the dead 10.250.50.54
and zero at the live 10.251.50.54, covering gen, M.O.G.-SEC, Scriberr, Embed,
Rerank, Reward, Coder, Dockge and six dormant seats.
The miss was structural, not careless. fv-ml1-rename-sweep.sh works from an
allowlist assembled from files that mention the HOST, and a homepage.href label
mentions only an IP -- so every stack whose sole stale reference was a label
fell outside it. The allowlist now covers those 24 files, and records how to
derive the list next time (grep the old address, subtract history) rather than
enumerating from memory.
History is still untouched, and the exclusions are now written down with the
reason each one keeps the old address: recorded benchmark results, whose
base_url is part of a measurement's provenance; the one LiteLLM comment
preserving a retired hand-test endpoint; and the cutover runbooks, where the old
address is the subject matter.
Two bugs found while applying it, both fixed here:
- deploy-stack.sh rejected any stack name containing a dot, so qwen3.5-122b,
qwopus3.5-122b and mistral-medium-3.5 could not be deployed by the script at
all. The check exists to stop path traversal, which means rejecting ".." and
"/" -- not every dot. Traversal is now rejected explicitly and tested.
- stacks/scriberr/.env.example allowed CORS only from the dead IP and from
scriberr.ana.internal, which no longer resolves; the box is at the fv site
and DNS already carries scriberr.fv.internal. The live .env had both stale
origins, i.e. an allowlist with nothing reachable in it.
Host side, applied separately: canonical pushed for the 16 stacks whose only
difference from the host was this renumber, and an in-place address-only fix for
the nine whose host copy has genuinely drifted or has no canonical copy, so that
drift survives for a deliberate reconciliation instead of being clobbered. Every
compose.yaml on fv-ml1 now reads 10.251.50.54. The labels themselves only take
effect at container creation, so the running containers still need recreating.
109 lines
4.3 KiB
YAML
109 lines
4.3 KiB
YAML
# qwopus3.5-122b — OpenYourMind/Qwopus3.5-122B-A10B-Kimi-K2.6-destilled-abliterated-NVFP4
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# on fv-ml1 GPU 0, REPLACING the bjk110 text-only qwen3.5-122b as the `gen` model
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# (operator 2026-06-19: "already ablated, already quanted, vision tower intact").
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#
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# Qwen3.5-122B-A10B MoE, Kimi-K2.6-distilled + abliterated, NVFP4 — and crucially
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# VISION-INTACT (Qwen3_5MoeForConditionalGeneration + vision_config). So it serves as
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# plain MULTIMODAL (no text-only patch, unlike the bjk110 checkpoint which had its
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# vision weights stripped). vLLM carries the arch natively.
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#
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# Served under --served-model-name qwen3.5-122-a10b so the existing litellm records
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# (gen / gen-reasoning / qwen3.5-122-a10b[-reasoning] / qwen-large[-reasoning]) route
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# here UNCHANGED — the operator's "replace those records with this model". The thinking
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# split (chat_template_kwargs.enable_thinking) + tool-calling (qwen3_coder — the
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# OpenYourMind card's specified parser for this checkpoint's XML tool calls).
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#
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# REVERT: down this; the bjk110 qwen3.5-122b stack is still staged.
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# Tunables in .env.
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name: qwopus3.5-122b
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services:
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vllm-qwopus35-122b:
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image: ${QWOPUS_IMAGE:-vllm/vllm-openai:latest}
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container_name: ${QWOPUS_CONTAINER_NAME:-vllm-qwopus35-122b}
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restart: unless-stopped
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ipc: host
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ports:
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- "${QWOPUS_PORT:-8013}:8000"
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volumes:
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- /tank/aimodels/huggingface:/hfcache
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- /tank/aimodels/qwopus3.5-122b-nvfp4:/model:ro
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environment:
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- HF_HOME=/hfcache
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- HF_HUB_CACHE=/hfcache/hub
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- VLLM_API_KEY=${API_KEY:-}
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# Reclaims PyTorch's reserved-but-unallocated fragmentation (4.2GB was stranded at
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# util 0.96, starving the FusedMoE workspace → OOM by 0.1GB). Lets the 3.09GB MoE
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# workspace allocate cleanly. Same knob the bjk110 qwen3.5-122b stack ran.
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- PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
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command:
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- /model
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- --served-model-name
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- ${QWOPUS_SERVED_NAME:-qwen3.5-122-a10b}
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- --host
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- 0.0.0.0
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- --port
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- "8000"
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- --gpu-memory-utilization
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- ${QWOPUS_GPU_MEM_UTIL:-0.92}
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- --max-model-len
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- ${QWOPUS_MAX_MODEL_LEN:-131072}
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- --max-num-seqs
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- ${QWOPUS_MAX_NUM_SEQS:-8}
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- --max-num-batched-tokens
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- "32768"
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- --trust-remote-code
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- --dtype
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- auto
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- --enable-prefix-caching
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- --enable-chunked-prefill
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# FULL 256K context on the STABLE image. fp8 KV (near-lossless) measured an 11.8GB
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# pool = 934,600 tokens = 3.5x concurrency at the full 262144 window. CUDA graphs ON
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# (no --enforce-eager) for decode tok/s. BINDING LIMIT = the FusedMoE transient
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# workspace (3.09GB, allocated OUTSIDE vLLM's budget into free VRAM): at util 0.96
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# only 2.99GB was free → OOM by 0.1GB, worsened by 4.2GB PyTorch fragmentation.
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# FIX = expandable_segments (env above, reclaims the fragmentation) + util 0.95 for
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# margin. The card can't go to 0 free — this workspace is the floor. video kept
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# ENABLED (operator wants it; banked at util 0.95 with headroom) — the video encoder
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# profiling eats into the budget so KV concurrency drops some, but stays well above 2x.
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- --kv-cache-dtype
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- ${QWOPUS_KV_CACHE_DTYPE:-fp8}
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- --limit-mm-per-prompt
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- '{"image": 2, "video": 1}'
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# reasoning split + tool-calling. The OpenYourMind card specifies qwen3_coder
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# as the tool-call parser for this checkpoint (Qwen3.5 XML tool-call format).
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- --reasoning-parser
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- qwen3
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- --enable-auto-tool-choice
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- --tool-call-parser
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- qwen3_coder
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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device_ids:
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- "${QWOPUS_GPU_ID:-0}"
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capabilities:
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- gpu
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healthcheck:
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test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
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interval: 30s
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timeout: 10s
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retries: 3
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start_period: 900s
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networks:
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- tnet
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labels:
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- homepage.group=AI - Dormant
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- homepage.name=Qwopus3.5-122B-A10B (abliterated NVFP4, vision)
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- homepage.icon=mdi-creation
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- homepage.description=Kimi-distilled abliterated Qwen3.5-122B-A10B NVFP4, vision-intact, the `gen` model (fv-ml1 GPU 0)
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- homepage.href=http://10.251.50.54:${QWOPUS_PORT:-8013}/docs
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networks:
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tnet:
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name: traefik-net
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external: true
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