vh
569e1af9ca
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.
85 lines
2.7 KiB
YAML
85 lines
2.7 KiB
YAML
# qwen-image-bench — flukethoughts/Qwen-Image-Bench-NVFP4 on ana-ml2 GPU 1,
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# REPLACING qwen3.6-35b-a3b (operator 2026-06-19). Qwen's text-to-image quality
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# JUDGE model (vision-language, NVFP4 weights / vision tower bf16). NOT generative —
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# it scores T2I outputs on 5 dims (overall quality, prompt match, aesthetic, LoRA
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# activation, confidence).
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#
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# Arch: Qwen3_5ForConditionalGeneration (dense Qwen3.5 hybrid SSM+attn + vision),
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# ~17B / ~20GB NVFP4. VISION-INTACT → served as multimodal; NO text-only patch
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# (unlike the qwen3.5-122b gen model, which had text-only weights). vLLM
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# production-validated per the model card.
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#
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# ⚠️ qwen3.6-35b-a3b was arbo's hero-judge (comfy-dev consumer). Downing it breaks
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# arbo's judging until comfy-dev repoints to qwen-image-bench (different I/O — a
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# 5-dim verdict vs a general VL judge). comfy-dev notified.
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#
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# DISPLACEMENT: GPU 1 is shared (granite/selene/embed/rerank/reward). qwen3.6 used
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# util 0.34 (~33GB); down it first, then this fits at util ~0.22 (~21GB). REVERT =
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# down this, `up -d` the qwen36 stack.
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#
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# Tunables in .env.
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name: qwen-image-bench
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services:
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vllm-qwen-image-bench:
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image: ${QIB_IMAGE:-vllm/vllm-openai:latest}
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container_name: ${QIB_CONTAINER_NAME:-vllm-qwen-image-bench}
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restart: unless-stopped
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ipc: host
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ports:
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- "${QIB_PORT:-8014}:8000"
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volumes:
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- /tank/aimodels/huggingface:/hfcache
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- /tank/aimodels/qwen-image-bench-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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command:
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- /model
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- --served-model-name
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- qwen-image-bench
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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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- ${QIB_GPU_MEM_UTIL:-0.32}
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- --max-model-len
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- ${QIB_MAX_MODEL_LEN:-32768}
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- --max-num-seqs
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- ${QIB_MAX_NUM_SEQS:-8}
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- --trust-remote-code
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- --dtype
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- auto
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- --enable-prefix-caching
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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device_ids:
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- "${QIB_GPU_ID:-1}"
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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: 600s
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networks:
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- tnet
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labels:
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- homepage.group=AI - Eval & Retrieval
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- homepage.name=Qwen-Image-Bench (T2I judge, NVFP4)
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- homepage.icon=mdi-image-check
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- homepage.description=Qwen text-to-image quality judge (NVFP4, vision-intact) on ana-ml2 GPU 1
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- homepage.href=http://10.250.50.54:${QIB_PORT:-8014}/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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