vh
2b40805b84
Prime (via albok-dev): understand why h2o failed and re-fit the judge. One vLLM on GPU 3 behind two fronts: :8034 with the shim's yes/no floor at 0.801 exactly as the cutover ran (same judge stamp), :8035 with SHIM_NOUL_FLOOR=0 and a distinct stamp (h2o-lightning-4b+noul-floor-0). Both refuse image URLs; the vLLM --allowed-media-domains backstop is now verified (400, no fetch).
91 lines
4.2 KiB
YAML
91 lines
4.2 KiB
YAML
# TRANSIENT h2o-lightning-4b eval seat on fv-ml1 GPU 3 (GPU 3 is for transient work only).
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# Round 1, 2026-10-12 1300-1319: albok-dev validated Nemi's judge on h2o before the GPU 1 cutover (Prime via brokkr).
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# Round 2, from 2026-10-12 ~1430 (Prime 1420, via albok-dev): "I'd like to understand why h2o failed, so stand it up
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# on gpu3 and refit it and let's get an understanding." albok-dev investigates the 154 texts h2o alone called adult
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# and re-fits the judge. Two fronts over ONE vLLM:
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# :8034 front the shim's yes/no floor ON (0.801), exactly as the live cutover ran; /health model stamp
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# h2o-lightning-4b@b43f759b..., identical to the cutover's
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# :8035 front-nofloor SHIM_NOUL_FLOOR=0 (floor OFF, brokkr's lever); stamp h2o-lightning-4b+noul-floor-0@b43f759b...
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# Each /health also reports backend.noul_floor {value, source}. NO load tests or other traffic while albok-dev's
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# runs are in (they name start/end on thread 01M4S026GWS354WZGXZ5E34F31). INC keeps :8033 on GPU 1, untouched.
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# Serving exactly as benched (docs/pfi/decision-sweep-followon-bench-2026-10-12.md, Amendment 1): stock vLLM 0.30.0
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# + the vendor's unmodified shim + the admission front (services/h2o-decision-front, copied into conf/front).
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# Weights: /tank/aimodels/h2o-lightning-4b-b43f759b (hashes match HF at b43f759b; see the stack README).
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# Inline images only (Prime 2026-10-12): LIGHTNING_IMAGE_URLS=off on both fronts + vLLM --allowed-media-domains.
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name: h2o-eval
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services:
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vllm:
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image: vllm/vllm-openai:v0.30.0
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container_name: h2o-eval-vllm
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restart: unless-stopped
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ports:
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- "127.0.0.1:18199:8000"
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environment:
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VLLM_USE_FLASHINFER_SAMPLER: "0"
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volumes:
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- /tank/aimodels/h2o-lightning-4b-b43f759b:/model:ro
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- h2o-eval-vllm-cache:/root/.cache/vllm
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command: ["--model", "/model", "--served-model-name", "h2oai/h2o-lightning-4b",
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"--max-model-len", "40960", "--max-num-seqs", "16", "--gpu-memory-utilization", "0.1506",
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"--limit-mm-per-prompt", "{\"image\": 4, \"video\": 0}",
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"--mm-processor-kwargs", "{\"max_pixels\": 1605632}",
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"--allowed-media-domains", "media.invalid"]
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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: ["3"]
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capabilities: [gpu]
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front:
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image: python:3.12-slim
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container_name: h2o-eval-front
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restart: unless-stopped
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network_mode: host
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depends_on: [vllm]
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env_file: .env
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environment:
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SHIM_VLLM: http://127.0.0.1:18199
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SHIM_PORT: "18191"
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SHIM_NOUL_FLOOR: "0.801"
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LIGHTNING_IMAGE_URLS: "off" # Prime 2026-10-12: inline images only, the seat never fetches an image URL
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FRONT_SHIM: http://127.0.0.1:18191
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FRONT_VLLM: http://127.0.0.1:18199
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FRONT_BIND: 0.0.0.0
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FRONT_PORT: "8034"
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FRONT_CAP: "32000"
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FRONT_SHIM_FILE: /model/h2o_lightning_shim.py
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FRONT_SERVE_CONFIG: /model/serve_config.json
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FRONT_MODEL_REVISION: b43f759b6385d21182f87c3829931ec3d4dfa98a
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volumes:
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- /tank/aimodels/h2o-lightning-4b-b43f759b:/model:ro
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- /opt/docker/conf/h2o-eval/front:/front:ro
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command: ["bash", "/front/run.sh"]
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front-nofloor:
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image: python:3.12-slim
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container_name: h2o-eval-front-nofloor
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restart: unless-stopped
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network_mode: host
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depends_on: [vllm]
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env_file: .env
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environment:
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SHIM_VLLM: http://127.0.0.1:18199
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SHIM_PORT: "18192"
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SHIM_NOUL_FLOOR: "0" # the floor OFF (the shim: 0 turns it off)
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LIGHTNING_IMAGE_URLS: "off" # Prime 2026-10-12: inline images only, the seat never fetches an image URL
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FRONT_SHIM: http://127.0.0.1:18192
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FRONT_VLLM: http://127.0.0.1:18199
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FRONT_BIND: 0.0.0.0
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FRONT_PORT: "8035"
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FRONT_CAP: "32000"
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FRONT_SHIM_FILE: /model/h2o_lightning_shim.py
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FRONT_SERVE_CONFIG: /model/serve_config.json
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FRONT_MODEL_NAME: h2o-lightning-4b+noul-floor-0 # a distinct judge stamp
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FRONT_MODEL_REVISION: b43f759b6385d21182f87c3829931ec3d4dfa98a
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volumes:
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- /tank/aimodels/h2o-lightning-4b-b43f759b:/model:ro
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- /opt/docker/conf/h2o-eval/front:/front:ro
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command: ["bash", "/front/run.sh"]
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volumes:
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h2o-eval-vllm-cache:
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