# TEMPORARY h2o-lightning-4b decision seat on fv-ml1 GPU 3 (Prime 2026-10-12 via brokkr: "stand up the h2o copy on
# gpu 3 if you need to test, it should replace the live seat as soon as possible and keep gpu3 only for transient
# tasks"). It exists so albok-dev can re-validate Nemi's sensitivity judge on h2o before the GPU 1 cutover; REMOVE it
# right after the cutover. INC (stacks/intern-decision) keeps serving production on GPU 1 meanwhile.
# Serving exactly as benched (docs/pfi/decision-sweep-followon-bench-2026-10-12.md, Amendment 1): stock vLLM 0.30.0
# + the vendor's unmodified shim + the admission front (services/h2o-decision-front, copied into conf/front).
# Weights: /tank/aimodels/h2o-lightning-4b-b43f759b (hashes match HF at b43f759b; see the stack README).
name: h2o-eval
services:
  vllm:
    image: vllm/vllm-openai:v0.30.0
    container_name: h2o-eval-vllm
    restart: unless-stopped
    ports:
      - "127.0.0.1:18199:8000"
    environment:
      VLLM_USE_FLASHINFER_SAMPLER: "0"
    volumes:
      - /tank/aimodels/h2o-lightning-4b-b43f759b:/model:ro
      - h2o-eval-vllm-cache:/root/.cache/vllm
    command: ["--model", "/model", "--served-model-name", "h2oai/h2o-lightning-4b",
              "--max-model-len", "40960", "--max-num-seqs", "16", "--gpu-memory-utilization", "0.1506",
              "--limit-mm-per-prompt", "{\"image\": 4, \"video\": 0}",
              "--mm-processor-kwargs", "{\"max_pixels\": 1605632}",
              "--allowed-media-domains", "media.invalid"]
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              device_ids: ["3"]
              capabilities: [gpu]
  front:
    image: python:3.12-slim
    container_name: h2o-eval-front
    restart: unless-stopped
    network_mode: host
    depends_on: [vllm]
    env_file: .env
    environment:
      SHIM_VLLM: http://127.0.0.1:18199
      SHIM_PORT: "18191"
      SHIM_NOUL_FLOOR: "0.801"
      LIGHTNING_IMAGE_URLS: "off"   # Prime 2026-10-12: inline images only, the seat never fetches an image URL
      FRONT_SHIM: http://127.0.0.1:18191
      FRONT_VLLM: http://127.0.0.1:18199
      FRONT_BIND: 0.0.0.0
      FRONT_PORT: "8034"
      FRONT_CAP: "32000"
      FRONT_SHIM_FILE: /model/h2o_lightning_shim.py
      FRONT_SERVE_CONFIG: /model/serve_config.json
      FRONT_MODEL_REVISION: b43f759b6385d21182f87c3829931ec3d4dfa98a
    volumes:
      - /tank/aimodels/h2o-lightning-4b-b43f759b:/model:ro
      - /opt/docker/conf/h2o-eval/front:/front:ro
    command: ["bash", "/front/run.sh"]
volumes:
  h2o-eval-vllm-cache: