Files
esh-pfi-infrastructure/stacks/h2o-eval/compose.yaml
T
vh f979cca1ea fix(intern-decision): roll the decision seat back to Intern-Decision-4B; h2o staged with inline-images-only
albok-dev withdrew the judge sign-off on fleet-scale evidence and brokkr
concurred: over 10,841 texts judged by both models, h2o flagged 242 adult at
0.5 against INC's 88, and no threshold reproduces INC's set. rollback-to-inc.sh
ran 14:03:28, INC healthy 14:03:56, /decide/shared smoke 200 x3.

compose.yaml is INC again; the h2o compose is kept as compose.h2o.yaml with
switch-to-h2o.sh (GPU 1 free-memory gate, falls back to INC). It now carries
Prime's inline-images-only setting: LIGHTNING_IMAGE_URLS=off on the front
(verified live: an https image URL is refused before any fetch, inline images
still answer) and vLLM --allowed-media-domains media.invalid as a backstop.
rollback-to-inc.sh no longer leaves timestamped compose copies behind.
2026-10-12 14:05:44 -07:00

59 lines
2.5 KiB
YAML

# 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: