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esh-pfi-infrastructure/stacks/reward-seat/.env.example
T
vh 52612cbe96 feat(reward-seat): move Skywork reward seat from fv-ml1 to esh-ml1; audit finds nothing superseding it
- Audit: Skywork-Reward-V2-Llama-3.1-8B is still #1 of 188 on AllenAI's
  RewardBench 2 per-sample results; no Skywork V3; the -40M sibling is
  vendor-marked experimental. Our AWQ W4A16 quant: 0.847 vs published bf16
  0.860 on a 150-prompt sample (within +/-2.9 pt SE), 96.2% pairwise
  agreement. Double BOS from vLLM on pre-templated text costs a further
  ~2.7 pts; callers must send add_special_tokens=false.
- No working consumer: 0 requests since 2026-09-13; Worldtree Domari points
  at a dead IP with a non-vLLM schema (reported to worldtree-dev).
- Move: sha256-identical model copy; vLLM v0.24.0 on esh-ml1 :8003 at 0.55
  util (KV 1.30x of a 16k request). Parity vs fv-ml1: 149/150 verdicts,
  99.8% pairwise signs, raw |delta| median 0.049.
- Gateway /scalar-judge passthrough -> 10.0.50.80:8003; fv-ml1 vllm-reward
  removed (~10.2 GB freed on GPU 1). stacks/vllm now holds only vllm-coder.
2026-09-25 09:09:48 -07:00

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# reward-seat tunables (esh-ml1). Copy to `.env` on the server.
# Same vLLM as fv-ml1's seat had, so the move changed only the GPU. The image
# is already on esh-ml1 from the vLLM embed/rerank era.
VLLM_VERSION=v0.24.0
# Same port as on fv-ml1, so the gateway passthrough changed only its host.
REWARD_PORT=8003
# Fraction of the Ada's TOTAL 16,380 MiB (≈9.0 GB). vLLM checks it against
# free memory at start; TEI embed+rerank hold ~2.6 GB of the rest. The KV pool
# must hold one full 16,384-token sequence (~2.1 GB for Llama-3.1-8B in bf16).
REWARD_GPU_MEM_UTIL=0.55
# Server-side cap; Worldtree's Domari budgets 14,000 tokens against it.
REWARD_MAX_MODEL_LEN=16384
# Matches fv-ml1: no key (the gateway passthrough fronts it).
API_KEY=