Files
esh-pfi-infrastructure/stacks/vllm/compose.yaml
T
vh 6851ecbd0b fix(fv-ml1): pin vLLM KV in bytes on meromero (22 GiB) and coder; gen-small KV 8 -> 5.5 GiB
meromero-rp sized its KV from --gpu-memory-utilization, and vLLM's profile
counts co-booting neighbours as its own non-torch memory. Three boots gave
20.37 / 26.74 / 29.04 GiB of KV, and the 2026-10-05 Docker-move restart cut
GPU 1 free memory to 3,981 MiB, below intern-decision's 32k-token budget.
Coder read negative KV on every co-boot. Both are now pinned, so util only
gates the boot check (meromero util 0.52 -> 0.47, just above its footprint).

GPU 0 plateaus at ~60 MiB free 1-2 days after a boot (Beszel), so
gen-small's KV drops to 5.5 GiB (461,215 tokens, 1.76x) and parakeet-nemo
stays on GPU 0 with room for its 3,840 MiB cap. GPU 3 stays clear.

Applied with playbooks/fv-ml1-kv-pin-20261005.yaml: GPU 1 free 3,981 ->
11,801 MiB, GPU 0 495 -> 5,039 MiB right after boot; all nine seats healthy.
2026-10-05 21:40:28 -07:00

134 lines
5.9 KiB
YAML

# vLLM — the coder FIM seat on fv-ml1 (the last utility seat left here).
#
# Originally created to replace the unmaintained Infinity stack (embed +
# rerank); generalized 2026-05-13 to host any vLLM-served model on fv-ml1,
# starting with the Skywork-Reward-V2-Llama-3.1-8B reward classifier
# (AWQ-quantized locally, served from /tank/aimodels/llm/).
#
# ⚠ Embedding + reranking LEFT this stack 2026-09-25 (Prime): they now run on TEI
# on esh-ml1 (stacks/embed-rerank), and TEI is the fleet's embed/rerank engine
# from now on. The reward classifier moved to esh-ml1 the same day
# (stacks/reward-seat). Do not re-add them here.
#
# All tunables live in .env — edit that, not this file.
#
# Skywork-Reward-V2-Llama-3.1-8B-AWQ is a locally-quantized model. The canonical
# copy still lives at /tank/aimodels/llm/Skywork-Reward-V2-Llama-3.1-8B-AWQ on
# fv-ml1; the serving copy is on esh-ml1. Not from HF Hub.
services:
# vllm-embed (Qwen3-Embedding-0.6B, :8001) and vllm-rerank-a3
# (bge-reranker-v2-m3, :8013) were RETIRED 2026-09-25 (Prime): embedding and
# reranking moved to TEI on esh-ml1 (stacks/embed-rerank), and TEI is now the
# fleet's embed/rerank engine. The gateway names `qwen3-embedding`, `reranker`
# and `reranker-a3-bge-v2-m3` did not change. Their definitions are in git
# history before this commit if a rollback is ever needed.
# vllm-reward (Skywork-Reward-V2-Llama-3.1-8B AWQ, :8003) — MOVED to esh-ml1
# 2026-09-25 (stacks/reward-seat); the gateway `/scalar-judge` passthrough
# follows it. The model files stay at /tank/aimodels/llm/ on fv-ml1 as the
# canonical copy of the local quant.
# vllm-granite (ibm-granite/granite-4.1-8b-fp8, :8004) — RETIRED 2026-08-12,
# service block removed 2026-08-20. It was the fleet summarizer until the
# `summarizer` and `classifier` aliases were repointed at the gen seat; the
# container was stopped then and sat Exited for 8 days while this block still
# claimed it as production.
#
# ⚠️ Retiring the SEAT did not retire its CONSUMERS, and nobody checked. The
# `granite-4.1-8b` gateway alias was deleted at the same time, but `nevermore`
# was still pinned to that alias by name — so its LLM summarization pass failed
# 67 consecutive times over 8 days, 0 tokens, entirely silently, because a
# failed gateway call still returns 200-shaped spend-log rows and nothing
# alerts on status=failure. Found 2026-08-20 only because someone asked an
# unrelated question about reranker VRAM.
#
# The rule this earns: RETIRING A MODEL IS A TWO-SIDED OPERATION. Grep every
# consumer's config for the alias BEFORE deleting it, and prefer that consumers
# pin stable ALIASES (`summarizer`) over model names (`granite-4.1-8b`) so the
# gateway can repoint them without anyone editing a downstream .env.
vllm-coder:
image: vllm/vllm-openai:${VLLM_VERSION}
container_name: vllm-coder
restart: unless-stopped
ipc: host
ports:
- "${CODER_PORT}:8000"
volumes:
- /tank/aimodels/huggingface:/hfcache
environment:
- HF_HOME=/hfcache
- HF_HUB_CACHE=/hfcache/hub
- HUGGING_FACE_HUB_TOKEN=${HF_TOKEN:-}
- VLLM_API_KEY=${API_KEY:-}
command:
# Qwen2.5-Coder-1.5B (BASE) — FIM code-completion seat for Zed edit-predictions
# (deep-research pick 2026-07-27). Native fill-in-the-middle: <|fim_prefix|> /
# <|fim_suffix|> / <|fim_middle|> (IDs 151659/151660/151661); Zed sends the
# FIM-formatted prompt to /v1/completions and vLLM passes it through (the FIM
# special tokens live in the tokenizer). BASE not -Instruct (FIM is a
# pretraining objective; base completions are cleaner). Apache-2.0. Runner-up =
# Qwen2.5-Coder-3B (higher HumanEval-FIM but non-commercial Qwen-Research license).
- ${CODER_MODEL}
- --served-model-name
- ${CODER_SERVED_NAME}
- --host
- 0.0.0.0
- --port
- "8000"
- --gpu-memory-utilization
- ${CODER_GPU_MEM_UTIL}
# KV pinned in bytes (2026-10-05): GPU 1 is shared, and util-sized profiling read
# negative KV on every co-boot (crash, then a retry). 1,104,674,816 B = 4,816 blocks
# = 77,056 tokens, the size every successful boot had landed on.
- --kv-cache-memory
- ${CODER_KV_CACHE_MEMORY:-1104674816}
- --max-model-len
- ${CODER_MAX_MODEL_LEN}
- --max-num-seqs
- ${CODER_MAX_NUM_SEQS}
- --dtype
- auto
- --kv-cache-dtype
- ${CODER_KV_CACHE_DTYPE}
- --enable-prefix-caching
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids:
- "${CODER_GPU_ID}"
capabilities:
- gpu
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 10s
retries: 3
start_period: 300s
networks:
- tnet
labels:
- homepage.group=AI - Inference
- homepage.name=vLLM Qwen2.5-Coder 1.5B (FIM)
- homepage.icon=mdi-code-braces
- homepage.description=Qwen2.5-Coder-1.5B FIM code-completion (fv-ml1, Zed edit-predictions)
- homepage.href=http://10.251.50.54:${CODER_PORT}/docs
# vllm-lfm25 (LiquidAI/LFM2.5-2.6B, :8021) — RETIRED PERMANENTLY 2026-08-20 by
# operator directive. It was an EVAL-ONLY bake-off seat against granite-4.1-8b
# (brokkr R-target, 2026-08-10) that never received the operator ruling it was
# pending. Its comparator is gone (granite retired from the roster 2026-08-15),
# it was deliberately never wired into any default/fallback routing chain, and
# LiteLLM spend logs showed 0 calls in the 4-day window ending 2026-08-21.
# Freed 8,772 MiB on fv-ml1 GPU1. The `lfm2.5-2.6b` gateway alias was removed
# in the same pass so the name 404s cleanly rather than erroring against a dead
# backend. Weights remain in the shared HF cache; nothing was deleted from disk.
networks:
tnet:
name: traefik-net
external: true