The gen-small EngineCore OOM (04:21 PT): our parked 3,582 MiB window cache left no room for vLLM's runtime workspace. Seat-side fix, three controls: - windowed path wraps every window in torch.cuda.empty_cache(), so the seat returns to ~2,108 MiB rest after a 12-min file instead of parking at the peak (measured: peak 3,028 MiB during, rest after, restarts=0); - MEM_CAP_MIB=3840 hard set_per_process_memory_fraction: over-cap requests answer 503 with the seat alive (proved at cap=2000), so the failure lands on us, never on a neighbour; - CUDA_GRAPHS=0: the graph decoder pins cache blocks that empty_cache must free (illegal-memory-access wedge when both were on first try). Cost: 12-min file 3.0 s vs 1.2 s, short bins 35-62 ms vs 33-42 ms -- still 4-15x under the sherpa seat. Measured, not computed: gen-small moved ZERO from 36,116 MiB across three realistic requests (1,351 in / ~180 out) -- its workspace lands at engine init; the growth window is restart-relative, matching infra-ops's observation. WINDOW_S is now a real compose tunable. README memory section rewritten.
70 lines
3.0 KiB
YAML
70 lines
3.0 KiB
YAML
# Parakeet ASR via NeMo torch (unified-en-0.6b, bf16 weights) + our own thin FastAPI wrapper.
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#
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# Replacement seat for stacks/parakeet (sherpa-onnx int8). Same port (:8300), same endpoints,
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# same body — LiteLLM and `talk` need no change. Rollback: stop this container, start the old
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# `parakeet` one (kept; container and image both intact).
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#
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# HOST: fv-ml1, GPU 0.
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#
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# ⚠ GPU 0 room came from gen-small's util SLACK, not its KV: util went 0.48 -> 0.36 (now 0.33 in its .env),
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# and the KV is byte-pinned (unchanged at 670,142 tokens). Plan GPU 0 against this seat's STEADY STATE of
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# 3,582 MiB (the torch cache after a long, windowed request), not its at-rest figure; that leaves Free ~385 MiB
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# (the old seat held 1,690 MiB). Do not raise that util back without re-measuring nvidia-smi Free
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# on GPU 0 — util does not predict resident VRAM (see the 09-15 note in gen-small-seat/.env).
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#
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# ⚠ Weights: /tank/aimodels/huggingface mounted READ-ONLY. nvidia/parakeet-unified-en-0.6b @
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# fe53cd885760c96b6a5f51a0bfd362cb4584a98b. HF_HUB_OFFLINE=1 in the image: the seat never phones home.
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#
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# API (identical to the replaced seat):
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# POST /transcribe — multipart file upload, returns {"text": "..."}
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# POST /v1/audio/transcriptions — same body, OpenAI-compatible path alias
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# GET /healthz
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#
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# All tunables live in .env — edit that, not this file.
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services:
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parakeet-nemo:
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image: local/parakeet-nemo:${PARAKEET_NEMO_TAG}
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container_name: parakeet-nemo
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restart: unless-stopped
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ports:
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- "${PARAKEET_NEMO_BIND:-0.0.0.0}:${PARAKEET_NEMO_PORT}:8000"
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environment:
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- MODEL_PATH=/hf/hub/models--nvidia--parakeet-unified-en-0.6b/snapshots/${PARAKEET_NEMO_REV}/parakeet-unified-en-0.6b.nemo
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- WARMUP_SECONDS=${PARAKEET_NEMO_WARMUP:-1,8,60}
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# CUDA graphs pin memory in torch's cache, which fights the empty_cache the windowed path
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# needs to return memory to GPU 0's neighbours (illegal-memory-access wedge, 2026-10-01).
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- CUDA_GRAPHS=${PARAKEET_NEMO_CUDA_GRAPHS:-0}
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- MEM_CAP_MIB=${PARAKEET_NEMO_MEM_CAP_MIB:-3840}
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- WINDOW_S=${PARAKEET_NEMO_WINDOW_S:-360}
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- LOG_LEVEL=${PARAKEET_NEMO_LOG_LEVEL:-INFO}
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volumes:
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- /tank/aimodels/huggingface:/hf:ro
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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device_ids: ["${PARAKEET_NEMO_GPU:-0}"]
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capabilities: [gpu]
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networks:
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- tnet
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healthcheck:
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test: ["CMD-SHELL", "wget -q -O /dev/null http://localhost:8000/healthz || exit 1"]
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interval: 30s
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timeout: 10s
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retries: 3
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# Import-time model load + three warm-up decodes; no download (weights are mounted).
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start_period: 240s
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labels:
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- homepage.group=AI - Audio Tools
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- homepage.name=Parakeet ASR (NeMo)
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- homepage.icon=mdi-microphone
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- homepage.description=Parakeet-unified-en speech-to-text via NeMo bf16 (fv-ml1 GPU 0)
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- homepage.href=http://10.251.50.54:${PARAKEET_NEMO_PORT}
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networks:
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tnet:
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name: traefik-net
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external: true
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