Keysat
98aeef8779
WhisperX docker build was crashing at the model-prewarm step: OSError: undefined symbol: torch_library_impl Root cause: the NGC PyTorch base ships custom builds of torch + torchaudio + torchvision matched together for Blackwell (sm_120). When pip installed whisperx, it pulled the latest stock torchaudio wheel as a transitive dep, which was compiled against a different libtorch and won't load against NGC's. Fix: at build time, capture NGC's actual torch/torchaudio/torchvision versions into /tmp/torch-constraints.txt, then `pip install -c` that constraint for all subsequent installs. pip can't swap torch out, so the ABI stays consistent. whisperx and pyannote are happy with torch>=2.0 — NGC's 2.10.0a0 satisfies that easily. The pinned versions print to the build log so you can see them. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
65 lines
2.9 KiB
Docker
65 lines
2.9 KiB
Docker
# WhisperX ASR + diarization container for Spark 2 (Blackwell GB10, sm_120).
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#
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# Replaces the custom Parakeet wrapper + Sortformer overlay with a single
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# mainline pipeline: faster-whisper for transcription + pyannote.audio 3.1
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# for diarization + wav2vec2 forced alignment for word-level timestamps.
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#
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# Build (on Spark 2, where Blackwell + nvcr.io credentials are available):
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# docker build -t whisperx-asr:latest .
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#
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# Run:
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# docker run -d --restart unless-stopped --name whisperx-asr \
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# --gpus all --memory=40g \
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# -p 8002:8002 \
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# -v whisperx-models:/root/.cache/huggingface \
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# -e HF_TOKEN="$(cat ~/.cache/huggingface/token)" \
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# -e WHISPER_MODEL=medium \
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# whisperx-asr:latest
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#
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# The memory cap is intentional: even if WhisperX hits a pathological input,
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# it gets OOM-killed cleanly instead of swap-thrashing the whole Spark.
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FROM nvcr.io/nvidia/pytorch:25.11-py3
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# WhisperX runs ffmpeg under the hood for audio decoding
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RUN apt-get update \
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&& apt-get install -y --no-install-recommends ffmpeg \
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&& rm -rf /var/lib/apt/lists/*
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# CRITICAL: the NGC base image ships custom builds of torch + torchaudio +
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# torchvision compiled together for Blackwell (sm_120). If pip pulls a stock
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# torchaudio wheel as a transitive dep of whisperx/pyannote, the resulting
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# ABI mismatch crashes at import time:
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# "undefined symbol: torch_library_impl"
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# Generate a constraints.txt from whatever versions NGC actually shipped,
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# then pass it to every pip install so pip cannot swap torch out.
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RUN python3 -c "import torch, torchaudio, torchvision; \
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import sys; \
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sys.stdout.write(f'torch=={torch.__version__}\ntorchaudio=={torchaudio.__version__}\ntorchvision=={torchvision.__version__}\n')" \
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> /tmp/torch-constraints.txt \
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&& echo '── pinned torch versions ──' && cat /tmp/torch-constraints.txt
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# Install whisperx + the FastAPI wrapper deps under the torch constraint.
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COPY requirements.txt /tmp/requirements.txt
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RUN pip install --break-system-packages --no-cache-dir \
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-c /tmp/torch-constraints.txt -r /tmp/requirements.txt
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# Pre-warm the default Whisper + alignment models at build time so first-call
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# latency on a fresh container is small. (~3 GB cached into the image; if you
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# want a smaller image, comment this out and accept the first-call download.)
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ARG WHISPER_MODEL=medium
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ENV WHISPER_MODEL=${WHISPER_MODEL}
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RUN python3 -c "import whisperx; whisperx.load_model('${WHISPER_MODEL}', 'cpu', compute_type='int8')" \
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&& python3 -c "import whisperx; whisperx.load_align_model(language_code='en', device='cpu')"
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WORKDIR /opt/whisperx
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COPY app /opt/whisperx/app
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# Expose for spark-control's proxy on Spark 2
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EXPOSE 8002
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HEALTHCHECK --interval=30s --timeout=10s --start-period=180s \
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CMD python3 -c "import urllib.request; urllib.request.urlopen('http://localhost:8002/health')" || exit 1
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CMD ["python3", "-m", "uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8002", "--workers", "1"]
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