Billy D.
2e3e014b80
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71 lines
2.5 KiB
Docker
71 lines
2.5 KiB
Docker
# syntax=docker/dockerfile:1.7
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# NVIDIA GPU Ray Worker for elminster (RTX 2070)
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# Used for: Whisper STT, XTTS Text-to-Speech
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#
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# Build:
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# docker build -t git.daviestechlabs.io/daviestechlabs/ray-worker-nvidia:latest \
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# -f dockerfiles/Dockerfile.ray-worker-nvidia .
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FROM docker.io/rayproject/ray:2.53.0-py312-cu121
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# OCI Image Spec labels
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LABEL org.opencontainers.image.title="Ray Worker - NVIDIA GPU"
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LABEL org.opencontainers.image.description="Ray Serve worker for NVIDIA GPUs (Whisper STT, XTTS TTS)"
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LABEL org.opencontainers.image.vendor="DaviesTechLabs"
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LABEL org.opencontainers.image.source="https://git.daviestechlabs.io/daviestechlabs/kuberay-images"
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LABEL org.opencontainers.image.licenses="MIT"
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LABEL gpu.target="nvidia-cuda-12.1"
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LABEL ray.version="2.53.0"
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WORKDIR /app
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# Install system dependencies in a single layer with cleanup
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USER root
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RUN --mount=type=cache,target=/var/cache/apt,sharing=locked \
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--mount=type=cache,target=/var/lib/apt,sharing=locked \
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apt-get update && apt-get install -y --no-install-recommends \
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ffmpeg \
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libsndfile1 \
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&& rm -rf /var/lib/apt/lists/*
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# Install uv for fast Python package management (ADR-0014)
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COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv
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# Switch back to non-root ray user
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USER ray
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# Install Python dependencies with uv cache mount (10-100x faster than pip)
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# Pinned versions for reproducibility
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RUN --mount=type=cache,target=/home/ray/.cache/uv,uid=1000,gid=1000 \
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uv pip install --system \
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'faster-whisper>=1.0.0,<2.0' \
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'coqui-tts>=0.27.0,<1.0' \
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'soundfile>=0.12.0,<1.0' \
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'pydub>=0.25.0,<1.0' \
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'librosa>=0.10.0,<1.0' \
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'torch>=2.0.0,<3.0' \
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'torchaudio>=2.0.0,<3.0' \
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'transformers>=4.46.0,<5.0' \
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'fastapi>=0.100.0,<1.0' \
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'uvicorn>=0.23.0,<1.0' \
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'httpx>=0.27.0,<1.0' \
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'pydantic>=2.0.0,<3.0'
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# Copy entrypoint script (ray-serve-apps is installed from PyPI at runtime)
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COPY --chown=1000:100 --chmod=755 dockerfiles/ray-entrypoint.sh /app/ray-entrypoint.sh
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# Environment configuration
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ENV PYTHONPATH=/app \
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PYTHONUNBUFFERED=1 \
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PYTHONDONTWRITEBYTECODE=1 \
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CUDA_VISIBLE_DEVICES=0 \
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RAY_HEAD_SVC="ai-inference-raycluster-head-svc" \
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GPU_RESOURCE="gpu_nvidia" \
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NUM_GPUS="1"
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# Health check - verify Ray worker can connect
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HEALTHCHECK --interval=30s --timeout=10s --start-period=60s --retries=3 \
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CMD ray status --address=localhost:6379 || exit 1
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ENTRYPOINT ["/app/ray-entrypoint.sh"]
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