steve
17b19999de
Nvidia: install torch+torchvision from PyTorch cu130 index, drop onnxruntime-gpu. ROCm: use local torch wheel with rocm6.4 index for torchvision, clean up nvidia remnants from the venv. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
36 lines
899 B
Docker
36 lines
899 B
Docker
FROM nvidia/cuda:13.0.1-runtime-ubuntu24.04
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ENV DEBIAN_FRONTEND=noninteractive
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RUN apt-get update && apt-get install -y --no-install-recommends \
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python3.12 python3.12-venv python3.12-dev python3-pip \
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libpoppler-cpp-dev poppler-utils \
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libgl1 libglib2.0-0 \
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build-essential curl \
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&& rm -rf /var/lib/apt/lists/*
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COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv
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WORKDIR /app
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COPY pyproject.toml ./
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COPY kb/ kb/
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COPY main.py ./
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COPY VERSION ./
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RUN uv venv .venv && \
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. .venv/bin/activate && \
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UV_HTTP_TIMEOUT=600 uv pip install torch torchvision --index-url https://download.pytorch.org/whl/cu130 && \
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uv pip install -e .
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ENV PATH="/app/.venv/bin:$PATH"
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ENV VIRTUAL_ENV="/app/.venv"
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ENV KB_DEVICE=auto
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ENV KB_INGEST_DEVICE=auto
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ENV KB_DATA_DIR=/data
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EXPOSE 8000
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VOLUME ["/data"]
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CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
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