906d3aa318
- notebooks: Marimo notebook server with CUDA/Polars GPU support - Uses nvidia/cuda base with uv package manager - Includes cudf-polars for GPU-accelerated dataframes - GPU benchmark comparing Polars CPU/GPU and Pandas - zotero: Web-accessible Zotero via Selkies EGL desktop - Uses nvidia-egl-desktop with KasmVNC for browser access - GPU-accelerated desktop streaming - Persistent Zotero data directory - compose.yml: Docker Compose orchestration for all services Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
48 lines
1.4 KiB
Docker
48 lines
1.4 KiB
Docker
# syntax=docker/dockerfile:1
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FROM nvidia/cuda:12.6.0-runtime-ubuntu24.04
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ARG USERNAME=kert
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ARG USER_UID=1000
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ARG USER_GID=1000
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ARG PYTHON_VERSION=3.13
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ENV DEBIAN_FRONTEND=noninteractive \
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PATH="/home/${USERNAME}/.local/bin:${PATH}" \
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NVIDIA_VISIBLE_DEVICES=all \
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NVIDIA_DRIVER_CAPABILITIES=compute,utility
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# System dependencies
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RUN apt-get update && apt-get install -y --no-install-recommends \
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curl \
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ca-certificates \
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git \
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build-essential \
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&& rm -rf /var/lib/apt/lists/*
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# Rename existing ubuntu user/group to kert and fix home ownership
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RUN groupmod -n ${USERNAME} ubuntu \
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&& usermod -l ${USERNAME} -d /home/${USERNAME} -m -s /bin/bash ubuntu \
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&& chown -R ${USER_UID}:${USER_GID} /home/${USERNAME}
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# Install uv
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COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv
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COPY --from=ghcr.io/astral-sh/uv:latest /uvx /usr/local/bin/uvx
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# Switch to user
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USER ${USERNAME}
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WORKDIR /home/${USERNAME}
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# Initialize uv project and install dependencies
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RUN uv python install ${PYTHON_VERSION} \
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&& uv init workspace --python ${PYTHON_VERSION} \
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&& cd workspace \
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&& uv add "marimo[recommended]" polars cudf-polars-cu12 pandas numpy pyarrow \
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--extra-index-url https://pypi.nvidia.com
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EXPOSE 2718
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CMD ["uv", "run", "--project", "/home/kert/workspace", \
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"marimo", "edit", \
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"--host", "0.0.0.0", "--port", "2718", "--headless", "--no-token", \
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"/home/kert/notebooks"]
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