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Dockerfile

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+# Use the development container, which includes necessary CUDA libraries and the CUDA Compiler.
+FROM nvidia/cuda:12.8.1-cudnn-devel-ubuntu22.04
+# could this be a better base image? pytorch/pytorch:2.5.1-cuda12.4-cudnn9-runtime
+
+# Set system variables
+ENV DEBIAN_FRONTEND=noninteractive
+ENV NVIDIA_VISIBLE_DEVICES=all
+ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
+
+ENV CUDA_HOME=/usr/local/cuda
+ENV PATH="$CUDA_HOME/bin:$PATH"
+ENV LD_LIBRARY_PATH="$CUDA_HOME/lib64:$LD_LIBRARY_PATH"
+
+# Ensure Python outputs everything that's printed inside the application
+# (solvws the issue of not seeing the output of the application in the container)
+ENV PYTHONUNBUFFERED=1
+
+# Dynamic memory allocation for PyTorch in order to reduce memory fragmentation.
+# (reduces risk of OOM eerors in low VRAM scenarios)
+ENV PYTORCH_CUDA_ALLOC_CONF="expandable_segments:True"
+
+# Software configuration
+ENV PINOKIO_DOWNLOAD_URL=https://github.com/pinokiocomputer/pinokio/releases/download/v5.1.10/Pinokio_5.1.10_amd64.deb
+
+# Install system dependencies required by Pinokio and VNC
+RUN apt update \
+    && apt install -y \
+    wget git xdg-utils \
+    libgtk-3-0 libnotify4 libnss3 libxss1 libxtst6 \
+    libatspi2.0-0 libsecret-1-0 libappindicator3-1 \
+    libgbm1 libasound2 \
+    xvfb \
+    dbus dbus-x11 \
+    libcudnn8 \
+    && rm -rf /var/lib/apt/lists/*
+
+# Download and install the Pinokio .deb package
+RUN wget -O pinokio.deb $PINOKIO_DOWNLOAD_URL
+RUN apt install -y ./pinokio.deb && rm pinokio.deb
+
+# Folder structures and assets
+RUN mkdir /app
+WORKDIR /app
+COPY config.json config.json
+COPY startup.sh startup.sh
+RUN chmod +x startup.sh
+
+EXPOSE 42000
+
+CMD ["./startup.sh"]