Dockerfile-gpu

# syntax=docker/dockerfile:1

# Base image with NVIDIA CUDA
FROM nvidia/cuda:12.4.1-base-ubuntu20.04 as base

# Prevents Python from writing pyc files.
ENV PYTHONDONTWRITEBYTECODE=1

# Keeps Python from buffering stdout and stderr to avoid situations where
# the application crashes without emitting any logs due to buffering.
ENV PYTHONUNBUFFERED=1
ENV RUNTIME docker

WORKDIR /app

# Install software-properties-common to add PPAs
RUN apt-get update && apt-get install -y software-properties-common && \
    add-apt-repository ppa:deadsnakes/ppa

# Install Python, pip and other necessary packages
RUN apt-get install -y \
    python3.11 \
    python3-pip \
    curl \
    && ln -s /usr/bin/python3.11 /usr/bin/python \
    && rm -rf /var/lib/apt/lists/*

# Make Python 3.11 the default Python version
RUN ln -sf /usr/bin/python3.11 /usr/bin/python3 && \
    ln -sf /usr/bin/python3.11 /usr/bin/python

# Install UV
RUN curl -LsSf https://astral.sh/uv/0.2.1/install.sh | sh

# Download dependencies as a separate step to take advantage of Docker's caching.
# Leverage a cache mount to /root/.cache/uv to speed up subsequent builds.
# Leverage a bind mount to requirements to avoid having to copy them into
# into this layer.
RUN --mount=type=cache,target=/root/.cache/uv \
    --mount=type=bind,source=requirements.lock,target=requirements.lock \
    /root/.cargo/bin/uv pip install --system -r requirements.lock

# Install some executables
RUN apt-get update \
    && apt-get install -y curl procps sysstat ifstat \
    && rm -rf /var/lib/apt/lists/*

# Copy the source code into the container.
COPY src/ src/
COPY entrypoint.sh .

# Run the application.
ENTRYPOINT ["/app/entrypoint.sh"]