.docker/dockerfile

# Base image with CUDA 12.6.3 and cuDNN
FROM nvidia/cuda:12.6.3-cudnn-runtime-ubuntu22.04

# Set environment variables
ARG DEBIAN_FRONTEND=noninteractive
ENV PYTHONUNBUFFERED=1 \
    GRADIO_ALLOW_FLAGGING=never \
    GRADIO_NUM_PORTS=1 \
    GRADIO_SERVER_NAME=0.0.0.0 \
    GRADIO_THEME=huggingface \
    SYSTEM=spaces \
    AM_I_IN_A_DOCKER_CONTAINER=Yes \
    PYTHONPATH=/home/appuser/app \
    HF_HOME=/home/appuser/.cache \
    TORCH_HOME=/home/appuser/.cache \
    NVIDIA_VISIBLE_DEVICES=all \
    NVIDIA_DRIVER_CAPABILITIES=compute,utility

# Install system dependencies
RUN apt-get update && apt-get install --no-install-recommends -y \
    build-essential \
    python3.10 \
    python3.10-distutils \
    python3-pip \
    ffmpeg \
    libsm6 \
    libxext6 \
    libgl1 \
    && apt-get clean && rm -rf /var/lib/apt/lists/*

# Set Python 3.10 as the default python3 and pip
RUN ln -sf /usr/bin/python3.10 /usr/bin/python \
    && ln -sf /usr/bin/pip3 /usr/bin/pip

# Install `uv`
RUN pip install --upgrade pip \
    && pip install uv

# Create a non-root user
RUN useradd -m -u 1000 appuser

# Set working directory to the user's home directory
WORKDIR /home/appuser/app

# Copy dependency files, including LICENSE and README.md
COPY --chown=appuser pyproject.toml uv.lock LICENSE README.md ./

# Install dependencies using `uv`
RUN uv sync --frozen

# Copy the application code
COPY --chown=appuser app app

# Ensure non-root user has write access to the cache directory
RUN mkdir -p /home/appuser/.cache && chown -R appuser:appuser /home/appuser/.cache

# Set ownership for all files to the app user
# Avoid unnecessary `chown` for better performance since `COPY --chown` already sets ownership

# Switch to the non-root user
USER appuser

# Set the cache directory for Hugging Face and other tools
ENV HF_HOME=$CACHE_DIR \
    TRANSFORMERS_CACHE=$CACHE_DIR \
    TORCH_HOME=$CACHE_DIR

# Expose the port for Gradio
EXPOSE 7862

# Command to run the application
CMD ["uv", "run", "python", "app/main.py"]