Dockerfile.gpu

# Use NVIDIA CUDA base image
FROM nvidia/cuda:11.6.2-cudnn8-runtime-ubuntu20.04

# Set environment variables
ENV PYTHONDONTWRITEBYTECODE=1 \
    PYTHONUNBUFFERED=1 \
    DEBIAN_FRONTEND=noninteractive

# Install system dependencies
RUN apt-get update && apt-get install -y \
    python3-pip \
    python3-dev \
    curl \
    libglib2.0-0 \
    libsm6 \
    libxrender1 \
    libxext6 \
    libfontconfig1 \
    libgl1 \
    && rm -rf /var/lib/apt/lists/*

# Set the working directory in the container
WORKDIR /app

# Copy the current directory contents into the container at /app
COPY . /app

# Install any needed packages specified in requirements.txt
RUN pip3 install --no-cache-dir -r requirements.txt

# Install PyTorch with CUDA support
RUN pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116

# Make port 8501 available to the world outside this container
EXPOSE 8501

# Healthcheck to verify the application is running
HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health || exit 1

# Run app.py when the container launches
CMD ["streamlit", "run", "--server.address", "0.0.0.0", "app.py"]