Dockerfile.cuda

# Use the NVIDIA CUDA image as the base
FROM nvidia/cuda:12.0.1-cudnn8-devel-ubuntu22.04

# Set the working directory
WORKDIR /app

# Install system dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
    python3.11 \
    python3-pip \
    build-essential \
    libssl-dev \
    libffi-dev \
    libjpeg-dev \
    zlib1g-dev \
    libpng-dev \
    libsentencepiece-dev \
    curl \
    gcc \
    g++ \
    python3.11-dev \
    cmake \
    && rm -rf /var/lib/apt/lists/*

# Set Python 3.11 as the default
RUN update-alternatives --install /usr/bin/python python /usr/bin/python3.11 1
RUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.11 1

# Upgrade pip and install base packages
RUN pip install --upgrade pip setuptools wheel

# Set PYTHONPATH correctly
ENV PYTHONPATH=/app

# Install PyTorch with CUDA support
RUN pip3 install --no-cache-dir \
    torch \
    torchvision \
    torchaudio \
    --index-url https://download.pytorch.org/whl/cu124

# Copy the requirements file
COPY requirements_cuda.txt .

# Install additional Python dependencies
RUN pip3 install --no-cache-dir -r requirements_cuda.txt

# Copy the rest of the application code
COPY . .

# Set environment variables for better GPU memory handling and protobuf implementation
ENV PYTORCH_CUDA_ALLOC_CONF=max_split_size_mb:512
ENV PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python
ENV PYTHONUNBUFFERED=1

# Set up the environment and logging
RUN python -m pip install --upgrade pip && \
    python -c "from config.env_config import setup_environment; setup_environment()"
RUN python -c "from pathlib import Path; from config.logging_config import setup_logging; setup_logging(Path('flux_pipeline.log'))"

# Expose the application port
EXPOSE 7860

# Healthcheck to verify Gradio service status
HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
    CMD curl -f http://localhost:7860/ || exit 1

# Set the command to run the application with updated arguments
CMD ["python3", "-u", "gui.py", "--host", "0.0.0.0", "--port", "7860", "--share"]