# Use an official PyTorch image with CUDA support as the base image
FROM pytorch/pytorch:1.9.01-cuda11.1-cudnn8-runtime

# Install Git, OpenGL libraries, and libglib2.0
RUN apt-get update && apt-get install -y git libgl1-mesa-glx libglib2.0-0

# Install necessary dependencies, including CMake, a C++ compiler, and others
RUN apt-get update && apt-get install -y unzip ffmpeg cmake g++ build-essential aria2

# Set up a new user named "user" with user ID 1000
RUN useradd -m -u 1000 user

# Switch to the "user" user
USER user

# Set environment variables
ENV HOME=/home/user \
    CUDA_HOME=/usr/local/cuda \
    PATH=/home/user/.local/bin:$PATH \
    LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH} \
    LIBRARY_PATH=${CUDA_HOME}/lib64/stubs:${LIBRARY_PATH} \
    PYTHONPATH=$HOME/app \
    PYTHONUNBUFFERED=1 \
    GRADIO_ALLOW_FLAGGING=never \
    GRADIO_NUM_PORTS=1 \
    GRADIO_SERVER_NAME=0.0.0.0 \
    GRADIO_THEME=huggingface \
    GRADIO_SHARE=False \
    SYSTEM=spaces

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

# Clone your repository or add your code to the container
RUN git clone -b main https://github.com/fffiloni/video-retalking $HOME/app

# Install specific versions of PyTorch and TorchVision
RUN pip install torch==1.9.0 torchvision==0.10.0

# Install dependencies
COPY requirements.txt $HOME/app/requirements.txt
RUN pip install --no-cache-dir -r requirements.txt

# Download checkpoint files using aria2
RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/camenduru/video-retalking/resolve/main/30_net_gen.pth -d $HOME/app/checkpoints -o 30_net_gen.pth
# Continue with the other aria2c download commands

# Unzip BFM.zip
RUN unzip -d $HOME/app/checkpoints/BFM $HOME/app/checkpoints/BFM.zip

# Ensure the compiled CUDA code can be found
ENV LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}

# Update package lists and install other dependencies as needed
# Ensure that CUDA components are correctly installed and configured
# Install any other required packages

# Set the environment variable to specify the GPU device
ENV CUDA_DEVICE_ORDER=PCI_BUS_ID
ENV CUDA_VISIBLE_DEVICES=0

# Run your app.py script
CMD ["python", "app.py"]