Create Dockerfile

Dockerfile

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+FROM pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime
+
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Set the MKL_THREADING_LAYER environment variable to GNU
+ENV MKL_THREADING_LAYER=GNU
+
+# Install Git, OpenGL libraries, and libglib2.0
+RUN apt-get update && apt-get install -y git libgl1-mesa-glx libglib2.0-0
+
+RUN apt-get update && apt-get install -y ninja-build
+
+# 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/MiniGPT4-video $HOME/app
+
+# Install dependencies
+#COPY requirements.txt $HOME/app/requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
+
+RUN mkdir checkpoints
+
+# Download checkpoint files using aria2
+RUN aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/Vision-CAIR/MiniGPT4-Video/resolve/main/checkpoints/video_llama_checkpoint_last.pth -d $HOME/app/checkpoints -o video_llama_checkpoint_last.pth
+
+# 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", "minigpt4_video_demo.py"]