Create Dockerfile

Dockerfile

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+# Use the official PyTorch 2.0.1 image as a base
+FROM pytorch/pytorch:2.0.1-cuda11.1-cudnn8-runtime
+
+# Install Git and system libraries required for OpenGL without interactive prompts
+ENV DEBIAN_FRONTEND=noninteractive
+
+# Install Git, OpenGL libraries, and libglib2.0
+RUN apt-get update && apt-get install -y git libgl1-mesa-glx libglib2.0-0
+
+# Set the pip resolver to "legacy"
+RUN pip config set global.resolver legacy
+
+RUN apt-get update && apt-get install -y ninja-build
+
+# 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
+
+COPY . .
+
+# Install dependencies
+#COPY requirements.txt $HOME/app/requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt gradio 
+
+
+# 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"]