Create Dockerfile

Dockerfile

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+# Start from a minimal Debian image
+FROM debian:bullseye-slim
+
+# Set NVIDIA environment variables
+ENV NVIDIA_VISIBLE_DEVICES all
+ENV NVIDIA_DRIVER_CAPABILITIES compute,utility
+ENV NVIDIA_REQUIRE_CUDA "cuda>=11.8"
+ENV LD_LIBRARY_PATH=/usr/local/cuda-11.8/lib64:$LD_LIBRARY_PATH
+
+# Update and install required packages
+RUN apt-get update && apt-get install -y \
+    gnupg2 curl python3-pip ffmpeg \
+    libcublas-11-8 libcudnn8=8.6.0.163-1+cuda11.8
+
+# Import NVIDIA repository GPG key
+RUN curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/7fa2af80.pub | \
+    gpg --dearmor -o /usr/share/keyrings/cuda-archive-keyring.gpg
+
+# Add CUDA repository to sources list
+RUN echo "deb [signed-by=/usr/share/keyrings/cuda-archive-keyring.gpg] https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64 /" > /etc/apt/sources.list.d/cuda.list
+
+# Update package lists
+RUN apt-get update
+
+# Install Python dependencies
+WORKDIR /app
+COPY ./requirements.txt /app/requirements.txt
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+# Copy application files
+COPY ./app.py /app/app.py
+COPY ./interface.html /app/interface.html
+COPY ./styles.css /app/styles.css
+
+# Create a non-root user for security
+RUN useradd -m -u 1000 user
+USER user
+
+# Set environment and working directory
+ENV HOME=/home/user
+WORKDIR $HOME/app
+
+# Copy remaining files
+COPY --chown=user . $HOME/app
+
+# Expose the port and run the application
+EXPOSE 7860
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]