docker name

Dockerfile

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+# Use NVIDIA CUDA base image
+FROM nvidia/cuda:11.8-devel-ubuntu20.04
+
+# Set environment variables
+ENV DEBIAN_FRONTEND=noninteractive
+ENV PYTHONUNBUFFERED=1
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    python3.9 \
+    python3.9-dev \
+    python3-pip \
+    ffmpeg \
+    git \
+    wget \
+    curl \
+    && rm -rf /var/lib/apt/lists/*
+
+# Create symlinks for python
+RUN ln -s /usr/bin/python3.9 /usr/bin/python
+
+# 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 home to the user's home directory
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH
+
+# Set the working directory to the user's home directory
+WORKDIR $HOME/app
+
+# Upgrade pip
+RUN python -m pip install --no-cache-dir --upgrade pip
+
+# Install PyTorch with CUDA support first
+RUN pip install --no-cache-dir torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
+
+# Copy requirements file
+COPY --chown=user requirements.txt .
+
+# Install other Python dependencies
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Copy the application code
+COPY --chown=user . .
+
+# Expose the port
+EXPOSE 7860
+
+# Run the application
+CMD ["python", "unified_socket_server.py", "--host", "0.0.0.0", "--port", "7860"]