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# Use Nvidia CUDA runtime as the base image
FROM nvidia/cuda:12.6.1-cudnn-runtime-ubuntu24.04
# Set build arguments for repository configuration
ARG REPO_URL=https://github.com/rmusser01/tldw.git
ARG BRANCH=main
ARG GPU_SUPPORT=cpu
# Install system dependencies
RUN apt-get update && apt-get install -y \
ffmpeg \
libsqlite3-dev \
build-essential \
git \
python3 \
python3-pyaudio \
portaudio19-dev \
python3-pip \
python3-venv \
&& rm -rf /var/lib/apt/lists/*
# Create a new user named "user" with user ID 1000
RUN useradd -m -u 1009 user9
# Switch to the "user" user
USER user9
# Set environment variables for the user's home directory and PATH
ENV HOME=/home/user \
PATH=/home/user/.local/bin:$PATH
# Set the working directory to the user's app directory
WORKDIR $HOME/app
# Upgrade pip and install wheel as the non-root user
#RUN pip install --no-cache-dir --upgrade pip wheel
# Clone the repository into the working directory
RUN git clone -b ${BRANCH} ${REPO_URL} .
# Create and activate a virtual environment
RUN python3 -m venv venv
ENV PATH="$HOME/app/venv/bin:$PATH"
# Install CUDA libraries
RUN pip install --no-cache-dir nvidia-cublas-cu12 nvidia-cudnn-cu12
# Install PyTorch based on GPU support
RUN if [ "$GPU_SUPPORT" = "cuda" ]; then \
pip install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 --index-url https://download.pytorch.org/whl/cu123; \
elif [ "$GPU_SUPPORT" = "amd" ]; then \
pip install torch-directml; \
else \
pip install torch==2.2.2 torchvision==0.17.2 torchaudio==2.2.2 --index-url https://download.pytorch.org/whl/cpu; \
fi
# Install other Python dependencies
RUN pip install --no-cache-dir -r requirements.txt
# Update config.txt for CPU if needed
RUN if [ "$GPU_SUPPORT" = "cpu" ]; then \
sed -i 's/cuda/cpu/' ./Config_Files/config.txt; \
fi
# Expose port 7860 to the outside world
EXPOSE 7860
# Set environment variable for Gradio to listen on all interfaces
ENV GRADIO_SERVER_NAME="0.0.0.0"
# Define the default command to run the application
CMD ["python", "summarize.py", "-gui"]
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