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coqui-bark-voice-cloning-docker / Dockerfile

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	# Use an official PyTorch image with CUDA support as the base image
	FROM pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime

	RUN apt-get update && apt-get install -y build-essential

	# Install a specific version of pip (e.g., 20.2.4)
	RUN pip install --upgrade pip

	# 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 . .

	USER root
	RUN chmod -R 777 $HOME/app/bark_voices
	USER user

	# Install dependencies
	# Use the new pip resolver and always take the latest version if not specified
	RUN pip install --use-feature=fast-deps -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"]