#!/bin/zsh

# requires Nvidia GPU

# Update package list
sudo apt update

# Remove Outdated Signing Key
sudo apt-key del 7fa2af80

# Install dependencies
sudo apt install -y curl

# Install Anaconda3
echo "Installing Anaconda3..."
if [ ! -f Anaconda3-2023.03-1-Linux-x86_64.sh ]; then
    wget https://repo.anaconda.com/archive/Anaconda3-2023.03-1-Linux-x86_64.sh
fi
bash Anaconda3-2023.03-1-Linux-x86_64.sh -u -p $HOME/anaconda3

# Add Anaconda3 to the PATH
echo ". $HOME/anaconda3/etc/profile.d/conda.sh" >> $HOME/.zshrc
source ~/.zshrc

# Create a new conda environment
echo "Creating a new conda environment..."
conda create -n bark_env python=3.8 -y

# Activate the conda environment
echo "Activating the conda environment..."
conda activate bark_env

# Install Bark and other necessary packages
echo "Installing Bark and other necessary packages..."
pip install git+https://github.com/suno-ai/bark.git
conda install -y scipy
conda install -y ipykernel
conda install -y notebook
conda install -c conda-forge ipywidgets

# Add the conda environment to Jupyter
echo "Adding the conda environment to Jupyter..."
python3 -m ipykernel install --user --name=bark_env

# Install Cuda
echo "Installing Cuda..."
if [ ! -f cuda_12.1.1_530.30.02_linux.run ]; then
    wget https://developer.download.nvidia.com/compute/cuda/12.1.1/local_installers/cuda_12.1.1_530.30.02_linux.run
fi
sudo sh cuda_12.1.1_530.30.02_linux.run

# For WSL, do not install cuda-drivers or cuda-toolkit using apt-get
# Follow the instructions provided in the NVIDIA WSL User Guide:
# https://docs.nvidia.com/cuda/wsl-user-guide/index.html#installing-nvidia-driver

# Launch Jupyter Notebook
echo "Launching Jupyter Notebook..."
jupyter notebook