Apptainer.backend

Bootstrap: docker
From: pytorch/pytorch:latest

%setup
    mkdir -p ${SINGULARITY_ROOTFS}/CropDoc

%files
    ./CropDoc/requirements.txt /CropDoc/requirements.txt

%post
    apt-get update && apt-get install -y \
        git \
        vim \
        wget \
        curl \
        htop \
        && apt-get clean \
        && rm -rf /var/lib/apt/lists/*

    ln -s /usr/bin/python3 /usr/local/bin/python
    ln -s /usr/bin/pip3 /usr/local/bin/pip

    cd /CropDoc
    python -m venv /venv
    . /venv/bin/activate
    pip install --no-cache-dir torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu124
    if [ -f requirements.txt ]; then
        pip install -r requirements.txt
    else
        echo "requirements.txt not found in /CropDoc"
        ls -la /CropDoc  # This will list the contents of the /CropDoc directory
    fi

%environment
    export PYTHONPATH="/venv/lib/python3.10/site-packages:$PYTHONPATH"
    export APP_NAME='CropDoc'
    export SECRET_KEY='secretkey'
    export FLASK_APP=manage.py
    export FLASK_ENV=development
    export LOGGING_LEVEL=DEBUG
    export ALLOWED_ORIGINS=http://localhost:3000,http://localhost:5000
    export LC_ALL=C

%runscript
    . /venv/bin/activate
    cd /CropDoc
    if [ -x "$(command -v nvidia-smi)" ]; then
        echo "CUDA is available. Using GPU."
        python -c "import torch; print('CUDA available:', torch.cuda.is_available()); print('CUDA version:', torch.version.cuda); print('GPU:', torch.cuda.get_device_name(0) if torch.cuda.is_available() else 'None')"
    else
        echo "CUDA is not available. Using CPU."
    fi
    python manage.py runserver --reload

%startscript
    . /venv/bin/activate
    cd /CropDoc && python manage.py runserver --reload