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    """This package provides a complete workflow to users how want to proced to NIRS analysis without particular knowledge.
    
    This is a webapp with Streamlit.
    GUI shows whatever is needed for Samples Selection based on NIRS spectra and then, to compute a model to predict
        chemical values on your samples.
    
    Examples:
        streamlit run ./app.py
    """
    
    from Packages import *
    # from utils import read_dx, DxRead,  Plsr, LinearPCA, Umap, find_col_index, PinardPlsr, Nmf, AP
    # from utils import LWPLSR, list_files, metrics, TpeIpls, reg_plot, resid_plot, Sk_Kmeans, DxRead, Hdbscan, read_dx, PlsProcess, PinardPlsr, Plsr
    from utils.DATA_HANDLING import *
    from utils.Miscellaneous import prediction, download_results, plot_spectra, local_css, desc_stats, hash_data
    from utils.Hash import create_hash, check_hash
    from report import report
    css_file = Path("style/")
    pages_folder = Path("pages/")
    from style import add_header, add_sidebar
    # from style.header import add_header, add_sidebar
    from config.config import pdflatex_path
    
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    local_css(css_file / "style.css")