# -*- coding: utf-8 -*-

from __future__ import absolute_import
from __future__ import division, print_function, unicode_literals

import psutil
from sumy.parsers.html import HtmlParser
from sumy.parsers.plaintext import PlaintextParser
from sumy.nlp.tokenizers import Tokenizer
from sumy.summarizers.lsa import LsaSummarizer as Summarizer
from sumy.nlp.stemmers import Stemmer
from sumy.utils import get_stop_words
import nltk
import streamlit as st


class SumySummarizer:
    LANGUAGE = "german"
    SENTENCES_COUNT = 10

    def __init__(self):
        nltk.download('punkt_tab')

    def summarize(self, text: str):
        parser = PlaintextParser.from_string(text, Tokenizer(self.LANGUAGE))
        stemmer = Stemmer(self.LANGUAGE)

        summarizer = Summarizer(stemmer)
        st.info("Using Textsummarization Model Sumy Summarizer")
        summarizer.stop_words = get_stop_words(self.LANGUAGE)

        summary = summarizer(parser.document, self.SENTENCES_COUNT)
        summary = [str(sentence) for sentence in summary]
        return summary