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from sumy.parsers.plaintext import PlaintextParser
from sumy.parsers.html import HtmlParser
from sumy.nlp.tokenizers import Tokenizer
from sumy.nlp.stemmers import Stemmer
from sumy.utils import get_stop_words
import gradio as gr
import nltk
nltk.download('punkt')
def summarize(method, language, sentence_count, input_type, input_):
if method== 'LSA':
from sumy.summarizers.lsa import LsaSummarizer as Summarizer
if method=='text-rank':
from sumy.summarizers.text_rank import TextRankSummarizer as Summarizer
if method=='lex-rank':
from sumy.summarizers.lex_rank import LexRankSummarizer as Summarizer
if method=='edmundson':
from sumy.summarizers.edmundson import EdmundsonSummarizer as Summarizer
if method=='luhn':
from sumy.summarizers.luhn import LuhnSummarizer as Summarizer
if method=='kl-sum':
from sumy.summarizers.kl import KLSummarizer as Summarizer
if method=='random':
from sumy.summarizers.random import RandomSummarizer as Summarizer
if method=='reduction':
from sumy.summarizers.reduction import ReductionSummarizer as Summarizer
if input_type=="URL":
parser = HtmlParser.from_url(input_, Tokenizer(language))
if input_type=="text":
parser = PlaintextParser.from_string(input_, Tokenizer(language))
stemmer = Stemmer(language)
summarizer = Summarizer(stemmer)
stop_words = get_stop_words(language)
if method=='edmundson':
summarizer.null_words = stop_words
summarizer.bonus_words = parser.significant_words
summarizer.stigma_words = parser.stigma_words
else:
summarizer.stop_words = stop_words
summary_sentences = summarizer(parser.document, sentence_count)
summary = ' '.join([str(sentence) for sentence in summary_sentences])
return summary
title = "sumy library space for automatic text summarization"
description = """
This is a space for [sumy](https://github.com/miso-belica/sumy), an automatic text summarization library.
The summary can be extracted either from an HTML page or plain text. You can find a list of available summarization
methods [here](https://github.com/miso-belica/sumy/blob/main/docs/summarizators.md).
"""
methods = ["LSA", "luhn", "edmundson", "text-rank", "lex-rank", "random", "reduction", "kl-sum"]
supported_languages = ["english", "french", "arabic", "chinese", "czech", "german", "italian", "hebrew",
"japanese", "portuguese", "slovak", "spanish", "ukrainian", "greek"]
iface = gr.Interface(
summarize,
[
gr.inputs.Dropdown(methods),
gr.inputs.Dropdown(supported_languages),
gr.inputs.Number(default=5),
gr.inputs.Radio(["URL", "text"], default="URL"),
gr.inputs.Textbox(5),
],
"text",
title=title,
description=description,
examples=[
["luhn", 'english', 2, "URL", "https://en.wikipedia.org/wiki/Automatic_summarization"]
],
)
iface.launch()