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", "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()