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| from gensim.parsing.preprocessing import STOPWORDS | |
| import wikipedia | |
| import gradio as gr | |
| from gradio.mix import Parallel | |
| import requests | |
| import nltk | |
| from nltk.tokenize import word_tokenize | |
| from nltk.tokenize import sent_tokenize | |
| import re | |
| nltk.download('punkt') | |
| import numpy as np | |
| import pandas as pd | |
| from os import path | |
| from PIL import Image | |
| from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator | |
| import matplotlib.pyplot as plt | |
| def opendomain(text,wikipedia_language="en"): | |
| question_words = STOPWORDS.union(set(['likes','play','.',',','like',"don't",'?','use','choose','important','better','?'])) | |
| lower_text = text.lower() | |
| lower_text = word_tokenize(lower_text) | |
| new_text = [i for i in lower_text if i not in question_words] | |
| new_txt = "".join(new_text) | |
| if wikipedia_language: | |
| wikipedia.set_lang(wikipedia_language) | |
| et_page = wikipedia.page(new_txt.replace(" ", "")) | |
| title = et_page.title | |
| content = et_page.content | |
| page_url = et_page.url | |
| linked_pages = et_page.links | |
| text = content | |
| print(type(text)) | |
| wordcloud = WordCloud(font_path="HelveticaWorld-Regular.ttf").generate(text) | |
| plt.imshow(wordcloud, interpolation='bilinear') | |
| plt.axis("off") | |
| final_out = re.sub(r'\=.+\=', '', text) | |
| result = list(filter(lambda x: x != '', final_out.split('\n\n'))) | |
| answer = [] | |
| for i in range(6): | |
| if len(result[i]) > 500: | |
| summary_point=result[i].split(".")[0] | |
| answer.append(summary_point) | |
| l = [] | |
| for i in range(len(answer)): | |
| l.append("".join(answer[i])) | |
| gen_output = [] | |
| for i in range(len(l)): | |
| gen_output.append(l[i] + ".") | |
| listToStr = ' '.join([str(elem) for elem in gen_output]) | |
| listToStr = listToStr.replace("\n", "") | |
| return listToStr | |
| iface = gr.Interface(fn=opendomain, inputs=[gr.inputs.Textbox(lines=5)], outputs="text") | |
| iface.launch() | |