app.py

import gradio as gr
import nltk
nltk.download('punkt')
nltk.download('averaged_perceptron_tagger')
nltk.download('brown')

from transformers import pipeline
from newspaper import Article
from textblob import TextBlob

def Article_outline(url): #可輸入文章網址，提取該文章的標題、內文、摘要和進行情感分析

  article = Article(url)
  article.download()
  article.parse()
  summerizer = pipeline("summarization")
  blob = TextBlob(article.text)

  title=""
  title = "文章標題：" + article.title 
  txt=""
  txt = "內文：" + article.text
  sum=""
  sum = "摘要：" + str(summerizer(article.text))
  txtsen=''
  if blob.sentiment.polarity > 0:
    txtsen = "本文偏向正向情緒"
  elif blob.sentiment.polarity < 0:
    txtsen = "本文偏向負向情緒"

  result=title + txt + sum + txtsen

  return result

demo = gr.Interface(fn=Article_outline, inputs="text", outputs="text")

demo.launch()