Update app.py

app.py

@@ -1,6 +1,7 @@
 import streamlit as st
 import torch
-From newspaper import Article
+import newspaper
+import json
 
 # Load model directly
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
@@ -8,11 +9,20 @@ from transformers import AutoTokenizer, AutoModelForSequenceClassification
 tokenizer = AutoTokenizer.from_pretrained("sofzcc/distilbert-base-uncased-fake-news-checker")
 model = AutoModelForSequenceClassification.from_pretrained("sofzcc/distilbert-base-uncased-fake-news-checker")
 
-def newspaper_text_extraction(article_url):
-    article = Article(article_url)
+def extract_news_text(url):
+    article = newspaper.Article(url=url, language='en')
     article.download()
     article.parse()
-    return article. title,article.text
+
+    article ={
+        "title": str(article.title),
+        "text": str(article.text),
+        "published_date": str(article.publish_date),
+        "keywords": article.keywords,
+        "summary": str(article.summary)
+    }
+
+    return article['text']
 
 
 # Function to predict if news is real or fake
@@ -33,7 +43,7 @@ news_url = st.text_area("News URL", height=100)
 
 if st.button("Evaluate"):
     if news_url:
-        news_text = newspaper_text_extraction(news_url)
+        news_text = extract_news_text(news_url)
         prediction = predict_news(news_text)
         st.write(f"The news article is predicted to be: **{prediction}**")
     else: