Update app.py

app.py

@@ -7,6 +7,13 @@ 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)
+    article.download()
+    article.parse()
+    return article. title,article.text
+
+
 # Function to predict if news is real or fake
 def predict_news(news_text):
     inputs = tokenizer(news_text, return_tensors="pt", truncation=True, padding=True, max_length=512)
@@ -19,13 +26,14 @@ def predict_news(news_text):
 # Streamlit App
 st.title("Fake News Detector")
 
-st.write("Enter a news article below to check if it's real or fake:")
+st.write("Enter a news article URL below to check if it's real or fake:")
 
-news_text = st.text_area("News Article", height=300)
+news_url = st.text_area("News URL", height=100)
 
 if st.button("Evaluate"):
-    if news_text:
+    if news_url:
+        news_text = newspaper_text_extraction(news_url)
         prediction = predict_news(news_text)
         st.write(f"The news article is predicted to be: **{prediction}**")
     else:
-        st.write("Please enter some news text to evaluate.")
+        st.write("Please enter some news URL to evaluate.")