Update app.py

app.py

@@ -172,21 +172,25 @@ def detect_deepfake_image(image_path):
 #             st.error(f"⚠️ Result: This news is **FAKE**. (Confidence: {confidence:.2f})")
 #         else:
 #             st.success(f"✅ Result: This news is **REAL**. (Confidence: {confidence:.2f})")
+from transformers import pipeline
 import streamlit as st
 
+# ✅ Load a Valid Fake News Detection Model
+fake_news_detector = pipeline("text-classification", model="MoritzLaurer/deberta-v3-large-contrastive-fake-news")
+
 st.subheader("📝 Fake News Detection")
 news_input = st.text_area("Enter News Text:", placeholder="Type here...")
 
 if st.button("Check News"):
     st.write("🔍 Processing...")
 
-    # Use AI model to classify the news
+    # ✅ Get Model Prediction
     prediction = fake_news_detector(news_input)
     label = prediction[0]['label'].lower()
     confidence = prediction[0]['score']
 
-    # Ensure proper classification
-    if label in ["fake", "false", "negative"] or confidence < 0.5:
+    # ✅ Ensure Correct Classification
+    if "fake" in label or confidence < 0.5:
         st.error(f"⚠️ Result: This news is **FAKE**. (Confidence: {confidence:.2f})")
     else:
         st.success(f"✅ Result: This news is **REAL**. (Confidence: {confidence:.2f})")