Update app.py

app.py

@@ -139,18 +139,28 @@ def detect_deepfake_image(image_path):
 
 # ---- Fake News Detection Section ----
 st.subheader("📝 Fake News Detection")
-news_input = st.text_area("Enter News Text:", placeholder="Type here...")
+news_input = st.text_area("Enter News Text:", placeholder="Type your news here...")
 
 if st.button("Check News"):
-    st.write("🔍 Processing...")
-    prediction = fake_news_detector(news_input)
-    label = prediction[0]['label']
-    confidence = prediction[0]['score']
-    
-    if label == "FAKE":
-        st.error(f"⚠️ Result: This news is FAKE. (Confidence: {confidence:.2f})")
+    if not news_input.strip():
+        st.warning("⚠️ Please enter some news text to analyze.")
     else:
-        st.success(f"✅ Result: This news is REAL. (Confidence: {confidence:.2f})") 
+        st.write("🔍 Processing...")
+
+        # Detect Fake News
+        prediction = fake_news_detector(news_input)
+        label = prediction[0]['label']
+        confidence = round(prediction[0]['score'], 2)
+
+        # Improved Classification
+        if label.lower() in ["fake", "negative"]:
+            st.error(f"⚠️ Fake News Detected! This news appears to be FAKE. (Confidence: {confidence:.2f})")
+            st.write("❌ **Warning:** This content might be misleading or false.")
+        elif label.lower() in ["real", "positive"]:
+            st.success(f"✅ This news appears to be REAL. (Confidence: {confidence:.2f})")
+            st.write("✔️ **Verified:** This content seems legitimate.")
+        else:
+            st.warning("⚠️ Unable to classify the news confidently. Please check the content manually.")
 # ---- Deepfake Image Detection Section ----
 st.subheader("📸 Deepfake Image Detection")
 uploaded_image = st.file_uploader("Upload an Image", type=["jpg", "png", "jpeg"])