Update app.py

app.py

@@ -144,16 +144,24 @@ news_input = st.text_area("Enter News Text:", placeholder="Type here...")
 if st.button("Check News"):
     st.write("🔍 Processing...")
     prediction = fake_news_detector(news_input)
-    label = prediction[0]['label'].lower()  # Convert label to lowercase for consistency
+    label = prediction[0]['label'].lower()  # Convert label to lowercase
     confidence = prediction[0]['score']
     
-    # Strict classification: FAKE news is always FAKE, and REAL news is always REAL
-    if "fake" in label or "false" in label or "negative" in label:
-        st.error(f"⚠️ Result: This news is **FAKE**. (Confidence: {confidence:.2f})")
-    elif "real" in label or "true" in label or "positive" in label:
-        st.success(f"✅ Result: This news is **REAL**. (Confidence: {confidence:.2f})")
+    # Force classification based on confidence threshold
+    threshold = 0.5  # Adjust if needed
+    if confidence >= threshold:
+        if "fake" in label or "false" in label or "negative" in label:
+            st.error(f"⚠️ Result: This news is **FAKE**. (Confidence: {confidence:.2f})")
+        else:
+            st.success(f"✅ Result: This news is **REAL**. (Confidence: {confidence:.2f})")
     else:
-        st.warning("⚠️ Unable to classify the news with high confidence. Please verify manually.") 
+        # If confidence is too low, classify based on probability
+        final_label = "FAKE" if confidence < 0.5 else "REAL"
+        if final_label == "FAKE":
+            st.error(f"⚠️ Result: This news is **FAKE**. (Confidence: {confidence:.2f})")
+        else:
+            st.success(f"✅ Result: This news is **REAL**. (Confidence: {confidence:.2f})")
+
 # ---- Deepfake Image Detection Section ----
 st.subheader("📸 Deepfake Image Detection")
 uploaded_image = st.file_uploader("Upload an Image", type=["jpg", "png", "jpeg"])