Update app.py

app.py

@@ -173,8 +173,6 @@ def detect_deepfake_image(image_path):
 #         else:
 #             st.success(f"✅ Result: This news is **REAL**. (Confidence: {confidence:.2f})")
 # ---- Fake News Detection Section ----
-import streamlit as st
-
 st.subheader("📝 Fake News Detection")
 news_input = st.text_area("Enter News Text:", placeholder="Type here...")
 
@@ -186,12 +184,13 @@ if st.button("Check News"):
     label = prediction[0]['label'].lower()
     confidence = prediction[0]['score']
 
-    # Ensure proper classification
-    if label in ["fake", "false", "negative"] or confidence < 0.7:
+    # Ensure correct classification
+    if confidence > 0.75 and label in ["real", "true", "positive"]:
+        st.success(f"✅ Result: This news is **REAL**. (Confidence: {confidence:.2f})")
+    elif confidence < 0.5 or label in ["fake", "false", "negative"]:
         st.error(f"⚠️ Result: This news is **FAKE**. (Confidence: {confidence:.2f})")
     else:
-        st.success(f"✅ Result: This news is **REAL**. (Confidence: {confidence:.2f})")
-
+        st.warning(f"⚠️ Unable to classify with high confidence. Please verify manually. (Confidence: {confidence:.2f})")
 # ---- Deepfake Image Detection Section ----
 st.subheader("📸 Deepfake Image Detection")
 uploaded_image = st.file_uploader("Upload an Image", type=["jpg", "png", "jpeg"])