d

app.py

@@ -238,12 +238,12 @@ def AI_vs_AI_RandomForest_88_Samples(df):
         clf_loaded = pickle.load(file)
 
     input_features = df['paragraph'].apply(extract_features_AI_vs_AI_RandomForest_88_Samples)
-    #try:
-    predicted_llm = clf_loaded.predict(input_features)
-    st.write(f"Predicted LLM: {predicted_llm[0]}")
-    predicted_proba = clf_loaded.predict_proba(input_features)
-    #except Exception as e:
-        #st.write(f"An error occurred: {str(e)}")
+    try:
+        predicted_llm = clf_loaded.predict(input_features)
+        st.write(f"Predicted LLM: {predicted_llm[0]}")
+        predicted_proba = clf_loaded.predict_proba(input_features)
+    except Exception as e:
+        st.write(f"An error occurred: {str(e)}")
 
     # labels = clf_loaded.classes_