Update app_pages/page1_model_comparison.py

app_pages/page1_model_comparison.py

@@ -2,6 +2,7 @@ import streamlit as st
 from app_models.rubert_MODEL import classify_text
 from app_models.bag_of_words_MODEL import predict
 from app_models.lstm_MODEL import predict_review
+import time
 
 class_prefix =  'This review is likely...'
 
@@ -14,17 +15,24 @@ def run():
 
 
     if st.button('Classify with All Models'):
-        # Bag of Words/TF-IDF prediction
+        # Measure and display Bag of Words/TF-IDF prediction time
+        start_time = time.time()
         bow_tfidf_result = predict(user_input)
-        st.write(f'{class_prefix} {bow_tfidf_result} according to Bag of Words/TF-IDF.')
+        end_time = time.time()
+        st.write(f'{class_prefix} {bow_tfidf_result} according to Bag of Words/TF-IDF. Time taken: {end_time - start_time:.2f} seconds.')
         
-        # LSTM prediction
+        # Measure and display LSTM prediction time
+        start_time = time.time()
         lstm_result = predict_review(user_input)
-        st.write(f'{class_prefix} {lstm_result} according to LSTM.')
+        end_time = time.time()
+        st.write(f'{class_prefix} {lstm_result} according to LSTM. Time taken: {end_time - start_time:.2f} seconds.')
         
-        # ruBERT prediction
+        # Measure and display ruBERT prediction time
+        start_time = time.time()
         rubert_result = classify_text(user_input)
-        st.write(f'{class_prefix} {rubert_result} according to ruBERT.')
+        end_time = time.time()
+        st.write(f'{class_prefix} {rubert_result} according to ruBERT. Time taken: {end_time - start_time:.2f} seconds.')
+
 
     # Placeholder buttons for model selection
     # if st.button('Classify with BoW/TF-IDF'):