fix most frequent phrase

app.py

@@ -195,33 +195,40 @@ with gr.Blocks() as app:
         new_step = math.ceil(float_step * 2)
         return new_step, float_step * 2
 
+
     def perform_search(step, rounds_combination, tlang, strip_spaces, strip_in_braces, strip_diacritics_chk, merge_results, include_torah, include_bible, include_quran, gematria_text, date_words_output):
         els_results = perform_els_search(step, rounds_combination, tlang, strip_spaces, strip_in_braces, strip_diacritics_chk, merge_results, include_torah, include_bible, include_quran)
 
         # --- Network Search Integration ---
-        df_data = []
+        updated_els_results = []  # List to store updated results with most frequent phrase
         for result in els_results:
-            gematria_sum = calculate_gematria(result['match'])
-            max_words = len(result['match'].split())
+            print("DEBUG: Result from perform_els_search:", result)
+            try:
+                gematria_sum = calculate_gematria(result['result_text'])
+            except KeyError as e:
+                print(f"DEBUG: KeyError - Key '{e.args[0]}' not found in result. Skipping this result.")
+                continue
+
+            max_words = len(result['result_text'].split())
             matching_phrases = search_gematria_in_db(gematria_sum, max_words)
+
+            # Find most frequent phrase for this specific result
             most_frequent_phrase = get_most_frequent_phrase(matching_phrases)
 
-            # Add data to the list for DataFrame creation
-            df_data.append({
-                'book': result['book'],
-                'chapter': result['chapter'],
-                'verse': result['verse'],
-                'match': result['match'],
-                'Most Frequent Phrase': most_frequent_phrase
-            })
-
-        # Create DataFrame
-        df = pd.DataFrame(df_data)
+            # Add most frequent phrase to the result dictionary
+            result['Most Frequent Phrase'] = most_frequent_phrase
+
+            updated_els_results.append(result)  # Append updated result to the list
+
+        # --- Prepare Dataframe ---
+        df = pd.DataFrame(updated_els_results)  # Create DataFrame from updated results
         df.index = range(1, len(df) + 1)
         df.reset_index(inplace=True)
         df.rename(columns={'index': 'Result Number'}, inplace=True)
 
-        return df, df['Most Frequent Phrase'].iloc[0] if not df.empty else None
+        return df, most_frequent_phrase  # Note: most_frequent_phrase here will be from the last iteration, but it's not used for the DataFrame
+
+
 
     # --- Event Triggers ---
     round_x.change(update_rounds_combination, inputs=[round_x, round_y], outputs=rounds_combination)
@@ -254,4 +261,4 @@ with gr.Blocks() as app:
     )
 
 if __name__ == "__main__":
-    app.launch(share=False)
+    app.launch(share=False)