Update app.py

app.py

@@ -212,13 +212,6 @@ def re_rank_candidates(query, candidates, method):
             key=lambda x: x[1]['cross_score'],
             reverse=True
         )
-    elif method == 'encoder':
-        # Filter and sort by cross_score + bi_score
-        filtered_sorted_result = sorted(
-            [(k, v) for k, v in candidates.items() if (v['cross_score'] > DEFAULT_SCORE) & (v['bi_score'] > DEFAULT_SCORE)],
-            key=lambda x: x[1]['cross_score'] + x[1]['bi_score'],
-            reverse=True
-        )
     elif method == 'gms':
         filtered_sorted_by_encoder = sorted(
             [(k, v) for k, v in candidates.items() if (v['cross_score'] > DEFAULT_SCORE) & (v['bi_score'] > DEFAULT_SCORE)],
@@ -228,6 +221,14 @@ def re_rank_candidates(query, candidates, method):
         # first sort by cross_score + bi_score
         filtered_sorted_result = sorted(filtered_sorted_by_encoder, key=lambda x: x[1]['gms'], reverse=True
         )
+    else:
+        # use default method cross_score + bi_score
+        # Filter and sort by cross_score + bi_score
+        filtered_sorted_result = sorted(
+            [(k, v) for k, v in candidates.items() if (v['cross_score'] > DEFAULT_SCORE) & (v['bi_score'] > DEFAULT_SCORE)],
+            key=lambda x: x[1]['cross_score'] + x[1]['bi_score'],
+            reverse=True
+        )
     data_dicts = [{'query': item[0], **item[1]} for item in filtered_sorted_result]
     # Convert the list of dictionaries into a DataFrame
     df = pd.DataFrame(data_dicts)
@@ -237,7 +238,7 @@ def re_rank_candidates(query, candidates, method):
 # st.write("## Raw Candidates:")
 if st.button('Generated Expansion'): 
     candidates = generate_query_expansion_candidates(query = user_query)
-    df = re_rank_candidates(user_query, candidates, method='cross_score')
+    df = re_rank_candidates(user_query, candidates, method='cross_encoder')
     result = list(df['query'][:maxtags_sidebar])
     st.write(result)
     ## convert into dataframe