Update app.py

app.py

@@ -62,6 +62,10 @@ def hybrid_scale(dense, sparse, alpha):
 
 
 def process_input(query, slider_value):
+    #####################
+    filtered_items = [item for item in item_list if re.search(pattern, item)]
+    filtered_df = fashion[fashion['productDisplayName'].isin(filtered_items)]
+    #####################
     try:
         slider_value = float(slider_value)
         sparse = bm25.encode_queries(query)
@@ -79,8 +83,8 @@ def process_input(query, slider_value):
         matches = [x["metadata"]['productDisplayName'] for x in result["matches"]]
 
         ###########
-        exact_match = fashion.filter(lambda x: x['productDisplayName'] == query)[0]['productDisplayName']
-        exact_img = fashion.filter(lambda x: x['productDisplayName'] == query)[0]['image']
+        exact_match = filtered_df.filter(lambda x: x['productDisplayName'] == query)[0]['productDisplayName']
+        exact_img = filtered_df.filter(lambda x: x['productDisplayName'] == query)[0]['image']
         if exact_match is not None:
             imgs.insert(0, exact_img)
             matches.insert(0, exact_match)