Update app.py

app.py

@@ -48,9 +48,9 @@ def embed_data(dataset):
 
 @stl.cache_resource
 def init_search(_embedded_data, _embedder):
-    text_search = ripple.TextSearch(_embedded_data, _embedder.embed_model)
+    finder = ripple.TextSearch(_embedded_data, _embedder.embed_model)
     stl.success("Initialized text search class")
-    return text_search
+    return finder
 
 def get_images_from_description(finder, description):
     scores, ret_images = finder.get_similar_images(description, k_images=4)
@@ -66,12 +66,16 @@ if embedded_data and embedder:
     finder = init_search(embedded_data, embedder)
 
 
-search_term = stl.text_input("Text description/search for image")
-
-if search_term is not None:
-    with stl.spinner("retrieving images with description.."):
-        scores, ret_images = get_images_from_description(finder, search_term)
-        stl.success(f"sucessfully retrieved {len(ret_images)} images")
+try:
+    search_term = stl.text_input("Text description/search for image")
+    
+    if search_term is not None:
+        with stl.spinner(f"retrieving images with description..'{search_term}'"):
+            scores, ret_images = get_images_from_description(finder, search_term)
+            stl.success(f"sucessfully retrieved {len(ret_images)} images")
+            
+except Exception as e:
+    stl.error(e)
 
 try:
     for count, score, image in tqdm(zip(range(len(ret_images)), scores, ret_images)):