Update app.py

app.py

@@ -115,7 +115,9 @@ class NearestNeighbors:
                     
 model = CLIPTextModelWithProjection.from_pretrained("Searchium-ai/clip4clip-webvid150k")
 tokenizer = CLIPTokenizer.from_pretrained("Searchium-ai/clip4clip-webvid150k")
-    
+nn_search = NearestNeighbors(n_neighbors=5, metric='binary', rerank_from=100)
+nn_search.fit(np.packbits((ft_visual_features_database > 0.0).astype(bool), axis=1), o_data=ft_visual_features_database)
+
 def search(search_sentence):
     inputs = tokenizer(text=search_sentence , return_tensors="pt")
     outputs = model(input_ids=inputs["input_ids"], attention_mask=inputs["attention_mask"])
@@ -123,11 +125,8 @@ def search(search_sentence):
     # Normalizing the embeddings:
     final_output = outputs[0] / outputs[0].norm(dim=-1, keepdim=True)
     sequence_output = final_output.cpu().detach().numpy()
-    
-    nn_search = NearestNeighbors(n_neighbors=5, metric='binary', rerank_from=100)
-    nn_search.fit(np.packbits((ft_visual_features_database > 0.0).astype(bool), axis=1), o_data=ft_visual_features_database)
-    sims, idxs = nn_search.kneighbors(sequence_output)
-    # print(database_df.iloc[idxs[0]]['contentUrl'])
+        
+    sims, idxs = nn_search.kneighbors(sequence_output)    
     urls = database_df.iloc[idxs[0]]['contentUrl'].to_list()
     AUTOPLAY_VIDEOS = []
     for url in urls: