Update app.py

app.py

@@ -7,12 +7,13 @@ import pynndescent
 import numpy as np
 
 # Only runs once when the script is first run.
-#with open("slugs_1024_new.pickle", "rb") as handle:
-#    index = pickle.load(handle)
-
+with open("slugs_1024_new.pickle", "rb") as handle:
+    index = pickle.load(handle)
+'''
 embs= np.load('slugs_embeddings_1024k.npy', 'r')
 index = pynndescent.NNDescent(embs, metric="cosine")
 index.prepare()
+'''
 
 # Load model for computing embeddings.
 feature_extractor = AutoFeatureExtractor.from_pretrained("sasha/autotrain-sea-slug-similarity-2498977005")