Update app.py

app.py

@@ -41,7 +41,9 @@ class VectorStore:
     # Method to populate the vector store with embeddings from a dataset
     def populate_vectors(self, dataset, batch_size=100):
         # Use dataset streaming
-        dataset = load_dataset('Thefoodprocessor/recipe_new_with_features_full', split='train[:1500]', streaming=True)
+        #dataset = load_dataset('Thefoodprocessor/recipe_new_with_features_full', split='train[:1500]', streaming=True)
+        dataset = load_dataset('Thefoodprocessor/recipe_new_with_features_full', split='train')
+        dataset = dataset.select(range(1500))  # Select the first 1500 examples
 
         texts = []
         i = 0  # Initialize index