Update app.py

app.py

@@ -21,11 +21,11 @@ class VectorStore:
     # Method to populate the vector store with embeddings from a dataset
     def populate_vectors(self, dataset):
         # Select the text columns to concatenate
-        title = dataset['train']['title_cleaned'][:5000]  # Limiting to 100 examples for the demo
-        recipe = dataset['train']['recipe_new'][:5000]
-        meal_type = dataset['train']['meal_type'][:5000]
-        allergy = dataset['train']['allergy_type'][:5000]
-        ingredients_alternative = dataset['train']['ingredients_alternatives'][:5000]
+        title = dataset['train']['title_cleaned'][:2500]  # Limiting to 100 examples for the demo
+        recipe = dataset['train']['recipe_new'][:2500]
+        meal_type = dataset['train']['meal_type'][:2500]
+        allergy = dataset['train']['allergy_type'][:2500]
+        ingredients_alternative = dataset['train']['ingredients_alternatives'][:2500]
 
         # Concatenate the text from both columns
         texts = [f"{tit} {rep} {meal} {alle} {ingr} " for tit, rep, meal,alle, ingr in zip(title,recipe,meal_type,allergy,ingredients_alternative)]