Update app.py

app.py

@@ -42,17 +42,24 @@ class VectorStore:
 
     def populate_vectors(self, dataset):
         # Sélectionner les colonnes pertinentes à concaténer
-        names = dataset['train']['name'][:200]
-        ingredients = dataset['train']['ingredients'][:200]
-        instructions = dataset['train']['instructions'][:200]
+        titles = dataset['train']['title'][:2000]
+        servings = dataset['train']['servings'][:2000]
+        total_times = dataset['train']['total_time'][:2000]
+        courses = dataset['train']['course'][:2000]
+        sections = dataset['train']['sections'][:2000]
+        instructions = dataset['train']['instructions'][:2000]
+        cuisines = dataset['train']['cuisine'][:2000]
+        calories = dataset['train']['calories'][:2000]
         
-        cuisine = dataset['train']['cuisine'][:200]
-        total_time = dataset['train']['total_time'][:200]
-
         # Concaténer les textes à partir des colonnes sélectionnées
         texts = [
-            f"Name: {name}. Ingredients: {ingr}. Instructions: {instr}. Cuisine: {cui}. Total time: {total} minutes."
-            for name, ingr, instr, cui, total in zip(names, ingredients, instructions, cuisine, total_time)
+            f"Title: {title}. Servings: {serving}. Total Time: {total_time} minutes. "
+            f"Course: {course}. Sections: {section}. Instructions: {instruction}. "
+            f"Cuisine: {cuisine}. Calories: {calorie}."
+            for title, serving, total_time, course, section, instruction, cuisine, calorie 
+            in zip(titles, servings, total_times, courses, sections, instructions, cuisines, calories)
+]
+        
                    
         ]
 
@@ -67,7 +74,7 @@ class VectorStore:
         return results['documents']
 
 # Initialisation du store de vecteurs et peuplement
-dataset = load_dataset('Maryem2025/dataset-test')
+dataset = load_dataset("Maryem2025/final_dataset")
 vector_store = VectorStore("embedding_vector")
 vector_store.populate_vectors(dataset)