Upload app.py

app.py

@@ -136,6 +136,7 @@ def recommend_books(target_book: str, num_recommendations: int = 10) -> str:
 
     if dataset is None or faiss_index is None or normalized_data is None or book_titles is None:
         load_and_prepare_data()
+        dataset = dataset.drop_duplicates(subset=['ISBN'])
 
     target_book = target_book.lower()
     # Fuzzy match the input to the closest book title
@@ -144,7 +145,7 @@ def recommend_books(target_book: str, num_recommendations: int = 10) -> str:
 
     correlations = compute_correlations_faiss(faiss_index, book_titles, closest_match)
 
-    recommendations = correlations[correlations['book'] != target_book].drop_duplicates(subset=['ISBN'])
+    recommendations = correlations[correlations['book'] != target_book]
 
     recommendations = recommendations.head(num_recommendations)