Upload app.py

app.py

@@ -138,13 +138,10 @@ def recommend_books(target_book: str, num_recommendations: int = 10) -> str:
 
     target_book = target_book.lower()
     # Fuzzy match the input to the closest book title
-    closest_match, score = process.extractOne(target_book, book_titles)
+    closest_match = process.extractOne(target_book, book_titles)
 
-    if score < 50:  # threshold
-        return f"No close match found for '{target_book}'. Please try a different title."
 
-
-    correlations = compute_correlations_faiss(faiss_index, normalized_data, book_titles, closest_match)
+    correlations = compute_correlations_faiss(faiss_index, book_titles, closest_match)
 
     recommendations = correlations[correlations['book'] != target_book].head(num_recommendations)