Update app.py

app.py

@@ -44,7 +44,7 @@ def find_similar_texts(model_name, input_text):
         distances = euclidean_distances(embedding_matrix, input_embedding).flatten()
         text_embeddings['euclidean_distance'] = distances
         sorted_embeddings = text_embeddings.sort_values(by='euclidean_distance', ascending=True)
-    #    top_five = sorted_embeddings.head(5)[['abstract', 'patent no', 'title']]
+        top_five = sorted_embeddings.head(5)[['abstract', 'patent no', 'title']]
     #    formatted_output = '\n\n'.join([f"<Patent No: {row['patent no']}\nTitle: {row['title']}\nAbstract: {row['abstract']}" for index, row in top_five.iterrows()])
         formatted_output = '\n\n'.join([
         f"<strong>Patent No:</strong> {row['patent no']}<br>"