Update app.py

app.py

@@ -252,7 +252,8 @@ def extract_problem_domains(df, text_column='Problem_Description', cluster_range
     # Get representative words for each cluster
     cluster_representations = {}
     for i in range(optimal_n_clusters):
-        cluster_representations[i] = topic_model.get_topic_info(i)['words'][:top_words]
+        # cluster_representations[i] = topic_model.get_topic_info(i)['words'][:top_words]
+        cluster_representations[i] = topic_model.get_topic_info(i).get('words', [])[:top_words]
     
     # Map cluster labels to representative words
     df["Problem_Cluster"] = cluster_labels