Update app.py

app.py

@@ -353,32 +353,31 @@ def extract_problem_domains(df,
             # top_words = [feature_names[index] for index in top_word_indices]
             # cluster_representations[i] = top_words
 
+
             try:
                 center = kmeans.cluster_centers_[i]
                 console_messages.append(f"Processing cluster {i}")
                 console_messages.append(f"Center shape: {center.shape}, type: {type(center)}")
                 
-
-                if isinstance(center, np.ndarray) and center.ndim == 1:
-                    # Ensure center.argsort() returns a numpy array
-                    sorted_indices = center.argsort()
-                    if isinstance(sorted_indices, np.ndarray):
-                        sorted_indices = sorted_indices.tolist()
+                if not isinstance(center, np.ndarray):
+                    center = np.array(center)
                     
-                    # Extract top word indices
-                    top_word_indices = sorted_indices[-top_words:][::-1]
+                sorted_indices = center.argsort()
+                if isinstance(sorted_indices, list):
+                    sorted_indices = np.array(sorted_indices)
                     
-                    # Debug output
-                    console_messages.append(f"Sorted indices: {sorted_indices}")
-                    console_messages.append(f"Top word indices for cluster {i}: {top_word_indices}")
-    
-                    top_words = [feature_names[index] for index in top_word_indices]
-                    console_messages.append(f"Top words: {top_words}")
-                    cluster_representations[i] = top_words
-                else:
-                    console_messages.append(f"Error: Cluster center is not a 1D array for cluster {i}")
+                top_word_indices = sorted_indices[-top_words:][::-1]
+
                     
+                # Debug output
+                console_messages.append(f"Sorted indices: {sorted_indices}")
+                console_messages.append(f"Top word indices for cluster {i}: {top_word_indices}")
+
+                top_words = [feature_names[index] for index in top_word_indices]
+                console_messages.append(f"Top words: {top_words}")
+                cluster_representations[i] = top_words
                 
+
                 
             except Exception as e:
                 console_messages.append(f"Error processing cluster {i}: {str(e)}")