Update app.py

app.py

@@ -458,9 +458,11 @@ def nlp_pipeline(original_df):
 
 
     
-    return processed_df
-    # # Create cluster dataframes
-    # budget_cluster_df, problem_cluster_df = create_cluster_dataframes(processed_df)
+    
+    # Create cluster dataframes
+    budget_cluster_df, problem_cluster_df = create_cluster_dataframes(processed_df)
+
+    return processed_df, budget_cluster_df
 
     # # # Generate project proposals
     # # location_clusters = dict(enumerate(processed_df['Location_Category_Words'].unique()))
@@ -489,7 +491,7 @@ def process_excel(file):
         # Process the DataFrame
         console_messages.append("Processing the DataFrame...")
         # processed_df, budget_cluster_df, problem_cluster_df, project_proposals, location_clusters, problem_clusters = nlp_pipeline(df)
-        processed_df = nlp_pipeline(df)
+        processed_df , budget_cluster_df = nlp_pipeline(df)
 
         output_filename = "OutPut_PPs.xlsx"
         with pd.ExcelWriter(output_filename) as writer:
@@ -499,7 +501,7 @@ def process_excel(file):
             # project_proposals_df.reset_index(inplace=True)
             # project_proposals_df.to_excel(writer, sheet_name='Project_Proposals', index=False)
             
-            # budget_cluster_df.to_excel(writer, sheet_name='Financial_Weights')
+            budget_cluster_df.to_excel(writer, sheet_name='Financial_Weights')
             # problem_cluster_df.to_excel(writer, sheet_name='Problem_Descriptions')
             processed_df.to_excel(writer, sheet_name='Input_Processed', index=False)