Update app.py

app.py

@@ -405,6 +405,8 @@ def create_project_proposals(budget_cluster_df, problem_cluster_df, location_clu
     consoleMessage_and_Print("\n Starting function: create_project_proposals")
     proposals = {}
 
+    sanban_debug = False
+    
     for loc in budget_cluster_df.index:
         consoleMessage_and_Print(f"\n loc: {loc}")
         
@@ -436,8 +438,15 @@ def create_project_proposals(budget_cluster_df, problem_cluster_df, location_clu
                 # Check if proposal is valid
                 if isinstance(proposal, str) and proposal.strip():  # Valid string that's not empty
                     proposals[(loc, prob)] = proposal
+                    
+                    sanban_debug = True
+                    break
+                    
             else:
                 print(f"Skipping empty problem descriptions for location: {location}, problem domain: {problem_domain}")
+        
+        if sanban_debug:
+            break
     
     return proposals
         
@@ -609,27 +618,82 @@ def process_excel(file):
         consoleMessage_and_Print("Processing the DataFrame...")
         processed_df, budget_cluster_df, problem_cluster_df, project_proposals, location_clusters, problem_clusters = nlp_pipeline(df)
         # processed_df, budget_cluster_df, problem_cluster_df, location_clusters, problem_clusters  = nlp_pipeline(df)
+
+        consoleMessage_and_Print("Error was here")
+        #This code first converts the dictionary to a DataFrame with a single column for the composite key.
+        #Then, it splits the composite key into separate columns for Location_Cluster and Problem_Cluster.
+        #Finally, it reorders the columns and writes the DataFrame to an Excel sheet.
+        try: # Meta AI Solution
+            # Convert project_proposals dictionary to DataFrame
+            project_proposals_df = pd.DataFrame(list(project_proposals.items()), columns=['Location_Cluster_Problem_Cluster', 'Solutions Proposed'])
+            consoleMessage_and_Print("CheckPoint 1")
+            
+            # Split the composite key into separate columns
+            project_proposals_df[['Location_Cluster', 'Problem_Cluster']] = project_proposals_df['Location_Cluster_Problem_Cluster'].apply(pd.Series)
+            consoleMessage_and_Print("CheckPoint 2")
+            
+            # Drop the composite key column
+            project_proposals_df.drop('Location_Cluster_Problem_Cluster', axis=1, inplace=True)
+            consoleMessage_and_Print("CheckPoint 3")
+    
+            # Reorder the columns
+            project_proposals_df = project_proposals_df[['Location_Cluster', 'Problem_Cluster', 'Solutions Proposed']]
+            consoleMessage_and_Print("CheckPoint 4")
+            
+        except Exception as e:
+            consoleMessage_and_Print("Meta AI Solution did not work, trying CHATGPT solution")
+            try:
+                
+                # Convert project_proposals dictionary to DataFrame
+                project_proposals_df = pd.DataFrame.from_dict(
+                    proposals, orient='index', columns=['Solutions Proposed']
+                )
+                
+                # If the index is a tuple, it automatically becomes a MultiIndex, so we handle naming correctly:
+                if isinstance(project_proposals_df.index, pd.MultiIndex):
+                    project_proposals_df.index.names = ['Location_Cluster', 'Problem_Cluster']
+                else:
+                    # If for some reason it's not a MultiIndex, we name it appropriately
+                    project_proposals_df.index.name = 'Cluster'
+                
+                # Reset index to have Location_Cluster and Problem_Cluster as columns
+                project_proposals_df.reset_index(inplace=True)
+            
+            except Exception as e:
+                print(e)
+
+            
+
+
+
+
+
+
+        # ### Convert project_proposals dictionary to DataFrame
+        # project_proposals_df = pd.DataFrame.from_dict(project_proposals, orient='index', columns=['Solutions Proposed'])
+        # project_proposals_df.index.names = ['Location_Cluster', 'Problem_Cluster']
+        # project_proposals_df.reset_index(inplace=True)
+
         
-        ### Convert project_proposals dictionary to DataFrame
-        project_proposals_df = pd.DataFrame.from_dict(project_proposals, orient='index', columns=['Solutions Proposed'])
-        project_proposals_df.index.names = ['Location_Cluster', 'Problem_Cluster']
-        project_proposals_df.reset_index(inplace=True)
+
+
+
+
+    
 
         consoleMessage_and_Print("Creating the Excel file.")
         output_filename = "OutPut_PPs.xlsx"
         with pd.ExcelWriter(output_filename) as writer:
+            processed_df.to_excel(writer, sheet_name='Input_Processed', index=False)
             
             try:
                 project_proposals_df.to_excel(writer, sheet_name='Project_Proposals', index=False)
             except Exception as e:
                 consoleMessage_and_Print("Error during Project Proposal excelling at the end")
-                
-                
-            
             
             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)
+