Update app.py

app.py

@@ -974,7 +974,7 @@ def Create_Graph_Tool(
 # MAIN ORCHESTRATION WORKFLOW
 # ============================================================================
 
-def orchestrate_turn(user_input: str, session_id: str = "default") -> str:
+def orchestrate_turn(user_input: str, conversation_history: list = None, session_id: str = "default") -> str:
     """
     Main orchestration function implementing the redesign workflow.
     
@@ -1008,9 +1008,12 @@ def orchestrate_turn(user_input: str, session_id: str = "default") -> str:
         # ====================================================================
         step_start = log_step("Step 2: Process user input")
         
-        # Get conversation history
-        conversation_state = global_state_manager.get_conversation_state(session_id)
-        conversation_history = conversation_state['conversation_state'][-8:] if conversation_state['conversation_state'] else []
+        # Use conversation_history passed from Gradio state (no global state call)
+        if conversation_history is None:
+            conversation_history = []
+        
+        # Take last 8 messages
+        conversation_history = conversation_history[-8:] if conversation_history else []
         
         # Format history for agents
         conversation_history_formatted = "\n".join([
@@ -1409,7 +1412,7 @@ def generate_response(chat_history, conversation_state):
     try:
         # Call orchestration
         orch_start = log_step("orchestrate_turn call")
-        raw_response = orchestrate_turn(last_user_message)
+        raw_response = orchestrate_turn(last_user_message, conversation_state)
         log_step("orchestrate_turn call", orch_start)
         
         # Stream the processed response
@@ -1437,8 +1440,10 @@ def generate_response(chat_history, conversation_state):
         final_response = chunk if 'chunk' in locals() else raw_response
         new_conversation_state = conversation_state + [{"role": "assistant", "content": final_response}]
         
-        # Update global state with final conversation
-        # global_state_manager.update_conversation_state(chat_history, new_conversation_state)
+        threading.Thread(
+            target=lambda: global_state_manager.update_conversation_state(chat_history, new_conversation_state),
+            daemon=True
+        ).start()
         
         # Final yield with complete states
         yield chat_history, new_conversation_state