debug: Add callback chain debugging to InferencePipeline and WorkflowOrchestrator

- Add debug output in InferencePipeline result callback to see if it's called
- Add debug output in WorkflowOrchestrator handle_result to trace callback flow
- This will help identify exactly where the callback chain is breaking
- Previous test showed GUI can receive signals but callbacks aren't triggered

cluster4npu_ui/core/functions/InferencePipeline.py

@@ -485,7 +485,10 @@ class InferencePipeline:
                         
                         # Call result callback
                         if self.result_callback:
+                            print(f"🔍 PIPELINE DEBUG: Calling result_callback with: {current_data}")
                             self.result_callback(current_data)
+                        else:
+                            print(f"🔍 PIPELINE DEBUG: No result_callback set!")
                             
                     except queue.Full:
                         # Drop oldest and add new

cluster4npu_ui/core/functions/workflow_orchestrator.py

@@ -159,6 +159,9 @@ class WorkflowOrchestrator:
         """
         Callback function to handle results from the pipeline.
         """
+        print(f"🔍 ORCHESTRATOR DEBUG: handle_result called with: {result_data}")
+        print(f"🔍 ORCHESTRATOR DEBUG: result_callback is: {self.result_callback}")
+        
         if self.result_handler:
             try:
                 # Convert PipelineData to a dictionary for serialization