fix: Complete array comparison fix and improve stop button functionality

- Fix remaining array comparison error in inference result validation
- Update PyQt signal signature for proper numpy array handling
- Improve DeploymentWorker to keep running after deployment
- Enhance stop button with non-blocking UI updates and better error handling

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

cluster4npu_ui/core/functions/InferencePipeline.py

@@ -227,7 +227,8 @@ class PipelineStage:
                         break
                 time.sleep(0.01)
             
-            if not inference_result:
+            # Check if inference_result is empty (handle both dict and tuple types)
+            if inference_result is None or (isinstance(inference_result, dict) and not inference_result):
                 print(f"[Stage {self.stage_id}] Warning: No inference result received")
                 inference_result = {'probability': 0.0, 'result': 'No Result'}
             

cluster4npu_ui/ui/dialogs/deployment.py

@@ -64,7 +64,7 @@ class DeploymentWorker(QThread):
     deployment_started = pyqtSignal()
     deployment_completed = pyqtSignal(bool, str)  # success, message
     error_occurred = pyqtSignal(str)
-    frame_updated = pyqtSignal(object)  # For live view
+    frame_updated = pyqtSignal('PyQt_PyObject')  # For live view
     
     def __init__(self, pipeline_data: Dict[str, Any]):
         super().__init__()
@@ -136,6 +136,10 @@ class DeploymentWorker(QThread):
                 self.progress_updated.emit(100, "Pipeline deployed successfully!")
                 self.deployment_completed.emit(True, f"Pipeline '{config.pipeline_name}' deployed with {len(config.stage_configs)} stages")
                 
+                # Keep running until stop is requested
+                while not self.should_stop:
+                    self.msleep(100)  # Sleep for 100ms and check again
+                
             except Exception as e:
                 self.error_occurred.emit(f"Pipeline deployment failed: {str(e)}")
                 
@@ -533,20 +537,30 @@ Stage Configurations:
             if reply == QMessageBox.Yes:
                 self.deployment_log.append("Stopping inference...")
                 self.status_label.setText("Stopping inference...")
-                self.deployment_worker.stop()
-                self.deployment_worker.wait(3000)  # Wait up to 3 seconds
                 
-                # Update UI
+                # Disable stop button immediately to prevent multiple clicks
                 self.stop_button.setEnabled(False)
+                
+                self.deployment_worker.stop()
+                
+                # Wait for worker to finish in a separate thread to avoid blocking UI
+                def wait_for_stop():
+                    if self.deployment_worker.wait(5000):  # Wait up to 5 seconds
+                        self.deployment_log.append("Inference stopped successfully.")
+                    else:
+                        self.deployment_log.append("Warning: Inference may not have stopped cleanly.")
+                    
+                    # Update UI on main thread
                     self.stop_button.setVisible(False)
                     self.deploy_button.setEnabled(True)
                     self.close_button.setText("Close")
                     self.progress_bar.setVisible(False)
-                
-                self.deployment_log.append("Inference stopped.")
                     self.status_label.setText("Inference stopped")
                     self.dongle_status.setText("Pipeline stopped")
                 
+                import threading
+                threading.Thread(target=wait_for_stop, daemon=True).start()
+    
     def update_progress(self, value: int, message: str):
         """Update deployment progress."""
         self.progress_bar.setValue(value)