models CKPts auto save

core/orchestrator.py

@@ -7930,6 +7930,42 @@ class TradingOrchestrator:
             logger.error(f"Error initializing checkpoint manager: {e}")
             self.checkpoint_manager = None
 
+    def autosave_models(self):
+        """Attempt to autosave best model checkpoints periodically."""
+        try:
+            if not self.checkpoint_manager:
+                return
+            # CNN autosave when current_loss equals best_loss
+            try:
+                cnn_stats = self.model_states.get('cnn', {})
+                if cnn_stats and cnn_stats.get('current_loss') is not None:
+                    if cnn_stats.get('best_loss') is not None and cnn_stats['current_loss'] <= cnn_stats['best_loss']:
+                        path = self.checkpoint_manager.save_model_checkpoint(
+                            model_name='enhanced_cnn',
+                            model=self.cnn_model,
+                            metrics={'loss': float(cnn_stats['current_loss'])},
+                            metadata={'source': 'autosave'}
+                        )
+                        if path:
+                            logger.info(f"Autosaved CNN checkpoint: {path}")
+            except Exception:
+                pass
+            # COB RL autosave
+            try:
+                cob_stats = self.model_states.get('cob_rl', {})
+                if cob_stats and cob_stats.get('current_loss') is not None:
+                    if cob_stats.get('best_loss') is not None and cob_stats['current_loss'] <= cob_stats['best_loss']:
+                        self.checkpoint_manager.save_model_checkpoint(
+                            model_name='cob_rl',
+                            model=self.cob_rl_agent,
+                            metrics={'loss': float(cob_stats['current_loss'])},
+                            metadata={'source': 'autosave'}
+                        )
+            except Exception:
+                pass
+        except Exception as e:
+            logger.debug(f"Autosave models skipped: {e}")
+
     def _schedule_database_cleanup(self):
         """Schedule periodic database cleanup"""
         try:

web/clean_dashboard.py

@@ -958,14 +958,7 @@ class CleanTradingDashboard:
             def update_model_inference_toggle(value):
                 return self._handle_model_toggle(model_name, 'inference', value)
             
-            # Create training toggle callback
-            @self.app.callback(
-                Output(f'{model_name}-training-toggle', 'value'),
-                [Input(f'{model_name}-training-toggle', 'value')],
-                prevent_initial_call=True
-            )
-            def update_model_training_toggle(value):
-                return self._handle_model_toggle(model_name, 'training', value)
+            # Skip training toggle callback registration until components exist in layout
             
             logger.debug(f"Created toggle callbacks for model: {model_name}")