fix model CP

ANNOTATE/web/app.py

@@ -245,7 +245,9 @@ class AnnotationDashboard:
             return best_checkpoint
             
         except Exception as e:
-            logger.debug(f"Error getting checkpoint info for {model_name}: {e}")
+            logger.error(f"Error getting checkpoint info for {model_name}: {e}")
+            import traceback
+            logger.error(traceback.format_exc())
             return None
     
     def _load_model_lazy(self, model_name: str) -> dict:
@@ -1280,6 +1282,7 @@ class AnnotationDashboard:
                 # Don't call training_adapter.get_available_models() as it may return objects
                 
                 # Build model state dict with checkpoint info
+                logger.info(f"Building model states for {len(self.available_models)} models: {self.available_models}")
                 model_states = []
                 for model_name in self.available_models:
                     is_loaded = model_name in self.loaded_models
@@ -1303,9 +1306,13 @@ class AnnotationDashboard:
                     
                     # If not loaded, try to read best checkpoint from disk
                     if not checkpoint_info:
-                        checkpoint_info = self._get_best_checkpoint_info(model_name)
-                        if checkpoint_info:
-                            checkpoint_info['source'] = 'disk'
+                        try:
+                            checkpoint_info = self._get_best_checkpoint_info(model_name)
+                            if checkpoint_info:
+                                checkpoint_info['source'] = 'disk'
+                        except Exception as e:
+                            logger.error(f"Error reading checkpoint for {model_name}: {e}")
+                            # Continue without checkpoint info
                     
                     model_states.append({
                         'name': model_name,
@@ -1315,6 +1322,7 @@ class AnnotationDashboard:
                         'checkpoint': checkpoint_info  # Checkpoint metadata (loaded or from disk)
                     })
                 
+                logger.info(f"Returning {len(model_states)} model states")
                 return jsonify({
                     'success': True,
                     'models': model_states,

test_checkpoint_reading.py

@@ -0,0 +1,67 @@
+#!/usr/bin/env python3
+"""Test checkpoint reading without loading models"""
+
+import os
+import glob
+import torch
+
+def test_checkpoint_reading():
+    """Test reading checkpoint info from disk"""
+    
+    checkpoint_dirs = {
+        'Transformer': 'models/checkpoints/transformer',
+        'CNN': 'models/checkpoints/enhanced_cnn',
+        'DQN': 'models/checkpoints/dqn_agent'
+    }
+    
+    for model_name, checkpoint_dir in checkpoint_dirs.items():
+        print(f"\n{model_name}:")
+        print(f"  Directory: {checkpoint_dir}")
+        print(f"  Exists: {os.path.exists(checkpoint_dir)}")
+        
+        if not os.path.exists(checkpoint_dir):
+            print(f"  ❌ Directory not found")
+            continue
+        
+        # Find checkpoint files
+        checkpoint_files = glob.glob(os.path.join(checkpoint_dir, '*.pt'))
+        print(f"  Checkpoints found: {len(checkpoint_files)}")
+        
+        if not checkpoint_files:
+            print(f"  ❌ No checkpoint files")
+            continue
+        
+        # Try to load best checkpoint
+        best_checkpoint = None
+        best_accuracy = -1
+        
+        for cp_file in checkpoint_files:
+            try:
+                print(f"    Loading: {os.path.basename(cp_file)}")
+                checkpoint = torch.load(cp_file, map_location='cpu')
+                
+                epoch = checkpoint.get('epoch', 0)
+                loss = checkpoint.get('loss', 0.0)
+                accuracy = checkpoint.get('accuracy', 0.0)
+                
+                print(f"      Epoch: {epoch}, Loss: {loss:.6f}, Accuracy: {accuracy:.2%}")
+                
+                if accuracy > best_accuracy:
+                    best_accuracy = accuracy
+                    best_checkpoint = {
+                        'filename': os.path.basename(cp_file),
+                        'epoch': epoch,
+                        'loss': loss,
+                        'accuracy': accuracy
+                    }
+            except Exception as e:
+                print(f"      ❌ Error: {e}")
+        
+        if best_checkpoint:
+            print(f"  ✅ Best: {best_checkpoint['filename']}")
+            print(f"     Epoch: {best_checkpoint['epoch']}, Loss: {best_checkpoint['loss']:.6f}, Accuracy: {best_checkpoint['accuracy']:.2%}")
+        else:
+            print(f"  ❌ No valid checkpoint found")
+
+if __name__ == '__main__':
+    test_checkpoint_reading()