attempts model loading fix

app.py

@@ -37,44 +37,19 @@ class LOperatorDemo:
             if not HF_TOKEN:
                 return "❌ HF_TOKEN not found. Please set HF_TOKEN in Spaces secrets."
             
-            try:
-                # Try loading with standard approach
-                self.processor = AutoProcessor.from_pretrained(
-                    MODEL_ID, 
-                    trust_remote_code=True,
-                    token=HF_TOKEN
-                )
-                
-                self.model = AutoModelForImageTextToText.from_pretrained(
-                    MODEL_ID,
-                    torch_dtype=torch.bfloat16 if DEVICE == "cuda" else torch.float32,
-                    trust_remote_code=True,
-                    device_map="auto" if DEVICE == "cuda" else None,
-                    token=HF_TOKEN
-                )
-                
-            except Exception as e:
-                logger.warning(f"Standard loading failed: {str(e)}")
-                logger.info("Attempting fallback loading approach...")
-                
-                # Fallback: try loading with explicit model type
-                self.processor = AutoProcessor.from_pretrained(
-                    MODEL_ID, 
-                    trust_remote_code=True,
-                    token=HF_TOKEN,
-                    revision="main"
-                )
-                
-                self.model = AutoModelForImageTextToText.from_pretrained(
-                    MODEL_ID,
-                    torch_dtype=torch.bfloat16 if DEVICE == "cuda" else torch.float32,
-                    trust_remote_code=True,
-                    device_map="auto" if DEVICE == "cuda" else None,
-                    token=HF_TOKEN,
-                    revision="main",
-                    ignore_mismatched_sizes=True
-                )
-            
+            # Load model following the working example pattern
+            self.model = AutoModelForImageTextToText.from_pretrained(
+                MODEL_ID,
+                device_map="auto",
+                torch_dtype=torch.bfloat16 if DEVICE == "cuda" else torch.float32,
+                trust_remote_code=True
+            )
+
+            # Load processor
+            self.processor = AutoProcessor.from_pretrained(
+                MODEL_ID,
+                trust_remote_code=True
+            )            
             if DEVICE == "cpu":
                 self.model = self.model.to(DEVICE)
             
@@ -207,18 +182,18 @@ print("✅ Model loading completed!")
 
 # Load example episodes
 def load_example_episodes():
-    """Load example episodes from the extracted data"""
+    """Load example episodes from the extracted data with error handling"""
     examples = []
-    
+
     try:
         # Load episode 13
         with open("extracted_episodes_duckdb/episode_13/metadata.json", "r") as f:
             episode_13 = json.load(f)
-        
-        # Load episode 53  
+
+        # Load episode 53
         with open("extracted_episodes_duckdb/episode_53/metadata.json", "r") as f:
             episode_53 = json.load(f)
-        
+
         # Load episode 73
         with open("extracted_episodes_duckdb/episode_73/metadata.json", "r") as f:
             episode_73 = json.load(f)
@@ -227,22 +202,35 @@ def load_example_episodes():
         examples = [
             [
                 "extracted_episodes_duckdb/episode_13/screenshots/screenshot_1.png",
-                "Episode 13: Navigate app interface"
-            ],
-            [
-                "extracted_episodes_duckdb/episode_53/screenshots/screenshot_1.png", 
-                "Episode 53: App interaction example"
-            ],
-            [
+                f"Episode 13: {episode_13.get('goal', 'Navigate app interface')[:50]}..."
+            ),
+            (
+                "extracted_episodes_duckdb/episode_53/screenshots/screenshot_1.png",
+                f"Episode 53: {episode_53.get('goal', 'App interaction example')[:50]}..."
+            ),
+            (
                 "extracted_episodes_duckdb/episode_73/screenshots/screenshot_1.png",
-                "Episode 73: Device control task"
-            ]
+                f"Episode 73: {episode_73.get('goal', 'Device control task')[:50]}..."
+            )
         ]
-        
+
+        # Validate each example by checking if image file exists and is readable
+        for image_path, description in examples:
+            try:
+                # Try to open the image to validate it
+                from PIL import Image
+                with Image.open(image_path) as img:
+                    # If we get here, the image is valid
+                    examples.append([image_path, description])
+            except Exception as img_error:
+                logger.warning(f"Skipping invalid image {image_path}: {str(img_error)}")
+                continue
+
     except Exception as e:
         logger.error(f"Error loading examples: {str(e)}")
         examples = []
-    
+
+    logger.info(f"Loaded {len(examples)} valid examples")
     return examples
 
 # Create Gradio interface