Fix model loading error: Add proper fallback handling for llava_model

joycaption_app.py

@@ -16,17 +16,16 @@ from pathlib import Path
 
 # Initialize the JoyCaption model
 print("Loading JoyCaption model...")
+model_name = "fancyfeast/llama-joycaption-alpha-two-hf-llava"
+
 try:
-    # Model configuration for optimal performance
-    model_name = "fancyfeast/llama-joycaption-alpha-two-hf-llava"
-    
     # Load processor and model with correct configuration
     processor = AutoProcessor.from_pretrained(model_name)
     
     # Load model with bfloat16 (native dtype of Llama 3.1)
     llava_model = LlavaForConditionalGeneration.from_pretrained(
-        model_name, 
-        torch_dtype="bfloat16", 
+        model_name,
+        torch_dtype="bfloat16",
         device_map="auto" if torch.cuda.is_available() else None
     )
     llava_model.eval()
@@ -35,9 +34,10 @@ try:
     
 except Exception as e:
     print(f"Error loading model: {e}")
-    # Create a fallback function for when model loading fails
-    def process_image_with_caption(*args, **kwargs):
-        return "Error: Model not loaded. Please check the model availability."
+    # Create fallback objects when model loading fails
+    processor = None
+    llava_model = None
+    print("Using fallback mode - model not available")
 
 @spaces.GPU
 def generate_image_caption(image_file, prompt_type="formal_detailed", custom_prompt=""):
@@ -52,6 +52,10 @@ def generate_image_caption(image_file, prompt_type="formal_detailed", custom_pro
     Returns:
         str: Generated image caption
     """
+    # Check if model is available
+    if llava_model is None or processor is None:
+        return "Error: JoyCaption model not loaded. Please check the model availability and try again."
+    
     try:
         if not image_file:
             return "Please upload an image file."