Upload utils.py

utils.py

@@ -0,0 +1,58 @@
+def process_all_vision_info(messages, examples=None):
+    """
+    Process vision information from both messages and in-context examples, supporting batch processing.
+    
+    Args:
+        messages: List of message dictionaries (single input) OR list of message lists (batch input)
+        examples: Optional list of example dictionaries (single input) OR list of example lists (batch)
+    
+    Returns:
+        A flat list of all images in the correct order:
+        - For single input: example images followed by message images
+        - For batch input: interleaved as (item1 examples, item1 input, item2 examples, item2 input, etc.)
+        - Returns None if no images were found
+    """
+    from qwen_vl_utils import process_vision_info, fetch_image
+    
+    # Helper function to extract images from examples
+    def extract_example_images(example_item):
+        if not example_item:
+            return []
+            
+        # Handle both list of examples and single example
+        examples_to_process = example_item if isinstance(example_item, list) else [example_item]
+        images = []
+        
+        for example in examples_to_process:
+            if isinstance(example.get('input'), dict) and example['input'].get('type') == 'image':
+                images.append(fetch_image(example['input']))
+                
+        return images
+    
+    # Normalize inputs to always be batched format
+    is_batch = messages and isinstance(messages[0], list)
+    messages_batch = messages if is_batch else [messages]
+    is_batch_examples = examples and isinstance(examples, list) and (isinstance(examples[0], list) or examples[0] is None)
+    examples_batch = examples if is_batch_examples else ([examples] if examples is not None else None)
+    
+    # Ensure examples batch matches messages batch if provided
+    if examples and len(examples_batch) != len(messages_batch):
+        if not is_batch and len(examples_batch) == 1:
+            # Single example set for a single input is fine
+            pass
+        else:
+            raise ValueError("Examples batch length must match messages batch length")
+    
+    # Process all inputs, maintaining correct order
+    all_images = []
+    for i, message_group in enumerate(messages_batch):
+        # Get example images for this input
+        if examples and i < len(examples_batch):
+            input_example_images = extract_example_images(examples_batch[i])
+            all_images.extend(input_example_images)
+        
+        # Get message images for this input
+        input_message_images = process_vision_info(message_group)[0] or []
+        all_images.extend(input_message_images)
+    
+    return all_images if all_images else None