feat: Enable MCP

app.py

@@ -40,6 +40,25 @@ def sample(
     output_folder: str = "outputs",
     progress=gr.Progress(track_tqdm=True)
 ):
+    """
+    Generate a video from a single image using Stable Video Diffusion.
+    
+    Args:
+        image: Input PIL Image to generate video from
+        seed: Random seed for generation reproducibility
+        randomize_seed: Whether to randomize the seed
+        motion_bucket_id: Controls the amount of motion in the generated video (1-255)
+        fps_id: Frames per second for the output video
+        version: Model version to use
+        cond_aug: Conditioning augmentation strength
+        decoding_t: Number of frames decoded at a time (affects VRAM usage)
+        device: Device to run the model on
+        output_folder: Directory to save the output video
+        progress: Gradio progress tracker
+        
+    Returns:
+        tuple: (video_path, seed) - Path to the generated video and the seed used
+    """
     if image.mode == "RGBA":
         image = image.convert("RGB")
         
@@ -58,6 +77,16 @@ def sample(
     return video_path, seed
 
 def resize_image(image, output_size=(1024, 576)):
+    """
+    Resize and crop an image to the specified output size while maintaining aspect ratio.
+    
+    Args:
+        image: PIL Image to resize
+        output_size: Target size as (width, height) tuple
+        
+    Returns:
+        PIL.Image: Resized and cropped image
+    """
     # Calculate aspect ratios
     target_aspect = output_size[0] / output_size[1]  # Aspect ratio of the desired size
     image_aspect = image.width / image.height  # Aspect ratio of the original image
@@ -125,4 +154,4 @@ with gr.Blocks() as demo:
 
 if __name__ == "__main__":
     #demo.queue(max_size=20, api_open=False)
-    demo.launch(share=True, show_api=False)
+    demo.launch(share=True, show_api=False, mcp_server=True)