Add MCP compatibility

app.py

@@ -62,6 +62,16 @@ model.load_state_dict(ckpt_dict, strict=True)
 
 # get random seed
 def get_random_seed(randomize_seed, seed):
+    """
+    Generate or return a random seed based on user preferences.
+    
+    Args:
+        randomize_seed (bool): Whether to generate a new random seed
+        seed (int): The current seed value
+        
+    Returns:
+        int: New random seed if randomize_seed is True, otherwise returns the input seed
+    """
     if randomize_seed:
         seed = np.random.randint(0, MAX_SEED)
     return seed
@@ -69,6 +79,15 @@ def get_random_seed(randomize_seed, seed):
 # process image
 @spaces.GPU(duration=10)
 def process_image(image_path):
+    """
+    Process input image by removing background, recentering, and resizing.
+    
+    Args:
+        image_path (str): Path to the input image file
+        
+    Returns:
+        numpy.ndarray: Processed RGBA image array of size (518, 518, 4)
+    """
     image = cv2.imread(image_path, cv2.IMREAD_UNCHANGED)
     if image.shape[-1] == 4:
         image = cv2.cvtColor(image, cv2.COLOR_BGRA2RGBA)
@@ -84,6 +103,21 @@ def process_image(image_path):
 # process generation
 @spaces.GPU(duration=90)
 def process_3d(input_image, num_steps=50, cfg_scale=7, grid_res=384, seed=42, simplify_mesh=False, target_num_faces=100000):
+    """
+    Generate 3D mesh from input image using PartPacker model.
+    
+    Args:
+        input_image (numpy.ndarray): Processed RGBA input image
+        num_steps (int): Number of inference steps for generation
+        cfg_scale (float): Classifier-free guidance scale
+        grid_res (int): Grid resolution for mesh extraction
+        seed (int): Random seed for reproducibility
+        simplify_mesh (bool): Whether to simplify the output mesh
+        target_num_faces (int): Target number of faces if simplifying mesh
+        
+    Returns:
+        str: Path to the generated GLB file containing the 3D mesh
+    """
 
     # seed
     kiui.seed_everything(seed)
@@ -216,4 +250,4 @@ with block:
         process_3d, inputs=[seg_image, num_steps, cfg_scale, input_grid_res, seed, simplify_mesh, target_num_faces], outputs=[output_model]
     )
 
-block.launch(ssr_mode=False)
+block.launch(ssr_mode=False, mcp_server=True)