add mcp support

app.py

@@ -54,13 +54,33 @@ def imagelist_to_pptx(img_files):
         return tmp.name
 
 def export_gallery(images):
-    # images: list of image file paths
+    """
+    Export gallery images to a PowerPoint file.
+
+    Args:
+        images (list):
+            List of tuples containing (file_path, _) for each image.
+
+    Returns:
+        str:
+            Path to the generated PPTX file.
+    """
     images = [e[0] for e in images]
     pptx_path = imagelist_to_pptx(images)
     return pptx_path
 
 def export_gallery_zip(images):
-    # images: list of tuples (file_path, caption)
+    """
+    Export gallery images to a ZIP archive.
+
+    Args:
+        images (list):
+            List of tuples containing (file_path, _) for each image.
+
+    Returns:
+        str:
+            Path to the generated ZIP file containing all images.
+    """
     images = [e[0] for e in images]
     
     with tempfile.NamedTemporaryFile(suffix=".zip", delete=False) as tmp:
@@ -73,20 +93,65 @@ def export_gallery_zip(images):
         return tmp.name
 
 @spaces.GPU(duration=180)
-def infer(input_image,
-          seed=777,
-          randomize_seed=False,
-          prompt=None,
-          neg_prompt=" ",
-          true_guidance_scale=4.0,
-          num_inference_steps=50,
-          layer=4,
-          cfg_norm=True,
-          use_en_prompt=True):
-    
+def infer(
+    input_image,
+    seed: int = 777,
+    randomize_seed: bool = False,
+    prompt: str = None,
+    neg_prompt: str = " ",
+    true_guidance_scale: float = 4.0,
+    num_inference_steps: int = 50,
+    layer: int = 4,
+    cfg_norm: bool = True,
+    use_en_prompt: bool = True
+):
+    """
+    Decompose an image into multiple layers using Qwen-Image-Layered.
+
+    Takes an input image and separates it into distinct visual layers,
+    useful for design, editing, or creating layered presentations.
+
+    Args:
+        input_image (PIL.Image.Image):
+            The input image to decompose. Can be a PIL Image, file path,
+            or numpy array.
+        seed (int, optional):
+            Random seed for reproducible generation. Ignored if
+            `randomize_seed=True`. Defaults to 777.
+        randomize_seed (bool, optional):
+            If True, a random seed is chosen per call. Defaults to False.
+        prompt (str, optional):
+            Text prompt describing the overall content of the image,
+            including elements that may be partially occluded.
+            Defaults to None.
+        neg_prompt (str, optional):
+            Negative prompt to guide what to avoid in generation.
+            Defaults to " ".
+        true_guidance_scale (float, optional):
+            Guidance scale controlling prompt adherence. Higher values
+            follow the prompt more strictly. Defaults to 4.0.
+        num_inference_steps (int, optional):
+            Number of denoising steps. More steps generally produce
+            better quality but take longer. Defaults to 50.
+        layer (int, optional):
+            Number of layers to decompose the image into (2-10).
+            Defaults to 4.
+        cfg_norm (bool, optional):
+            Whether to enable CFG normalization. Defaults to True.
+        use_en_prompt (bool, optional):
+            If True, uses English for automatic captioning when no prompt
+            is provided. If False, uses Chinese. Defaults to True.
+
+    Returns:
+        Tuple[List[PIL.Image.Image], str, str]:
+            - List of decomposed layer images (from background to foreground).
+            - Path to the generated PPTX file containing all layers.
+            - Path to the generated ZIP file containing all layer images.
+    """
     if randomize_seed:
         seed = random.randint(0, MAX_SEED)
         
+        
     if isinstance(input_image, list):
         input_image = input_image[0]
         
@@ -251,5 +316,7 @@ with gr.Blocks() as demo:
         outputs=[gallery, export_file, export_zip_file],
     )
 
+    gr.api(infer, api_name="decompose_image")
+
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch(mcp_server=True, footer_links=["api", "gradio", "settings"])