fix

app.py

@@ -265,7 +265,7 @@ def split_image(image: Image.Image) -> List[Image.Image]:
         images.append(Image.fromarray(image[:, s:e+1]))
     return [preprocess_image(image) for image in images]
 
-@spaces.GPU
+@spaces.GPU(api_name="quick_generate_glb")
 def quick_generate_glb(
     image: Image.Image,
     multiimages: List[Tuple[Image.Image, str]],
@@ -341,7 +341,8 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
             with gr.Row():
                 extract_glb_btn = gr.Button("Extract GLB", interactive=False)
                 extract_gs_btn = gr.Button("Extract Gaussian", interactive=False)
-                generate_glb_btn = gr.Button("Quick Generate GLB")
+                generate_glb_btn = gr.Button("Quick Generate GLB in layout")
+                quick_generate_glb_btn = gr.Button("Quick Generate GLB with download")
             gr.Markdown("""
                         *NOTE: Gaussian file can be very large (~50MB), it will take a while to display and download.*
                         """)
@@ -472,6 +473,28 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
         lambda: gr.update(interactive=True),
         outputs=[download_glb]
     )
+
+    quick_generate_glb_btn.click(
+        fn=quick_generate_glb,
+        inputs=[
+            image_input,
+            gr.State([]),  # multiimages
+            gr.State(False),  # is_multiimage
+            gr.State(0),  # seed
+            gr.State(7.5),  # ss_guidance_strength
+            gr.State(12),  # ss_sampling_steps
+            gr.State(3.0),  # slat_guidance_strength
+            gr.State(12),  # slat_sampling_steps
+            gr.State("stochastic"),  # multiimage_algo
+            gr.State(0.95),  # mesh_simplify
+            gr.State(1024),  # texture_size
+        ],
+        outputs=[model_output, glb_download],
+        api_name="quick_generate_glb"
+    )
+
+
+
     
 
 # Launch the Gradio app
@@ -482,4 +505,4 @@ if __name__ == "__main__":
         pipeline.preprocess_image(Image.fromarray(np.zeros((512, 512, 3), dtype=np.uint8)))    # Preload rembg
     except:
         pass
-    demo.launch(show_error=True)
+    demo.launch(show_error=True,show_api=True)