Update app.py

app.py

@@ -50,15 +50,22 @@ class Model:
         self.pipe.to(self.device)
         # Ensure the text encoder is in half precision to avoid dtype mismatches.
         if torch.cuda.is_available():
-            self.pipe.text_encoder = self.pipe.text_encoder.half()
+            try:
+                self.pipe.text_encoder = self.pipe.text_encoder.half()
+            except AttributeError:
+                pass
 
         self.pipe_img = ShapEImg2ImgPipeline.from_pretrained("openai/shap-e-img2img", torch_dtype=torch.float16)
         self.pipe_img.to(self.device)
+        # Use getattr with a default value to avoid AttributeError if text_encoder is missing.
         if torch.cuda.is_available():
-            self.pipe_img.text_encoder = self.pipe_img.text_encoder.half()
+            text_encoder_img = getattr(self.pipe_img, "text_encoder", None)
+            if text_encoder_img is not None:
+                self.pipe_img.text_encoder = text_encoder_img.half()
 
     def to_glb(self, ply_path: str) -> str:
         mesh = trimesh.load(ply_path)
+        # Rotate the mesh for proper orientation
         rot = trimesh.transformations.rotation_matrix(-np.pi / 2, [1, 0, 0])
         mesh.apply_transform(rot)
         rot = trimesh.transformations.rotation_matrix(np.pi, [0, 1, 0])
@@ -447,4 +454,4 @@ demo = gr.ChatInterface(
 
 if __name__ == "__main__":
     # To create a public link, set share=True in launch().
-    demo.queue(max_size=20).launch(share=True)
+    demo.queue(max_size=20).launch(share=True)