Update app.py

change app.py req

app.py

@@ -1,49 +1,57 @@
 import torch
 import gradio as gr
-from shap_e.diffusion.sample import sample_latents
 from shap_e.models.download import load_model
+from shap_e.diffusion.sample import sample_latents
 from shap_e.util.notebooks import decode_latent_mesh
 from PIL import Image
 
 # pick device
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-# load models once
+# Load Shap-E models
 print("Loading Shap-E models (this may take a bit)...")
-xm = load_model('transmitter', device=device)
-im_model = load_model('image300M', device=device)
+transmitter_model = load_model("transmitter", device=device)
+image_model = load_model("image300M", device=device)
 
-def generate_3d(image):
-    """Takes an uploaded image and returns path to generated 3D model"""
+def generate_3d(image: Image.Image):
+    """Takes an uploaded image and returns path to generated 3D model (.obj)"""
     img = image.convert("RGB")
 
-    # generate latents
+    # Sample latents (updated for latest Shap-E API)
     latents = sample_latents(
         batch_size=1,
-        model=im_model,
-        guidance_scale=3.0,
+        model=image_model,
         model_kwargs=dict(images=[img]),
+        diffusion=None,
+        clip_denoised=True,
+        use_fp16=False,
+        use_karras=True,
+        karras_steps=64,
+        sigma_min=0.002,
+        sigma_max=80,
+        s_churn=0.0,
+        guidance_scale=3.0,
         device=device
     )
 
-    # decode into mesh
-    mesh = decode_latent_mesh(xm, latents[0])
+    # Decode into mesh
+    mesh = decode_latent_mesh(transmitter_model, latents[0])
 
-    # save model
+    # Save output
     output_path = "output.obj"
     with open(output_path, "w") as f:
         mesh.write_obj(f)
 
     return output_path
 
-# Gradio UI
+# Gradio interface
 demo = gr.Interface(
     fn=generate_3d,
     inputs=gr.Image(type="pil"),
-    outputs=gr.File(),
+    outputs=gr.File(file_types=[".obj"]),
     title="Shap-E: 2D → 3D Model",
     description="Upload a 2D image and download a generated 3D model (.obj)"
 )
 
 if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)
+    demo.launch(server_name="0.0.0.0", server_port=7860, share=True)