Update app.py

let's see if this works a bit simpler implementation

app.py

@@ -110,9 +110,9 @@ def image_to_3d(
     slat_guidance_strength: float,
     slat_sampling_steps: int,
     req: gr.Request,
-) -> Tuple[dict, str, str]:
+) -> Tuple[dict, str]:
     """
-    Convert an image to a 3D model and generate a GLB file.
+    Convert an image to a 3D model.
 
     Args:
         image (Image.Image): The input image.
@@ -124,7 +124,7 @@ def image_to_3d(
         req (gr.Request): Gradio request object.
 
     Returns:
-        Tuple[dict, str, str]: The state dictionary, path to the generated video, and path to the standard GLB file.
+        Tuple[dict, str]: The state dictionary and the path to the generated video.
     """
     user_dir = os.path.join(TMP_DIR, str(req.session_hash))
     outputs = pipeline.run(
@@ -148,20 +148,8 @@ def image_to_3d(
     video_path = os.path.join(user_dir, f"{trial_id}.mp4")
     imageio.mimsave(video_path, video, fps=15)
     state = pack_state(outputs['gaussian'][0], outputs['mesh'][0], trial_id)
-    
-    # Generate standard GLB file with default simplification and texture size
-    glb = postprocessing_utils.to_glb(
-        outputs['gaussian'][0],
-        outputs['mesh'][0],
-        simplify=0.95,          # Default simplification
-        texture_size=1024,      # Default texture size
-        verbose=False
-    )
-    glb_path = os.path.join(user_dir, f"{trial_id}.glb")
-    glb.export(glb_path)
-    
     torch.cuda.empty_cache()
-    return state, video_path, glb_path
+    return state, video_path
 
 # Existing GLB Extraction Function
 @spaces.GPU
@@ -170,7 +158,7 @@ def extract_glb(
     mesh_simplify: float,
     texture_size: int,
     req: gr.Request,
-) -> Tuple[dict, bytes]:
+) -> Tuple[str, str]:
     """
     Extract a GLB file from the 3D model.
 
@@ -181,31 +169,22 @@ def extract_glb(
         req (gr.Request): Gradio request object.
 
     Returns:
-        Tuple[dict, bytes]: The model state and the GLB file bytes.
+        Tuple[str, str]: The path to the extracted GLB file.
     """
     user_dir = os.path.join(TMP_DIR, str(req.session_hash))
     gs, mesh, trial_id = unpack_state(state)
-    glb = postprocessing_utils.to_glb(
-        gs,
-        mesh,
-        simplify=mesh_simplify,
-        texture_size=texture_size,
-        verbose=False
-    )
+    glb = postprocessing_utils.to_glb(gs, mesh, simplify=mesh_simplify, texture_size=texture_size, verbose=False)
     glb_path = os.path.join(user_dir, f"{trial_id}.glb")
     glb.export(glb_path)
-    # Read the GLB file as bytes
-    with open(glb_path, "rb") as f:
-        glb_bytes = f.read()
     torch.cuda.empty_cache()
-    return state, glb_bytes
+    return glb_path, glb_path
 
-# New High-Quality GLB Extraction Function
+# **New High-Quality GLB Extraction Function**
 @spaces.GPU
 def extract_glb_high_quality(
     state: dict,
     req: gr.Request,
-) -> Tuple[dict, bytes]:
+) -> Tuple[str, str]:
     """
     Extract a high-quality GLB file from the 3D model without polygon reduction.
 
@@ -214,37 +193,27 @@ def extract_glb_high_quality(
         req (gr.Request): Gradio request object.
 
     Returns:
-        Tuple[dict, bytes]: The model state and the high-quality GLB file bytes.
+        Tuple[str, str]: The path to the high-quality GLB file.
     """
     user_dir = os.path.join(TMP_DIR, str(req.session_hash))
     gs, mesh, trial_id = unpack_state(state)
     # Set simplify to 0.0 to disable polygon reduction
     # Set texture_size to 2048 for maximum texture quality
-    glb = postprocessing_utils.to_glb(
-        gs,
-        mesh,
-        simplify=0.0,
-        texture_size=2048,
-        verbose=False
-    )
+    glb = postprocessing_utils.to_glb(gs, mesh, simplify=0.0, texture_size=2048, verbose=False)
     glb_path = os.path.join(user_dir, f"{trial_id}_high_quality.glb")
     glb.export(glb_path)
-    # Read the GLB file as bytes
-    with open(glb_path, "rb") as f:
-        glb_bytes = f.read()
     torch.cuda.empty_cache()
-    return state, glb_bytes
+    return glb_path, glb_path
 
 # Gradio Interface Definition
 with gr.Blocks(delete_cache=(600, 600)) as demo:
     gr.Markdown("""
     ## Image to 3D Asset with [TRELLIS](https://trellis3d.github.io/)
-    * **Generate:** Upload an image and click "Generate" to create a 3D asset. If the image has an alpha channel, it will be used as the mask. Otherwise, the background will be removed automatically.
-    * **Extract GLB:** If the generated 3D asset is satisfactory, click "Extract GLB" to extract the GLB file based on your chosen settings and download it.
-    * **Download High Quality GLB:** Click this button to download a high-quality GLB file without any polygon reduction and with maximum texture quality.
-    * **Status:** View messages and feedback about your actions below.
+    * Upload an image and click "Generate" to create a 3D asset. If the image has an alpha channel, it will be used as the mask. Otherwise, the background will be removed automatically.
+    * If you find the generated 3D asset satisfactory, click "Extract GLB" to extract the GLB file and download it.
+    * **New:** Click "Download High Quality GLB" to download the GLB file without any polygon reduction and with maximum texture quality.
     """)
-    
+
     with gr.Row():
         with gr.Column():
             # Image Input
@@ -322,12 +291,12 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
                     step=512
                 )
             
-            # Extract GLB Button
-            extract_glb_btn = gr.Button("Extract GLB")
+            # Existing Extract GLB Button
+            extract_glb_btn = gr.Button("Extract GLB", interactive=True)
             
-            # Download High Quality GLB Button
-            download_glb_high_quality_btn = gr.Button("Download High Quality GLB")
-        
+            # **New Download High Quality GLB Button**
+            download_high_quality_glb_btn = gr.Button("Download High Quality GLB", interactive=True)
+
         with gr.Column():
             # Video Output
             video_output = gr.Video(
@@ -342,26 +311,21 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
                 exposure=20.0,
                 height=300
             )
-            # Download GLB Buttons
+            # Existing Download GLB Button
             download_glb = gr.DownloadButton(
-                label="Download GLB"
+                label="Download GLB",
+                file_count="single",
             )
+            # **New Download High Quality GLB Button**
             download_high_quality_glb = gr.DownloadButton(
-                label="Download High Quality GLB"
-            )
-            
-            # Status Message
-            status_message = gr.Textbox(
-                label="Status",
-                value="Awaiting your action...",
-                interactive=False,
-                lines=2
+                label="Download High Quality GLB",
+                file_count="single",
             )
 
     # State Variables
     output_buf = gr.State()
-    glb_bytes_state = gr.State()  # For standard GLB
-    glb_high_quality_bytes_state = gr.State()  # For high-quality GLB
+    glb_path_state = gr.State()  # For standard GLB
+    glb_high_quality_path_state = gr.State()  # For high-quality GLB
 
     # Example Images
     with gr.Row():
@@ -403,57 +367,44 @@ with gr.Blocks(delete_cache=(600, 600)) as demo:
             slat_guidance_strength,
             slat_sampling_steps
         ],
-        outputs=[output_buf, video_output, glb_path := gr.State()]
+        outputs=[output_buf, video_output],
     ).then(
-        lambda state, video, glb: "Generation successful! You can now extract and download GLB files.",
-        inputs=[output_buf, video_output, glb_path],
-        outputs=[status_message]
+        lambda: gr.Button.update(interactive=True),
+        outputs=[extract_glb_btn, download_high_quality_glb_btn],
     )
 
-    # Extract GLB Button Click Handler
+    # Existing Extract GLB Button Click Handler
     extract_glb_btn.click(
         extract_glb,
         inputs=[output_buf, mesh_simplify, texture_size],
-        outputs=[output_buf, glb_bytes_state],
+        outputs=[model_output, glb_path_state],
     ).then(
-        # Map the GLB bytes to the DownloadButton with filename
-        lambda state, glb_bytes: (glb_bytes, "model.glb"),
-        inputs=[output_buf, glb_bytes_state],
+        lambda glb_path: glb_path if glb_path else "",
+        inputs=[glb_path_state],
         outputs=[download_glb],
-    ).then(
-        # Update status message
-        lambda: "GLB extraction successful! Click 'Download GLB' to save your model.",
-        inputs=None,
-        outputs=[status_message]
     )
 
-    # Download High Quality GLB Button Click Handler
-    download_glb_high_quality_btn.click(
+    # **New Download High Quality GLB Button Click Handler**
+    download_high_quality_glb_btn.click(
         extract_glb_high_quality,
         inputs=[output_buf],
-        outputs=[output_buf, glb_high_quality_bytes_state],
+        outputs=[model_output, glb_high_quality_path_state],
     ).then(
-        # Map the high-quality GLB bytes to the DownloadButton with filename
-        lambda state, glb_bytes: (glb_bytes, "model_high_quality.glb"),
-        inputs=[output_buf, glb_high_quality_bytes_state],
+        lambda glb_path: glb_path if glb_path else "",
+        inputs=[glb_high_quality_path_state],
         outputs=[download_high_quality_glb],
-    ).then(
-        # Update status message
-        lambda: "High-quality GLB extraction successful! Click 'Download High Quality GLB' to save your model.",
-        inputs=None,
-        outputs=[status_message]
     )
 
     # Handle Clearing of Video Output
     video_output.clear(
-        lambda: "Video output cleared. Please generate a new 3D asset.",
-        outputs=[status_message],
+        lambda: (gr.Button.update(interactive=True), gr.Button.update(interactive=True)),
+        outputs=[extract_glb_btn, download_high_quality_glb_btn],
     )
 
     # Handle Clearing of Model Output
     model_output.clear(
-        lambda: "Model output cleared. Please extract and download GLB files again.",
-        outputs=[status_message],
+        lambda: (gr.File.update(value=None), gr.File.update(value=None)),
+        outputs=[download_glb, download_high_quality_glb],
     )
 
 # Launch the Gradio app
@@ -465,4 +416,4 @@ if __name__ == "__main__":
         pipeline.preprocess_image(Image.fromarray(np.zeros((512, 512, 3), dtype=np.uint8)))    # Preload rembg
     except:
         pass
-    demo.launch()
+    demo.queue(concurrency_count=1, max_size=10).launch()