Fix ZeroGPU pickling error: save files inside @spaces.GPU function

The Gaussian object contains lambdas that can't be pickled across
the multiprocessing boundary. Move all file I/O into _run_pipeline
so only paths/numbers are returned.

app.py

@@ -118,9 +118,14 @@ async def get_example(idx: int):
 # ----------------------------------------------------------------------------
 
 @spaces.GPU
-def _run_pipeline(pil_image, seed, steps, guidance_scale, num_gaussians):
-    """Run the full pipeline (preprocess → encode → sample → decode)
-    in a single GPU acquisition."""
+def _run_pipeline(pil_image, seed, steps, guidance_scale, num_gaussians,
+                  out_dir, output_format):
+    """Run the full pipeline (preprocess → encode → sample → decode → save)
+    in a single GPU acquisition.
+
+    All file I/O happens here so the unpicklable Gaussian object never
+    crosses the ZeroGPU multiprocessing boundary.
+    """
     t0 = time.time()
     prepared = PIPE.preprocess_image(pil_image)
     gen = torch.Generator(device=PIPE._device).manual_seed(int(seed))
@@ -134,7 +139,27 @@ def _run_pipeline(pil_image, seed, steps, guidance_scale, num_gaussians):
     )
     gaussian = PIPE.decode_latent(out["latent"], num_gaussians=int(num_gaussians))
     gen_dt = time.time() - t0
-    return prepared, gaussian, gen_dt
+
+    # Save preprocessed image
+    prep_path = out_dir / "preprocessed.png"
+    prepared.save(str(prep_path))
+
+    # Save PLY (always needed for the viewer)
+    ply_path = out_dir / "splat.ply"
+    gaussian.save_ply(str(ply_path))
+
+    # Save in the requested download format
+    fmt = output_format.lower()
+    if fmt == "splat":
+        download_path = out_dir / "splat.splat"
+        gaussian.save_splat(str(download_path))
+    else:
+        download_path = ply_path
+
+    n_gaussians = gaussian.get_xyz.shape[0]
+
+    # Return only picklable primitives / paths
+    return str(prep_path), str(ply_path), str(download_path), n_gaussians, gen_dt
 
 
 # ----------------------------------------------------------------------------
@@ -157,38 +182,23 @@ def generate(
     """
     pil_image = Image.open(image["path"]).convert("RGBA")
 
-    prepared, gaussian, gen_dt = _run_pipeline(
-        pil_image, seed, steps, guidance_scale, num_gaussians,
-    )
-
     out_dir = OUT_ROOT / uuid4().hex[:12]
     out_dir.mkdir(parents=True, exist_ok=True)
 
-    # Save preprocessed image
-    prep_path = out_dir / "preprocessed.png"
-    prepared.save(str(prep_path))
-
-    # Save PLY (always needed for the viewer)
-    ply_path = out_dir / "splat.ply"
-    gaussian.save_ply(str(ply_path))
-
-    # Save in the requested download format
-    fmt = output_format.lower()
-    if fmt == "splat":
-        download_path = out_dir / "splat.splat"
-        gaussian.save_splat(str(download_path))
-    else:
-        download_path = ply_path
+    prep_path, ply_path, download_path, n_gaussians, gen_dt = _run_pipeline(
+        pil_image, seed, steps, guidance_scale, num_gaussians,
+        out_dir, output_format,
+    )
 
     info = (
-        f"{gaussian.get_xyz.shape[0]:,} gaussians  ·  "
-        f"generation: {gen_dt:.1f}s  ·  saved: {download_path.name}"
+        f"{n_gaussians:,} gaussians  ·  "
+        f"generation: {gen_dt:.1f}s  ·  saved: {Path(download_path).name}"
     )
 
     return (
-        FileData(path=str(prep_path)),
-        FileData(path=str(ply_path)),
-        FileData(path=str(download_path)),
+        FileData(path=prep_path),
+        FileData(path=ply_path),
+        FileData(path=download_path),
         info,
     )