feat: auto-download SelVA weights on first use

Uses selva_core/utils/download_utils.py (already has URLs + MD5s for all
weights). Models download to models/selva/ on first load. Synchformer reuses
models/prismaudio/synchformer_state_dict.pth if already present (no duplicate
download for PrismAudio users), otherwise downloads to models/selva/.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

nodes/selva_model_loader.py

@@ -1,4 +1,5 @@
 import os
+from pathlib import Path
 import torch
 import folder_paths
 
@@ -12,17 +13,26 @@ _VARIANTS = {
     "large_44k":  ("generator_large_44k_sup_5.pth",  "44k", False),
 }
 
-_SELVA_DIR = os.path.join(folder_paths.models_dir, "selva")
+_SELVA_DIR = Path(folder_paths.models_dir) / "selva"
+_PRISMAUDIO_DIR = Path(folder_paths.models_dir) / "prismaudio"
 
 
-def _selva_path(*parts):
+def _ensure(filename, subdir=None):
-    return os.path.join(_SELVA_DIR, *parts)
+    """Return path to weight file, downloading it if missing."""
+    from selva_core.utils.download_utils import download_model_if_needed
+    dest_dir = _SELVA_DIR / subdir if subdir else _SELVA_DIR
+    path = dest_dir / filename
+    download_model_if_needed(path)
+    return str(path)
 
 
-def _require(path, hint):
+def _synchformer_path():
-    if not os.path.exists(path):
+    """Return synchformer path, reusing models/prismaudio/ if already present."""
-        raise RuntimeError(f"[SelVA] Missing: {path}\n{hint}")
+    prismaudio_path = _PRISMAUDIO_DIR / "synchformer_state_dict.pth"
-    return path
+    if prismaudio_path.exists():
+        return str(prismaudio_path)
+    # Not downloaded for PrismAudio yet — download to models/selva/
+    return _ensure("synchformer_state_dict.pth")
 
 
 class SelvaModelLoader:
@@ -53,29 +63,12 @@ class SelvaModelLoader:
         strategy = determine_offload_strategy(offload_strategy)
         device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
-        # Resolve weight paths
+        print("[SelVA] Resolving weights (auto-downloading if missing)...", flush=True)
-        video_enc_path = _require(
+        video_enc_path = _ensure("video_enc_sup_5.pth")
-            _selva_path("video_enc_sup_5.pth"),
+        gen_path       = _ensure(gen_filename)
-            "Download from https://huggingface.co/jnwnlee/selva and place in models/selva/"
+        vae_path       = _ensure(f"v1-{mode}.pth", subdir="ext")
-        )
+        synch_path     = _synchformer_path()
-        gen_path = _require(
+        bigvgan_path   = _ensure("best_netG.pt", subdir="ext") if has_bigvgan else None
-            _selva_path(gen_filename),
-            f"Download {gen_filename} from https://huggingface.co/jnwnlee/selva and place in models/selva/"
-        )
-        vae_path = _require(
-            _selva_path("ext", f"v1-{mode}.pth"),
-            f"Download v1-{mode}.pth from MMAudio/SelVA release and place in models/selva/ext/"
-        )
-        synch_path = _require(
-            os.path.join(folder_paths.models_dir, "prismaudio", "synchformer_state_dict.pth"),
-            "Synchformer checkpoint missing from models/prismaudio/ — download from FunAudioLLM/PrismAudio"
-        )
-        bigvgan_path = None
-        if has_bigvgan:
-            bigvgan_path = _require(
-                _selva_path("ext", "best_netG.pt"),
-                "Download best_netG.pt (BigVGAN 16k vocoder) from MMAudio release and place in models/selva/ext/"
-            )
 
         print(f"[SelVA] Loading TextSynch from {video_enc_path}", flush=True)
         net_video_enc = get_my_textsynch("depth1").to(device, dtype).eval()