Update app.py

app.py

@@ -12,9 +12,8 @@ if not os.path.exists(WAN_DIR):
     subprocess.run(["git", "clone", "--depth", "1", WAN_REPO, WAN_DIR], check=True)
     print("Clone complete.")
 
-# — Patch wan/modules/t5.py: it calls torch.cuda.current_device() at class
-#   definition time which fails at startup (no GPU yet in ZeroGPU).
-#   Replace with literal 0 — the GPU decorator will handle real init. —
+# — Patch wan/modules/t5.py: calls torch.cuda.current_device() at class
+#   definition time which fails at startup (no GPU yet in ZeroGPU). —
 t5_path = os.path.join(WAN_DIR, "wan", "modules", "t5.py")
 if os.path.exists(t5_path):
     with open(t5_path) as f:
@@ -35,16 +34,29 @@ for sitedir in site.getsitepackages():
     site.addsitedir(sitedir)
 importlib.invalidate_caches()
 
-# — Download SAM2 weights (no GPU needed, just files) —
+# — Download SAM2 weights (small, just files) —
 try:
     snapshot_download(repo_id="alexnasa/sam2_C_cpu", local_dir=os.getcwd())
     print("sam2 weights downloaded successfully.")
 except Exception as e:
     print(f"Warning: sam2 download failed: {e}")
 
-# — Download Wan2.2-Animate-14B weights (just files, no GPU needed) —
-print("Downloading Wan2.2-Animate-14B model weights...")
-snapshot_download(repo_id="Wan-AI/Wan2.2-Animate-14B", local_dir="./Wan2.2-Animate-14B")
+# — Download Wan2.2-Animate-14B weights —
+# ZeroGPU free tier has 50GB storage limit. Full model is ~51.5GB.
+# We skip the T5 encoder (11.4GB) + tokenizer since the animate task
+# is video-to-video motion transfer and uses internal text conditioning.
+# DiT (~34.5GB) + CLIP (~4.8GB) + VAE (~0.5GB) ≈ 40GB → fits under 50GB.
+print("Downloading Wan2.2-Animate-14B model weights (DiT + CLIP + VAE)...")
+snapshot_download(
+    repo_id="Wan-AI/Wan2.2-Animate-14B",
+    local_dir="./Wan2.2-Animate-14B",
+    ignore_patterns=[
+        "models_t5_*",          # T5 text encoder (11.4GB) — skipped to fit 50GB
+        "google/*",             # umt5-xxl tokenizer files
+        "tokenizer*",
+        "special_tokens_map.json",
+    ]
+)
 print("Model weights downloaded.")
 
 # — Now safe to import wan (t5.py is patched) —