Delete model_runtime.py

model_runtime.py

@@ -1,54 +0,0 @@
-from __future__ import annotations
-
-import os
-from pathlib import Path
-from typing import Callable
-
-from huggingface_hub import snapshot_download
-
-TARGET_OMNI_MODEL = os.getenv("PB3D_TARGET_MODEL", "tencent/Hunyuan3D-Omni")
-DEFAULT_CACHE_ROOT = Path(os.getenv("PB3D_MODEL_CACHE", "./models"))
-
-
-def get_target_model_dir(model_id: str = TARGET_OMNI_MODEL) -> Path:
-    safe = model_id.replace("/", "--")
-    return DEFAULT_CACHE_ROOT / safe
-
-
-def ensure_target_model_cached(
-    model_id: str = TARGET_OMNI_MODEL,
-    progress: Callable[[str], None] | None = None,
-) -> dict:
-    """
-    Best-effort local cache of the upstream target model repo.
-
-    This fetches the model repo into the Space filesystem so later integration work
-    can call the upstream inference stack directly. It does not assume internal file
-    names beyond the official repo id.
-    """
-    target_dir = get_target_model_dir(model_id)
-    target_dir.mkdir(parents=True, exist_ok=True)
-
-    if progress:
-        progress(f"Checking local cache for {model_id}…")
-
-    try:
-        local_path = snapshot_download(
-            repo_id=model_id,
-            local_dir=str(target_dir),
-            local_dir_use_symlinks=False,
-            resume_download=True,
-        )
-        return {
-            "ok": True,
-            "model_id": model_id,
-            "local_path": local_path,
-            "message": f"Cached {model_id} in {local_path}",
-        }
-    except Exception as exc:  # pragma: no cover
-        return {
-            "ok": False,
-            "model_id": model_id,
-            "local_path": str(target_dir),
-            "message": f"Could not cache {model_id}: {exc}",
-        }