Update model.py

model.py

@@ -57,16 +57,26 @@ def get_api() -> Optional[HfApi]:
 def get_model_id() -> str:
     """
     Returns model ID to load.
-    Prefers private fine-tuned model if available, falls back to base model.
+    Prefers private fine-tuned model only if it has actual weights (config.json with model_type).
+    Falls back to base model if private repo is empty or not ready.
     """
     api = get_api()
     if api and PRIVATE_MODEL:
         try:
-            api.model_info(PRIVATE_MODEL, token=TOKEN)
-            logger.info(f"Using private model: {PRIVATE_MODEL}")
-            return PRIVATE_MODEL
-        except Exception:
-            logger.info(f"Private model not ready — using base: {MODEL_REPO}")
+            files = api.list_repo_files(PRIVATE_MODEL, repo_type="model", token=TOKEN)
+            has_config = "config.json" in list(files)
+            if has_config:
+                # Double-check it's a real model config, not just a README
+                from huggingface_hub import hf_hub_download
+                import json
+                cfg_path = hf_hub_download(PRIVATE_MODEL, "config.json", token=TOKEN)
+                cfg = json.loads(open(cfg_path).read())
+                if "model_type" in cfg:
+                    logger.info(f"Using private model: {PRIVATE_MODEL}")
+                    return PRIVATE_MODEL
+            logger.info(f"Private repo exists but has no weights yet — using base: {MODEL_REPO}")
+        except Exception as e:
+            logger.info(f"Private model check failed ({type(e).__name__}) — using base: {MODEL_REPO}")
     return MODEL_REPO
 
 
@@ -176,4 +186,4 @@ def status() -> dict:
         "private_model": PRIVATE_MODEL,
         "dataset_repo":  DATASET_REPO,
         "hf_api":        "authenticated" if get_api() else "unauthenticated",
-    }
+    }