Upload app.py with huggingface_hub

app.py

@@ -21,10 +21,14 @@ async def load_model():
         cache_dir = "/tmp/hf_cache"
         os.makedirs(cache_dir, exist_ok=True)
 
+        # Get HF token from environment (set as Space secret)
+        hf_token = os.environ.get("HF_TOKEN")
+
         model_path = hf_hub_download(
             repo_id="emp-admin/headache-predictor-xgboost",
             filename="model.pkl",
-            cache_dir=cache_dir
+            cache_dir=cache_dir,
+            token=hf_token  # Use token for private repo access
         )
         with open(model_path, 'rb') as f:
             model = pickle.load(f)