Update app.py

app.py

@@ -16,24 +16,11 @@ import matplotlib
 matplotlib.use("Agg")
 import matplotlib.pyplot as plt
 from matplotlib.ticker import FuncFormatter
+from huggingface_hub import hf_hub_download
 
 import plotly.graph_objects as go
 from sklearn.metrics import mean_squared_error
 
-repo_id = "Smart-Thinking/minstress_model"
-model_file = "minstress_model/minstress_model.joblib"
-meta_file  = "minstress_model/minstress_meta.json"
-token = os.environ.get("AUTH_TOKEN", "") or (
-    st.secrets.get("AUTH_TOKEN", "") if hasattr(st, "secrets") else ""
-)
-
-model_path = hf_hub_download(repo_id=repo_id, filename=model_file, token=token)
-model = joblib.load(model_path)
-
-meta_path = hf_hub_download(repo_id=repo_id, filename=meta_file, token=token)
-with open(meta_path, "r", encoding="utf-8") as f:
-    meta = json.load(f)
-
 
 # =========================
 # App constants / defaults
@@ -502,10 +489,14 @@ def _hf_token() -> str:
     return os.environ.get("AUTH_TOKEN", "") or (st.secrets.get("AUTH_TOKEN", "") if hasattr(st, "secrets") else "")
 
 def _model_file() -> str:
-    return os.environ.get("MODEL_FILE", "") or (st.secrets.get("MODEL_FILE", "") if hasattr(st, "secrets") else "") or "minstress_model.joblib"
+    return (os.environ.get("MODEL_FILE", "")
+            or (st.secrets.get("MODEL_FILE", "") if hasattr(st, "secrets") else "")
+            or "minstress_model/minstress_model.joblib")
 
 def _meta_file() -> str:
-    return os.environ.get("META_FILE", "") or (st.secrets.get("META_FILE", "") if hasattr(st, "secrets") else "") or "minstress_meta.json"
+    return (os.environ.get("META_FILE", "")
+            or (st.secrets.get("META_FILE", "") if hasattr(st, "secrets") else "")
+            or "minstress_model/minstress_meta.json")
 
 @st.cache_resource(show_spinner=False)
 def load_model_from_hub_or_local() -> object: