Update app.py

app.py

@@ -19,8 +19,7 @@ import gradio as gr
 import joblib
 import numpy as np
 import pandas as pd
-from concrete.ml.sklearn import FHEModel  # type: ignore
-
+# concrete-ml import kaldırıldı; model joblib ile doğrudan yükleniyor.
 # -----------------------------------------------------------------------------
 # PATHS & CONSTANTS
 # -----------------------------------------------------------------------------
@@ -51,9 +50,8 @@ SELECTED_FEATS = [
 # -----------------------------------------------------------------------------
 # LOAD MODELS / ENCODER
 # -----------------------------------------------------------------------------
-FHE_MODEL: FHEModel = joblib.load(FHE_MODEL_PATH)
-if not getattr(FHE_MODEL, "is_compiled", False):
-    FHE_MODEL.compile(np.zeros((1, len(SELECTED_FEATS)), dtype=np.float32))
+# Compiled FHE model doğrudan yüklenir.
+FHE_MODEL = joblib.load(FHE_MODEL_PATH)  # type: ignore), dtype=np.float32))
 
 PIPE: Any
 ENC: Any
@@ -89,6 +87,11 @@ _b64_load = lambda txt: joblib.loads(base64.b64decode(txt.encode()))
 
 encrypted_pred_state = gr.State(value=None)
 
+# helper: gerekli FHE metodlarının varlığını hızlıca kontrol et
+for fn in ("keygen", "encrypt", "run", "decrypt"):
+    if not hasattr(FHE_MODEL, fn):
+        raise AttributeError(f"FHE model eksik metod: {fn}")
+
 
 def encrypt_and_predict(excel_file: gr.File):
     if excel_file is None: