Update app.py

app.py

@@ -178,7 +178,10 @@ scaler_sel = MinMaxScaler().fit(X_tr[COLS])
 Xtr_sel = scaler_sel.transform(X_tr[COLS])
 final_model = ConcreteXGBClassifier(n_bits=8, **best_params, random_state=42)
 final_model.fit(Xtr_sel, ytr_e)
-fhe_model = final_model.compile(Xtr_sel)
+fhe_circuit = final_model.compile(Xtr_sel)
+keys = fhe_circuit.keygen()
+serialized_eval_key = keys.evaluation.serialize()
+
 
 
 print("\n🔍 Seçilen Özellikler (%95 etkili):")
@@ -188,11 +191,12 @@ for i, col in enumerate(COLS, 1):
 
 # ------------------------ FONKSİYONLAR ------------------------
 def generate_keys():
-    global fhe_model
-    if fhe_model is None:
-        raise gr.Error("FHE circuit hazır değil.")
-    keys = fhe_model.keygen()
-    return keys.serialize()[:120] + "..."
+    global fhe_circuit, keys
+    if fhe_circuit is None:
+        raise gr.Error("Model henüz derlenmedi.")
+    keys = fhe_circuit.keygen()
+    return keys.evaluation.serialize()[:120].decode() + "..."
+
 
 
 
@@ -204,18 +208,20 @@ def encrypt_excel(file):
     enriched = compute_ratios(raw_df)
     X_input = enriched[COLS].dropna()
     scaled = scaler_sel.transform(X_input)
-    enc_input = fhe_model.encrypt(scaled)
+    enc_input = fhe_circuit.encrypt(scaled, keys.evaluation)
     return str(enc_input)[:150] + "..."
 
+
 def run_fhe():
-    import time
     global enc_output
+    import time
     start = time.time()
-    enc_output = fhe_model.run(enc_input)
+    enc_output = fhe_circuit.run(enc_input)
     return f"{time.time() - start:.2f}"
 
+
 def decrypt_result():
-    y_pred = fhe_model.decrypt(enc_output)
+    y_pred = fhe_circuit.decrypt(enc_output, keys.decryption)
     return encoder.inverse_transform([y_pred])[0]
 
 # -------------------- Gradio UI -------------------- #