Update app.py

app.py

@@ -127,33 +127,34 @@ def predict_eurusd():
         next_day_preds, ensemble_pred = predict_next_day(models, scaler, df, feature_cols)
         
         # Mevcut fiyat
-        current_price = df['Close'].iloc[-1]
+        current_price = float(df['Close'].iloc[-1])
         
         # Sonuçları hazırla
-        result = f"""
-🔄 **GÜNCELLEME ZAMANI:** {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
+        result = f"""🔄 GÜNCELLEME ZAMANI: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
 
-📊 **MEVCUT EUR/USD FİYATI:** {current_price:.5f}
+📊 MEVCUT EUR/USD FİYATI: {current_price:.5f}
 
-🎯 **ERTESİ GÜN TAHMİNLERİ:**
+🎯 ERTESİ GÜN TAHMİNLERİ:
 
 """
         
         for model_name, pred in next_day_preds.items():
-            change = ((pred - current_price) / current_price) * 100
+            pred_value = float(pred)
+            change = ((pred_value - current_price) / current_price) * 100
             arrow = "📈" if change > 0 else "📉"
-            result += f"{arrow} **{model_name}:** {pred:.5f} ({change:+.2f}%)\n"
+            result += f"{arrow} {model_name}: {pred_value:.5f} ({change:+.2f}%)\n"
         
-        ensemble_change = ((ensemble_pred - current_price) / current_price) * 100
+        ensemble_pred_value = float(ensemble_pred)
+        ensemble_change = ((ensemble_pred_value - current_price) / current_price) * 100
         ensemble_arrow = "📈" if ensemble_change > 0 else "📉"
         
-        result += f"\n{ensemble_arrow} **🏆 ENSEMBLE ORTALAMA:** {ensemble_pred:.5f} ({ensemble_change:+.2f}%)\n"
+        result += f"\n{ensemble_arrow} 🏆 ENSEMBLE ORTALAMA: {ensemble_pred_value:.5f} ({ensemble_change:+.2f}%)\n"
         
         # Model performansları
-        result += f"\n\n📈 **MODEL PERFORMANSLARI (Son 5 Gün):**\n"
+        result += f"\n\n📈 MODEL PERFORMANSLARI (Son 5 Gün):\n"
         for i, (model_name, preds) in enumerate(test_predictions.items()):
-            mse = np.mean((preds - y_test) ** 2)
-            mae = np.mean(np.abs(preds - y_test))
+            mse = float(np.mean((preds - y_test) ** 2))
+            mae = float(np.mean(np.abs(preds - y_test)))
             result += f"• {model_name}: MAE={mae:.5f}, MSE={mse:.8f}\n"
         
         # Grafik için veri hazırla
@@ -162,18 +163,19 @@ def predict_eurusd():
         fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 10))
         
         # Üst grafik: Fiyat geçmişi
-        ax1.plot(df.index[-30:], df['Close'].iloc[-30:], label='Gerçek Fiyat', linewidth=2)
+        last_30_days = df.tail(30)
+        ax1.plot(range(len(last_30_days)), last_30_days['Close'].values, label='Gerçek Fiyat', linewidth=2)
         ax1.axhline(y=current_price, color='gray', linestyle='--', alpha=0.5, label='Mevcut Fiyat')
-        ax1.axhline(y=ensemble_pred, color='red', linestyle='--', alpha=0.7, label='Tahmin')
+        ax1.axhline(y=ensemble_pred_value, color='red', linestyle='--', alpha=0.7, label='Tahmin')
         ax1.set_title('EUR/USD Son 30 Gün Fiyat Hareketi', fontsize=14, fontweight='bold')
-        ax1.set_xlabel('Tarih')
+        ax1.set_xlabel('Gün')
         ax1.set_ylabel('Fiyat')
         ax1.legend()
         ax1.grid(True, alpha=0.3)
         
         # Alt grafik: Model tahminleri karşılaştırması
         model_names = list(next_day_preds.keys())
-        model_values = list(next_day_preds.values())
+        model_values = [float(v) for v in next_day_preds.values()]
         colors = ['#FF6B6B', '#4ECDC4', '#45B7D1', '#FFA07A', '#98D8C8']
         
         bars = ax2.barh(model_names, model_values, color=colors)
@@ -194,7 +196,9 @@ def predict_eurusd():
         return result, fig
         
     except Exception as e:
-        return f"❌ Hata oluştu: {str(e)}", None
+        import traceback
+        error_msg = f"❌ Hata oluştu: {str(e)}\n\n{traceback.format_exc()}"
+        return error_msg, None
 
 # Gradio arayüzü
 with gr.Blocks(title="EUR/USD Fiyat Tahmini", theme=gr.themes.Soft()) as app:
@@ -234,4 +238,3 @@ with gr.Blocks(title="EUR/USD Fiyat Tahmini", theme=gr.themes.Soft()) as app:
 
 if __name__ == "__main__":
     app.launch()
-