update models 1.5-2

models.py

@@ -1,7 +1,7 @@
 import torch
 import numpy as np
 import pandas as pd
-from chronos_forecasting.pipeline import BaseChronosPipeline # Corrected import path
+from chronos import BaseChronosPipeline # <--- PERBAIKAN: Impor langsung dari 'chronos'
 import warnings
 warnings.filterwarnings('ignore')
 
@@ -39,15 +39,14 @@ def predict_stock_prices(model_pipeline, data, forecast_horizon):
         # Konversi data numpy mentah ke tensor float32 (standar PyTorch)
         context_tensor = torch.tensor(data, dtype=torch.float32)
         
-        # Chronos memprediksi sebagai sampel kuantil. Kita ambil mediannya (point forecast).
+        # Chronos Pipeline expects context as a list of tensors
         raw_forecasts = model_pipeline.predict(
             context=[context_tensor], 
             prediction_length=forecast_horizon,
-            num_samples=20 # Mengambil 20 sampel untuk mendapatkan perkiraan median
+            num_samples=20 
         )
         
         # Ambil median dari semua sampel (axis=0) untuk mendapatkan point forecast
-        # raw_forecasts[0] is of shape (num_samples, prediction_length)
         point_forecast = np.median(raw_forecasts[0].cpu().numpy(), axis=0)
         
         return point_forecast