Update app.py

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import pandas as pd
 from core.data import load_data
 from core.model_runner import get_model
-from core.plot import plot_forecast, plot_metrics_precision, plot_metrics_risk, plot_loss_curve, plot_future_forecast
+from core.plot import plot_forecast, plot_metrics_precision, plot_metrics_risk, plot_loss_curve, plot_future_forecast, plot_model_architecture
 from config import AVAILABLE_MODELS, DEFAULT_TICKERS
 
 
@@ -31,6 +31,7 @@ def main_interface():
                 dropout = gr.Slider(0.0, 0.3, label="Drop Out", value=0.2)
                 window_size = gr.Slider(5, 90, label="Window Size", value=30)
                 test_split = gr.Slider(0.05, 0.5, label="Test Split", value=0.2)
+                scheduler_factor = gr.Slider(0.1, 0.9, label="Scheduler Factor (LR Reduction)", value=0.5, step=0.1)
 
                 run_btn = gr.Button("🚀 Train & Predict")
                 status = gr.Textbox(label="Status", interactive=False, lines=2)
@@ -39,13 +40,14 @@ def main_interface():
                 backtest_plot = gr.Plot(label="📊 Backtesting: Actual vs Forecast")
                 future_plot = gr.Plot(label="🔮 Future Forecast with Actuals")
                 future_table = gr.Dataframe(label="📋 Future Predictions")
-                precision_plot = gr.Plot(label="📉 Precision Metrics (Model Accuracy: R², Explained Variance, MDA)")
-                risk_plot = gr.Plot(label="📉 Risk Metrics (Error Magnitude: RMSE, MAE, MAPE, MASE)")
+                precision_plot = gr.Plot(label="📉 Precision Metrics (Model Accuracy: R² (%), Explained Variance (%), MDA (%))")
+                risk_plot = gr.Plot(label="📉 Risk Metrics (Error Magnitude: RMSE, MAE, MAPE (%), MASE)")
                 loss_plot = gr.Plot(label="📈 Training Loss Curve")
+                architecture_plot = gr.Plot(label="🧠 Model Architecture")
 
         def run_pipeline(data_src, ticker, file_upload, start_date, end_date, horizon, model,
                         hidden_units, n_layers, epochs, learning_rate, beta1, beta2, weight_decay,
-                        dropout, window_size, test_split):
+                        dropout, window_size, test_split, scheduler_factor):
             try:
                 pd.to_datetime(start_date)
                 pd.to_datetime(end_date)
@@ -54,7 +56,7 @@ def main_interface():
                 main_df, future_df = load_data(data_src=source_key, ticker=ticker, file_upload=file_upload, 
                                              start=start_date, end=end_date, horizon=horizon)
                 if main_df is None or main_df.empty:
-                    return None, None, None, None, None, None, "❌ Failed to load data. Please check input."
+                    return None, None, None, None, None, None, None, "❌ Failed to load data. Please check input."
 
                 result = get_model(
                     df=main_df,
@@ -70,13 +72,15 @@ def main_interface():
                     weight_decay=weight_decay,
                     dropout=dropout,
                     window_size=window_size,
-                    test_split=test_split
+                    test_split=test_split,
+                    scheduler_factor=scheduler_factor
                 )
                 forecast_plot = plot_forecast(result)
                 future_plot = plot_future_forecast(main_df, result, future_df)
                 precision_plot = plot_metrics_precision(result)
                 risk_plot = plot_metrics_risk(result)
                 loss_plot = plot_loss_curve(result)
+                architecture_plot = plot_model_architecture(result)
 
                 msg = "✅ Done."
                 if "latest_prediction" in result:
@@ -90,9 +94,9 @@ def main_interface():
                 else:
                     future_df_out = pd.DataFrame()
 
-                return forecast_plot, future_plot, future_df_out, precision_plot, risk_plot, loss_plot, msg
+                return forecast_plot, future_plot, future_df_out, precision_plot, risk_plot, loss_plot, architecture_plot, msg
             except Exception as e:
-                return None, None, None, None, None, None, f"❌ Error: {str(e)}"
+                return None, None, None, None, None, None, None, f"❌ Error: {str(e)}"
 
         run_btn.click(
             fn=run_pipeline,
@@ -100,9 +104,9 @@ def main_interface():
                 data_src, ticker, file_upload,
                 start_date, end_date, horizon, model,
                 hidden_units, n_layers, epochs, learning_rate,
-                beta1, beta2, weight_decay, dropout, window_size, test_split
+                beta1, beta2, weight_decay, dropout, window_size, test_split, scheduler_factor
             ],
-            outputs=[backtest_plot, future_plot, future_table, precision_plot, risk_plot, loss_plot, status]
+            outputs=[backtest_plot, future_plot, future_table, precision_plot, risk_plot, loss_plot, architecture_plot, status]
         )
 
         def toggle_file(src):