Added the import of the losses

app.py

@@ -15,6 +15,7 @@ from statsforecast.models import (
 )
 
 from utilsforecast.evaluation import evaluate
+from utilsforecast.losses import mae, rmse, bias, mape
 
 # Function to load and process uploaded CSV
 def load_data(file):
@@ -110,7 +111,7 @@ def run_forecast(
     try:
         if eval_strategy == "Cross Validation":
             cv_results = sf.cross_validation(df=df, h=horizon, step_size=step_size, n_windows=num_windows)
-            evaluation = evaluate(df=cv_results, metrics=['me', 'mae', 'rmse', 'mape'], models=model_aliases)
+            evaluation = evaluate(df=cv_results, metrics=['bias', 'mae', 'rmse', 'mape'], models=model_aliases)
             eval_df = pd.DataFrame(evaluation).reset_index()
             fig_forecast = create_forecast_plot(cv_results, df)
             return eval_df, cv_results, fig_forecast, "Cross validation completed successfully!"
@@ -207,4 +208,4 @@ with gr.Blocks(title="StatsForecast Demo") as app:
     )
 
 if __name__ == "__main__":
-    app.launch(share=True)
+    app.launch(share=False)