Guardar mis cambios locales

app.py

@@ -24,15 +24,21 @@ def forecast_sales(uploaded_file, start_date, end_date, forecast_period=30):
     df['Date'] = pd.to_datetime(df['Date'])
     df = df.rename(columns={'Date': 'ds', 'Sale': 'y'})
 
-    # Filtrar los datos según el rango de fechas seleccionado por el usuario
-    df_filtered = df[(df['ds'] >= pd.to_datetime(start_date)) & (df['ds'] <= pd.to_datetime(end_date))]
+    # Filtrar los datos según el rango de fechas introducido por el usuario
+    try:
+        start = pd.to_datetime(start_date)
+        end = pd.to_datetime(end_date)
+    except ValueError:
+        return "Please enter valid dates in YYYY-MM-DD format.", None
+
+    df_filtered = df[(df['ds'] >= start) & (df['ds'] <= end)]
 
     arima_model, error = load_model()
     if arima_model is None:
         return error, None
 
     try:
-        forecast_index = pd.date_range(start=pd.to_datetime(end_date), periods=forecast_period + 1, freq='D')[1:]
+        forecast_index = pd.date_range(start=end, periods=forecast_period + 1, freq='D')[1:]
         forecast = arima_model.get_forecast(steps=forecast_period)
         forecast_df = pd.DataFrame({'Date': forecast_index, 'Sales Forecast': forecast.predicted_mean})
     except Exception as e:
@@ -40,9 +46,7 @@ def forecast_sales(uploaded_file, start_date, end_date, forecast_period=30):
 
     try:
         fig, ax = plt.subplots(figsize=(10, 6))
-        # Dibujar las ventas actuales en rojo
         ax.plot(df_filtered['ds'], df_filtered['y'], label='Actual Sales', color='red')
-        # Dibujar la predicción en azul
         ax.plot(forecast_df['Date'], forecast_df['Sales Forecast'], label='Sales Forecast', color='blue', linestyle='--')
         ax.set_xlabel('Date')
         ax.set_ylabel('Sales')
@@ -56,8 +60,8 @@ def setup_interface():
     with gr.Blocks() as demo:
         gr.Markdown("## MLCast v1.1 - Intelligent Sales Forecasting System")
         file_input = gr.File(label="Upload your store data here (must contain Date and Sales)")
-        start_date_input = gr.inputs.Date(label="Start Date")
-        end_date_input = gr.inputs.Date(label="End Date")
+        start_date_input = gr.Textbox(label="Start Date (YYYY-MM-DD)", placeholder="Enter Start Date")
+        end_date_input = gr.Textbox(label="End Date (YYYY-MM-DD)", placeholder="Enter End Date")
         forecast_button = gr.Button("Forecast Sales")
         output_text = gr.Textbox(visible=True)
         output_plot = gr.Plot()