Guardar mis cambios locales

app.py

@@ -98,4 +98,58 @@ def upload_and_forecast(uploaded_file, period):
 
     future_n_periods = forecast_period
     future_fitted, confint = train_test_model.predict(X=df.iloc[-future_n_periods:, 1:], n_periods=future_n_periods, return_conf_int=True, freq='3D')
-    future_index_of_fc = pd.date_range(df['Sales'].index[-1], periods=future)
+    future_index_of_fc = pd.date_range(df['Sales'].index[-1], periods=future_n_periods, freq='3D')
+    future_fitted_series = pd.Series(future_fitted)
+    future_fitted_series.index = future_index_of_fc
+
+    # Calculate sales growth
+    future_sales_growth = sales_growth(df, future_fitted_series)
+    
+    # Prepare merged data for chart plotting
+    merged_data = merge_forecast_data(df['Sales'], fitted_series, future_fitted_series)
+    
+    # Plot the charts
+    fig_compare = go.Figure()
+    fig_compare.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=merged_data['Actual Sales'], mode='lines', name='Actual Sales'))
+    fig_compare.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=merged_data['Predicted Sales'], mode='lines', name='Predicted Sales', line=dict(color='#006400')))
+    fig_compare.update_layout(title='📊 Historical Sales Data', xaxis_title='Date', yaxis_title='Sales')
+
+    fig_forecast = go.Figure()
+    fig_forecast.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=merged_data['Actual Sales'], mode='lines', name='Actual Sales'))
+    fig_forecast.add_trace(go.Scatter(x=merged_data[merged_data.columns[0]], y=merged_data['Forecasted Future Sales'], mode='lines', name='Future Forecasted Sales'))
+    fig_forecast.update_layout(title='🔮 Forecasted Sales Data', xaxis_title='Date', yaxis_title='Sales')
+
+    # Return the figures and growth data
+    return fig_compare, fig_forecast, future_sales_growth
+
+# Create the sidebar (inputs) and main interface for outputs
+def create_sidebar():
+    with gr.Column():
+        gr.Markdown("### 📂 Upload your sales data (CSV)")
+        uploaded_file = gr.File(label="Choose your file", elem_id="file-uploader")
+        gr.Markdown("### ⏳ Forecast Period (Days)")
+        period = gr.Slider(minimum=30, maximum=90, step=1, label="Forecast period (in days)")
+        return uploaded_file, period
+
+# Create the sidebar and main interface
+uploaded_file, period = create_sidebar()
+
+# Gradio interface for output display (results shown below)
+output_plots = [
+    gr.Plot(label="📈 Historical vs Predicted Sales"),
+    gr.Plot(label="🔮 Forecasted Sales Data"),
+    gr.DataFrame(label="📊 Sales Growth")
+]
+
+# Create and launch the gradio interface
+iface = gr.Interface(
+    fn=upload_and_forecast,
+    inputs=[uploaded_file, period],
+    outputs=output_plots,
+    live=True,
+    title="Sales Forecasting System ✨",
+    description="Upload your sales data to start forecasting 🚀",
+    css=open("styles.css", "r").read()  # Load the external CSS file here
+)
+
+iface.launch()