Commit
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93a5668
1
Parent(s):
9f65c7c
Guardar mis cambios locales
Browse files
app.py
CHANGED
@@ -23,7 +23,7 @@ def parse_date(date_str):
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except ValueError:
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return None, None, "Date format should be 'Month-Year', e.g., 'January-2024'."
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-
def forecast_sales(uploaded_file,
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if uploaded_file is None:
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return "No file uploaded.", None, "Please upload a file."
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@@ -34,13 +34,14 @@ def forecast_sales(uploaded_file, date_str, forecast_period=30):
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except Exception as e:
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return None, f"Failed to read the uploaded CSV file: {str(e)}", "Error reading file."
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df['Date'] = pd.to_datetime(df['Date'])
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df = df.rename(columns={'Date': 'ds', 'Sale': 'y'})
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-
start_date, end_date, error = parse_date(date_str)
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if error:
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return None, error, "Invalid date format."
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-
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df_filtered = df[(df['ds'] >= start_date) & (df['ds'] <= end_date)]
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arima_model, error = load_model()
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@@ -48,8 +49,8 @@ def forecast_sales(uploaded_file, date_str, forecast_period=30):
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return None, error, "Failed to load ARIMA model."
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try:
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forecast = arima_model.get_forecast(steps=forecast_period)
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forecast_index = pd.date_range(start=end_date, periods=forecast_period + 1, freq='D')[1:]
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forecast_df = pd.DataFrame({'Date': forecast_index, 'Sales Forecast': forecast.predicted_mean})
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except Exception as e:
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return None, f"Failed during forecasting: {str(e)}", "Forecasting failed."
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@@ -62,7 +63,7 @@ def forecast_sales(uploaded_file, date_str, forecast_period=30):
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ax.set_ylabel('Sales')
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ax.set_title('Sales Forecasting with ARIMA')
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ax.legend()
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-
return
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except Exception as e:
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return None, f"Failed to generate plot: {str(e)}", "Plotting failed."
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@@ -71,14 +72,15 @@ def setup_interface():
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gr.Markdown("## MLCast v1.1 - Intelligent Sales Forecasting System")
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with gr.Row():
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file_input = gr.File(label="Upload your store data here (must contain Date and Sales)")
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-
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forecast_button = gr.Button("Forecast Sales")
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output_plot = gr.Plot()
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output_message = gr.Textbox(label="System Messages", visible=True)
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forecast_button.click(
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forecast_sales,
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inputs=[file_input,
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outputs=[
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)
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return demo
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except ValueError:
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return None, None, "Date format should be 'Month-Year', e.g., 'January-2024'."
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+
def forecast_sales(uploaded_file, start_date_str, end_date_str, forecast_period=30):
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if uploaded_file is None:
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return "No file uploaded.", None, "Please upload a file."
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except Exception as e:
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return None, f"Failed to read the uploaded CSV file: {str(e)}", "Error reading file."
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+
start_date, _, error = parse_date(start_date_str)
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+
_, end_date, error_end = parse_date(end_date_str)
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if error or error_end:
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return None, error or error_end, "Invalid date format."
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+
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df['Date'] = pd.to_datetime(df['Date'])
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df = df.rename(columns={'Date': 'ds', 'Sale': 'y'})
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df_filtered = df[(df['ds'] >= start_date) & (df['ds'] <= end_date)]
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arima_model, error = load_model()
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return None, error, "Failed to load ARIMA model."
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try:
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forecast_index = pd.date_range(start=end_date, periods=forecast_period + 1, freq='D')[1:]
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forecast = arima_model.get_forecast(steps=forecast_period)
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forecast_df = pd.DataFrame({'Date': forecast_index, 'Sales Forecast': forecast.predicted_mean})
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except Exception as e:
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return None, f"Failed during forecasting: {str(e)}", "Forecasting failed."
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ax.set_ylabel('Sales')
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ax.set_title('Sales Forecasting with ARIMA')
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ax.legend()
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return None, fig, "File loaded and processed successfully."
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except Exception as e:
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return None, f"Failed to generate plot: {str(e)}", "Plotting failed."
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gr.Markdown("## MLCast v1.1 - Intelligent Sales Forecasting System")
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with gr.Row():
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file_input = gr.File(label="Upload your store data here (must contain Date and Sales)")
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start_date_input = gr.Textbox(label="Start Date (e.g., January-2024)", placeholder="Enter Start Date")
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end_date_input = gr.Textbox(label="End Date (e.g., January-2024)", placeholder="Enter End Date")
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forecast_button = gr.Button("Forecast Sales")
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output_plot = gr.Plot()
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output_message = gr.Textbox(label="System Messages", visible=True)
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forecast_button.click(
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forecast_sales,
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inputs=[file_input, start_date_input, end_date_input],
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outputs=[output_message, output_plot]
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)
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return demo
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