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| import subprocess | |
| import time | |
| import streamlit as st | |
| import pandas as pd | |
| def fn_process_excel(lv_file_name,ui_status_message,sm): | |
| try: | |
| # Read the Excel file | |
| excel_data = pd.read_excel(lv_file_name,sheet_name=None) | |
| # Iterate over each sheet in the Excel file | |
| for sheet_name, sheet_data in excel_data.items(): | |
| # Process the data in each sheet | |
| print(f"Sheet Name: {sheet_name}") | |
| print(sheet_data.head()) | |
| # Display a success message | |
| sm.fn_display_status_messages("Excel data processed successfully!", "Success", ui_status_message) | |
| except Exception as e: | |
| # Display an error message if there is an exception | |
| sm.fn_display_status_messages(f"Error: {e}", "Error", ui_status_message) | |
| # Function to start the Flask server | |
| def start_flask_server(): | |
| """ | |
| Function to start the Flask server. | |
| Returns: | |
| None | |
| """ | |
| lv_proc = subprocess.Popen(["python", "flask_app.py"]) | |
| st.session_state.sv_flask_server_proc = lv_proc | |
| # Function to stop the Flask server | |
| def stop_flask_server(): | |
| """ | |
| Function to stop the Flask server. | |
| Returns: | |
| None | |
| """ | |
| lv_proc = st.session_state.sv_flask_server_proc | |
| if lv_proc is not None: | |
| lv_proc.terminate() | |
| lv_proc.wait(timeout=5) | |
| if lv_proc.poll() is None: | |
| lv_proc.kill() | |
| st.session_state.sv_flask_server_proc = None | |
| # Function to configure the sidebar UI elements. | |
| def fn_sidebar_configuration(ui_status_message,sm): | |
| """ | |
| Function to configure the sidebar UI elements. | |
| Parameters: | |
| - ui_status_message (str): The status message to be display in UI. | |
| Returns: | |
| None | |
| """ | |
| try: | |
| if not(st.session_state.sv_flask_server_proc): | |
| # Start Flask Server | |
| start_flask_server() | |
| # Toggle button to enable/disable training mode | |
| ui_training_indicator = st.toggle("Training", value=False) | |
| # Container to hold the UI elements | |
| ui_container = st.container(border=True) | |
| with ui_container: | |
| # Training new domain | |
| if ui_training_indicator: | |
| # File uploader for training file | |
| ui_training_file = st.file_uploader("Training File", type=["xlsx"], accept_multiple_files=False, key="training_file") | |
| # Text input for domain name | |
| ui_domain_name = st.text_input("Domain Name") | |
| # Button to submit the form | |
| if st.button("Submit"): | |
| # Check if the training file is uploaded | |
| if ui_training_file is not None and ui_domain_name != "": | |
| lv_file_name = "storage/"+ui_domain_name+".xlsx" | |
| # Saving File | |
| with open(lv_file_name, "wb") as f: | |
| f.write(ui_training_file.getvalue()) | |
| # Process the Excel file | |
| fn_process_excel(lv_file_name, ui_status_message,sm) | |
| else: | |
| # Display an error message if the training file is not uploaded | |
| sm.fn_display_status_messages("Please upload the training file.", "Error", ui_status_message) | |
| # Mapping data to trained domain | |
| else: | |
| # Selectbox for domain selection | |
| ui_training_vector_db = st.selectbox("Domain", ["OFSLL", "OBRL"]) | |
| except Exception as e: | |
| # Display an error message if there is an exception | |
| sm.fn_display_status_messages(f"Error: {e}", "Error", ui_status_message) | |