Ho do I combine multiple sheets in excel files into one csv file with mappings in Python?

Question

im trying to combine excel files in a directory into one csv. All the current excel files have same number of columns and same headers. file 1 df- sheet1

State   Region  Brand   Coverage Type   Initial Effective Date  Issue
GA       S       gg        Out                 8/1/2012        Need Records
OH       NE      gg        Out                 7/31/2021       Pre-existing

file 2 df- sheet2

State   Region  Brand   Coverage Type   Initial Effective Date  Issue
CA       S       gg        Out                 8/1/2012        Need Records
IA       NE      gg        Out                 7/31/2021       Pre-existing

I want my final combined csv to look like

Rownumber Sheetname Filename  State Region  Brand   Coverage Type   Initial Effective Date  Issue
 1           2       df2      CA         S       gg        Out             8/1/2012        Need 
 2           2       df2      IA         NE      gg        Out             7/31/2021       Pre-

The row number should reflect exact row number from sheet they belong to. How do I do this so that all future excel files created in the directory append to a combined csv file in the above format? currently there are 2 csv files but soon there will be more added with the same columns and headers. I want this code to pick up the excel files and append to the final combined csv like this. Will setup a task scheduler for the same. I attempted the below but it is only giving me an empty df-

import os
import pandas as pd
cwd = os.path.abspath('') 
files = os.listdir(cwd)  
df_total = pd.DataFrame()
for file in files:                         # loop through Excel files
    if file.endswith('.xlsx'):
        excel_file = pd.ExcelFile(file)
        sheets = excel_file.sheet_names
        for sheet in sheets:               # loop through sheets inside an Excel file
            df = excel_file.parse(sheet_name = sheet)
            df_total = df_total.append(df)
df_total.to_csv('combined_file.csv')