Update app.py

app.py

@@ -1077,7 +1077,7 @@ def save_file_to_hostinger(save_file_path):
     ftp_host = 'ftp.redmindtechnologies.com'  # Replace with your FTP server address
     ftp_user = 'u852023448.redmindGpt'         # Replace with your FTP username
     ftp_pass = 'RedMind@505'         # Replace with your FTP password
-    remote_file_path = '/alborj/test.xlsx'  # Replace with the desired path on the server
+    remote_file_path = '/RedMindGPT/Output.xlsx'  # Replace with the desired path on the server
 
     # Create an FTP connection
     ftp = FTP(ftp_host)
@@ -1107,8 +1107,18 @@ def handle_large_dataset(df):
         # 4. Add SNo (serial number) as the first column, starting from 1
         limited_data_without_first_column.insert(0, 'SNo', range(1, len(limited_data_without_first_column) + 1))
         # 3. Save the full dataset to a downloadable file
-        df.to_excel('output_data.xlsx', index=False)
-        save_file_to_hostinger('output_data.xlsx')
+        # Get the current working directory
+        current_directory = os.getcwd()
+        
+        # Define the filename
+        filename = 'output_data.xlsx'
+        
+        # Create the complete path by joining the current directory with the filename
+        file_path = os.path.join(current_directory, filename)
+
+        
+        df.to_excel(file_path, index=False)
+        save_file_to_hostinger(file_path)
         # 4. Create a summary and table of the first 10 rows for display
     
         columns = list(df.columns)