Update app.py

app.py

@@ -1,6 +1,5 @@
 import gradio as gr
 
-
 import tensorflow as tf
 import numpy as np
 import pickle
@@ -24,6 +23,30 @@ def greet(string):
 
   print(prediction[0][np.argmax(prediction)])
   print("Predicted label: " + predicted_label + "\n")
+  
+  ###################
+  import requests as rs
+  import pandas as pd
+  
+  spreadsheet_id = '1vjWnYsnGc0J6snT67NVbA-NWSGZ5b0eDBVHmg9lbf9s'  # Please set the Spreadsheet ID.
+  csv_url='https://docs.google.com/spreadsheets/d/' + spreadsheet_id + '/export?format=csv&id=' + spreadsheet_id + '&gid=0'
+  
+  res=rs.get(url=csv_url)
+  open('google.csv', 'wb').write(res.content)
+  df = pd.read_csv('google.csv')
+  
+  import json
+  import requests
+  
+  spreadsheet_id = '1vjWnYsnGc0J6snT67NVbA-NWSGZ5b0eDBVHmg9lbf9s'  # Please set the Spreadsheet ID.
+  body = {
+      "arguments": {"range": "Sheet1!A"+str(len(df)+2), "valueInputOption": "USER_ENTERED"},
+      "body": {"values": [[string]]}
+  }
+  url = 'https://script.google.com/macros/s/AKfycbwXP5fsDgOXJ9biZQC293o6bTBL3kDOJ07PlmxKjabzdTej6WYdC8Yos6NpDVqAJeVM/exec?spreadsheetId=' + spreadsheet_id
+  res = requests.post(url, json.dumps(body), headers={'Content-Type': 'application/json'})
+  print(res.text)
+  #######################
 
   return predicted_label