if flag:
question_list, email_id, intent_list, answer_list = self.fetch_data(sheet, yesterday)
if len(question_list) != 0:
Response_list = self.call_rasa_api(question_list)
# if response got from rasa
if Response_list != "ConnectionError":
dict = {'Date': yesterday, 'Email': email_id, 'Questions': question_list,
'bot1_intent': intent_list,
'bot1_answer': answer_list, 'bot2_intent': intent_list, 'bot2_answer': Response_list}
Rasa_dataframe = pd.DataFrame(dict)
df_list_value = Rasa_dataframe.values.tolist()
return df_list_value
else:
logger.info("No interaction happened in yesterday.")
if __name__ == "__main__":
# create instances
rasa_obj = Rasa_Test()
sheet_handler = Google_sheet_handler()
logger = logger_hander.set_logger()
# get google sheet
sheet = sheet_handler.call_sheet("Chatbot_Daily_Report","Chatbot_Daily_Report")
if sheet != 'WorksheetNotFound':
df_list_value = rasa_obj.extract_data_and_return_dataframe_in_list(sheet)
created_sheet = sheet_handler.call_sheet("Chatbot_Daily_Report", "BL_BOT_Compare")
if created_sheet != 'WorksheetNotFound':
output = sheet_handler.save_output_into_sheet(created_sheet, df_list_value)
logger.info(" Sheet Updated Successfully...!!!") if (output == True) else logger.error(" Something went wrong while Updating sheet ")
State_dataframe = pd.DataFrame(dict)
Find_State_Obj.preprocessTestLocation(State_dataframe, 'Current Location')
Current_State_df, Current_test_column_name = Find_State_Obj.final_output(State_dataframe, 'Current Location')
Find_State_Obj.preprocessTestLocation(State_dataframe, 'Permanent Address')
Permanent_State_df, Permanent_test_column_name = Find_State_Obj.final_output(State_dataframe,
'Permanent Address')
dict = {'Timestamp': Timestamp_list, 'Email Address': Email_id_list, 'Name': Name_list,
'Mobile Number': MobileNumber_list,
'Final University Name': University_list,
'University State': '',
'Current Location': CurrentLocation_list,
Current_test_column_name: Current_State_df,
'Permanent Address': PermanentLocation_list,
Permanent_test_column_name: Permanent_State_df}
final_df = pd.DataFrame(dict)
return final_df
if __name__ == "__main__":
Find_State_Obj = Find_State_Location()
sheet_handler = Google_sheet_handler()
logger = logger_hander.set_logger()
sheet = sheet_handler.call_sheet("CodInClub Student Information_Till_Oct_2020", "Learners_Data")
if sheet != 'WorksheetNotFound':
final_df = Find_State_Obj.get_date()
df_list_value = final_df.values.tolist()
Output_sheet = sheet_handler.call_sheet("CodInClub Student Information_Till_Oct_2020", "Copy of Processed_Data")
if Output_sheet != 'WorksheetNotFound':
output = sheet_handler.save_output_into_sheet(Output_sheet, df_list_value)
logger.info(" Sheet Updated Successfully...!!!") if (output == True) else logger.error(
" Something went wrong while Updating sheet ")
for question in questions_list:
df = pd.DataFrame([{'Question': question}])
intent = self.answer_Prediction(df, model_file)
intent_list.append(intent)
return intent_list
if __name__ == "__main__":
# create instances
retrain_obj = ReTrain_bot()
sheet_handler = Google_sheet_handler()
logger = logger_hander.set_logger()
# get google sheet
sheet = sheet_handler.call_sheet("Chatbot_Daily_Report", "BL_BOT_Compare")
if sheet != 'WorksheetNotFound':
yesterday = retrain_obj.find_yesterday_date()
# yesterday = "Sep 21, 2020"
print(yesterday)
List_of_cell_name = [
'Date', 'Email', 'Question', 'BOT1_Intent', 'BOT2_Intent',
'Question_is_proper_or_not', 'Actual_intent_must_be',
'Bot1_Result', 'Bot2_Result'
]
# check cell name is valid or not
flag = retrain_obj.check_cell_name_valid_or_not(
sheet, List_of_cell_name)
if flag: