def __send_responses_with_delay(cls, contents, sender_id, user_id,
cluster_id, response_type):
try:
delay = 0
for idx, content in enumerate(contents):
try:
if idx == 0:
send_message(sender_id, content)
models.Response.save_response_data(user_id,
cluster_id,
content,
response_type,
has_sent=True)
else:
delay = cls.__update_delay(delay, len(content))
models.Response.save_response_data(user_id,
cluster_id,
content,
response_type,
has_sent=False,
delay=delay)
send_typing_on(sender_id)
except:
logging.exception('')
except:
logging.exception('')
def __call__(self, message_dicts: List[Dict[str, str]], sender_id, from_preprocessor=True):
try:
if from_preprocessor:
message_dicts = self.__convert_attachment(message_dicts)
message_dicts = self.__normalize_apostrophe(message_dicts)
w_toks = WordFormatter.MsgDict2WToks(message_dicts)
else:
w_toks = message_dicts
print('\nword_tokenized\n', w_toks)
normalized_w_toks = self.normalize_message_by_w_toks(w_toks)
send_typing_on(sender_id)
# make original_df with sidx, widx, word, pos tag
df = OriginalDFGenerator.create_original_df_by_w_toks(normalized_w_toks)
df = self.normalize_message_by_df(df)
return df
except:
logging.exception('')
return None
def reply(self):
send_typing_on(self.user.sender_id)
response_data = self.create_response()
self.send_responses(response_data)
send_typing_off(self.user.sender_id)
def reply(self):
try:
send_typing_on(self.user.sender_id)
response_data = self.create_response()
self.send_responses(response_data)
send_typing_off(self.user.sender_id)
except:
logging.exception('')
def reply(self):
try:
if self.therapy_session.status == SessionStatus.prepared.value:
self.therapy_session.activate()
send_typing_on(self.user.sender_id)
self.message = self.preprocess_message()
send_typing_on(self.user.sender_id)
UsersFeeling.save_feelings(self.message.text_kw_df, self.user.id)
message_types = self.analyze_message_type()
send_typing_on(self.user.sender_id)
response_data = self.create_response(message_types)
send_typing_on(self.user.sender_id)
self.send_responses(response_data, message_types)
print("\nBot finished sending responses")
except:
logging.exception('')
print(
'\n*********************** Bot couldnt make responses ***********************'
)
def reply(self):
"""
Here bot sends typing indicator on constantly because nlp processing takes long.
:return:
"""
if self.therapy_session.status == SessionStatus.prepared.value:
self.therapy_session.activate()
send_typing_on(self.user.sender_id)
self.message = self.__preprocess_message()
send_typing_on(self.user.sender_id)
UsersFeeling.save_feelings(self.message.text_kw_df, self.user.id)
message_types = self.__analyze_message_type()
send_typing_on(self.user.sender_id)
response_data = self.create_response(message_types)
send_typing_on(self.user.sender_id)
self.send_responses(response_data, message_types)
print("\nBot finished sending responses")
def send_response_regularly():
try:
responses = get_unsent_responses()
if len(responses) == 0:
return None
print("\nSending response_generator >>>>>")
pprint(responses)
for i in responses:
send_message(sender_id=i[2], content=i[1])
send_typing_on(sender_id=i[2])
user_ids_list = set(map(tuple, [[i[0], i[2]] for i in responses]))
MyDB.control_typing_indicator(user_ids_list)
except:
logging.exception('')