def start_socket(self, port=42424):
"""
Listens socket for input phrases.
"""
host = ""
buf = 1024
addr = (host, port)
UDPSock = socket(AF_INET, SOCK_DGRAM)
UDPSock.bind(addr)
print("Listening socket")
occupation = multiprocessing.Event()
# listener_queue = multiprocessing.Queue(maxsize=0)
# recognizer_queue = multiprocessing.Queue(maxsize=0)
speaker_queue = multiprocessing.Queue(maxsize=0)
speaker = multiprocessing.Process(target=speech.speaker,
args=(
occupation,
speaker_queue,
))
# recognizer = multiprocessing.Process(
# target=speech.recognizer,
# args=(recognizer_queue, listener_queue, ))
# listener = multiprocessing.Process(
# target=speech.listener,
# args=(occupation, recognizer_queue, ))
speaker.start()
# recognizer.start()
# listener.start()
occupation.set()
print("======")
for state in self.expected:
print("\t %s" % (state))
print("======")
while True:
# process routines answers
answers = self.returns.get_returns()
for answer in answers:
tosay, questions = answer.accept()
speaker_queue.put(tosay)
print("Bot> " + tosay)
self._extend_expected(questions)
# process input
(data, addr) = UDPSock.recvfrom(buf)
input_phrase = data.decode("utf-8")
print("You> " + input_phrase)
while not input_phrase.strip():
print("Empty input string")
input_phrase = input("You> ")
input_phrase = link_parser.parse(input_phrase)
state = self.interpret(input_phrase)
if state:
tosay, questions = state.accept(input_phrase)
for answer in tosay:
if answer != "":
speaker_queue.put(answer)
print("Bot> " + answer)
self._extend_expected(questions)
UDPSock.close()
def _parse(self):
"""
Parses input string using regex.
"""
pattern = re.compile(r'`([a-zA-Z0-9_]*)((\:|\~|\<)([^`]+))?`')
for inline in pattern.finditer(self.origin):
if bool(inline.group(2)):
if inline.group(3) == ':':
self._create_fixed_setter(
inline.group(1),
inline.group(4),
*inline.span())
elif inline.group(3) == '~':
self._create_flexible_setter(
inline.group(1),
inline.group(4),
*inline.span())
elif inline.group(3) == '<':
self._create_routine_request(
inline.group(1),
inline.group(4),
*inline.span())
else:
self._create_substition(inline.group(1), *inline.span())
self._erase_fixed_setters()
self._erase_flexible_setters()
self._erase_routine_requests()
try:
self.latest = self.evaluate()
self.parsed = link_parser.parse(self.latest)
self._link_flexible_setters()
except KeyError: # not all keys available now
pass
def start_text(self):
"""
Interprets dialog in text mode.
"""
print("======")
for state in self.expected:
print("\t %s" % (state))
print("======")
while True:
# process routines answers
answers = self.returns.get_returns()
for answer in answers:
tosay, questions = answer.accept()
print("Bot> " + tosay)
self._extend_expected(questions)
# process input
input_phrase = input("You> ")
while not input_phrase.strip():
# print("Empty input string")
# process routines second time! duplex tests
answers = self.returns.get_returns()
# print(answers)
for answer in answers:
tosay, questions = answer.accept()
print("Bot> " + tosay)
self._extend_expected(questions)
input_phrase = input("You> ")
input_phrase = link_parser.parse(input_phrase)
state = self.interpret(input_phrase)
if state:
tosay, questions = state.accept(input_phrase)
for answer in tosay:
if answer != "":
print("Bot> " + answer)
self._extend_expected(questions)
def _parse(self):
"""
Parses input string using regex.
"""
pattern = re.compile(r'`([a-zA-Z0-9_]*)((\:|\~|\<)([^`]+))?`')
for inline in pattern.finditer(self.origin):
if bool(inline.group(2)):
if inline.group(3) == ':':
self._create_fixed_setter(inline.group(1), inline.group(4),
*inline.span())
elif inline.group(3) == '~':
self._create_flexible_setter(inline.group(1),
inline.group(4),
*inline.span())
elif inline.group(3) == '<':
self._create_routine_request(inline.group(1),
inline.group(4),
*inline.span())
else:
self._create_substition(inline.group(1), *inline.span())
self._erase_fixed_setters()
self._erase_flexible_setters()
self._erase_routine_requests()
try:
self.latest = self.evaluate()
self.parsed = link_parser.parse(self.latest)
self._link_flexible_setters()
except KeyError: # not all keys available now
pass
def start_text(self):
"""
Interprets dialog in text mode.
"""
print("======")
for state in self.expected:
print("\t %s" % (state))
print("======")
while True:
# process routines answers
answers = self.returns.get_returns()
for answer in answers:
tosay, questions = answer.accept()
print("Bot> "+tosay)
self._extend_expected(questions)
# process input
input_phrase = input("You> ")
while not input_phrase.strip():
# print("Empty input string")
# process routines second time! duplex tests
answers = self.returns.get_returns()
# print(answers)
for answer in answers:
tosay, questions = answer.accept()
print("Bot> "+tosay)
self._extend_expected(questions)
input_phrase = input("You> ")
input_phrase = link_parser.parse(input_phrase)
state = self.interpret(input_phrase)
if state:
tosay, questions = state.accept(input_phrase)
for answer in tosay:
if answer != "":
print("Bot> "+answer)
self._extend_expected(questions)
def start_socket(self, port=42424):
"""
Listens socket for input phrases.
"""
host = ""
buf = 1024
addr = (host, port)
UDPSock = socket(AF_INET, SOCK_DGRAM)
UDPSock.bind(addr)
print("Listening socket")
occupation = multiprocessing.Event()
# listener_queue = multiprocessing.Queue(maxsize=0)
# recognizer_queue = multiprocessing.Queue(maxsize=0)
speaker_queue = multiprocessing.Queue(maxsize=0)
speaker = multiprocessing.Process(
target=speech.speaker,
args=(occupation, speaker_queue, ))
# recognizer = multiprocessing.Process(
# target=speech.recognizer,
# args=(recognizer_queue, listener_queue, ))
# listener = multiprocessing.Process(
# target=speech.listener,
# args=(occupation, recognizer_queue, ))
speaker.start()
# recognizer.start()
# listener.start()
occupation.set()
print("======")
for state in self.expected:
print("\t %s" % (state))
print("======")
while True:
# process routines answers
answers = self.returns.get_returns()
for answer in answers:
tosay, questions = answer.accept()
speaker_queue.put(tosay)
print("Bot> "+tosay)
self._extend_expected(questions)
# process input
(data, addr) = UDPSock.recvfrom(buf)
input_phrase = data.decode("utf-8")
print("You> "+input_phrase)
while not input_phrase.strip():
print("Empty input string")
input_phrase = input("You> ")
input_phrase = link_parser.parse(input_phrase)
state = self.interpret(input_phrase)
if state:
tosay, questions = state.accept(input_phrase)
for answer in tosay:
if answer != "":
speaker_queue.put(answer)
print("Bot> "+answer)
self._extend_expected(questions)
UDPSock.close()
def start_offline(self):
"""
Interprets dialog with offline TTS and STT.
"""
import dialog.speech as speech
occupation = multiprocessing.Event()
listener_queue = multiprocessing.Queue(maxsize=0)
recognizer_queue = multiprocessing.Queue(maxsize=0)
speaker_queue = multiprocessing.Queue(maxsize=0)
speaker = multiprocessing.Process(target=speech.speaker_pico,
args=(
occupation,
speaker_queue,
))
recognizer = multiprocessing.Process(target=speech.recognizer_sphinx,
args=(
recognizer_queue,
listener_queue,
))
listener = multiprocessing.Process(target=speech.listener,
args=(
occupation,
recognizer_queue,
))
speaker.start()
recognizer.start()
listener.start()
occupation.set()
print("======")
for state in self.expected:
print("\t %s" % (state))
print("======")
while True:
# process routines answers
answers = self.returns.get_returns()
for answer in answers:
tosay, questions = answer.accept()
speaker_queue.put(tosay)
print("Bot> " + tosay)
self._extend_expected(questions)
# process input
if not listener_queue.empty():
input_phrase = listener_queue.get()
input_phrase = link_parser.parse(input_phrase)
state = self.interpret(input_phrase)
if state:
tosay, questions = state.accept(input_phrase)
for answer in tosay:
if answer != "":
speaker_queue.put(answer)
print("Bot> " + answer)
self._extend_expected(questions)
def _update_parsed(self):
"""
Method evaulates string and if it's changed,
parses the new one with link-parser.
"""
# TODO: probably add check for changed vaules before eval
try:
if self.evaluate() != self.latest:
self.latest = self.evaluate()
self.parsed = link_parser.parse(self.latest)
self._link_flexible_setters()
except KeyError:
print("WARNING: Can't evaluate")
def _update_parsed(self):
"""
Method evaulates string and if it's changed,
parses the new one with link-parser.
"""
# TODO: probably add check for changed vaules before eval
try:
if self.evaluate() != self.latest:
self.latest = self.evaluate()
self.parsed = link_parser.parse(self.latest)
self._link_flexible_setters()
except KeyError:
print("WARNING: Can't evaluate")
def start_offline(self):
"""
Interprets dialog with offline TTS and STT.
"""
import dialog.speech as speech
occupation = multiprocessing.Event()
listener_queue = multiprocessing.Queue(maxsize=0)
recognizer_queue = multiprocessing.Queue(maxsize=0)
speaker_queue = multiprocessing.Queue(maxsize=0)
speaker = multiprocessing.Process(
target=speech.speaker_pico,
args=(occupation, speaker_queue, ))
recognizer = multiprocessing.Process(
target=speech.recognizer_sphinx,
args=(recognizer_queue, listener_queue, ))
listener = multiprocessing.Process(
target=speech.listener,
args=(occupation, recognizer_queue, ))
speaker.start()
recognizer.start()
listener.start()
occupation.set()
print("======")
for state in self.expected:
print("\t %s" % (state))
print("======")
while True:
# process routines answers
answers = self.returns.get_returns()
for answer in answers:
tosay, questions = answer.accept()
speaker_queue.put(tosay)
print("Bot> "+tosay)
self._extend_expected(questions)
# process input
if not listener_queue.empty():
input_phrase = listener_queue.get()
input_phrase = link_parser.parse(input_phrase)
state = self.interpret(input_phrase)
if state:
tosay, questions = state.accept(input_phrase)
for answer in tosay:
if answer != "":
speaker_queue.put(answer)
print("Bot> "+answer)
self._extend_expected(questions)
def start_server(self, to_user, to_ds):
"""
Interprets dialog
"""
# occupation = multiprocessing.Event()
# listener_queue = multiprocessing.Queue(maxsize=0)
# recognizer_queue = multiprocessing.Queue(maxsize=0)
# speaker_queue = multiprocessing.Queue(maxsize=0)
# speaker = multiprocessing.Process(
# target=speech.speaker,
# args=(occupation, speaker_queue, ))
# recognizer = multiprocessing.Process(
# target=speech.recognizer,
# args=(recognizer_queue, listener_queue, ))
# listener = multiprocessing.Process(
# target=speech.listener,
# args=(occupation, recognizer_queue, ))
# speaker.start()
# recognizer.start() # IN CASE OF SPEECH RECOGNITION
# listener.start() # IN CASE OF SPEECH RECOGNITION
# occupation.set()
# print("======")
# for state in self.expected:
# print("\t%s" % (state))
# print("======")
while True:
# process routines answers
answers = self.returns.get_returns()
for answer in answers:
tosay, questions = answer.accept()
to_user.put(json.dumps({'type': 'phrase', 'text': tosay}))
self._extend_expected(questions)
# process input
if not to_ds.empty():
input_origin = to_ds.get()
# input_phrase = listener_queue.get() # IN CASE OF SPEECH RECOGNITION
input_phrase = link_parser.parse(input_origin)
states_probability = []
for state in self.expected:
# print(state, state.compare(input_phrase))
states_probability.append((state, state.compare(input_phrase)))
states_probability = sorted(states_probability, key=lambda x: x[1], reverse=True)
# print("======")
# for state in states_probability:
# print("%.2f\t%s" % (state[1], state[0]))
# print("======")
state = states_probability[0][0]
if states_probability[0][1] < 0.2:
# print("Bot> ???")
to_user.put(json.dumps({
'type': 'origin',
'text': input_origin
}))
to_user.put(json.dumps({'type': 'unknown'}))
#TODO: save unknown request, with state!!!
else:
to_user.put(json.dumps({
'type': 'interpretation',
'origin': input_origin,
'phrase': str(state),
'similarity': states_probability[0][1]
}))
tosay, questions = state.accept(input_phrase)
for answer in tosay:
if answer != "":
# speaker_queue.put(answer)
# print("Bot> "+answer)
to_user.put(json.dumps({'type': 'phrase', 'text': answer}))
self._extend_expected(questions)
def start_server(self, to_user, to_ds):
"""
Interprets dialog
"""
# occupation = multiprocessing.Event()
# listener_queue = multiprocessing.Queue(maxsize=0)
# recognizer_queue = multiprocessing.Queue(maxsize=0)
# speaker_queue = multiprocessing.Queue(maxsize=0)
# speaker = multiprocessing.Process(
# target=speech.speaker,
# args=(occupation, speaker_queue, ))
# recognizer = multiprocessing.Process(
# target=speech.recognizer,
# args=(recognizer_queue, listener_queue, ))
# listener = multiprocessing.Process(
# target=speech.listener,
# args=(occupation, recognizer_queue, ))
# speaker.start()
# recognizer.start() # IN CASE OF SPEECH RECOGNITION
# listener.start() # IN CASE OF SPEECH RECOGNITION
# occupation.set()
# print("======")
# for state in self.expected:
# print("\t%s" % (state))
# print("======")
while True:
# process routines answers
answers = self.returns.get_returns()
for answer in answers:
tosay, questions = answer.accept()
to_user.put(json.dumps({'type': 'phrase', 'text': tosay}))
self._extend_expected(questions)
# process input
if not to_ds.empty():
input_origin = to_ds.get()
# input_phrase = listener_queue.get() # IN CASE OF SPEECH RECOGNITION
input_phrase = link_parser.parse(input_origin)
states_probability = []
for state in self.expected:
# print(state, state.compare(input_phrase))
states_probability.append(
(state, state.compare(input_phrase)))
states_probability = sorted(states_probability,
key=lambda x: x[1],
reverse=True)
# print("======")
# for state in states_probability:
# print("%.2f\t%s" % (state[1], state[0]))
# print("======")
state = states_probability[0][0]
if states_probability[0][1] < 0.2:
# print("Bot> ???")
to_user.put(
json.dumps({
'type': 'origin',
'text': input_origin
}))
to_user.put(json.dumps({'type': 'unknown'}))
#TODO: save unknown request, with state!!!
else:
to_user.put(
json.dumps({
'type': 'interpretation',
'origin': input_origin,
'phrase': str(state),
'similarity': states_probability[0][1]
}))
tosay, questions = state.accept(input_phrase)
for answer in tosay:
if answer != "":
# speaker_queue.put(answer)
# print("Bot> "+answer)
to_user.put(
json.dumps({
'type': 'phrase',
'text': answer
}))
self._extend_expected(questions)