class ChitChat(object):
def __init__(self):
self.BOT_PREDICATES = {
"name": "KanoBot",
"birthday": "January 1st 1969",
"location": "London",
"master": "Judoka",
"website": "https://github.com/brandonjackson/make-chatterbot",
"gender": "",
"age": "",
"size": "",
"religion": "",
"party": ""
}
self.DEVNULL = open(os.devnull, 'wb')
self.k = MyKernel()
# Load the AIML files on first load, and then save as "brain" for speedier startup
if os.path.isfile("cache/standard.brn") is False:
self.k.learn("aiml/standard/std-startup.xml")
self.k.respond("load aiml b")
self.k.saveBrain("cache/standard.brn")
else:
self.k.loadBrain("cache/standard.brn")
# Give the bot a name and lots of other properties
for key, val in self.BOT_PREDICATES.items():
self.k.setBotPredicate(key, val)
# Start Infinite Loop
def chat(self, sentence):
# Prompt user for input
# input = raw_input("> ")
input = sentence
# Send input to bot and print chatbot's response
matchedPattern = self.k.matchedPattern(
input) # note: this has to come before the
# call to respond as to reflect
# the correct history
response = self.k.respond(input)
return response
while True:
# Prompt user for input
setEyes(0)
#input = raw_input("> ")
with sr.Microphone(device_index=2) as source:
audio_input = recognizer.listen(source)
try:
input = recognizer.recognize(audio_input)
except LookupError:
input = 'Kauderwelsch'
print( input )
setEyes(1)
setHead(int(np.random.uniform(-25, 25)))
# Send input to bot and print chatbot's response
matchedPattern = k.matchedPattern(input) # note: this has to come before the
# call to respond as to reflect
# the correct history
response = k.respond(input)
if SHOW_MATCHES:
print "Matched Pattern: "
print k.formatMatchedPattern(matchedPattern[0])
print "Response: "
if not PRESENTATION_MODE:
print response
# Output response as speech using espeak
if TTS_ENABLED is False:
pass
elif TTS_ENGINE == "espeak":
subprocess.call(["espeak", "-s", str(TTS_SPEED), "-v", TTS_VOICE,
elif (part_speech == 'VERB'):
word = wn.morphy(i[0], wn.VERB)
elif (part_speech == 'ADV'):
word = wn.morphy(i[0], wn.ADV)
elif (part_speech == 'ADJ'):
word = wn.morphy(i[0], wn.ADJ)
word1 = wn.synsets(word)[0].lemmas()[0].name()
if i[0] in grade_codes:
word1 = i[0]
except:
word1 = i[0]
new_sentence = new_sentence + " " + word1.lower()
new_sentence = remove_aiml_char(new_sentence)
if DEBUG:
matchedPattern = k.matchedPattern(myinput)
response = k.respond(myinput)
try:
if SHOW_MATCHES:
print "Matched Pattern: "
print k.formatMatchedPattern(matchedPattern[0])
pattern = k.getPredicate("topic", '_global')
print "TOPIC:", pattern
else:
print "-------------------------"
except:
print "No match found"
print "Normal Response: ", response
print "--------------------------------"
print "new_sentence :", new_sentence
matchedPattern = k.matchedPattern(new_sentence)
k.respond("load aiml b")
k.saveBrain("cache/standard.brn")
else:
k.loadBrain("cache/standard.brn")
# Give the bot a name and lots of other properties
for key, val in BOT_PREDICATES.items():
k.setBotPredicate(key, val)
# Start Infinite Loop
while True:
# Prompt user for input
input = raw_input("> ")
# Send input to bot and print chatbot's response
matchedPattern = k.matchedPattern(
input) # note: this has to come before the
# call to respond as to reflect
# the correct history
response = k.respond(input)
if SHOW_MATCHES:
print "Matched Pattern: "
print k.formatMatchedPattern(matchedPattern[0])
print "Response: "
print response
# Output response as speech using espeak
if TTS_ENABLED is False:
pass
elif TTS_ENGINE == "espeak":
subprocess.call([
"espeak", "-s",
