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
if TTS_ENGINE == "espeak":
try:
subprocess.call(["espeak","-q","foo"])
except OSError:
TTS_ENABLED = False
print "Warning: espeak command not found, skipping voice generation"
else:
# non-espeak TTS engine being used
pass
# Create Kernel (using our custom version of the aiml kernel class)
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: #FIXME undo this.
k.learn("aiml/std-startup.xml")
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)
# Init STT engine
recognizer = sr.Recognizer()
# Start Infinite Loop
while True:
# Prompt user for input
BOT_INFO = {
"name": "Amanda",
"birthday": "July 5th 2017",
"location": "Kanpur",
"master": "I have no Master",
"website":"follow me on twitter",
"gender": "Female",
"age": "20",
"size": "",
"religion": "Humanity",
"party": "All night !"
}
k = MyKernel()
k.learn("aiml/standard/std-startup.xml")
k.respond("LOAD AIML B")
for key,val in BOT_INFO.items():
k.setBotPredicate(key,val)
class PopupBox(ModalView):
'''
:Events:
`on_open`:
Fired when the Popup is opened.
`on_dismiss`:
Fired when the Popup is closed. If the callback returns True, the
dismiss will be canceled.
'''
if TTS_ENGINE == "espeak":
try:
subprocess.call(["espeak", "-q", "foo"])
except OSError:
TTS_ENABLED = False
print "Warning: espeak command not found, skipping voice generation"
else:
# non-espeak TTS engine being used
pass
# Create Kernel (using our custom version of the aiml kernel class)
k = MyKernel()
# Load the AIML files on first load, and then save as "brain" for speedier startup
if os.path.isfile("brain.brn") is False:
k.learn("inizializzazione.xml")
k.respond("load aiml b")
k.saveBrain("brain.brn")
else:
k.loadBrain("brain.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
