def processIncoming(user_id, message, just_text=False):
# First time user
if not Mongo.user_exists(users, user_id):
g.user = Mongo.get_user_mongo(users, user_id)
return handle_first_time_user(users, g.user)
else:
g.user = Mongo.get_user_mongo(users, user_id)
last_seen = datetime.strptime(g.user['last_seen'],"%Y-%m-%d %H:%M:%S")
recent5min = datetime.now() - timedelta(minutes=5)
if last_seen < recent5min:
Mongo.update_last_seen(users, g.user)
contextData = g.user['contexts']
# Text message type =========================================================
if just_text or message['type'] == 'text':
# just_text is transcribe audio
message_text = message if just_text else message['data']
if dev_area(message_text): # go through development codes
return 'pseudo'
if message_text.lower() == "help":
handle_help(user_id)
return 'pseudo'
if message_text[-1] != ".": # help separate sentence for parsetree
dotted_message = message_text + "."
s = parsetree(dotted_message, relations=True, lemmata=True)
sentence = s[0]
nounPhrase = NLP.findNounPhrase(sentence)
if NLP.isAskingBotInformation(sentence):
return NLP.handleBotInfo(sentence)
if contextData is not None and len(contextData) > 0:
context = contextData[-1]
if NLP.isDismissPreviousRequest(message_text):
Mongo.pop_context(users, g.user)
return "Sure, no problem"
# Find food functionality
if context['context'] == 'find-food':
return handle_find_food(user_id, context, sentence, nounPhrase, message, message_text, 'receive_location_text')
elif context['context'] == 'yelp-rename':
handle_yelp_rename(user_id, g.user, context, message_text)
Mongo.pop_context(users, g.user) # pop yelp-rename
return "Ta da! %s is now in my cloudy memory :D"%(message_text)
elif context['context'] == 'create-memo':
return handle_memo(user_id, message_text)
else:
if NLP.isGreetings(message_text):
greeting = "%s %s :D"%(NLP.sayHiTimeZone(g.user), g.user['first_name'])
FB.send_message(app.config['PAT'], user_id, greeting)
return "How can I help you?"
elif NLP.isGoodbye(message_text):
return NLP.sayByeTimeZone(g.user)
elif NLP.isYelp(sentence):
print nounPhrase
return handle_find_food(user_id, None, sentence, nounPhrase, message, message_text, 'receive_request')
elif NLP.isMemoCommandOnly(message_text):
data = { 'context': 'create-memo' }
Mongo.add_context(users, g.user, data)
return "I'm listening, go ahead :D"
elif NLP.isMemo(message_text):
content = NLP.get_memo_content(message_text)
return handle_memo(user_id, content)
elif NLP.isGetNews(sentence):
keyword = NLP.getNewsQuery(sentence)
FB.send_message(app.config['PAT'], user_id, "Scanning %s documents on the Internet B-)"%(random.randint(9999,999999)*random.randint(9999,999999)+random.randint(1,9)) )
FB.show_typing(app.config['PAT'], user_id)
posts = News.get_trending_news(keyword)
FB.show_typing(app.config['PAT'], user_id, 'typing_off')
# Log if there's no result to analyze
if len(posts) == 0:
FB.send_message(app.config['PAT'], user_id, "Sorry, I can't find any news for that :(")
Mongo.log_message(log, user_id, 'no_news', keyword)
else:
FB.send_trending_news(app.config['PAT'], user_id, posts)
return 'pseudo'
else:
# Log this message for categorization later
Mongo.log_message(uncategorized_messages, user_id, "text", message_text)
try:
response = simSimi.getConversation(message_text)['response']
bad_times = 0
while NLP.badWords(response):
bad_times += 1
print response
response = simSimi.getConversation(message_text)['response']
if bad_times == 5:
return "Hmm... I can't think of anything witty enough to respond to that :P"
if 'simsimi' in response.lower():
response = response.lower().replace("simsimi", "Optimist Prime")
return response
except simsimi.SimSimiException as e:
print e
return # return None will trigger a bot confusion response
# ==/ END Text message type =====================================================
# Location message type =========================================================
elif message['type'] == 'location':
FB.send_message(app.config['PAT'], user_id, "I've received location (%s,%s) (y)"%(message['data'][0],message['data'][1]))
if contextData is not None and len(contextData) > 0:
context = contextData[-1]
if 'context' in context and context['context'] == 'find-food':
return handle_find_food(user_id, context, None, None, message, None, 'receive_location_gps')
else:
return 'pseudo'
# ==/ END Location message type ==================================================
# Audio message type =========================================================
elif message['type'] == 'audio':
audio_url = message['data']
# Get text from audio
try:
message_text = STT.transcribe(audio_url)
if message_text == "" or message_text == None:
return
# if 'DISPLAY_STT_RESULT' in os.environ and os.environ['DISPLAY_STT_RESULT'] != 0:
print message_text
except Exception, e:
message_text = "Sorry I can't process that now :("
FB.send_message(app.config['PAT'], user_id, message_text)
print e
return
# Begin processing audio command
message_text = message_text.decode('utf-8')
return processIncoming(user_id, message_text, True)
def processIncoming(user_id, message, just_text=False):
# First time user
if not Mongo.user_exists(users, user_id):
g.user = Mongo.get_user_mongo(users, user_id)
return handle_first_time_user(users, g.user)
else:
g.user = Mongo.get_user_mongo(users, user_id)
last_seen = datetime.strptime(g.user['last_seen'], "%Y-%m-%d %H:%M:%S")
recent5min = datetime.now() - timedelta(minutes=5)
if last_seen < recent5min:
Mongo.update_last_seen(users, g.user)
contextData = g.user['contexts']
# Text message type =========================================================
if just_text or message['type'] == 'text':
# just_text is transcribe audio
message_text = message if just_text else message['data']
if dev_area(message_text): # go through development codes
return 'pseudo'
if message_text.lower() == "help":
handle_help(user_id)
return 'pseudo'
if message_text[-1] != ".": # help separate sentence for parsetree
dotted_message = message_text + "."
s = parsetree(dotted_message, relations=True, lemmata=True)
sentence = s[0]
nounPhrase = NLP.findNounPhrase(sentence)
if NLP.isAskingBotInformation(sentence):
return NLP.handleBotInfo(sentence)
if contextData is not None and len(contextData) > 0:
context = contextData[-1]
if NLP.isDismissPreviousRequest(message_text):
Mongo.pop_context(users, g.user)
return "Sure, no problem"
# Find food functionality
if context['context'] == 'find-food':
return handle_find_food(user_id, context, sentence, nounPhrase,
message, message_text,
'receive_location_text')
elif context['context'] == 'yelp-rename':
handle_yelp_rename(user_id, g.user, context, message_text)
Mongo.pop_context(users, g.user) # pop yelp-rename
return "Ta da! %s is now in my cloudy memory :D" % (
message_text)
elif context['context'] == 'create-memo':
return handle_memo(user_id, message_text)
else:
if NLP.isGreetings(message_text):
greeting = "%s %s :D" % (NLP.sayHiTimeZone(
g.user), g.user['first_name'])
FB.send_message(app.config['PAT'], user_id, greeting)
return "How can I help you?"
elif NLP.isGoodbye(message_text):
return NLP.sayByeTimeZone(g.user)
elif NLP.isYelp(sentence):
print nounPhrase
return handle_find_food(user_id, None, sentence, nounPhrase,
message, message_text,
'receive_request')
elif NLP.isMemoCommandOnly(message_text):
data = {'context': 'create-memo'}
Mongo.add_context(users, g.user, data)
return "I'm listening, go ahead :D"
elif NLP.isMemo(message_text):
content = NLP.get_memo_content(message_text)
return handle_memo(user_id, content)
elif NLP.isGetNews(sentence):
keyword = NLP.getNewsQuery(sentence)
FB.send_message(
app.config['PAT'], user_id,
"Scanning %s documents on the Internet B-)" %
(random.randint(9999, 999999) *
random.randint(9999, 999999) + random.randint(1, 9)))
FB.show_typing(app.config['PAT'], user_id)
posts = News.get_trending_news(keyword)
FB.show_typing(app.config['PAT'], user_id, 'typing_off')
# Log if there's no result to analyze
if len(posts) == 0:
FB.send_message(
app.config['PAT'], user_id,
"Sorry, I can't find any news for that :(")
Mongo.log_message(log, user_id, 'no_news', keyword)
else:
FB.send_trending_news(app.config['PAT'], user_id, posts)
return 'pseudo'
else:
# Log this message for categorization later
Mongo.log_message(uncategorized_messages, user_id, "text",
message_text)
try:
response = simSimi.getConversation(
message_text)['response']
bad_times = 0
while NLP.badWords(response):
bad_times += 1
print response
response = simSimi.getConversation(
message_text)['response']
if bad_times == 5:
return "Hmm... I can't think of anything witty enough to respond to that :P"
if 'simsimi' in response.lower():
response = response.lower().replace(
"simsimi", "Optimist Prime")
return response
except simsimi.SimSimiException as e:
print e
return # return None will trigger a bot confusion response
# ==/ END Text message type =====================================================
# Location message type =========================================================
elif message['type'] == 'location':
FB.send_message(
app.config['PAT'], user_id, "I've received location (%s,%s) (y)" %
(message['data'][0], message['data'][1]))
if contextData is not None and len(contextData) > 0:
context = contextData[-1]
if 'context' in context and context['context'] == 'find-food':
return handle_find_food(user_id, context, None, None, message,
None, 'receive_location_gps')
else:
return 'pseudo'
# ==/ END Location message type ==================================================
# Audio message type =========================================================
elif message['type'] == 'audio':
audio_url = message['data']
# Get text from audio
try:
message_text = STT.transcribe(audio_url)
if message_text == "" or message_text == None:
return
# if 'DISPLAY_STT_RESULT' in os.environ and os.environ['DISPLAY_STT_RESULT'] != 0:
print message_text
except Exception, e:
message_text = "Sorry I can't process that now :("
FB.send_message(app.config['PAT'], user_id, message_text)
print e
return
# Begin processing audio command
message_text = message_text.decode('utf-8')
return processIncoming(user_id, message_text, True)
def handle_messages():
# print "Handling Messages"
payload = request.get_data()
if app.config['PRINT_INCOMING_PAYLOAD']:
print payload
token = app.config['PAT']
webhook_type = get_type_from_payload(payload)
# Handle Postback
# Developer-defined postbacks
# Currently in use: Help button (in Persistent Menu), and Getting Started button (first-time users will see this)
if webhook_type == 'postback':
for sender_id, postback_payload in postback_events(payload):
if postback_payload == 'OPTIMIST_HELP':
handle_help(sender_id)
elif postback_payload == 'OPTIMIST_GET_STARTED':
if not Mongo.user_exists(users, sender_id):
g.user = Mongo.get_user_mongo(users, sender_id)
return handle_first_time_user(users, g.user)
# Handle messages
elif webhook_type == 'message':
for sender_id, message in messaging_events(payload):
# Only process message in here
if not message:
return "ok"
# Handle Facebook's bug when receiving long audio
# The bug: The app keeps receiving the same POST request
# This acts as a rescue exit signal
global temp_message_id
mid = message['message_id']
if mid == temp_message_id:
return 'ok'
temp_message_id = mid
# Start processing valid requests
if app.config['PRINT_INCOMING_MESSAGE']:
print "User ID: %s\nMessage:%s" % (sender_id, message)
try:
FB.show_typing(token, sender_id)
response = processIncoming(sender_id, message)
FB.show_typing(token, sender_id, 'typing_off')
if response is not None and response != 'pseudo':
# 'pseudo' is an "ok" signal for functions that sends response on their own
# without returning anything back this function
print response
FB.send_message(token, sender_id, response)
elif response != 'pseudo':
if NLP.randOneIn(7):
FB.send_message(token, sender_id, NLP.oneOf(NLP.no_response))
FB.send_picture(token, sender_id, 'https://monosnap.com/file/I6WEAs2xvpZ5qTNmVauNguEzcaRrnI.png')
except Exception, e:
print e
traceback.print_exc()
FB.send_message(app.config['PAT'], sender_id, NLP.oneOf(NLP.error))
Mongo.pop_context(users, g.user)
if NLP.randOneIn(7):
FB.send_picture(app.config['PAT'], sender_id, 'https://monosnap.com/file/3DnnKT60TkUhF93dwjGbNQCaCUK9WH.png')
def handle_messages():
# print "Handling Messages"
payload = request.get_data()
if app.config['PRINT_INCOMING_PAYLOAD']:
print payload
token = app.config['PAT']
webhook_type = get_type_from_payload(payload)
# Handle Postback
# Developer-defined postbacks
# Currently in use: Help button (in Persistent Menu), and Getting Started button (first-time users will see this)
if webhook_type == 'postback':
for sender_id, postback_payload in postback_events(payload):
if postback_payload == 'OPTIMIST_HELP':
handle_help(sender_id)
elif postback_payload == 'OPTIMIST_GET_STARTED':
if not Mongo.user_exists(users, sender_id):
g.user = Mongo.get_user_mongo(users, sender_id)
return handle_first_time_user(users, g.user)
# Handle messages
elif webhook_type == 'message':
for sender_id, message in messaging_events(payload):
# Only process message in here
if not message:
return "ok"
# Handle Facebook's bug when receiving long audio
# The bug: The app keeps receiving the same POST request
# This acts as a rescue exit signal
global temp_message_id
mid = message['message_id']
if mid == temp_message_id:
return 'ok'
temp_message_id = mid
# Start processing valid requests
if app.config['PRINT_INCOMING_MESSAGE']:
print "User ID: %s\nMessage:%s" % (sender_id, message)
try:
FB.show_typing(token, sender_id)
response = processIncoming(sender_id, message)
FB.show_typing(token, sender_id, 'typing_off')
if response is not None and response != 'pseudo':
# 'pseudo' is an "ok" signal for functions that sends response on their own
# without returning anything back this function
print response
FB.send_message(token, sender_id, response)
elif response != 'pseudo':
if NLP.randOneIn(7):
FB.send_message(token, sender_id,
NLP.oneOf(NLP.no_response))
FB.send_picture(
token, sender_id,
'https://monosnap.com/file/I6WEAs2xvpZ5qTNmVauNguEzcaRrnI.png'
)
except Exception, e:
print e
traceback.print_exc()
FB.send_message(app.config['PAT'], sender_id,
NLP.oneOf(NLP.error))
Mongo.pop_context(users, g.user)
if NLP.randOneIn(7):
FB.send_picture(
app.config['PAT'], sender_id,
'https://monosnap.com/file/3DnnKT60TkUhF93dwjGbNQCaCUK9WH.png'
)