"""
Train retrieval-based chatbot on xiaohuangji subtitle dataset.
Use python 3
"""
import os
import sys
sys.path.append(os.getcwd())
sys.path.append(os.getcwd() + '/chatbot')
sys.path.append(os.getcwd() + '/chatbot/corpus')
args_in = '--device gpu0 ' \
'--test daemon ' \
'--modelTag xiaohuangji_2l_lr002_dr09_emb256_len20_vocab8000 ' \
'--vocabularySize 8000 --maxLength 20 ' \
'--learningRate 0.002 --dropout 0.9 ' \
'--rootDir /Users/xushuang/sf/chatbot/DeepQA/ ' \
'--saveEvery 500 ' \
'--corpus xiaohuangji '.split() # --datasetTag wechat ' \
from chatbot import chatbot
print(args_in)
chatbot = chatbot.Chatbot()
chatbot.main(args_in)
print(chatbot.daemonPredict("工作"))
def setUp(self):
self.chatbot = chatbot.Chatbot()
def __init__(self):
bot = chatbot.Chatbot()
def get_negative_timeline():
telco = request.args.get("telco")
data = t_sentis.get_negative_count(telco)
return jsonify(data)
@app.route("/totalTweets",methods=["GET"])
def get_total_tweets():
telco = request.args.get("telco")
data = t_graph.get_total_tweets(telco)
return jsonify(data)
if __name__ == "__main__":
#Init all the ML Models
app.config["DATA"] = os.path.join(app.root_path, 'data', 'DATA.csv')
app.config["M1"] = os.path.join(app.root_path, 'data', 'm1.csv')
app.config["STARHUB"] = os.path.join(app.root_path, 'data', 'starhub.csv')
app.config["GREV"] = os.path.join(app.root_path, 'data', 'GREV.json')
app.config["GREVS"] = os.path.join(app.root_path, 'data', 'GREVS.json')
app.config["GREVM"] = os.path.join(app.root_path, 'data', 'GREVM.json')
global chat_bot, t_graph, t_tweets, t_sentis, t_grev
chat_bot = chatbot.Chatbot(app)
t_graph = graphs.Graphs(app)
t_tweets = tweets.Tweets(app)
t_sentis = sentiments.Sentiments(app)
t_grev = grev.Greviance(app)
#Have a config file for ports and static stuff
app.run()
def get_chatbot(self):
cbot = chatbot.Chatbot()
cbot.initResponseCall()
return cbot
import os
from flask import Flask, request, send_file, send_from_directory, session
from werkzeug import secure_filename
# belows include self-define libs and func
from AWWW_wav_to_spectro import wav2sep
from AWWW_wav_to_STT import input_filename
from AWWW_jiebaCut import func_cut
from AWWW_chatbot_response import Chat_with_Bot
from AWWW_pic_pred import pred
# aboves include self-define libs and func
import numpy as np
import json
from chatbot import chatbot
AkishinoProjectBot = chatbot.Chatbot()
AkishinoProjectBot.main([
'--modelTag', 'taiwa20170709', '--test', 'daemon', '--initEmbeddings',
'--embeddingSource=wiki.zh.bin'
])
app = Flask(__name__)
app.config['UPLOAD_FOLDER'] = 'uploads/'
app.config['ALLOWED_EXTENSIONS'] = set(['wave', 'wav'])
def allowed_file(filename):
return '.' in filename and \
filename.rsplit('.', 1)[1] in app.config['ALLOWED_EXTENSIONS']
def __init__(self):
# instantiate QA Chatbot
self.chat = chatbot.Chatbot()
self.chat.telecomChatBotSessionOpen()
def main():
client = vkl.Client()
while not client.authorization():
continue
client.save_full_message_history()
cb = chatbot.Chatbot()
cb.main()
print(__info__)
url = client.make_url()
c = pycurl.Curl()
m = pycurl.CurlMulti()
last_rnd_id = 1
reply_count = 0
while True:
s = BytesIO()
c.setopt(c.URL, url)
c.setopt(c.WRITEFUNCTION, s.write)
m.add_handle(c)
while True:
ret, num_handles = m.perform()
if ret != pycurl.E_CALL_MULTI_PERFORM:
break
while num_handles: # main loop
animate_loading(
'Listening long poll... {} {ans}'.format(
reply_count,
ans = 'answer' if reply_count == 1 else 'answers'
), 1
)
while 1: # main loop (2)
ret, num_handles = m.perform()
if ret != pycurl.E_CALL_MULTI_PERFORM:
break
m.remove_handle(c)
response = s.getvalue()
response = response.decode('utf-8')
response = json.loads(response)
url = client.make_url(keep_ts=response['ts'])
for update in response['updates']:
if update[0] == 4 and\
update[7] !=\
last_rnd_id and\
update[6] != '':
# response == message
# message != last_message
# message != ''
text = update[6]
mark_msg = True
if re.sub('^( )*', '', text).startswith('/'):
text = text[1:]
if text.startswith('/'):
mark_msg = False
text = text[1:]
text = parse_input(text, replace_vkurl=False, replace_nl=False)
words = text.split()
if not words:
words = ' '
if re.match('^((help)|(помощь)|(info)|(инфо)|(информация)|\?)',\
words[0].lower()):
text = __info__
elif re.match('^((скажи)|(say))', words[0].lower()):
del words[0]
text = ' '.join(words)
else:
text = re.sub('(__nm__)|(__nl__)', '\n', cb.daemonPredict(text))
else:
continue
last_rnd_id = update[7] + 1
client.reply(
uid = update[3],
text = text + "'" if mark_msg else text,
rnd_id = last_rnd_id
)
reply_count += 1
def index():
if request.method == 'POST':
file = request.files['file']
if file and allowed_file(file.filename):
# print(file)
filename = secure_filename(file.filename)
file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
# return redirect(url_for('uploaded_file',filename = filename))
"""wav2sep(filename)
ans = pred()
# below decode json from nvidia digits output
jsondec = json.loads(ans.decode('utf8'))
jsondec = jsondec['predictions']
jsondec = str(jsondec).replace("[", "")
jsondec = str(jsondec).replace("]", "")
jsondec = "{" + jsondec + "}"
jsondec = jsondec.replace("',", "':")
jsondec = jsondec.replace("'", '"')
jsondec = json.loads(jsondec)
respred = ((jsondec['happy'], jsondec['sad'], jsondec['calm'], jsondec['fearful'], jsondec['angry']))
maxpred = (max(jsondec['happy'], jsondec['sad'], jsondec['calm'], jsondec['fearful'], jsondec['angry']))
if maxpred == jsondec['happy']:
print("開心 : " + str(jsondec['happy']))
elif maxpred == jsondec['sad']:
print("傷心 : " + str(jsondec['sad']))
elif maxpred == jsondec['calm']:
print("平靜 : " + str(jsondec['calm']))
elif maxpred == jsondec['fearful']:
print("害怕 : " + str(jsondec['fearful']))
elif maxpred == jsondec['angry']:
print("生氣 : " + str(jsondec['angry']))
else:
print("無法辨識")"""
from chatbot import chatbot
AkishinoProjectBot = chatbot.Chatbot()
"""if maxpred == (jsondec['happy']):
AkishinoProjectBot.main(['--modelTag', 'positive_negative_correct', '--test', 'daemon'])
elif maxpred == jsondec['sad']:
AkishinoProjectBot.main(['--modelTag', 'positive_negative_correct', '--test', 'daemon'])
elif maxpred == jsondec['calm']:
AkishinoProjectBot.main(['--modelTag', 'positive_negative_correct', '--test', 'daemon'])
elif maxpred == jsondec['fearful']:
AkishinoProjectBot.main(['--modelTag', 'positive_negative_correct', '--test', 'daemon'])
elif maxpred == jsondec['angry']:
AkishinoProjectBot.main(['--modelTag', 'positive_negative_correct', '--test', 'daemon'])
else:
print("無法辨識")"""
AkishinoProjectBot.main(
['--modelTag', 'model-AIA', '--test', 'daemon'])
asking = str(input_filename(filename))
print("asking = " + asking)
if asking == "None":
#responsing = Chat_with_Bot(asking, AkishinoProjectBot)
asking = "無法辨識"
print("chatbot_responsing asking = " + asking)
else:
asking = func_cut(input_filename(filename))
responsing = Chat_with_Bot(asking, AkishinoProjectBot)
print("chatbot_responsing asking_res = " + responsing)
if responsing == "":
responsing = "無法回應"
print("responsing = " + responsing)
#asking = str(input_filename(filename))
print("asking = " + asking)
#ans_del = pred_del(filename)
json_res = [{'1_ask': asking, '2_response': responsing}]
#print("maxpred = " + str(maxpred[0]))
#shutdown web server
shutdown()
#print(ans.decode('utf8').replace("\n"," "))
#return str(maxpred[0])
#reload = restart()
return jsonify(json_res)
#return (ans.decode('utf8') + "|" +"ask = "+ asking_res + "," + "response = "+ responsing)
return ("ask = " + asking + "," + "response = " + responsing)
return '''
def compute():
question = request.form['input_message']
chat = chatbot.Chatbot()
chat.main()
answer = chat.mainTestInteractive(message=question)
return
def init():
bot = chatbot.Chatbot()
bot.main(args_in)
return bot
def __init__(self, model_tag, chatbot_path):
self.bot = chatbot.Chatbot()
self.bot.main([
'--modelTag', model_tag, '--test', 'daemon', '--rootDir',
chatbot_path, '--keepAll'
])
def __init__(self, model_path):
self._model = chatbot.Chatbot(model_path)
self._model.start([])
self._response = "I didn't understand your question ?"
