def bot_ui():
corp_dir = os.path.join(PROJECT_ROOT, 'Data', 'Corpus')
knbs_dir = os.path.join(PROJECT_ROOT, 'Data', 'KnowledgeBase')
res_dir = os.path.join(PROJECT_ROOT, 'Data', 'Result')
with tf.Session() as sess:
predictor = BotPredictor(sess,
corpus_dir=corp_dir,
knbase_dir=knbs_dir,
result_dir=res_dir,
result_file='basic')
# This command UI has a single chat session only
session_id = predictor.session_data.add_session()
print("Welcome to Chat with ChatLearner!")
print("Type exit and press enter to end the conversation.")
# Waiting from standard input.
sys.stdout.write("> ")
sys.stdout.flush()
question = sys.stdin.readline()
while question:
if question.strip() == 'exit':
print("Thank you for using ChatLearner. Goodbye.")
break
print(predictor.predict(session_id, question))
print("> ", end="")
sys.stdout.flush()
question = sys.stdin.readline()
def test_demo():
print("# Creating TF session ...")
corp_dir = os.path.join(PROJECT_ROOT, 'Data', 'Corpus')
knbs_dir = os.path.join(PROJECT_ROOT, 'Data', 'KnowledgeBase')
res_dir = os.path.join(PROJECT_ROOT, 'Data', 'Result')
test_dir = os.path.join(PROJECT_ROOT, 'Data', 'Test')
in_file = os.path.join(test_dir, 'samples.txt')
out_file = os.path.join(test_dir, 'responses.txt')
with tf.Session() as sess:
predictor = BotPredictor(sess, corpus_dir=corp_dir, knbase_dir=knbs_dir,
result_dir=res_dir, result_file='basic')
session_id = predictor.session_data.add_session()
print("# Prediction started ...")
t0 = time.time()
with open(in_file, 'r') as f_in:
with open(out_file, 'a') as f_out:
f_out.write(get_header())
for line in f_in:
sentence = line.strip()
if not sentence or sentence.startswith("#=="):
continue
f_out.write("> {}\n".format(sentence))
f_out.write("{}\n\n".format(predictor.predict(session_id, sentence)))
t1 = time.time()
print("# Prediction completed. Time spent on prediction: {:4.2f} seconds".format(t1-t0))
def bot_ui(resultfolder):
corp_dir = os.path.join(PROJECT_ROOT, 'Data', 'Corpus')
knbs_dir = os.path.join(PROJECT_ROOT, 'Data', 'KnowledgeBase')
res_dir = os.path.join(PROJECT_ROOT, 'Data', resultfolder)
with tf.Session() as sess:
predictor = BotPredictor(sess,
corpus_dir=corp_dir,
knbase_dir=knbs_dir,
result_dir=res_dir,
hparams_dir=res_dir)
print("Welcome to Chat with ChatLearner!")
print("Type exit and press enter to end the conversation.")
# Waiting from standard input.
sys.stdout.write("> ")
sys.stdout.flush()
sentence = sys.stdin.readline()
while sentence:
if not sentence.strip():
continue
if sentence.strip() == 'exit':
print("Thank you for using ChatLearner. Goodbye.")
break
print(predictor.predict(sentence))
print("> ", end="")
sys.stdout.flush()
sentence = sys.stdin.readline()
def bot_ui():
corp_dir = os.path.join(PROJECT_ROOT, 'Data', 'Corpus')
knbs_dir = os.path.join(PROJECT_ROOT, 'Data', 'KnowledgeBase')
res_dir = os.path.join(PROJECT_ROOT, 'Data', 'Result')
with tf.Session() as sess:
predictor = BotPredictor(sess,
corpus_dir=corp_dir,
knbase_dir=knbs_dir,
result_dir=res_dir,
result_file='basic')
# This command UI has a single chat session only
session_id = predictor.session_data.add_session()
print("Type exit and press enter to end the conversation.")
# Waiting from standard input.
sys.stdout.write(
"Say something to be recognized by the google cloud API voices\n")
sys.stdout.write("> ")
sys.stdout.flush()
# question = recognize_voice()
question = sys.stdin.readline()
while question:
if question.strip() == 'exit':
break
# import pdb
# pdb.set_trace()
result = re.sub(r'_nl_|_np_', '\n',
predictor.predict(session_id, question)).strip()
print(result)
text_to_speech_recognizer(result)
# print(re.sub(r'_nl_|_np_', '\n', predictor.predict(session_id, question)).strip())
print("> ", end="")
sys.stdout.flush()
question = sys.stdin.readline()
def bot_ui():
corp_dir = os.path.join(PROJECT_ROOT, 'Data', 'Corpus')
knbs_dir = os.path.join(PROJECT_ROOT, 'Data', 'KnowledgeBase')
res_dir = os.path.join(PROJECT_ROOT, 'Data', 'Result')
with tf.Session() as sess:
predictor = BotPredictor(sess,
corpus_dir=corp_dir,
knbase_dir=knbs_dir,
result_dir=res_dir,
result_file='basic')
# This command UI has a single chat session only
session_id = predictor.session_data.add_session()
# Waiting from standard input.
question = ''.join(sys.argv[1:])
#print(question)#, file=sys.stdout)
#print("\n")
print(
re.sub(r'_nl_|_np_', ' ', predictor.predict(session_id,
question)).strip())
def main():
corp_dir = os.path.join(PROJECT_ROOT, 'Data', 'Corpus')
knbs_dir = os.path.join(PROJECT_ROOT, 'Data', 'KnowledgeBase')
res_dir = os.path.join(PROJECT_ROOT, 'Data', 'Result')
with tf.Session() as sess:
predictor = BotPredictor(sess,
corpus_dir=corp_dir,
knbase_dir=knbs_dir,
result_dir=res_dir,
result_file='basic-32334')
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
host = '127.0.0.1'
port = int(2000)
sock.bind((host, port))
sock.listen(1)
print("chatServer Start...\n")
while True:
connection, client_addr = sock.accept()
# print(connection, client_addr)
data = connection.recv(1024)
data = data.decode("utf-8")
print("data > " + data)
# This command UI has a single chat session only
session_id = predictor.session_data.add_session()
question = data
if question.strip() == 'exit':
print("Thank you for using HeroBot. Goodbye.")
break
answer = predictor.predict(session_id, question)
print("answ > " + answer)
connection.sendall(answer.encode("utf-8"))
connection.close()
sock.close()