def run_main_get_answer(request):
if enc_vocab == None:
chat_bot(request)
req_dict = eval(request.data.decode('utf8'))
user = req_dict['user']
project = req_dict['project']
question = req_dict['msg']
_, answer_num = run.run_chatbot(enc_vocab, rev_dec_vocab, question, False,
language)
if answer_num == '':
_, answer_num = run.run_chatbot(enc_vocab, rev_dec_vocab,
question + ' ', False, language)
if len(answer_num.split(";")) > 1:
answer = '해당 질문에 대한 답변이 하나 이상입니다. 좀더 구체적으로 부탁드립니다!'
else:
answer, _ = db_chat.get_answer_by_answer_num(user, project, answer_num)
_, point = sentence_comparator.compare_by_formula(user, project, question,
answer_num)
v, e = voca_util.get_voca_and_entity_from_question(question, all_voca)
word = ",".join(v)
entity = ""
for i in range(len(e)):
if e[i] != None and e[i] != "":
entity += e[i]
if i < len(e) - 1:
entity += ","
res = {'answer': answer, 'point': point, 'word': word, 'entity': entity}
return jsonify(res)
def reserve_list(request):
question = request.form['msg']
collect_q = False
_, answer_num = run.run_chatbot(enc_vocab, rev_dec_vocab, question,
collect_q, language)
if answer_num == '':
_, answer_num = run.run_chatbot(enc_vocab, rev_dec_vocab,
question + ' ', collect_q, language)
q_list = []
print(question, answer_num)
answer_num_arr = answer_num.split(";")
for aa in answer_num_arr:
q_list.append(answer_num_and_rpsn_question[aa])
num = len(q_list)
res = {'num': str(num)}
for i in range(num):
res['text' + str(i + 1)] = q_list[i]
bucket_id = bucket_util.get_bucket_id_by_sentence(buckets, question)
res['bucket_id'] = bucket_id
res['bucket_range'] = ''
if bucket_id < len(buckets) - 1:
res['bucket_range'] = buckets[bucket_id] + '~' + str(
int(buckets[bucket_id + 1]) - 1)
else:
res['bucket_range'] = buckets[bucket_id] + '~∞'
return jsonify(res)
def get_action_principle(request):
user = request.form['user']
project = request.form['project']
question = request.form['question']
enc_token_words = run.get_token_words(question)
enc_token_ids = run.get_token_ids(question, enc_vocab, language)
dec_token_ids, dec_token_words = run.run_chatbot(enc_vocab, rev_dec_vocab,
question, False, language)
res = {}
res['enc_token_words'] = str(enc_token_words)
res['enc_token_ids'] = str(enc_token_ids)
res['dec_token_words'] = str(dec_token_words)
res['dec_token_ids'] = str(dec_token_ids)
answer_dict = get_answer_dict(user, project)
dec_token_words_arr = dec_token_words.split(";")
answer = ''
if len(dec_token_words_arr) > 1:
for i in range(len(dec_token_words_arr)):
answer += '(' + str(i + 1) + ')\n' + answer_dict[
dec_token_words_arr[i]] + '\n'
else:
answer = answer_dict[dec_token_words]
res['answer'] = answer
return jsonify(res)
def reply_group_chat(request):
user, project = request.form['user'], request.form['project']
question = request.form['msg']
_, answer_num = run.run_chatbot(enc_vocab, rev_dec_vocab, question, False,
language)
if answer_num == '':
_, answer_num = run.run_chatbot(enc_vocab, rev_dec_vocab,
question + ' ', False, language)
if len(answer_num.split(";")) > 1:
answer = '해당 질문에 대한 답변이 하나 이상입니다. 좀더 구체적으로 부탁드립니다!'
else:
answer, _ = db_chat.get_answer_by_answer_num(user, project, answer_num)
image_path = faq_manager.get_image_path(user, project, answer_num)
user_ip = request.remote_addr
db_chat.collect_question(user_ip, question, answer_num)
res = {'answer': answer, 'image_path': str(image_path)}
return jsonify(res)
def run_main_get_answer(request):
if enc_vocab == None:
chat_bot(request)
req_dict = eval(request.data.decode('utf8'))
user = req_dict['user']
project = req_dict['project']
question = req_dict['msg']
_, answer_num = run.run_chatbot(enc_vocab, rev_dec_vocab, question, False, language)
if answer_num == '':
_, answer_num = run.run_chatbot(enc_vocab, rev_dec_vocab, question + ' ', False, language)
if len(answer_num.split(";")) > 1:
answer = 'more than one answer!'
else:
answer, _ = db_chat.get_answer_by_answer_num(user, project, answer_num)
_, point = sentence_comparator.compare_by_formula(user, project, question, answer_num)
res = {'answer' : answer, 'point' : point}
return jsonify(res)
def reply_group_chat(request):
user, project = request.form['user'], request.form['project']
question = request.form['msg']
question = question.lower()
_, answer_num = run.run_rc_chatbot(enc_vocab, rev_dec_vocab, question, False, language)
if answer_num == '':
_, answer_num = run.run_chatbot(enc_vocab, rev_dec_vocab, question + ' ', False, language)
if len(answer_num.split(";")) > 1:
answer = 'more than one answer!'
else:
answer, _ = db_chat.get_answer_by_answer_num(user, project, answer_num)
res = {'answer' : answer}
return jsonify(res)
def reply_dynamic_popup(request):
user, project = request.form['user'], request.form['project']
question = request.form['msg']
question = question.lower()
param_holder = eval(request.form['param_holder'])
_, answer_num = run.run_chatbot(enc_vocab, rev_dec_vocab, question, False, language)
answer, _ = db_chat.get_answer_by_answer_num(user, project, answer_num)
param = [param_holder]
msg = ['']
if answer[:1] == '$':
param[0]['function_nm'] = answer.replace('\n', '').split(" ")[1]
msg, _, _, param_holder = function_adapter.get_message_by_function(param, -1, 'Y')
res = {'text' : msg[0]}
return jsonify(res)
def reply(request):
user, project = request.form['user'], request.form['project']
global message_count
msg, question, image_path, tmp, page, answer_num, right_yn, collect_q, cq_num, cq, schedule_updated, trained_yn = [], request.form['msg'], '', request.form['tmp'], request.form['pge'], '', '', True, 0, [], 'N', True
mdfc_rgsn_date = ''
multiple_answer_num = request.form['multiple_answer_num']
message_count += 1
function_yn = 'N'
user_ip = request.remote_addr
param_holder = ''
if multiple_answer_num != '':
msg, tmp = faq_manager.get_answer_in_multiple(multiple_answer_num,
question, user,
project), ''
multiple_answer_num = ''
elif tmp != '':
msg, tmp, function_nm, param_holder = function_adapter.continue_dialogue(
user_ip, question, tmp)
if function_nm == 'set_my_schedule()':
schedule_updated = 'Y'
else:
param, replacedMsg = function_adapter.get_param_and_replaced_msg(
question)
is_fixed = fixed_question_processor.is_fixed_question(question)
if is_fixed == False:
_, answer_num = run.run_chatbot(enc_vocab, rev_dec_vocab,
replacedMsg, collect_q, language)
if answer_num == '':
_, answer_num = run.run_chatbot(enc_vocab, rev_dec_vocab,
replacedMsg + ' ', collect_q,
language)
if len(answer_num.split(";")) > 1:
answer = ''
message = faq_manager.get_reserve_question_list(
question, answer_num, answer_num_and_rpsn_question)
msg.append(message)
else:
answer, mdfc_rgsn_date = db_chat.get_answer_by_answer_num(
user, project, answer_num)
else:
answer = fixed_question_processor.get_function_by_question(
question)
multiple_answer_num = ''
if answer != '':
if answer[:1] == '$':
param[0]['function_nm'] = answer.replace('\n',
'').split(" ")[1]
msg, tmp, function_nm, param_holder = function_adapter.get_message_by_function(
param, message_count, 'N')
function_yn = 'Y'
else:
tmp = ''
multiple_answer_num, multiple_answer = faq_manager.check_multiple_answer(
answer_num, user, project)
if multiple_answer_num != '':
msg.append(multiple_answer)
else:
msg, right_yn, image_path, trained_yn = faq_manager.get_faq_answer(
user, project, msg, answer_num, answer, question,
message_count, mdfc_rgsn_date)
db_chat.collect_question(user_ip, question, answer_num)
cq = db_chat.get_same_category_question_list(
user, project, answer_num)
cq_num = len(cq)
num = len(msg)
res = {
'num': str(num),
'cq_num': str(cq_num),
'message_count': message_count,
'qst': question,
'ans_num': answer_num,
'image_path': str(image_path),
'right_yn': right_yn,
'temp': tmp,
'page': page,
'schedule_updated': schedule_updated,
'multiple_answer_num': multiple_answer_num
}
res['rpsn_question'] = ''
res['function_yn'] = function_yn
res['param_holder'] = param_holder
if trained_yn == True:
res['rpsn_question'] = answer_num_and_rpsn_question.get(answer_num, '')
for i in range(num):
res['text' + str(i + 1)] = msg[i]
for i in range(cq_num):
res['cq' + str(i + 1)] = cq[i]
return jsonify(res)
