def verify_password(token, password):
# first try to authenticate by token
user = None
s = Serializer(app.config['SECRET_KEY'])
try:
data = s.loads(token)
rows = connectDB.db_select(
"select id, username from users where id = %s ;", (data['id'], ))
user = {'id': rows[0][0], 'username': rows[0][1].strip()}
except SignatureExpired:
print("SignatureExpired") # valid token, but expired
except BadSignature:
print("BadSignature") # invalid token
if not user:
# try to authenticate with username/password
rows = connectDB.db_select(
"select id, username, password from users where username = %s limit 1;",
(token, ))
# verify password
if len(rows) == 0 or not pwd_context.verify(password,
rows[0][2].strip()):
print("no user " + token)
return False
user = {'id': rows[0][0], 'username': rows[0][1].strip()}
g.user = user
s = Serializer(app.config['SECRET_KEY'], expires_in=3600)
return jsonify({
'user': user['username'],
'duration': 3600,
'token': s.dumps({
'id': user['id']
}).decode('ascii')
})
def WordIntentList():
# list all intent
i = request.args.get('i')
if i is None or i == "":
rows = connectDB.db_select(
"select word, intent from word_intent order by intent ", [])
else:
rows = connectDB.db_select(
"select word, intent from word_intent where intent = %s ", [i])
# store to dict
i_dict = {}
for row in rows:
word = row[0].strip()
intent = row[1].strip()
if intent not in i_dict:
i_dict[intent] = []
i_dict[intent].append(word)
# reconstruct
print(i_dict)
ret = []
for intent in i_dict:
ii = {'intent': intent, 'words': []}
ii['words'] = i_dict[intent]
ret.append(ii)
return jsonify(ret)
def retest():
global classifier
global tmp_training_file
print("testing trained data...")
# write training file
rows = connectDB.db_select(
"select message, keywords, intent from train_set;", [])
count = 0
total = 0
for row in rows:
m = row[0].strip()
i = row[2].strip()
res = test(m, False)
r_i = res['intent']
r_f = res['found']
r_c = res['confidence']
print("m: '" + m + "' i: '" + i + "' r: '" + r_i + "' f: '" + r_f +
"' c: " + str(r_c))
total += 1
if i == r_i:
count += 1
else:
print("wrong! expexted: " + i + " got: " + r_i)
print("-------------------------------")
rate = (count / total) * 100
print("result, total: " + str(total) + " correct: " + str(count) +
" percent: " + str(rate))
result = {'total': str(total), 'correct': str(count), 'percent': str(rate)}
return result
def searchWord(m):
rows = connectDB.db_select(
"select distinct intent from word_intent where word = %s ", [m])
if len(rows) > 0:
return (rows)
else:
return ("empty")
def WordIntent(w):
# get intent i for word w
rows = connectDB.db_select(
"select word, intent from word_intent where word = %s ", [w])
intent = []
for row in rows:
intent.append(row[1].strip())
return jsonify(intent)
def trainWordList(q):
result = []
ql = '%' + q + '%'
rows = connectDB.db_select(
'select message, keywords, intent from train_set where message like %s or intent like %s',
[ql, ql])
for row in rows:
message = row[0].strip()
keywords = row[1].strip()
intent = row[2].strip()
result.append({
'message': message,
'intent': intent,
'keyword': keywords
})
return jsonify(result)
def load_classifier():
global classifier
global tmp_training_file
epoch = 10
# write training file
rows = connectDB.db_select(
"select message, keywords, intent from train_set;", [])
count = 0
with open(tmp_training_file, "w") as t_f:
for e in range(0, epoch):
for row in rows:
l = '__label__' + \
row[2].strip().replace(" ", "_;") + \
' __label__' + row[1].strip() + "\n"
t_f.write(l)
count += 1
# reload classifier
if count > 0:
#classifier = fasttext.train_supervised(tmp_training_file, 'class', label_prefix='__label__', pretrained_vectors='model.vec')
classifier = fasttext.train_supervised(input="tmp_train_2.txt", lr=1)
classifier.save_model("model.bin")
