def train(cll, collection):
sockets.send("What's the label?")
label = sockets.recv(BUFFER_SIZE)
sockets.send("What's the command?")
command = sockets.recv(BUFFER_SIZE)
new_data = [(command, label)]
cll.update(new_data)
post = {"label":label, "command":command}
collection.insert_one(post)
f = open(classifier_file, 'wb')
pickle.dump(cll, f)
sockets.send("Got it!")
def parseCommand(command, cll, classifier_file):
confidence_threshold = config.confidence_threshold
prob_dist = cll.prob_classify(command)
labels = cll.labels()
prob_label_dict = dict()
risk = algorithms.getRisk(command)
mpl = labels[0]
# for correcting spelling mistakes, don't think i'll use this
#command = str(TextBlob(command).correct())
#print "Corrected command " + command
# before using the classifier, check if it is a built in command
if isBuiltIn(command):
return command, algorithms.getRisk(command)
for label in labels:
if prob_dist.prob(label) > prob_dist.prob(mpl):
mpl = label
prob_label_dict[label] = prob_dist.prob(label)
print "Most probable label: " + str(mpl) + ", prob: " + str(prob_dist.prob(mpl))
# this is if the threshold wasn't passed. Add more to knowledge
if prob_dist.prob(mpl) < confidence_threshold:
sockets.send("Is this a " + mpl + " command?")
a = sockets.recv(BUFFER_SIZE)
if a == "yes" or a == "yeah":
new_data = [(command, mpl)]
addKnowledge(new_data, cll)
return mpl, risk
else:
sockets.send("Want to add this to something I already know?")
ans = sockets.recv(BUFFER_SIZE)
if ans == "yes" or ans == "yeah":
update_classifier(command, cll)
return -1, 0
else:
sockets.send("Okay then!")
return -1, 0
# add what was just said to the classifier if it passed the threshold
if prob_dist.prob(mpl) > confidence_threshold:
new_data = [(command, mpl)]
addKnowledge(new_data, cll)
return mpl, risk
def update_classifier(command, cll):
sockets.send("Ok what type of command is this?")
new_label = sockets.recv(BUFFER_SIZE)
if new_label != "no command":
sockets.send("Okay, let's try that again then!")
new_data = [(command, new_label)]
cll.update(new_data)
f = open(classifier_file, 'wb')
pickle.dump(cll, f)
def test_command(cll):
sockets.send("What command would you like to test?")
command = sockets.recv(BUFFER_SIZE)
labels = cll.labels()
mpl = labels[0]
prob_dist = cll.prob_classify(command)
for label in labels:
if prob_dist.prob(label) > prob_dist.prob(mpl):
mpl = label
per = prob_dist.prob(mpl)
per = "{0:.4f}".format(per)
per = int(float(per)*100.0)
sockets.send("I am %s percent certain this is a %s command" %(str(per), str(mpl)))
def dealClient(conn, addr):
szBuf = sockets.recv(conn)
logging.info(szBuf)
# 执行命令
if szBuf.find(exe_c) == 0:
szBuf = szBuf.replace(exe_c, '')
# 执行命令
out = commands.getstatusoutput(szBuf)
result = ""
# 获取结果,根据返回值判断是否出错
if out[0] == 0:
result = "[resp]" + out[1]
else:
result = "[error]" + out[1]
# 修改ip以及其他地址
elif szBuf.find(ip_c) == 0:
szBuf = szBuf.replace(ip_c, "")
# config to auto get ip
if '|' not in szBuf:
if szBuf.find(ip_c_null) == 0:
with open(ip_c_file, "w") as f:
f.write(ip_c_str_null)
result = "[resp]ip conf null ok"
else:
result = "[error]argvs error"
# 设置静态ip
else:
argvs = szBuf.split("|")
# 三个参数,否则出错
if len(argvs) == 3:
text = ip_c_str.format(argvs[0], argvs[1], argvs[2])
with open(ip_c_file, "w") as f:
f.write(text)
out = commands.getstatusoutput("chmod a+x " + ip_c_file)
if out[0] == 0:
result = "[resp]ip conf ok"
else:
result = '[error]ip cong error file i/o error'
else:
result = "[error]argvs error"
else:
conn.close()
return
logging.info(result)
conn.send(result)
conn.close()
#!/usr/bin/python # coding:utf-8 import sockets import logging logging.basicConfig(level=logging.INFO) s = sockets.connectServer() exe = "mkdir /var/lib/test/ddd" logging.info(exe) exe = "[exec]" + exe s.send(exe) result = sockets.recv(s) logging.info(result) s.close()
import sockets
import parser
import time
#from pymongo import MongoClient
import built_in
import algorithms
cll = parser.cll
classifier_file = parser.classifier_file
#client = MongoClient('localhost', 27000)
#db = client.smartTalk_db
#collection = db.responses
while True:
command = sockets.recv(1024)
if not command:
break
return_label, risk = parser.parseCommand(command, cll, classifier_file)
print "return_label: " + str(return_label)
print "risk: " + str(risk)
if return_label == "greeting":
#response = algorithms.greet(return_label, command, collection)
response = "Hello"
sockets.send(str(response))
continue
elif return_label == "test command":
built_in.test_command(cll)
continue
elif return_label == "train":
built_in.train(cll, collection)