123 lines
3.4 KiB
Python
123 lines
3.4 KiB
Python
from bot import *
|
|
|
|
import dataset, random, time, re
|
|
|
|
async def rec(self, m):
|
|
prew = shared.db['prew']
|
|
noch = shared.db['noun']
|
|
beg = shared.db['beg']
|
|
end = shared.db['end']
|
|
pre = ''
|
|
words = m.split(' ')
|
|
if words[0] == 'admin':
|
|
return
|
|
for w in words:
|
|
if pre == '':
|
|
beg.insert(dict(word=w))
|
|
else:
|
|
prew.insert_ignore(dict(pre=pre, pro=w),['id'])
|
|
pre = w
|
|
noch.insert(dict(word=w))
|
|
end.insert(dict(word=pre))
|
|
|
|
async def getNoun(self, words, c):
|
|
if c in shared.cstate:
|
|
oldnoun = shared.cstate[c]
|
|
else:
|
|
oldnoun = None
|
|
|
|
shared.db['remsg'].insert_ignore(dict(noun=oldnoun,msg=' '.join(words)),['id'])
|
|
|
|
nouns = [i['word'] for i in shared.db['noun'].find()]
|
|
out = {}
|
|
for i in words:
|
|
out[i] = nouns.count(i)
|
|
noun = min(out, key=out.get)
|
|
|
|
conversation = shared.db['conver']
|
|
if oldnoun != None:
|
|
print("adding", [oldnoun,noun])
|
|
conversation.insert_ignore(dict(pre=oldnoun,pro=noun),['id'])
|
|
|
|
nextnoun = [i['pro'] for i in conversation.find(pre=noun)]
|
|
print("nextnoun:",nextnoun)
|
|
if len(nextnoun) > 0:
|
|
noun = random.choice(nextnoun)
|
|
shared.cstate[c] = noun
|
|
return noun
|
|
|
|
async def genOut(self, noun):
|
|
oldresponses = [i['msg'] for i in shared.db['remsg'].find(noun=noun)]
|
|
if len(oldresponses) > 0:
|
|
return random.choice(oldresponses).split(' ')
|
|
prew = shared.db['prew']
|
|
beg = [ i['word'] for i in shared.db['beg'].find() ]
|
|
end = [ i['word'] for i in shared.db['end'].find() ]
|
|
nouns = [i['word'] for i in shared.db['noun'].find()]
|
|
iter=0
|
|
coun=0
|
|
out = [noun]
|
|
while (out[0] not in beg or nouns.count(out[0])-1 > iter * shared.enmul) and iter < 7:
|
|
try:
|
|
out = [ random.choice(list(prew.find(pro=out[0])))['pre'] ] + out
|
|
except IndexError:
|
|
iter += 69
|
|
iter += 1
|
|
coun += 1
|
|
iter = 0
|
|
while (out[-1] not in end or nouns.count(out[-1])-1 > iter * shared.enmul) and iter < 7:
|
|
|
|
try:
|
|
out.append(random.choice(list(prew.find(pre=out[-1])))['pro'])
|
|
except IndexError:
|
|
iter += 69
|
|
iter += 1
|
|
coun += 1
|
|
if coun >= 14:
|
|
shared.enmul += 1
|
|
return out
|
|
|
|
|
|
async def filter(self, c, n, m):
|
|
if c in shared.qtime and shared.qtime[c] > time.time():
|
|
return
|
|
if m[:len(shared.prefix)] == shared.prefix:
|
|
m = m[len(shared.prefix):]
|
|
await go(self, c, n, m)
|
|
elif m[:len(self.nickname)+1] == self.nickname+' ':
|
|
m = m[len(self.nickname)+1:]
|
|
await go(self, c, n, m)
|
|
elif '#' not in c and n != self.nickname:
|
|
await go(self, c, n, m)
|
|
else:
|
|
if len(m.split(' ')) > 1:
|
|
if shared.learntime + shared.learndelay < time.time():
|
|
await rec(self, m)
|
|
shared.learntime = time.time()
|
|
|
|
async def go(self, c, n, m):
|
|
await rec(self, m)
|
|
words = re.sub(r'([\.,\?!])', r' \1', m).split()
|
|
if words[0] == 'admin':
|
|
return
|
|
msg = re.sub(r' ([\.,\?!])', r'\1', ' '.join(await genOut(self, await getNoun(self, words, c))))
|
|
if msg[-1] == "\x01" and msg[0] != "\x01":
|
|
msg = msg[:-1]
|
|
await self.message(c, msg)
|
|
|
|
async def init(self):
|
|
|
|
shared.qtime = {}
|
|
shared.learntime = 0
|
|
|
|
# delay between grabbing random messages and passively
|
|
# learning.
|
|
shared.learndelay = 1
|
|
# sentance ending weight, lower means longer sentances,
|
|
# higher means shorter sentances. this will need to slowly
|
|
# get larger as the database grows
|
|
shared.enmul = 10
|
|
|
|
|
|
shared.rawm['nlp'] = filter
|
|
shared.cstate = {}
|