from typing import Generator, List, Optional, Union, Tuple, Dict, Any from functools import cached_property, cmp_to_key from dataclasses import dataclass from collections import defaultdict import jieba_fast.analyse import threading import pypinyin import pymongo import time import random import re import atexit from nonebot.adapters.onebot.v11 import GroupMessageEvent, PrivateMessageEvent from nonebot.adapters.onebot.v11 import Message from utils.config import config mongo_client = pymongo.MongoClient(config.paimon_mongodb_url) mongo_db = mongo_client['PaimonChat'] message_mongo = mongo_db['message'] message_mongo.create_index(name='time_index', keys=[('time', pymongo.DESCENDING)]) context_mongo = mongo_db['context'] context_mongo.create_index(name='keywords_index', keys=[('keywords', pymongo.HASHED)]) context_mongo.create_index(name='count_index', keys=[('count', pymongo.DESCENDING)]) context_mongo.create_index(name='time_index', keys=[('time', pymongo.DESCENDING)]) context_mongo.create_index(name='answers_index', keys=[('answers.group_id', pymongo.TEXT), ('answers.keywords', pymongo.TEXT)], default_language='none') blacklist_mongo = mongo_db['blacklist'] blacklist_mongo.create_index(name='group_index', keys=[('group_id', pymongo.HASHED)]) @dataclass class ChatData: group_id: int user_id: int raw_message: str plain_text: str time: int bot_id: int _keywords_size: int = 3 @cached_property def is_plain_text(self) -> bool: return '[CQ:' not in self.raw_message and len(self.plain_text) != 0 @cached_property def is_image(self) -> bool: return '[CQ:image,' in self.raw_message or '[CQ:face,' in self.raw_message @cached_property def keywords(self) -> str: if not self.is_plain_text and len(self.plain_text) == 0: return self.raw_message keywords_list = jieba_fast.analyse.extract_tags( self.plain_text, topK=ChatData._keywords_size) if len(keywords_list) < 2: return self.plain_text else: # keywords_list.sort() return ' '.join(keywords_list) @cached_property def keywords_pinyin(self) -> str: return ''.join([item[0] for item in pypinyin.pinyin( self.keywords, style=pypinyin.NORMAL, errors='default')]).lower() @cached_property def to_me(self) -> bool: return self.plain_text.startswith('派蒙') class Chat: answer_threshold = config.paimon_answer_threshold # answer 相关的阈值，值越小废话越多，越大话越少 answer_limit_threshold = config.paimon_answer_limit_threshold # 上限阈值，一般正常的上下文不可能发 50 遍，一般是其他 bot 的回复，禁了！ cross_group_threshold = config.paimon_cross_group_threshold # N 个群有相同的回复，就跨群作为全局回复 repeat_threshold = config.paimon_repeat_threshold # 复读的阈值，群里连续多少次有相同的发言，就复读 speak_threshold = config.paimon_speak_threshold # 主动发言的阈值，越小废话越多 drunk_probability = config.paimon_drunk_probability # 喝醉的概率（回复没达到阈值的话） split_probability = 0.5 # 按逗号分割回复语的概率 voice_probability = config.paimon_voice_probability # 回复语音的概率（仅纯文字） speak_continuously_probability = config.paimon_speak_continuously_probability # 连续主动说话的概率 speak_poke_probability = config.paimon_speak_poke_probability # 主动说话加上随机戳一戳群友的概率 speak_continuously_max_len = config.paimon_speak_continuously_max_len # 连续主动说话最多几句话 save_time_threshold = 3600 # 每隔多久进行一次持久化 ( 秒 ) save_count_threshold = 1000 # 单个群超过多少条聊天记录就进行一次持久化。与时间是或的关系 blacklist_answer = defaultdict(set) blacklist_answer_reserve = defaultdict(set) learningGroup = config.paimon_chat_group# 机器学习群组 def __init__(self, data: Union[ChatData, GroupMessageEvent, PrivateMessageEvent]): if isinstance(data, ChatData): self.chat_data = data elif isinstance(data, GroupMessageEvent): self.chat_data = ChatData( group_id=data.group_id, user_id=data.user_id, # 删除图片子类型字段，同一张图子类型经常不一样，影响判断 raw_message=re.sub( r',subType=\d+\]', r']', data.raw_message), plain_text=data.get_plaintext(), time=data.time, bot_id=data.self_id, ) elif isinstance(data, PrivateMessageEvent): event_dict = data.dict() self.chat_data = ChatData( group_id=data.user_id, # 故意加个符号，和群号区分开来 user_id=data.user_id, # 删除图片子类型字段，同一张图子类型经常不一样，影响判断 raw_message=re.sub( r',subType=\d+\]', r']', data.raw_message), plain_text=data.get_plaintext(), time=data.time, bot_id=data.self_id, ) def learn(self) -> bool: """ 学习这句话 """ if len(self.chat_data.raw_message.strip()) == 0: return False group_id = self.chat_data.group_id if group_id in Chat._message_dict: group_msgs = Chat._message_dict[group_id] if group_msgs: group_pre_msg = group_msgs[-1] else: group_pre_msg = None # 群里的上一条发言 self._context_insert(group_pre_msg) user_id = self.chat_data.user_id if group_pre_msg and group_pre_msg['user_id'] != user_id: # 该用户在群里的上一条发言（倒序三句之内） for msg in group_msgs[:-3:-1]: if msg['user_id'] == user_id: self._context_insert(msg) break self._message_insert() return True def answer(self, with_limit: bool = True) -> Optional[Generator[Message, None, None]]: """ 回复这句话，可能会分多次回复，也可能不回复 """ group_id = self.chat_data.group_id bot_id = self.chat_data.bot_id group_bot_replies = Chat._reply_dict[group_id][bot_id] if with_limit: # # 不回复太短的对话，大部分是“？”、“草” # if self.chat_data.is_plain_text and len(self.chat_data.plain_text) < 2: # return None if len(group_bot_replies): latest_reply = group_bot_replies[-1] # 限制发音频率，最多 6 秒一次 if int(time.time()) - latest_reply['time'] < 6: return None # # 不要一直回复同一个内容 # if self.chat_data.raw_message == latest_reply['pre_raw_message']: # return None # 有人复读了牛牛的回复，不继续回复 # if self.chat_data.raw_message == latest_reply['reply']: # return None results = self._context_find() if results: raw_message = self.chat_data.raw_message keywords = self.chat_data.keywords with Chat._reply_lock: group_bot_replies.append({ 'time': int(time.time()), 'pre_raw_message': raw_message, 'pre_keywords': keywords, 'reply': '[PaimonChat: Reply]', # flag 'reply_keywords': '[PaimonChat: Reply]', # flag }) def yield_results(results: Tuple[List[str], str]) -> Generator[Message, None, None]: answer_list, answer_keywords = results group_bot_replies = Chat._reply_dict[group_id][bot_id] for item in answer_list: with Chat._reply_lock: group_bot_replies.append({ 'time': int(time.time()), 'pre_raw_message': raw_message, 'pre_keywords': keywords, 'reply': item, 'reply_keywords': answer_keywords, }) if '[CQ:' not in item and len(item) > 1 \ and random.random() < Chat.voice_probability: yield Chat._text_to_speech(item) else: yield Message(item) with Chat._reply_lock: group_bot_replies = group_bot_replies[-Chat._save_reserve_size:] return yield_results(results) return None @staticmethod def speak() -> Optional[Tuple[int, int, List[Message]]]: """ 主动发言，返回当前最希望发言的 bot 账号、群号、发言消息 List，也有可能不发言 """ basic_msgs_len = 10 basic_delay = 600 def group_popularity_cmp(lhs: Tuple[int, List[Dict[str, Any]]], rhs: Tuple[int, List[Dict[str, Any]]]) -> int: def cmp(a: Any, b: Any): return (a > b) - (a < b) lhs_group_id, lhs_msgs = lhs rhs_group_id, rhs_msgs = rhs lhs_len = len(lhs_msgs) rhs_len = len(rhs_msgs) # 默认是 0, 加个 1 避免乘没了 lhs_drunkenness = Chat._drunkenness_dict[lhs_group_id] + 1 rhs_drunkenness = Chat._drunkenness_dict[rhs_group_id] + 1 if lhs_len < basic_msgs_len or rhs_len < basic_msgs_len: return cmp(lhs_len * lhs_drunkenness, rhs_len * rhs_drunkenness) lhs_duration = lhs_msgs[-1]['time'] - lhs_msgs[0]['time'] rhs_duration = rhs_msgs[-1]['time'] - rhs_msgs[0]['time'] if not lhs_duration or not rhs_duration: return cmp(lhs_len, rhs_len) return cmp(lhs_len * lhs_drunkenness / lhs_duration, rhs_len * rhs_drunkenness / rhs_duration) # 按群聊热度排序 popularity = sorted(Chat._message_dict.items(), key=cmp_to_key(group_popularity_cmp)) cur_time = time.time() for group_id, group_msgs in popularity: group_replies = Chat._reply_dict[group_id] if not len(group_replies) or len(group_msgs) < basic_msgs_len: continue # 一般来说所有牛牛都是一起回复的，最后发言时间应该是一样的，随意随便选一个[0]就好了 group_replies_front = list(group_replies.values())[0] if not len(group_replies_front) or \ group_replies_front[-1]['time'] > group_msgs[-1]['time']: continue msgs_len = len(group_msgs) latest_time = group_msgs[-1]['time'] duration = latest_time - group_msgs[0]['time'] avg_interval = duration / msgs_len # 已经超过平均发言间隔 N 倍的时间没有人说话了，才主动发言 # print(cur_time - latest_time, '/', avg_interval * # Chat.speak_threshold + basic_delay) if cur_time - latest_time < avg_interval * Chat.speak_threshold + basic_delay: continue # append 一个 flag, 防止这个群热度特别高，但压根就没有可用的 context 时，每次 speak 都查这个群，浪费时间 with Chat._reply_lock: group_replies_front.append({ 'time': int(cur_time), 'pre_raw_message': '[PaimonChat: Speak]', 'pre_keywords': '[PaimonChat: Speak]', 'reply': '[PaimonChat: Speak]', 'reply_keywords': '[PaimonChat: Speak]', }) available_time = cur_time - 24 * 3600 speak_context = context_mongo.aggregate([ { '$match': { 'count': { '$gt': Chat.answer_threshold }, 'time': { '$gt': available_time }, # 上面两行为了加快查找速度，对查找到的结果不产生影响 'answers.group_id': group_id, 'answers.time': { '$gt': available_time }, 'answers.count': { '$gt': Chat.answer_threshold } } }, { '$sample': {'size': 1} # 随机一条 } ]) speak_context = list(speak_context) if not speak_context: continue ban_keywords = Chat._find_ban_keywords( context=speak_context[0], group_id=group_id) messages = [answer['messages'] for answer in speak_context[0]['answers'] if answer['count'] >= Chat.answer_threshold and answer['keywords'] not in ban_keywords and answer['group_id'] == group_id] if not messages: continue speak = random.choice(random.choice(messages)) bot_id = random.choice( [bid for bid in group_replies.keys() if bid]) with Chat._reply_lock: group_replies[bot_id].append({ 'time': int(cur_time), 'pre_raw_message': '[PaimonChat: Speak]', 'pre_keywords': '[PaimonChat: Speak]', 'reply': speak, 'reply_keywords': '[PaimonChat: Speak]', }) speak_list = [Message(speak), ] while random.random() < Chat.speak_continuously_probability \ and len(speak_list) < Chat.speak_continuously_max_len: pre_msg = str(speak_list[-1]) answer = Chat(ChatData(group_id, 0, pre_msg, pre_msg, cur_time, 0)).answer(False) if not answer: break speak_list.extend(answer) if random.random() < Chat.speak_poke_probability: target_id = random.choice( Chat._message_dict[group_id])['user_id'] speak_list.append(Message('[CQ:poke,qq={}]'.format(target_id))) return bot_id, group_id, speak_list return None @staticmethod def ban(group_id: int, bot_id: int, ban_raw_message: str, reason: str) -> bool: """ 禁止以后回复这句话，仅对该群有效果 """ if group_id not in Chat._reply_dict: return False ban_reply = None reply_data = Chat._reply_dict[group_id][bot_id][::-1] for reply in reply_data: cur_reply = reply['reply'] # 为空时就直接 ban 最后一条回复 if not ban_raw_message or ban_raw_message in cur_reply: ban_reply = reply break # 这种情况一般是有些 CQ 码，牛牛发送的时候，和被回复的时候，里面的内容不一样 if not ban_reply: search = re.search(r'(\[CQ:[a-zA-z0-9-_.]+)', ban_raw_message) if search: type_keyword = search.group(1) for reply in reply_data: cur_reply = reply['reply'] if type_keyword in cur_reply: ban_reply = reply break if not ban_reply: return False pre_keywords = reply['pre_keywords'] keywords = reply['reply_keywords'] # 考虑这句回复是从别的群捞过来的情况，所以这里要分两次 update # context_mongo.update_one({ # 'keywords': pre_keywords, # 'answers.keywords': keywords, # 'answers.group_id': group_id # }, { # '$set': { # 'answers.$.count': -99999 # } # }) context_mongo.update_one({ 'keywords': pre_keywords }, { '$push': { 'ban': { 'keywords': keywords, 'group_id': group_id, 'reason': reason, 'time': int(time.time()) } } }) if keywords in Chat.blacklist_answer_reserve[group_id]: Chat.blacklist_answer[group_id].add(keywords) if keywords in Chat.blacklist_answer_reserve[Chat._blacklist_flag]: Chat.blacklist_answer[Chat._blacklist_flag].add( keywords) else: Chat.blacklist_answer_reserve[group_id].add(keywords) return True @staticmethod def drink(group_id: int) -> None: """ 牛牛喝酒，仅对该群有效果。提高醉酒程度（降低回复阈值的概率） """ Chat._drunkenness_dict[group_id] += 1 @staticmethod def sober_up(group_id: int) -> bool: """ 牛牛醒酒，仅对该群有效果。返回醒酒是否成功 """ Chat._drunkenness_dict[group_id] -= 1 return Chat._drunkenness_dict[group_id] <= 0 # private: _reply_dict = defaultdict(lambda: defaultdict(list)) # 牛牛回复的消息缓存，暂未做持久化 _message_dict = {} # 群消息缓存 _drunkenness_dict = defaultdict(int) # 醉酒程度，不同群应用不同的数值 _save_reserve_size = 100 # 保存时，给内存中保留的大小 _late_save_time = 0 # 上次保存（消息数据持久化）的时刻 ( time.time(), 秒 ) _reply_lock = threading.Lock() _message_lock = threading.Lock() _blacklist_flag = 114514 def _message_insert(self): group_id = self.chat_data.group_id with Chat._message_lock: if group_id not in Chat._message_dict: Chat._message_dict[group_id] = [] Chat._message_dict[group_id].append({ 'group_id': group_id, 'user_id': self.chat_data.user_id, 'raw_message': self.chat_data.raw_message, 'is_plain_text': self.chat_data.is_plain_text, 'plain_text': self.chat_data.plain_text, 'keywords': self.chat_data.keywords, 'time': self.chat_data.time, }) cur_time = self.chat_data.time if Chat._late_save_time == 0: Chat._late_save_time = cur_time - 1 return if len(Chat._message_dict[group_id]) > Chat.save_count_threshold: Chat._sync(cur_time) elif cur_time - Chat._late_save_time > Chat.save_time_threshold: Chat._sync(cur_time) @staticmethod def _sync(cur_time: int = time.time()): """ 持久化 """ with Chat._message_lock: save_list = [msg for group_msgs in Chat._message_dict.values() for msg in group_msgs if msg['time'] > Chat._late_save_time] if not save_list: return Chat._message_dict = {group_id: group_msgs[-Chat._save_reserve_size:] for group_id, group_msgs in Chat._message_dict.items()} Chat._late_save_time = cur_time message_mongo.insert_many(save_list) def _context_insert(self, pre_msg): if not pre_msg: return raw_message = self.chat_data.raw_message # 在复读，不学 if pre_msg['raw_message'] == raw_message: return # 回复别人的，不学 if '[CQ:reply,' in raw_message: return keywords = self.chat_data.keywords group_id = self.chat_data.group_id pre_keywords = pre_msg['keywords'] cur_time = self.chat_data.time # update_key = { # 'keywords': pre_keywords, # 'answers.keywords': keywords, # 'answers.group_id': group_id # } # update_value = { # '$set': {'time': cur_time}, # '$inc': {'answers.$.count': 1}, # '$push': {'answers.$.messages': raw_message} # } # # update_value.update(update_key) # context_mongo.update_one( # update_key, update_value, upsert=True) # 这个 upsert 太难写了，搞不定_(:з」∠)_ # 先用 find + insert or update 凑合了 find_key = {'keywords': pre_keywords} context = context_mongo.find_one(find_key) if context: update_value = { '$set': { 'time': cur_time }, '$inc': {'count': 1} } answer_index = next((idx for idx, answer in enumerate(context['answers']) if answer['group_id'] == group_id and answer['keywords'] == keywords), -1) if answer_index != -1: update_value['$inc'].update({ f'answers.{answer_index}.count': 1 }) update_value['$set'].update({ f'answers.{answer_index}.time': cur_time }) # 不是纯文本的时候，raw_message 是完全一样的，没必要 push if self.chat_data.is_plain_text: update_value['$push'] = { f'answers.{answer_index}.messages': raw_message } else: update_value['$push'] = { 'answers': { 'keywords': keywords, 'group_id': group_id, 'count': 1, 'time': cur_time, 'messages': [ raw_message ] } } context_mongo.update_one(find_key, update_value) else: context = { 'keywords': pre_keywords, 'time': cur_time, 'count': 1, 'answers': [ { 'keywords': keywords, 'group_id': group_id, 'count': 1, 'time': cur_time, 'messages': [ raw_message ] } ] } context_mongo.insert_one(context) def _context_find(self) -> Optional[Tuple[List[str], str]]: group_id = self.chat_data.group_id raw_message = self.chat_data.raw_message keywords = self.chat_data.keywords bot_id = self.chat_data.bot_id # 复读！ if group_id in Chat._message_dict: group_msgs = Chat._message_dict[group_id] if len(group_msgs) >= Chat.repeat_threshold and \ all(item['raw_message'] == raw_message for item in group_msgs[:-Chat.repeat_threshold:-1]): # 到这里说明当前群里是在复读 group_bot_replies = Chat._reply_dict[group_id][bot_id] if len(group_bot_replies) and group_bot_replies[-1]['reply'] != raw_message: return [raw_message, ], keywords else: # 复读过一次就不再回复这句话了 return None context = context_mongo.find_one({'keywords': keywords}) if not context: return None if Chat._drunkenness_dict[group_id] > 0: answer_count_threshold = 1 else: answer_count_threshold = Chat.answer_threshold if self.chat_data.to_me: cross_group_threshold = 1 else: cross_group_threshold = Chat.cross_group_threshold ban_keywords = Chat._find_ban_keywords( context=context, group_id=group_id) candidate_answers = {} other_group_cache = {} answers_count = defaultdict(int) def candidate_append(dst, answer): answer_key = answer['keywords'] if answer_key not in dst: dst[answer_key] = answer else: pre_answer = dst[answer_key] pre_answer['count'] += answer['count'] pre_answer['messages'] += answer['messages'] for answer in context['answers']: answer_key = answer['keywords'] if answer_key in ban_keywords or answer['count'] < answer_count_threshold: continue sample_msg = answer['messages'][0] if self.chat_data.is_image and '[CQ:' not in sample_msg: # 图片消息不回复纯文本。图片经常是表情包，后面的纯文本啥都有，很乱 continue if answer['group_id'] == group_id: candidate_append(candidate_answers, answer) # 别的群的 at, 忽略 elif '[CQ:at,qq=' in sample_msg: continue else: # 有这么 N 个群都有相同的回复，就作为全局回复 answers_count[answer_key] += 1 cur_count = answers_count[answer_key] if cur_count < cross_group_threshold: # 没达到阈值前，先缓存 candidate_append(other_group_cache, answer) elif cur_count == cross_group_threshold: # 刚达到阈值时，将缓存加入 if cur_count > 1: candidate_append(candidate_answers, other_group_cache[answer_key]) candidate_append(candidate_answers, answer) else: # 超过阈值后，加入 candidate_append(candidate_answers, answer) if not candidate_answers: return None final_answer = random.choices(list(candidate_answers.values()), weights=[ # 防止某个回复权重太大，别的都 Roll 不到了 min(answer['count'], 10) for answer in candidate_answers.values()])[0] answer_str = random.choice(final_answer['messages']) answer_keywords = final_answer['keywords'] if 0 < answer_str.count('，') <= 3 and random.random() < Chat.split_probability: return answer_str.split('，'), answer_keywords return [answer_str, ], answer_keywords @staticmethod def _text_to_speech(text: str) -> Optional[Message]: # if plugin_config.enable_voice: # result = tts_client.synthesis(text, options={'per': 111}) # 度小萌 # if not isinstance(result, dict): # error message # return MessageSegment.record(result) return Message(f'[CQ:tts,text={text}]') @staticmethod def update_global_blacklist() -> None: Chat._select_blacklist() keywords_dict = defaultdict(int) global_blacklist = set() for _, keywords_list in Chat.blacklist_answer.items(): for keywords in keywords_list: keywords_dict[keywords] += 1 if keywords_dict[keywords] == Chat.cross_group_threshold: global_blacklist.add(keywords) Chat.blacklist_answer[Chat._blacklist_flag] |= global_blacklist @staticmethod def _select_blacklist() -> None: all_blacklist = blacklist_mongo.find() for item in all_blacklist: group_id = item['group_id'] if 'answers' in item: Chat.blacklist_answer[group_id] |= set(item['answers']) if 'answers_reserve' in item: Chat.blacklist_answer_reserve[group_id] |= set( item['answers_reserve']) @staticmethod def _sync_blacklist() -> None: Chat._select_blacklist() for group_id, answers in Chat.blacklist_answer.items(): if not len(answers): continue blacklist_mongo.update_one( {'group_id': group_id}, {'$set': {'answers': list(answers)}}, upsert=True) for group_id, answers in Chat.blacklist_answer_reserve.items(): if not len(answers): continue if group_id in Chat.blacklist_answer: answers = answers - Chat.blacklist_answer[group_id] blacklist_mongo.update_one( {'group_id': group_id}, {'$set': {'answers_reserve': list(answers)}}, upsert=True) @staticmethod def clearup_context() -> None: """ 清理所有超过 30 天没人说、且没有学会的话 """ cur_time = int(time.time()) expiration = cur_time - 30 * 24 * 3600 # 三十天前 context_mongo.delete_many({ 'time': {'$lt': expiration}, 'count': {'$lt': Chat.answer_threshold} # lt 是小于，不包括等于 }) all_context = context_mongo.find({ 'count': {'$gt': 100}, '$or': [ # 历史遗留问题，老版本的数据没有 clear_time 字段 {"clear_time": {"$exists": False}}, {"clear_time": {"$lt": expiration}} ] }) for context in all_context: answers = [ans for ans in context['answers'] # 历史遗留问题，老版本的数据没有 answers.$.time 字段 if ans['count'] > 1 or ('time' in ans and ans['time'] > expiration)] context_mongo.update_one({ 'keywords': context['keywords'] }, { '$set': { 'answers': answers, 'clear_time': cur_time } }) @staticmethod def completely_sober(): for key in Chat._drunkenness_dict.keys(): Chat._drunkenness_dict[key] = 0 @staticmethod def _find_ban_keywords(context, group_id) -> set: """ 找到在 group_id 群中对应 context 不能回复的关键词 """ # 全局的黑名单 ban_keywords = Chat.blacklist_answer[Chat._blacklist_flag] | Chat.blacklist_answer[group_id] # 针对单条回复的黑名单 if 'ban' in context: ban_count = defaultdict(int) for ban in context['ban']: ban_key = ban['keywords'] if ban['group_id'] == group_id or ban['group_id'] == Chat._blacklist_flag: ban_keywords.add(ban_key) else: # 超过 N 个群都把这句话 ban 了，那就全局 ban 掉 ban_count[ban_key] += 1 if ban_count[ban_key] == Chat.cross_group_threshold: ban_keywords.add(ban_key) return ban_keywords # Auto sync on program start Chat.update_global_blacklist() def _chat_sync(): Chat._sync() Chat._sync_blacklist() # Auto sync on program exit atexit.register(_chat_sync) if __name__ == '__main__': # Chat.clearup_context() # # while True: test_data: ChatData = ChatData( group_id=1234567, user_id=1111111, raw_message='完了又有新bug', plain_text='完了又有新bug', time=time.time(), bot_id=0, ) test_chat: Chat = Chat(test_data) print(test_chat.answer()) test_chat.learn() test_answer_data: ChatData = ChatData( group_id=1234567, user_id=1111111, raw_message='完了又有新bug', plain_text='完了又有新bug', time=time.time(), bot_id=0, ) test_answer: Chat = Chat(test_answer_data) print(test_chat.answer()) test_answer.learn() # time.sleep(5) # print(Chat.speak())