mirror of
https://github.com/zhayujie/chatgpt-on-wechat.git
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refactor: decouple openai session
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lanvent
@@ -2,6 +2,8 @@
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from bot.bot import Bot
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from bot.openai.open_ai_image import OpenAIImage
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from bot.openai.open_ai_session import OpenAISession
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from bot.session_manager import SessionManager
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from bridge.context import ContextType
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from bridge.reply import Reply, ReplyType
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from config import conf
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@@ -22,29 +24,34 @@ class OpenAIBot(Bot, OpenAIImage):
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if proxy:
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openai.proxy = proxy
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self.sessions = SessionManager(OpenAISession, model= conf().get("model") or "text-davinci-003")
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def reply(self, query, context=None):
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# acquire reply content
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if context and context.type:
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if context.type == ContextType.TEXT:
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logger.info("[OPEN_AI] query={}".format(query))
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from_user_id = context['session_id']
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session_id = context['session_id']
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reply = None
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if query == '#清除记忆':
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Session.clear_session(from_user_id)
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self.sessions.clear_session(session_id)
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reply = Reply(ReplyType.INFO, '记忆已清除')
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elif query == '#清除所有':
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Session.clear_all_session()
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self.sessions.clear_all_session()
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reply = Reply(ReplyType.INFO, '所有人记忆已清除')
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else:
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new_query = Session.build_session_query(query, from_user_id)
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session = self.sessions.session_query(query, session_id)
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new_query = str(session)
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logger.debug("[OPEN_AI] session query={}".format(new_query))
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reply_content = self.reply_text(new_query, from_user_id, 0)
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logger.debug("[OPEN_AI] new_query={}, user={}, reply_cont={}".format(new_query, from_user_id, reply_content))
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if reply_content and query:
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Session.save_session(query, reply_content, from_user_id)
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reply = Reply(ReplyType.TEXT, reply_content)
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total_tokens, completion_tokens, reply_content = self.reply_text(new_query, session_id, 0)
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logger.debug("[OPEN_AI] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(new_query, session_id, reply_content, completion_tokens))
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if total_tokens == 0 :
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reply = Reply(ReplyType.ERROR, reply_content)
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else:
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self.sessions.session_reply(reply_content, session_id, total_tokens)
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reply = Reply(ReplyType.TEXT, reply_content)
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return reply
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elif context.type == ContextType.IMAGE_CREATE:
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ok, retstring = self.create_img(query, 0)
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@@ -68,8 +75,10 @@ class OpenAIBot(Bot, OpenAIImage):
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stop=["\n\n\n"]
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)
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res_content = response.choices[0]['text'].strip().replace('<|endoftext|>', '')
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total_tokens = response["usage"]["total_tokens"]
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completion_tokens = response["usage"]["completion_tokens"]
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logger.info("[OPEN_AI] reply={}".format(res_content))
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return res_content
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return total_tokens, completion_tokens, res_content
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except openai.error.RateLimitError as e:
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# rate limit exception
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logger.warn(e)
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@@ -78,81 +87,9 @@ class OpenAIBot(Bot, OpenAIImage):
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logger.warn("[OPEN_AI] RateLimit exceed, 第{}次重试".format(retry_count+1))
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return self.reply_text(query, user_id, retry_count+1)
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else:
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return "提问太快啦，请休息一下再问我吧"
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return 0,0, "提问太快啦，请休息一下再问我吧"
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except Exception as e:
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# unknown exception
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logger.exception(e)
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Session.clear_session(user_id)
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return "请再问我一次吧"
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class Session(object):
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@staticmethod
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def build_session_query(query, user_id):
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'''
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build query with conversation history
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e.g. Q: xxx
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A: xxx
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Q: xxx
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:param query: query content
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:param user_id: from user id
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:return: query content with conversaction
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'''
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prompt = conf().get("character_desc", "")
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if prompt:
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prompt += "<|endoftext|>\n\n\n"
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session = user_session.get(user_id, None)
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if session:
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for conversation in session:
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prompt += "Q: " + conversation["question"] + "\n\n\nA: " + conversation["answer"] + "<|endoftext|>\n"
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prompt += "Q: " + query + "\nA: "
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return prompt
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else:
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return prompt + "Q: " + query + "\nA: "
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@staticmethod
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def save_session(query, answer, user_id):
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max_tokens = conf().get("conversation_max_tokens")
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if not max_tokens:
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# default 3000
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max_tokens = 1000
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conversation = dict()
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conversation["question"] = query
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conversation["answer"] = answer
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session = user_session.get(user_id)
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logger.debug(conversation)
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logger.debug(session)
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if session:
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# append conversation
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session.append(conversation)
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else:
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# create session
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queue = list()
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queue.append(conversation)
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user_session[user_id] = queue
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# discard exceed limit conversation
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Session.discard_exceed_conversation(user_session[user_id], max_tokens)
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@staticmethod
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def discard_exceed_conversation(session, max_tokens):
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count = 0
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count_list = list()
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for i in range(len(session)-1, -1, -1):
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# count tokens of conversation list
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history_conv = session[i]
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count += len(history_conv["question"]) + len(history_conv["answer"])
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count_list.append(count)
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for c in count_list:
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if c > max_tokens:
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# pop first conversation
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session.pop(0)
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@staticmethod
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def clear_session(user_id):
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user_session[user_id] = []
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@staticmethod
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def clear_all_session():
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user_session.clear()
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return 0,0, "请再问我一次吧"
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