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| # encoding:utf-8 | ||
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| import time | ||
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| import openai | ||
| import openai.error | ||
| from bot.bot import Bot | ||
| from bot.minimax.minimax_session import MinimaxSession | ||
| from bot.session_manager import SessionManager | ||
| from bridge.context import Context, ContextType | ||
| from bridge.reply import Reply, ReplyType | ||
| from common.log import logger | ||
| from config import conf, load_config | ||
| from bot.chatgpt.chat_gpt_session import ChatGPTSession | ||
| import requests | ||
| from common import const | ||
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| # ZhipuAI对话模型API | ||
| class MinimaxBot(Bot): | ||
| def __init__(self): | ||
| super().__init__() | ||
| self.args = { | ||
| "model": conf().get("model") or "abab6.5", # 对话模型的名称 | ||
| "temperature": conf().get("temperature", 0.3), # 如果设置，值域须为 [0, 1] 我们推荐 0.3，以达到较合适的效果。 | ||
| "top_p": conf().get("top_p", 0.95), # 使用默认值 | ||
| } | ||
| self.api_key = conf().get("Minimax_api_key") | ||
| self.group_id = conf().get("Minimax_group_id") | ||
| self.base_url = conf().get("Minimax_base_url", f"https://api.minimax.chat/v1/text/chatcompletion_pro?GroupId={self.group_id}") | ||
| # tokens_to_generate/bot_setting/reply_constraints可自行修改 | ||
| self.request_body = { | ||
| "model": self.args["model"], | ||
| "tokens_to_generate": 2048, | ||
| "reply_constraints": {"sender_type": "BOT", "sender_name": "MM智能助理"}, | ||
| "messages": [], | ||
| "bot_setting": [ | ||
| { | ||
| "bot_name": "MM智能助理", | ||
| "content": "MM智能助理是一款由MiniMax自研的，没有调用其他产品的接口的大型语言模型。MiniMax是一家中国科技公司，一直致力于进行大模型相关的研究。", | ||
| } | ||
| ], | ||
| } | ||
| self.sessions = SessionManager(MinimaxSession, model=const.MiniMax) | ||
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| def reply(self, query, context: Context = None) -> Reply: | ||
| # acquire reply content | ||
| logger.info("[Minimax_AI] query={}".format(query)) | ||
| if context.type == ContextType.TEXT: | ||
| session_id = context["session_id"] | ||
| reply = None | ||
| clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"]) | ||
| if query in clear_memory_commands: | ||
| self.sessions.clear_session(session_id) | ||
| reply = Reply(ReplyType.INFO, "记忆已清除") | ||
| elif query == "#清除所有": | ||
| self.sessions.clear_all_session() | ||
| reply = Reply(ReplyType.INFO, "所有人记忆已清除") | ||
| elif query == "#更新配置": | ||
| load_config() | ||
| reply = Reply(ReplyType.INFO, "配置已更新") | ||
| if reply: | ||
| return reply | ||
| session = self.sessions.session_query(query, session_id) | ||
| logger.debug("[Minimax_AI] session query={}".format(session)) | ||
|
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| model = context.get("Minimax_model") | ||
| new_args = self.args.copy() | ||
| if model: | ||
| new_args["model"] = model | ||
| # if context.get('stream'): | ||
| # # reply in stream | ||
| # return self.reply_text_stream(query, new_query, session_id) | ||
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| reply_content = self.reply_text(session, args=new_args) | ||
| logger.debug( | ||
| "[Minimax_AI] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format( | ||
| session.messages, | ||
| session_id, | ||
| reply_content["content"], | ||
| reply_content["completion_tokens"], | ||
| ) | ||
| ) | ||
| if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0: | ||
| reply = Reply(ReplyType.ERROR, reply_content["content"]) | ||
| elif reply_content["completion_tokens"] > 0: | ||
| self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"]) | ||
| reply = Reply(ReplyType.TEXT, reply_content["content"]) | ||
| else: | ||
| reply = Reply(ReplyType.ERROR, reply_content["content"]) | ||
| logger.debug("[Minimax_AI] reply {} used 0 tokens.".format(reply_content)) | ||
| return reply | ||
| else: | ||
| reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type)) | ||
| return reply | ||
|
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| def reply_text(self, session: MinimaxSession, args=None, retry_count=0) -> dict: | ||
| """ | ||
| call openai's ChatCompletion to get the answer | ||
| :param session: a conversation session | ||
| :param session_id: session id | ||
| :param retry_count: retry count | ||
| :return: {} | ||
| """ | ||
| try: | ||
| headers = {"Content-Type": "application/json", "Authorization": "Bearer " + self.api_key} | ||
| self.request_body["messages"].extend(session.messages) | ||
| logger.info("[Minimax_AI] request_body={}".format(self.request_body)) | ||
| # logger.info("[Minimax_AI] reply={}, total_tokens={}".format(response.choices[0]['message']['content'], response["usage"]["total_tokens"])) | ||
| res = requests.post(self.base_url, headers=headers, json=self.request_body) | ||
|
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| # self.request_body["messages"].extend(response.json()["choices"][0]["messages"]) | ||
| if res.status_code == 200: | ||
| response = res.json() | ||
| return { | ||
| "total_tokens": response["usage"]["total_tokens"], | ||
| "completion_tokens": response["usage"]["total_tokens"], | ||
| "content": response["reply"], | ||
| } | ||
| else: | ||
| response = res.json() | ||
| error = response.get("error") | ||
| logger.error(f"[Minimax_AI] chat failed, status_code={res.status_code}, " f"msg={error.get('message')}, type={error.get('type')}") | ||
|
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| result = {"completion_tokens": 0, "content": "提问太快啦，请休息一下再问我吧"} | ||
| need_retry = False | ||
| if res.status_code >= 500: | ||
| # server error, need retry | ||
| logger.warn(f"[Minimax_AI] do retry, times={retry_count}") | ||
| need_retry = retry_count < 2 | ||
| elif res.status_code == 401: | ||
| result["content"] = "授权失败，请检查API Key是否正确" | ||
| elif res.status_code == 429: | ||
| result["content"] = "请求过于频繁，请稍后再试" | ||
| need_retry = retry_count < 2 | ||
| else: | ||
| need_retry = False | ||
|
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| if need_retry: | ||
| time.sleep(3) | ||
| return self.reply_text(session, args, retry_count + 1) | ||
| else: | ||
| return result | ||
| except Exception as e: | ||
| logger.exception(e) | ||
| need_retry = retry_count < 2 | ||
| result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"} | ||
| if need_retry: | ||
| return self.reply_text(session, args, retry_count + 1) | ||
| else: | ||
| return result |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,72 @@ | ||
| from bot.session_manager import Session | ||
| from common.log import logger | ||
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| """ | ||
| e.g. | ||
| [ | ||
| {"role": "system", "content": "You are a helpful assistant."}, | ||
| {"role": "user", "content": "Who won the world series in 2020?"}, | ||
| {"role": "assistant", "content": "The Los Angeles Dodgers won the World Series in 2020."}, | ||
| {"role": "user", "content": "Where was it played?"} | ||
| ] | ||
| """ | ||
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| class MinimaxSession(Session): | ||
| def __init__(self, session_id, system_prompt=None, model="minimax"): | ||
| super().__init__(session_id, system_prompt) | ||
| self.model = model | ||
| # self.reset() | ||
|
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| def add_query(self, query): | ||
| user_item = {"sender_type": "USER", "sender_name": self.session_id, "text": query} | ||
| self.messages.append(user_item) | ||
|
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| def add_reply(self, reply): | ||
| assistant_item = {"sender_type": "BOT", "sender_name": "MM智能助理", "text": reply} | ||
| self.messages.append(assistant_item) | ||
|
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| def discard_exceeding(self, max_tokens, cur_tokens=None): | ||
| precise = True | ||
| try: | ||
| cur_tokens = self.calc_tokens() | ||
| except Exception as e: | ||
| precise = False | ||
| if cur_tokens is None: | ||
| raise e | ||
| logger.debug("Exception when counting tokens precisely for query: {}".format(e)) | ||
| while cur_tokens > max_tokens: | ||
| if len(self.messages) > 2: | ||
| self.messages.pop(1) | ||
| elif len(self.messages) == 2 and self.messages[1]["sender_type"] == "BOT": | ||
| self.messages.pop(1) | ||
| if precise: | ||
| cur_tokens = self.calc_tokens() | ||
| else: | ||
| cur_tokens = cur_tokens - max_tokens | ||
| break | ||
| elif len(self.messages) == 2 and self.messages[1]["sender_type"] == "USER": | ||
| logger.warn("user message exceed max_tokens. total_tokens={}".format(cur_tokens)) | ||
| break | ||
| else: | ||
| logger.debug("max_tokens={}, total_tokens={}, len(messages)={}".format(max_tokens, cur_tokens, len(self.messages))) | ||
| break | ||
| if precise: | ||
| cur_tokens = self.calc_tokens() | ||
| else: | ||
| cur_tokens = cur_tokens - max_tokens | ||
| return cur_tokens | ||
|
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| def calc_tokens(self): | ||
| return num_tokens_from_messages(self.messages, self.model) | ||
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| def num_tokens_from_messages(messages, model): | ||
| """Returns the number of tokens used by a list of messages.""" | ||
| # 官方token计算规则："对于中文文本来说，1个token通常对应一个汉字；对于英文文本来说，1个token通常对应3至4个字母或1个单词" | ||
| # 详情请产看文档：https://help.aliyun.com/document_detail/2586397.html | ||
| # 目前根据字符串长度粗略估计token数，不影响正常使用 | ||
| tokens = 0 | ||
| for msg in messages: | ||
| tokens += len(msg["text"]) | ||
| return tokens |
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