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+# encoding:utf-8
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+
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+import json
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+import time
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+from typing import List, Tuple
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+
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+import openai
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+import openai.error
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+import broadscope_bailian
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+from broadscope_bailian import ChatQaMessage
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+
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+from bot.bot import Bot
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+from bot.baidu.baidu_wenxin_session import BaiduWenxinSession
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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 common.log import logger
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+from config import conf, load_config
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+
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+class TongyiQwenBot(Bot):
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+ def __init__(self):
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+ super().__init__()
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+ self.access_key_id = conf().get("tongyi_access_key_id")
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+ self.access_key_secret = conf().get("tongyi_access_key_secret")
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+ self.agent_key = conf().get("tongyi_agent_key")
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+ self.app_id = conf().get("tongyi_app_id")
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+ self.node_id = conf().get("tongyi_node_id")
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+ self.api_key_client = broadscope_bailian.AccessTokenClient(access_key_id=self.access_key_id, access_key_secret=self.access_key_secret)
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+ self.api_key_expired_time = self.set_api_key()
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+ self.sessions = SessionManager(BaiduWenxinSession, model=conf().get("model") or "tongyi")
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+ self.temperature = conf().get("temperature", 0.2) # 值在[0,1]之间，越大表示回复越具有不确定性
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+ self.top_p = conf().get("top_p", 1)
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+
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+ def reply(self, query, context=None):
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+ # acquire reply content
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+ if context.type == ContextType.TEXT:
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+ logger.info("[TONGYI] query={}".format(query))
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+
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+ session_id = context["session_id"]
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+ reply = None
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+ clear_memory_commands = conf().get("clear_memory_commands", ["#清除记忆"])
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+ if query in clear_memory_commands:
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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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+ 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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+ elif query == "#更新配置":
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+ load_config()
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+ reply = Reply(ReplyType.INFO, "配置已更新")
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+ if reply:
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+ return reply
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+ session = self.sessions.session_query(query, session_id)
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+ logger.debug("[TONGYI] session query={}".format(session.messages))
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+
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+ reply_content = self.reply_text(session)
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+ logger.debug(
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+ "[TONGYI] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(
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+ session.messages,
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+ session_id,
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+ reply_content["content"],
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+ reply_content["completion_tokens"],
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+ )
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+ )
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+ if reply_content["completion_tokens"] == 0 and len(reply_content["content"]) > 0:
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+ reply = Reply(ReplyType.ERROR, reply_content["content"])
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+ elif reply_content["completion_tokens"] > 0:
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+ self.sessions.session_reply(reply_content["content"], session_id, reply_content["total_tokens"])
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+ reply = Reply(ReplyType.TEXT, reply_content["content"])
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+ else:
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+ reply = Reply(ReplyType.ERROR, reply_content["content"])
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+ logger.debug("[TONGYI] reply {} used 0 tokens.".format(reply_content))
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+ return reply
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+
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+ else:
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+ reply = Reply(ReplyType.ERROR, "Bot不支持处理{}类型的消息".format(context.type))
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+ return reply
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+
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+ def reply_text(self, session: BaiduWenxinSession, retry_count=0) -> dict:
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+ """
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+ call bailian's ChatCompletion to get the answer
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+ :param session: a conversation session
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+ :param retry_count: retry count
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+ :return: {}
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+ """
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+ try:
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+ prompt, history = self.convert_messages_format(session.messages)
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+ self.update_api_key_if_expired()
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+ # NOTE 阿里百炼的call()函数参数比较奇怪, top_k参数表示top_p, top_p参数表示temperature, 可以参考文档 https://help.aliyun.com/document_detail/2587502.htm
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+ response = broadscope_bailian.Completions().call(app_id=self.app_id, prompt=prompt, history=history, top_k=self.top_p, top_p=self.temperature)
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+ completion_content = self.get_completion_content(response, self.node_id)
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+ completion_tokens, total_tokens = self.calc_tokens(session.messages, completion_content)
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+ return {
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+ "total_tokens": total_tokens,
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+ "completion_tokens": completion_tokens,
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+ "content": completion_content,
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+ }
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+ except Exception as e:
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+ need_retry = retry_count < 2
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+ result = {"completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
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+ if isinstance(e, openai.error.RateLimitError):
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+ logger.warn("[TONGYI] RateLimitError: {}".format(e))
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+ result["content"] = "提问太快啦，请休息一下再问我吧"
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+ if need_retry:
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+ time.sleep(20)
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+ elif isinstance(e, openai.error.Timeout):
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+ logger.warn("[TONGYI] Timeout: {}".format(e))
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+ result["content"] = "我没有收到你的消息"
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+ if need_retry:
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+ time.sleep(5)
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+ elif isinstance(e, openai.error.APIError):
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+ logger.warn("[TONGYI] Bad Gateway: {}".format(e))
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+ result["content"] = "请再问我一次"
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+ if need_retry:
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+ time.sleep(10)
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+ elif isinstance(e, openai.error.APIConnectionError):
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+ logger.warn("[TONGYI] APIConnectionError: {}".format(e))
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+ need_retry = False
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+ result["content"] = "我连接不到你的网络"
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+ else:
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+ logger.exception("[TONGYI] Exception: {}".format(e))
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+ need_retry = False
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+ self.sessions.clear_session(session.session_id)
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+
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+ if need_retry:
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+ logger.warn("[TONGYI] 第{}次重试".format(retry_count + 1))
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+ return self.reply_text(session, retry_count + 1)
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+ else:
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+ return result
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+
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+ def set_api_key(self):
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+ api_key, expired_time = self.api_key_client.create_token(agent_key=self.agent_key)
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+ broadscope_bailian.api_key = api_key
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+ return expired_time
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+ def update_api_key_if_expired(self):
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+ if time.time() > self.api_key_expired_time:
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+ self.api_key_expired_time = self.set_api_key()
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+
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+ def convert_messages_format(self, messages) -> Tuple[str, List[ChatQaMessage]]:
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+ history = []
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+ user_content = ''
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+ assistant_content = ''
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+ for message in messages:
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+ role = message.get('role')
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+ if role == 'user':
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+ user_content += message.get('content')
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+ elif role == 'assistant':
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+ assistant_content = message.get('content')
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+ history.append(ChatQaMessage(user_content, assistant_content))
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+ user_content = ''
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+ assistant_content = ''
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+ if user_content == '':
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+ raise Exception('no user message')
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+ return user_content, history
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+
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+ def get_completion_content(self, response, node_id):
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+ text = response['Data']['Text']
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+ if node_id == '':
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+ return text
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+ # TODO: 当使用流程编排创建大模型应用时，响应结构如下，最终结果在['finalResult'][node_id]['response']['text']中，暂时先这么写
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+ # {
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+ # 'Success': True,
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+ # 'Code': None,
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+ # 'Message': None,
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+ # 'Data': {
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+ # 'ResponseId': '9822f38dbacf4c9b8daf5ca03a2daf15',
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+ # 'SessionId': 'session_id',
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+ # 'Text': '{"finalResult":{"LLM_T7islK":{"params":{"modelId":"qwen-plus-v1","prompt":"${systemVars.query}${bizVars.Text}"},"response":{"text":"作为一个AI语言模型，我没有年龄，因为我没有生日。\n我只是一个程序，没有生命和身体。"}}}}',
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+ # 'Thoughts': [],
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+ # 'Debug': {},
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+ # 'DocReferences': []
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+ # },
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+ # 'RequestId': '8e11d31551ce4c3f83f49e6e0dd998b0',
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+ # 'Failed': None
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+ # }
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+ text_dict = json.loads(text)
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+ completion_content = text_dict['finalResult'][node_id]['response']['text']
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+ return completion_content
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+
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+ def calc_tokens(self, messages, completion_content):
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+ completion_tokens = len(completion_content)
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+ prompt_tokens = 0
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+ for message in messages:
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+ prompt_tokens += len(message["content"])
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+ return completion_tokens, prompt_tokens + completion_tokens
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Han Fangyuan