NLP（六十五）LangChain中的重连（retry）机制

关于LangChain入门，读者可参考文章NLP（五十六）LangChain入门。
本文将会介绍LangChain中的重连机制，并尝试给出定制化重连方案。
本文以LangChain中的对话功能（ChatOpenAI）为例。

LangChain中的重连机制

查看LangChain中对话功能（ChatOpenAI）的重连机制（retry），其源代码如下：

class ChatOpenAI(BaseChatModel):...def _create_retry_decorator(self) -> Callable[[Any], Any]:import openaimin_seconds = 1max_seconds = 60# Wait 2^x * 1 second between each retry starting with# 4 seconds, then up to 10 seconds, then 10 seconds afterwardsreturn retry(reraise=True,stop=stop_after_attempt(self.max_retries),wait=wait_exponential(multiplier=1, min=min_seconds, max=max_seconds),retry=(retry_if_exception_type(openai.error.Timeout)| retry_if_exception_type(openai.error.APIError)| retry_if_exception_type(openai.error.APIConnectionError)| retry_if_exception_type(openai.error.RateLimitError)| retry_if_exception_type(openai.error.ServiceUnavailableError)),before_sleep=before_sleep_log(logger, logging.WARNING),)def completion_with_retry(self, **kwargs: Any) -> Any:"""Use tenacity to retry the completion call."""retry_decorator = self._create_retry_decorator()@retry_decoratordef _completion_with_retry(**kwargs: Any) -> Any:return self.client.create(**kwargs)return _completion_with_retry(**kwargs)

可以看到，其编码方式为硬编码（hardcore），采用tenacity模块实现重连机制，对于支持的报错情形，比如openai.error.Timeout, openai.error.APIError等，会尝试重连，最小等待时间为1s，最大等待时间为60s，每次重连等待时间会乘以2。

简单重连

我们尝试用一个错误的OpenAI key进行对话，代码如下：

from langchain.chat_models import ChatOpenAIdef chat_bot(input_text: str):llm = ChatOpenAI(temperature=0,model_name="gpt-3.5-turbo",openai_api_key="sk-xxx",max_retries=5)return llm.predict(input_text)if __name__ == '__main__':text = '中国的首都是哪里？'print(chat_bot(text))

尽管我们在代码中设置了重连最大次数（max_retries），代码运行时会直接报错，不会重连，原因是LangChain中的对话功能重连机制没有支持openai.error.AuthenticationError。输出结果如下：

openai.error.AuthenticationError: Incorrect API key provided: sk-xxx. You can find your API key at https://platform.openai.com/account/api-keys.

此时，我们尝试在源代码的基础上做简单的定制，使得其支持openai.error.AuthenticationError错误类型，代码如下：

# -*- coding: utf-8 -*-
import openai
from typing import Callable, Any
from tenacity import (before_sleep_log,retry,retry_if_exception_type,stop_after_attempt,wait_exponential,
)
from langchain.chat_models import ChatOpenAI
import logginglogger = logging.getLogger(__name__)class MyChatOpenAI(ChatOpenAI):def _create_retry_decorator(self) -> Callable[[Any], Any]:min_seconds = 1max_seconds = 60# Wait 2^x * 1 second between each retry starting with# 4 seconds, then up to 10 seconds, then 10 seconds after wardsreturn retry(reraise=True,stop=stop_after_attempt(self.max_retries),wait=wait_exponential(multiplier=1, min=min_seconds, max=max_seconds),retry=(retry_if_exception_type(openai.error.Timeout)| retry_if_exception_type(openai.error.APIError)| retry_if_exception_type(openai.error.APIConnectionError)| retry_if_exception_type(openai.error.RateLimitError)| retry_if_exception_type(openai.error.ServiceUnavailableError)# add new error| retry_if_exception_type(openai.error.AuthenticationError)),before_sleep=before_sleep_log(logger, logging.WARNING),)def completion_with_retry(self, **kwargs: Any) -> Any:"""Use tenacity to retry the completion call."""retry_decorator = self._create_retry_decorator()@retry_decoratordef _completion_with_retry(**kwargs: Any) -> Any:return self.client.create(**kwargs)return _completion_with_retry(**kwargs)def chat_bot(input_text: str):llm = MyChatOpenAI(temperature=0,model_name="gpt-3.5-turbo",openai_api_key="sk-xxx",max_retries=5)return llm.predict(input_text)if __name__ == '__main__':text = '中国的首都是哪里？'print(chat_bot(text))

分析上述代码，我们在继承ChatOpenAI类的基础上重新创建MyChatOpenAI类，在_create_retry_decorator中的重连错误情形中加入了openai.error.AuthenticationError错误类型，此时代码输出结果如下：

Retrying __main__.MyChatOpenAI.completion_with_retry.<locals>._completion_with_retry in 1.0 seconds as it raised AuthenticationError: Incorrect API key provided: sk-xxx. You can find your API key at https://platform.openai.com/account/api-keys..
Retrying __main__.MyChatOpenAI.completion_with_retry.<locals>._completion_with_retry in 2.0 seconds as it raised AuthenticationError: Incorrect API key provided: sk-xxx. You can find your API key at https://platform.openai.com/account/api-keys..
Retrying __main__.MyChatOpenAI.completion_with_retry.<locals>._completion_with_retry in 4.0 seconds as it raised AuthenticationError: Incorrect API key provided: sk-xxx. You can find your API key at https://platform.openai.com/account/api-keys..
Retrying __main__.MyChatOpenAI.completion_with_retry.<locals>._completion_with_retry in 8.0 seconds as it raised AuthenticationError: Incorrect API key provided: sk-xxx. You can find your API key at https://platform.openai.com/account/api-keys..
Traceback (most recent call last):......
openai.error.AuthenticationError: Incorrect API key provided: sk-xxx. You can find your API key at https://platform.openai.com/account/api-keys.

从输出结果中，我们可以看到，该代码确实对openai.error.AuthenticationError错误类型进行了重连，按照源代码的方式进行重连，一共尝试了5次重连，每次重连等待时间是上一次的两倍。

定制化重连

LangChain中的重连机制也支持定制化。
假设我们的使用场景：某个OpenAI key在调用过程中失效了，那么在重连时希望能快速切换至某个能正常使用的OpenAI key，以下为示例代码（仅需要修改completion_with_retry函数）：

    def completion_with_retry(self, **kwargs: Any) -> Any:"""Use tenacity to retry the completion call."""retry_decorator = self._create_retry_decorator()@retry_decoratordef _completion_with_retry(**kwargs: Any) -> Any:# 重连机制定制化(custom retry)kwargs['api_key'] = 'right openai key'return self.client.create(**kwargs)return _completion_with_retry(**kwargs)