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 openai
min_seconds = 1
max_seconds = 60
# Wait 2^x * 1 second between each retry starting with
# 4 seconds, then up to 10 seconds, then 10 seconds afterwards
return 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_decorator
def _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 ChatOpenAI
def 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 logging
logger = logging.getLogger(__name__)
class MyChatOpenAI(ChatOpenAI):
def _create_retry_decorator(self) -> Callable[[Any], Any]:
min_seconds = 1
max_seconds = 60
# Wait 2^x * 1 second between each retry starting with
# 4 seconds, then up to 10 seconds, then 10 seconds after wards
return 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_decorator
def _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_decorator
def _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)
此时就能进行正常的对话功能了。
总结
本文介绍了LangChain中的重连机制，并尝试给出定制化重连方案，希望能对读者有所帮助。
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