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commented
2 months ago @yxjun1984 Hello! I'm here to help you with any bugs, questions, or contributions you have.
I found several similar issues related to APIConnectionError in the LlamaIndex repository. Here are some relevant discussions and their solutions:
-
APIConnectionError on a custom agents implementation with AzureOpenAI (Closed):
- Solution: Ensure that the LLM and embed model are correctly set up and passed to the necessary components. Increase the timeout and max retries for the OpenAI client [1].
-
APIConnectionError: Connection error (Closed):
- Solution: Set the correct environment variables for the Azure OpenAI API and ensure the model version and API version are compatible [2].
To resolve the APIConnectionError in llama_index.llms.openai.base.OpenAI._achat when generating reply content asynchronously, you can increase the timeout and max_retries parameters. These parameters are used to configure the OpenAI client and can help mitigate connection issues.
Here's how you can adjust these parameters:
- Increase the Timeout: Set a higher value for the
timeoutparameter to give the API more time to respond. - Increase the Number of Retries: Set a higher value for the
max_retriesparameter to allow more attempts in case of connection failures.
You can do this by passing the desired values when initializing the OpenAI class:
from llama_index.llms.openai import OpenAI
# Initialize with increased timeout and max_retries
openai_llm = OpenAI(
api_key="your_api_key",
timeout=120.0, # Increase timeout to 120 seconds
max_retries=5, # Increase max retries to 5
reuse_client=False # Optionally, set reuse_client to False for large volumes of async calls
)Additionally, the llm_retry_decorator is used to handle retries with exponential backoff, which can further help in managing transient connection issues:
def llm_retry_decorator(f: Callable[[Any], Any]) -> Callable[[Any], Any]:
@functools.wraps(f)
def wrapper(self, *args: Any, **kwargs: Any) -> Any:
max_retries = getattr(self, "max_retries", 0)
if max_retries <= 0:
return f(self, *args, **kwargs)
retry = create_retry_decorator(
max_retries=max_retries,
random_exponential=True,
stop_after_delay_seconds=60,
min_seconds=1,
max_seconds=20,
)
return retry(f)(self, *args, **kwargs)
return wrapperBy increasing the timeout and max_retries, and utilizing the retry decorator, you can reduce the likelihood of encountering APIConnectionError during asynchronous operations [3][4][5][6].
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Bug Description
async def generate_reply_content_async(content, original_message): try:
检查缓存
Version
llama-index 0.11.11
Steps to Reproduce
i do not know
Relevant Logs/Tracbacks