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feat add support for alist_batches

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This commit is contained in:
Ishaan Jaff 2024-07-30 08:18:52 -07:00
parent 36dca6bcce
commit 43a06f408c
2 changed files with 177 additions and 30 deletions
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66
litellm/llms/openai.py
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@ -2602,26 +2602,52 @@ class OpenAIBatchesAPI(BaseLLM):
response = openai_client.batches.cancel(**cancel_batch_data)
return response
# def list_batch(
# self,
# list_batch_data: ListBatchRequest,
# api_key: Optional[str],
# api_base: Optional[str],
# timeout: Union[float, httpx.Timeout],
# max_retries: Optional[int],
# organization: Optional[str],
# client: Optional[OpenAI] = None,
# ):
# openai_client: OpenAI = self.get_openai_client(
# api_key=api_key,
# api_base=api_base,
# timeout=timeout,
# max_retries=max_retries,
# organization=organization,
# client=client,
# )
# response = openai_client.batches.list(**list_batch_data)
# return response
async def alist_batches(
self,
openai_client: AsyncOpenAI,
after: Optional[str] = None,
limit: Optional[int] = None,
):
verbose_logger.debug("listing batches, after= %s, limit= %s", after, limit)
response = await openai_client.batches.list(after=after, limit=limit)
return response
def list_batches(
self,
_is_async: bool,
api_key: Optional[str],
api_base: Optional[str],
timeout: Union[float, httpx.Timeout],
max_retries: Optional[int],
organization: Optional[str],
after: Optional[str] = None,
limit: Optional[int] = None,
client: Optional[OpenAI] = None,
):
openai_client: Optional[Union[OpenAI, AsyncOpenAI]] = self.get_openai_client(
api_key=api_key,
api_base=api_base,
timeout=timeout,
max_retries=max_retries,
organization=organization,
client=client,
_is_async=_is_async,
)
if openai_client is None:
raise ValueError(
"OpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
)
if _is_async is True:
if not isinstance(openai_client, AsyncOpenAI):
raise ValueError(
"OpenAI client is not an instance of AsyncOpenAI. Make sure you passed an AsyncOpenAI client."
)
return self.alist_batches( # type: ignore
openai_client=openai_client, after=after, limit=limit
)
response = openai_client.batches.list(after=after, limit=limit)
return response
class OpenAIAssistantsAPI(BaseLLM):