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Code Quality Improvement - remove file_apis
, fine_tuning_apis
from /llms
(#7156)
* remove files_apis from /llms * fix imports * move fine tuning api from /llms * fix importing fine tuning handlers * fix imports
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parent
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commit
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6 changed files with 5 additions and 6 deletions
181
litellm/llms/azure/fine_tuning/handler.py
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181
litellm/llms/azure/fine_tuning/handler.py
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@ -0,0 +1,181 @@
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from typing import Any, Coroutine, Optional, Union
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import httpx
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from openai import AsyncAzureOpenAI, AzureOpenAI
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from openai.pagination import AsyncCursorPage
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from openai.types.fine_tuning import FineTuningJob
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from litellm._logging import verbose_logger
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from litellm.llms.base import BaseLLM
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from litellm.llms.azure.files.handler import get_azure_openai_client
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from litellm.types.llms.openai import FineTuningJobCreate
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class AzureOpenAIFineTuningAPI(BaseLLM):
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"""
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AzureOpenAI methods to support for batches
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"""
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def __init__(self) -> None:
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super().__init__()
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async def acreate_fine_tuning_job(
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self,
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create_fine_tuning_job_data: dict,
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openai_client: AsyncAzureOpenAI,
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) -> FineTuningJob:
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response = await openai_client.fine_tuning.jobs.create(
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**create_fine_tuning_job_data # type: ignore
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)
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return response
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def create_fine_tuning_job(
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self,
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_is_async: bool,
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create_fine_tuning_job_data: dict,
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api_key: Optional[str],
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api_base: Optional[str],
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timeout: Union[float, httpx.Timeout],
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max_retries: Optional[int],
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organization: Optional[str] = None,
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client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None,
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api_version: Optional[str] = None,
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) -> Union[FineTuningJob, Coroutine[Any, Any, FineTuningJob]]:
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openai_client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = (
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get_azure_openai_client(
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api_key=api_key,
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api_base=api_base,
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timeout=timeout,
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max_retries=max_retries,
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organization=organization,
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api_version=api_version,
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client=client,
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_is_async=_is_async,
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)
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)
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if openai_client is None:
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raise ValueError(
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"AzureOpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
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)
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if _is_async is True:
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if not isinstance(openai_client, AsyncAzureOpenAI):
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raise ValueError(
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"AzureOpenAI client is not an instance of AsyncAzureOpenAI. Make sure you passed an AsyncAzureOpenAI client."
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)
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return self.acreate_fine_tuning_job( # type: ignore
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create_fine_tuning_job_data=create_fine_tuning_job_data,
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openai_client=openai_client,
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)
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verbose_logger.debug(
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"creating fine tuning job, args= %s", create_fine_tuning_job_data
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)
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response = openai_client.fine_tuning.jobs.create(**create_fine_tuning_job_data) # type: ignore
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return response
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async def acancel_fine_tuning_job(
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self,
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fine_tuning_job_id: str,
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openai_client: AsyncAzureOpenAI,
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) -> FineTuningJob:
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response = await openai_client.fine_tuning.jobs.cancel(
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fine_tuning_job_id=fine_tuning_job_id
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)
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return response
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def cancel_fine_tuning_job(
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self,
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_is_async: bool,
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fine_tuning_job_id: str,
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api_key: Optional[str],
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api_base: Optional[str],
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timeout: Union[float, httpx.Timeout],
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max_retries: Optional[int],
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organization: Optional[str] = None,
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api_version: Optional[str] = None,
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client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None,
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):
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openai_client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = (
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get_azure_openai_client(
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api_key=api_key,
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api_base=api_base,
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api_version=api_version,
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timeout=timeout,
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max_retries=max_retries,
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organization=organization,
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client=client,
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_is_async=_is_async,
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)
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)
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if openai_client is None:
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raise ValueError(
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"AzureOpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
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)
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if _is_async is True:
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if not isinstance(openai_client, AsyncAzureOpenAI):
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raise ValueError(
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"AzureOpenAI client is not an instance of AsyncAzureOpenAI. Make sure you passed an AsyncAzureOpenAI client."
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)
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return self.acancel_fine_tuning_job( # type: ignore
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fine_tuning_job_id=fine_tuning_job_id,
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openai_client=openai_client,
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)
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verbose_logger.debug("canceling fine tuning job, args= %s", fine_tuning_job_id)
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response = openai_client.fine_tuning.jobs.cancel(
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fine_tuning_job_id=fine_tuning_job_id
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)
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return response
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async def alist_fine_tuning_jobs(
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self,
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openai_client: AsyncAzureOpenAI,
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after: Optional[str] = None,
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limit: Optional[int] = None,
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):
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response = await openai_client.fine_tuning.jobs.list(after=after, limit=limit) # type: ignore
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return response
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def list_fine_tuning_jobs(
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self,
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_is_async: bool,
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api_key: Optional[str],
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api_base: Optional[str],
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timeout: Union[float, httpx.Timeout],
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max_retries: Optional[int],
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organization: Optional[str] = None,
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client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = None,
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api_version: Optional[str] = None,
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after: Optional[str] = None,
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limit: Optional[int] = None,
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):
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openai_client: Optional[Union[AzureOpenAI, AsyncAzureOpenAI]] = (
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get_azure_openai_client(
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api_key=api_key,
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api_base=api_base,
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api_version=api_version,
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timeout=timeout,
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max_retries=max_retries,
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organization=organization,
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client=client,
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_is_async=_is_async,
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)
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)
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if openai_client is None:
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raise ValueError(
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"AzureOpenAI client is not initialized. Make sure api_key is passed or OPENAI_API_KEY is set in the environment."
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)
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if _is_async is True:
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if not isinstance(openai_client, AsyncAzureOpenAI):
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raise ValueError(
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"AzureOpenAI client is not an instance of AsyncAzureOpenAI. Make sure you passed an AsyncAzureOpenAI client."
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)
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return self.alist_fine_tuning_jobs( # type: ignore
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after=after,
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limit=limit,
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openai_client=openai_client,
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)
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verbose_logger.debug("list fine tuning job, after= %s, limit= %s", after, limit)
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response = openai_client.fine_tuning.jobs.list(after=after, limit=limit) # type: ignore
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return response
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