mirror of
https://github.com/BerriAI/litellm.git
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9b7ebb6a7d
* build(pyproject.toml): add new dev dependencies - for type checking * build: reformat files to fit black * ci: reformat to fit black * ci(test-litellm.yml): make tests run clear * build(pyproject.toml): add ruff * fix: fix ruff checks * build(mypy/): fix mypy linting errors * fix(hashicorp_secret_manager.py): fix passing cert for tls auth * build(mypy/): resolve all mypy errors * test: update test * fix: fix black formatting * build(pre-commit-config.yaml): use poetry run black * fix(proxy_server.py): fix linting error * fix: fix ruff safe representation error
275 lines
9.8 KiB
Python
275 lines
9.8 KiB
Python
from typing import Any, Coroutine, Optional, Union
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import httpx
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from openai import AsyncAzureOpenAI, AsyncOpenAI, AzureOpenAI, OpenAI
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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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class OpenAIFineTuningAPI:
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"""
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OpenAI 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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def get_openai_client(
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self,
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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],
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client: Optional[
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Union[OpenAI, AsyncOpenAI, AzureOpenAI, AsyncAzureOpenAI]
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] = None,
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_is_async: bool = False,
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api_version: Optional[str] = None,
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litellm_params: Optional[dict] = None,
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) -> Optional[Union[OpenAI, AsyncOpenAI, AzureOpenAI, AsyncAzureOpenAI,]]:
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received_args = locals()
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openai_client: Optional[
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Union[OpenAI, AsyncOpenAI, AzureOpenAI, AsyncAzureOpenAI]
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] = None
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if client is None:
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data = {}
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for k, v in received_args.items():
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if k == "self" or k == "client" or k == "_is_async":
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pass
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elif k == "api_base" and v is not None:
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data["base_url"] = v
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elif v is not None:
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data[k] = v
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if _is_async is True:
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openai_client = AsyncOpenAI(**data)
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else:
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openai_client = OpenAI(**data) # type: ignore
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else:
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openai_client = client
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return openai_client
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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: Union[AsyncOpenAI, 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
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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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api_version: 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],
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client: Optional[
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Union[OpenAI, AsyncOpenAI, AzureOpenAI, AsyncAzureOpenAI]
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] = None,
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) -> Union[FineTuningJob, Coroutine[Any, Any, FineTuningJob]]:
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openai_client: Optional[
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Union[OpenAI, AsyncOpenAI, AzureOpenAI, AsyncAzureOpenAI]
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] = self.get_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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client=client,
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_is_async=_is_async,
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api_version=api_version,
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)
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if openai_client is None:
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raise ValueError(
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"OpenAI 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, (AsyncOpenAI, AsyncAzureOpenAI)):
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raise ValueError(
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"OpenAI client is not an instance of AsyncOpenAI. Make sure you passed an AsyncOpenAI 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)
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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: Union[AsyncOpenAI, 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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api_version: 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],
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client: Optional[
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Union[OpenAI, AsyncOpenAI, AzureOpenAI, AsyncAzureOpenAI]
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] = None,
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):
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openai_client: Optional[
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Union[OpenAI, AsyncOpenAI, AzureOpenAI, AsyncAzureOpenAI]
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] = self.get_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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client=client,
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_is_async=_is_async,
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api_version=api_version,
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)
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if openai_client is None:
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raise ValueError(
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"OpenAI 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, (AsyncOpenAI, AsyncAzureOpenAI)):
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raise ValueError(
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"OpenAI client is not an instance of AsyncOpenAI. Make sure you passed an AsyncOpenAI 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: Union[AsyncOpenAI, 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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api_version: 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],
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client: Optional[
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Union[OpenAI, AsyncOpenAI, AzureOpenAI, AsyncAzureOpenAI]
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] = 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[
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Union[OpenAI, AsyncOpenAI, AzureOpenAI, AsyncAzureOpenAI]
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] = self.get_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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client=client,
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_is_async=_is_async,
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api_version=api_version,
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)
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if openai_client is None:
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raise ValueError(
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"OpenAI 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, (AsyncOpenAI, AsyncAzureOpenAI)):
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raise ValueError(
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"OpenAI client is not an instance of AsyncOpenAI. Make sure you passed an AsyncOpenAI 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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async def aretrieve_fine_tuning_job(
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self,
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fine_tuning_job_id: str,
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openai_client: Union[AsyncOpenAI, AsyncAzureOpenAI],
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) -> FineTuningJob:
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response = await openai_client.fine_tuning.jobs.retrieve(
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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 retrieve_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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api_version: 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],
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client: Optional[
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Union[OpenAI, AsyncOpenAI, AzureOpenAI, AsyncAzureOpenAI]
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] = None,
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):
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openai_client: Optional[
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Union[OpenAI, AsyncOpenAI, AzureOpenAI, AsyncAzureOpenAI]
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] = self.get_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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client=client,
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_is_async=_is_async,
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api_version=api_version,
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)
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if openai_client is None:
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raise ValueError(
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"OpenAI 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, AsyncOpenAI):
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raise ValueError(
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"OpenAI client is not an instance of AsyncOpenAI. Make sure you passed an AsyncOpenAI client."
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)
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return self.aretrieve_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("retrieving fine tuning job, id= %s", fine_tuning_job_id)
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response = openai_client.fine_tuning.jobs.retrieve(
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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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