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(Feat) - new endpoint GET /v1/fine_tuning/jobs/{fine_tuning_job_id:path}
(#7427)
* init commit ft jobs logging * add ft logging * add logging for FineTuningJob * simple FT Job create test * simplify Azure fine tuning to use all methods in OAI ft * update doc string * add aretrieve_fine_tuning_job * re use from litellm.proxy.utils import handle_exception_on_proxy * fix naming * add /fine_tuning/jobs/{fine_tuning_job_id:path} * remove unused imports * update func signature * run ci/cd again * ci/cd run again * fix code qulity * ci/cd run again
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5 changed files with 400 additions and 227 deletions
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@ -9,12 +9,13 @@ import asyncio
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import traceback
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from typing import Optional
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from fastapi import APIRouter, Depends, HTTPException, Request, Response, status
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from fastapi import APIRouter, Depends, Request, Response
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import litellm
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from litellm._logging import verbose_proxy_logger
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from litellm.proxy._types import *
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from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
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from litellm.proxy.utils import handle_exception_on_proxy
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router = APIRouter()
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@ -171,21 +172,105 @@ async def create_fine_tuning_job(
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)
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)
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verbose_proxy_logger.debug(traceback.format_exc())
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if isinstance(e, HTTPException):
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raise ProxyException(
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message=getattr(e, "message", str(e.detail)),
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type=getattr(e, "type", "None"),
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param=getattr(e, "param", "None"),
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code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST),
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raise handle_exception_on_proxy(e)
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@router.get(
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"/v1/fine_tuning/jobs/{fine_tuning_job_id:path}",
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dependencies=[Depends(user_api_key_auth)],
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tags=["fine-tuning"],
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summary="✨ (Enterprise) Retrieve Fine-Tuning Job",
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)
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@router.get(
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"/fine_tuning/jobs/{fine_tuning_job_id:path}",
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dependencies=[Depends(user_api_key_auth)],
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tags=["fine-tuning"],
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summary="✨ (Enterprise) Retrieve Fine-Tuning Job",
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)
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async def retrieve_fine_tuning_job(
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request: Request,
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fastapi_response: Response,
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fine_tuning_job_id: str,
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custom_llm_provider: Literal["openai", "azure"],
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user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
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):
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"""
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Retrieves a fine-tuning job.
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This is the equivalent of GET https://api.openai.com/v1/fine_tuning/jobs/{fine_tuning_job_id}
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Supported Query Params:
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- `custom_llm_provider`: Name of the LiteLLM provider
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- `fine_tuning_job_id`: The ID of the fine-tuning job to retrieve.
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"""
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from litellm.proxy.proxy_server import (
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add_litellm_data_to_request,
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general_settings,
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get_custom_headers,
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premium_user,
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proxy_config,
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proxy_logging_obj,
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version,
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)
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data: dict = {}
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try:
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if premium_user is not True:
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raise ValueError(
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f"Only premium users can use this endpoint + {CommonProxyErrors.not_premium_user.value}"
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)
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else:
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error_msg = f"{str(e)}"
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raise ProxyException(
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message=getattr(e, "message", error_msg),
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type=getattr(e, "type", "None"),
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param=getattr(e, "param", "None"),
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code=getattr(e, "status_code", 500),
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# Include original request and headers in the data
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data = await add_litellm_data_to_request(
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data=data,
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request=request,
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general_settings=general_settings,
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user_api_key_dict=user_api_key_dict,
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version=version,
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proxy_config=proxy_config,
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)
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# get configs for custom_llm_provider
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llm_provider_config = get_fine_tuning_provider_config(
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custom_llm_provider=custom_llm_provider
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)
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if llm_provider_config is not None:
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data.update(llm_provider_config)
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response = await litellm.aretrieve_fine_tuning_job(
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**data,
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fine_tuning_job_id=fine_tuning_job_id,
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)
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### RESPONSE HEADERS ###
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hidden_params = getattr(response, "_hidden_params", {}) or {}
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model_id = hidden_params.get("model_id", None) or ""
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cache_key = hidden_params.get("cache_key", None) or ""
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api_base = hidden_params.get("api_base", None) or ""
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fastapi_response.headers.update(
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get_custom_headers(
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user_api_key_dict=user_api_key_dict,
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model_id=model_id,
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cache_key=cache_key,
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api_base=api_base,
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version=version,
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model_region=getattr(user_api_key_dict, "allowed_model_region", ""),
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)
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)
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return response
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except Exception as e:
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await proxy_logging_obj.post_call_failure_hook(
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user_api_key_dict=user_api_key_dict, original_exception=e, request_data=data
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)
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verbose_proxy_logger.error(
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"litellm.proxy.proxy_server.list_fine_tuning_jobs(): Exception occurred - {}".format(
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str(e)
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)
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)
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verbose_proxy_logger.debug(traceback.format_exc())
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raise handle_exception_on_proxy(e)
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@router.get(
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@ -286,21 +371,7 @@ async def list_fine_tuning_jobs(
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)
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)
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verbose_proxy_logger.debug(traceback.format_exc())
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if isinstance(e, HTTPException):
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raise ProxyException(
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message=getattr(e, "message", str(e.detail)),
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type=getattr(e, "type", "None"),
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param=getattr(e, "param", "None"),
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code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST),
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)
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else:
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error_msg = f"{str(e)}"
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raise ProxyException(
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message=getattr(e, "message", error_msg),
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type=getattr(e, "type", "None"),
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param=getattr(e, "param", "None"),
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code=getattr(e, "status_code", 500),
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)
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raise handle_exception_on_proxy(e)
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@router.post(
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@ -315,7 +386,7 @@ async def list_fine_tuning_jobs(
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tags=["fine-tuning"],
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summary="✨ (Enterprise) Cancel Fine-Tuning Jobs",
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)
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async def retrieve_fine_tuning_job(
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async def cancel_fine_tuning_job(
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request: Request,
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fastapi_response: Response,
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fine_tuning_job_id: str,
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@ -402,18 +473,4 @@ async def retrieve_fine_tuning_job(
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)
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)
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verbose_proxy_logger.debug(traceback.format_exc())
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if isinstance(e, HTTPException):
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raise ProxyException(
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message=getattr(e, "message", str(e.detail)),
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type=getattr(e, "type", "None"),
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param=getattr(e, "param", "None"),
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code=getattr(e, "status_code", status.HTTP_400_BAD_REQUEST),
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)
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else:
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error_msg = f"{str(e)}"
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raise ProxyException(
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message=getattr(e, "message", error_msg),
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type=getattr(e, "type", "None"),
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param=getattr(e, "param", "None"),
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code=getattr(e, "status_code", 500),
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)
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raise handle_exception_on_proxy(e)
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