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https://github.com/BerriAI/litellm.git
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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
This commit is contained in:
Ishaan Jaff
GitHub
parent
5e8c64f128
commit
2ece919f01
5 changed files with 400 additions and 227 deletions
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@ -171,6 +171,7 @@ def create_fine_tuning_job(
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response = openai_fine_tuning_apis_instance.create_fine_tuning_job(
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api_base=api_base,
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api_key=api_key,
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api_version=optional_params.api_version,
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organization=organization,
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create_fine_tuning_job_data=create_fine_tuning_job_data_dict,
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timeout=timeout,
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@ -223,6 +224,7 @@ def create_fine_tuning_job(
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timeout=timeout,
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max_retries=optional_params.max_retries,
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_is_async=_is_async,
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organization=optional_params.organization,
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)
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elif custom_llm_provider == "vertex_ai":
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api_base = optional_params.api_base or ""
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@ -279,7 +281,7 @@ def create_fine_tuning_job(
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async def acancel_fine_tuning_job(
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fine_tuning_job_id: str,
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custom_llm_provider: Literal["openai"] = "openai",
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custom_llm_provider: Literal["openai", "azure", "vertex_ai"] = "openai",
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extra_headers: Optional[Dict[str, str]] = None,
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extra_body: Optional[Dict[str, str]] = None,
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**kwargs,
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@ -374,6 +376,7 @@ def cancel_fine_tuning_job(
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response = openai_fine_tuning_apis_instance.cancel_fine_tuning_job(
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api_base=api_base,
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api_key=api_key,
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api_version=optional_params.api_version,
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organization=organization,
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fine_tuning_job_id=fine_tuning_job_id,
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timeout=timeout,
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@ -412,6 +415,7 @@ def cancel_fine_tuning_job(
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timeout=timeout,
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max_retries=optional_params.max_retries,
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_is_async=_is_async,
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organization=optional_params.organization,
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)
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else:
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raise litellm.exceptions.BadRequestError(
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@ -434,7 +438,7 @@ def cancel_fine_tuning_job(
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async def alist_fine_tuning_jobs(
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after: Optional[str] = None,
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limit: Optional[int] = None,
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custom_llm_provider: Literal["openai"] = "openai",
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custom_llm_provider: Literal["openai", "azure", "vertex_ai"] = "openai",
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extra_headers: Optional[Dict[str, str]] = None,
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extra_body: Optional[Dict[str, str]] = None,
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**kwargs,
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@ -533,6 +537,7 @@ def list_fine_tuning_jobs(
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response = openai_fine_tuning_apis_instance.list_fine_tuning_jobs(
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api_base=api_base,
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api_key=api_key,
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api_version=optional_params.api_version,
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organization=organization,
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after=after,
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limit=limit,
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@ -573,6 +578,7 @@ def list_fine_tuning_jobs(
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timeout=timeout,
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max_retries=optional_params.max_retries,
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_is_async=_is_async,
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organization=optional_params.organization,
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)
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else:
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raise litellm.exceptions.BadRequestError(
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@ -590,3 +596,153 @@ def list_fine_tuning_jobs(
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return response
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except Exception as e:
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raise e
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async def aretrieve_fine_tuning_job(
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fine_tuning_job_id: str,
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custom_llm_provider: Literal["openai", "azure", "vertex_ai"] = "openai",
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extra_headers: Optional[Dict[str, str]] = None,
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extra_body: Optional[Dict[str, str]] = None,
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**kwargs,
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) -> FineTuningJob:
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"""
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Async: Get info about a fine-tuning job.
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"""
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try:
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loop = asyncio.get_event_loop()
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kwargs["aretrieve_fine_tuning_job"] = True
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# Use a partial function to pass your keyword arguments
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func = partial(
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retrieve_fine_tuning_job,
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fine_tuning_job_id,
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custom_llm_provider,
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extra_headers,
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extra_body,
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**kwargs,
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)
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# Add the context to the function
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ctx = contextvars.copy_context()
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func_with_context = partial(ctx.run, func)
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init_response = await loop.run_in_executor(None, func_with_context)
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if asyncio.iscoroutine(init_response):
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response = await init_response
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else:
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response = init_response # type: ignore
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return response
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except Exception as e:
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raise e
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def retrieve_fine_tuning_job(
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fine_tuning_job_id: str,
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custom_llm_provider: Literal["openai", "azure", "vertex_ai"] = "openai",
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extra_headers: Optional[Dict[str, str]] = None,
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extra_body: Optional[Dict[str, str]] = None,
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**kwargs,
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) -> Union[FineTuningJob, Coroutine[Any, Any, FineTuningJob]]:
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"""
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Get info about a fine-tuning job.
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"""
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try:
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optional_params = GenericLiteLLMParams(**kwargs)
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### TIMEOUT LOGIC ###
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timeout = optional_params.timeout or kwargs.get("request_timeout", 600) or 600
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# set timeout for 10 minutes by default
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if (
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timeout is not None
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and isinstance(timeout, httpx.Timeout)
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and supports_httpx_timeout(custom_llm_provider) is False
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):
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read_timeout = timeout.read or 600
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timeout = read_timeout # default 10 min timeout
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elif timeout is not None and not isinstance(timeout, httpx.Timeout):
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timeout = float(timeout) # type: ignore
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elif timeout is None:
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timeout = 600.0
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_is_async = kwargs.pop("aretrieve_fine_tuning_job", False) is True
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# OpenAI
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if custom_llm_provider == "openai":
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api_base = (
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optional_params.api_base
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or litellm.api_base
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or os.getenv("OPENAI_API_BASE")
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or "https://api.openai.com/v1"
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)
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organization = (
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optional_params.organization
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or litellm.organization
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or os.getenv("OPENAI_ORGANIZATION", None)
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or None
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)
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api_key = (
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optional_params.api_key
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or litellm.api_key
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or litellm.openai_key
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or os.getenv("OPENAI_API_KEY")
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)
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response = openai_fine_tuning_apis_instance.retrieve_fine_tuning_job(
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api_base=api_base,
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api_key=api_key,
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api_version=optional_params.api_version,
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organization=organization,
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fine_tuning_job_id=fine_tuning_job_id,
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timeout=timeout,
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max_retries=optional_params.max_retries,
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_is_async=_is_async,
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)
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# Azure OpenAI
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elif custom_llm_provider == "azure":
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api_base = optional_params.api_base or litellm.api_base or get_secret_str("AZURE_API_BASE") # type: ignore
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api_version = (
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optional_params.api_version
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or litellm.api_version
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or get_secret_str("AZURE_API_VERSION")
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) # type: ignore
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api_key = (
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optional_params.api_key
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or litellm.api_key
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or litellm.azure_key
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or get_secret_str("AZURE_OPENAI_API_KEY")
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or get_secret_str("AZURE_API_KEY")
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) # type: ignore
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extra_body = optional_params.get("extra_body", {})
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if extra_body is not None:
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extra_body.pop("azure_ad_token", None)
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else:
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get_secret_str("AZURE_AD_TOKEN") # type: ignore
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response = azure_fine_tuning_apis_instance.retrieve_fine_tuning_job(
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api_base=api_base,
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api_key=api_key,
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api_version=api_version,
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fine_tuning_job_id=fine_tuning_job_id,
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timeout=timeout,
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max_retries=optional_params.max_retries,
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_is_async=_is_async,
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organization=optional_params.organization,
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)
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else:
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raise litellm.exceptions.BadRequestError(
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message="LiteLLM doesn't support {} for 'retrieve_fine_tuning_job'. Only 'openai' and 'azure' are supported.".format(
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custom_llm_provider
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),
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model="n/a",
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llm_provider=custom_llm_provider,
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response=httpx.Response(
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status_code=400,
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content="Unsupported provider",
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request=httpx.Request(method="retrieve_fine_tuning_job", url="https://github.com/BerriAI/litellm"), # type: ignore
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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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raise e
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