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cc156a73b8
The OpenAI fine-tuning handler built its SDK client from every local it received, so an api_version or litellm_params set on an openai finetune_settings entry reached OpenAI.__init__ and every fine-tuning call on that provider failed with "unexpected keyword argument 'api_version'". Build the client from its named params instead and cover it with a request-level regression test Co-authored-by: mateo-berri <277851410+mateo-berri@users.noreply.github.com>
94 lines
3.3 KiB
Python
94 lines
3.3 KiB
Python
import json
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from typing import Final, Literal
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import httpx
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import pytest
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import respx
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import litellm
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from litellm.types.utils import LiteLLMFineTuningJob
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API_BASE: Final = "https://fine-tuning.test"
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BASE_MODEL: Final = "gpt-4.1-nano-2025-04-14"
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PROVIDER_JOB: Final = {
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"id": "ftjob-abc123",
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"object": "fine_tuning.job",
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"created_at": 1700000000,
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"error": None,
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"fine_tuned_model": None,
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"finished_at": None,
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"hyperparameters": {"n_epochs": 3},
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"model": BASE_MODEL,
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"organization_id": "org-test",
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"result_files": [],
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"seed": 42,
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"status": "validating_files",
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"trained_tokens": None,
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"training_file": "file-abc123",
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"validation_file": None,
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}
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@pytest.mark.asyncio
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@respx.mock
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@pytest.mark.parametrize(
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("custom_llm_provider", "route"),
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[("openai", f"{API_BASE}/v1/fine_tuning/jobs"), ("azure", f"{API_BASE}/openai/fine_tuning/jobs")],
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)
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@pytest.mark.parametrize("prefixed", [True, False], ids=["provider-prefixed", "bare"])
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async def test_create_sends_the_model_without_the_provider_prefix(
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monkeypatch: pytest.MonkeyPatch, custom_llm_provider: str, route: str, prefixed: bool
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) -> None:
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sent: Final = respx.post(url__startswith=route).mock(return_value=httpx.Response(200, json=PROVIDER_JOB))
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async with httpx.AsyncClient() as session:
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monkeypatch.setattr(litellm, "aclient_session", session)
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await litellm.acreate_fine_tuning_job(
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model=f"{custom_llm_provider}/{BASE_MODEL}" if prefixed else BASE_MODEL,
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training_file="file-abc123",
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custom_llm_provider=custom_llm_provider,
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api_key="sk-test",
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api_base=f"{API_BASE}/v1" if custom_llm_provider == "openai" else API_BASE,
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**({"api_version": "2024-10-21"} if custom_llm_provider == "azure" else {}),
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)
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assert json.loads(sent.calls.last.request.content)["model"] == BASE_MODEL
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@pytest.mark.asyncio
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@respx.mock
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@pytest.mark.parametrize(
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("custom_llm_provider", "api_base", "route", "sent_api_version"),
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[
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("openai", f"{API_BASE}/v1", f"{API_BASE}/v1/fine_tuning/jobs", None),
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("azure", API_BASE, f"{API_BASE}/openai/fine_tuning/jobs", "2024-10-21"),
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],
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)
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@pytest.mark.parametrize("is_async", [True, False], ids=["async", "sync"])
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async def test_create_with_api_version_reaches_the_provider_and_only_azure_gets_it(
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monkeypatch: pytest.MonkeyPatch,
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custom_llm_provider: Literal["openai", "azure"],
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api_base: str,
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route: str,
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sent_api_version: str | None,
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is_async: bool,
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) -> None:
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sent: Final = respx.post(url__startswith=route).mock(return_value=httpx.Response(200, json=PROVIDER_JOB))
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request: Final = {
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"model": BASE_MODEL,
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"training_file": "file-abc123",
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"custom_llm_provider": custom_llm_provider,
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"api_key": "sk-test",
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"api_base": api_base,
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"api_version": "2024-10-21",
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}
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async with httpx.AsyncClient() as session:
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monkeypatch.setattr(litellm, "aclient_session", session)
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job: Final = (
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await litellm.acreate_fine_tuning_job(**request) if is_async else litellm.create_fine_tuning_job(**request)
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)
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assert isinstance(job, LiteLLMFineTuningJob)
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assert job.id == PROVIDER_JOB["id"]
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assert sent.calls.last.request.url.params.get("api-version") == sent_api_version
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