scriptoriumadmin/litellm
1
0
Fork 0
mirror of https://github.com/BerriAI/litellm.git synced 2026-10-06 02:48:13 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions 103

fix(responses): keep reasoning effort typed

Browse source
This commit is contained in:
Onat Özmen 2026-08-30 19:30:01 +03:00
parent d6514effab
commit 3a30409bec
1 changed files with 34 additions and 30 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

64
litellm/llms/openai/responses/transformation.py
View file

@ -81,6 +81,25 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
return OpenAIGPT5Config.effort_resolves_to_none(model, effort)
@staticmethod
def _is_unsupported_reasoning_effort(model: str, effort: str | None) -> bool:
"""Apply the GPT-5 reasoning-effort capability flags used by chat completions."""
from litellm.utils import _is_explicitly_disabled_factory, _supports_factory
if effort == "xhigh":
return not _supports_factory(
model=model,
custom_llm_provider=None,
key="supports_xhigh_reasoning_effort",
)
if effort in ("minimal", "low"):
return _is_explicitly_disabled_factory(
model=model,
custom_llm_provider=None,
key=f"supports_{effort}_reasoning_effort",
)
return False
@staticmethod
def _enforce_min_max_output_tokens(max_output_tokens: "int | None") -> "int | None":
"""Raise sub-minimum max_output_tokens up to the OpenAI Responses API minimum.
@ -130,46 +149,31 @@ class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
params["max_output_tokens"] = self._enforce_min_max_output_tokens(params.get("max_output_tokens"))
if self._is_gpt_5_model(model=model):
reasoning: Final = params.get("reasoning") or {}
effort: Final = reasoning.get("effort") if isinstance(reasoning, dict) else None
if isinstance(effort, str):
from litellm.llms.openai.chat.gpt_5_transformation import OpenAIGPT5Config
reasoning: Final = response_api_optional_params.get("reasoning")
effort: Final = reasoning.get("effort") if reasoning is not None else None
unsupported_effort: Final = self._is_unsupported_reasoning_effort(model, effort)
should_drop_effort: Final = unsupported_effort and (drop_params or litellm.drop_params)
unsupported_effort: Final = (
effort == "xhigh"
and not OpenAIGPT5Config._supports_reasoning_effort_level( # pyright: ignore[reportPrivateUsage, reportArgumentType, reportCallIssue] # shared GPT-5 capability gate
model,
effort, # pyright: ignore[reportArgumentType, reportCallIssue] # shared helper call
)
) or (
effort in ("minimal", "low")
and OpenAIGPT5Config._is_reasoning_effort_level_explicitly_disabled( # pyright: ignore[reportPrivateUsage, reportArgumentType, reportCallIssue] # shared GPT-5 capability gate
model,
effort, # pyright: ignore[reportArgumentType, reportCallIssue] # shared helper call
)
)
if unsupported_effort:
if drop_params or litellm.drop_params:
updated_reasoning: Final = dict(reasoning) # mutable-ok: local copy
if unsupported_effort:
if should_drop_effort:
if reasoning is not None:
updated_reasoning: Final = reasoning.copy() # mutable-ok: local copy
updated_reasoning.pop("effort", None)
if updated_reasoning:
params["reasoning"] = updated_reasoning
else:
params.pop("reasoning", None)
else:
raise litellm.UnsupportedParamsError(
message=f"reasoning.effort={effort} is not supported for this model.",
status_code=400,
)
else:
raise litellm.UnsupportedParamsError(
message=f"reasoning.effort={effort} is not supported for this model.",
status_code=400,
)
temperature: Final = params.get("temperature")
if temperature is not None and temperature != 1:
transformed_reasoning: Final = params.get("reasoning") or {} # mutable-ok: local view
transformed_effort: Final = (
transformed_reasoning.get("effort") if isinstance(transformed_reasoning, dict) else None
)
effective_effort: Final = None if should_drop_effort else effort
supports_none: Final = self._supports_reasoning_effort_none(model=model)
if supports_none and self._effort_resolves_to_none(model, transformed_effort):
if supports_none and self._effort_resolves_to_none(model, effective_effort):
pass # flexible temperature allowed
elif drop_params or litellm.drop_params:
params.pop("temperature", None)