From f84f986b4ee571c8b3db18a560e007801379a933 Mon Sep 17 00:00:00 2001 From: "devin-ai-integration[bot]" <158243242+devin-ai-integration[bot]@users.noreply.github.com> Date: Fri, 11 Sep 2026 18:16:33 -0700 Subject: [PATCH] fix(guardrails): keep post_call guardrail info on streamed chat completions (#40806) * fix(guardrails): sync logging_obj guardrail info on every record so post_call entries survive streamed chat completions Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> * test(guardrails): hoist regression test imports to module scope Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --------- Co-authored-by: yucheng Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com> --- litellm/integrations/custom_guardrail.py | 1 + .../integrations/test_custom_guardrail.py | 61 ++++++++++++++++++- 2 files changed, 61 insertions(+), 1 deletion(-) diff --git a/litellm/integrations/custom_guardrail.py b/litellm/integrations/custom_guardrail.py index bb54767edef..8a976a966a6 100644 --- a/litellm/integrations/custom_guardrail.py +++ b/litellm/integrations/custom_guardrail.py @@ -1217,6 +1217,7 @@ class CustomGuardrail(CustomLogger): _, metadata_bucket = get_or_create_metadata_bucket(request_data) _append_guardrail_info(metadata_bucket) + _sync_guardrail_info_to_logging_obj(request_data, request_data.get("litellm_logging_obj")) _guardrail_self_recorded.set(True) diff --git a/tests/test_litellm/integrations/test_custom_guardrail.py b/tests/test_litellm/integrations/test_custom_guardrail.py index 1644d78ae37..bb4822eae57 100644 --- a/tests/test_litellm/integrations/test_custom_guardrail.py +++ b/tests/test_litellm/integrations/test_custom_guardrail.py @@ -1,4 +1,5 @@ import asyncio +import datetime as dt from typing import TYPE_CHECKING, ClassVar, Final, Literal, Optional from unittest.mock import AsyncMock @@ -9,9 +10,16 @@ from litellm.integrations.custom_guardrail import ( CustomGuardrail, log_guardrail_information, ) +from litellm.litellm_core_utils.litellm_logging import Logging from litellm.proxy._types import CallTypes, UserAPIKeyAuth from litellm.types.guardrails import GuardrailEventHooks, Mode -from litellm.types.utils import GenericGuardrailAPIInputs, GuardrailTracingDetail +from litellm.types.utils import ( + Choices, + GenericGuardrailAPIInputs, + GuardrailTracingDetail, + Message, + ModelResponse, +) if TYPE_CHECKING: from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj @@ -2345,6 +2353,57 @@ class TestUndecoratedApplyGuardrailIsLogged: assert _Labelled.seen_label == "docs-style" + @pytest.mark.asyncio + async def test_post_call_recorded_outside_decorator_reaches_standard_logging_object(self): + """LIT-7608 regression: the auto-wrapped pre_call apply_guardrail copies the request bucket + into logging_obj.litellm_params["metadata"]. A post_call entry recorded later without the + decorator (the Bedrock streaming hook) must not be shadowed by that stale copy.""" + messages: Final = [{"role": "user", "content": "hello there"}] + litellm_metadata: Final[dict] = {"user_api_key_user_id": "u1"} + logging_obj: Final = Logging( + model="bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0", + messages=messages, + stream=True, + call_type=CallTypes.acompletion.value, + start_time=dt.datetime.now(), + litellm_call_id="call-1", + function_id="fn-1", + ) + logging_obj.update_environment_variables( + litellm_params={"litellm_metadata": litellm_metadata}, + optional_params={}, + model="bedrock/us.anthropic.claude-haiku-4-5-20251001-v1:0", + custom_llm_provider="bedrock", + ) + request_data: Final = { + "model": "bedrock-haiku", + "messages": messages, + "litellm_metadata": litellm_metadata, + "litellm_logging_obj": logging_obj, + } + guardrail: Final = _UndecoratedGuardrail(guardrail_name="bedrock-pre", event_hook=GuardrailEventHooks.pre_call) + + await guardrail.apply_guardrail( + inputs=GenericGuardrailAPIInputs(texts=["hello there"]), + request_data=request_data, + input_type="request", + logging_obj=logging_obj, + ) + guardrail.add_standard_logging_guardrail_information_to_request_data( + guardrail_json_response={"action": "NONE"}, + request_data=request_data, + guardrail_status="success", + event_type=GuardrailEventHooks.post_call, + ) + await logging_obj.async_success_handler( + result=ModelResponse(choices=[Choices(message=Message(role="assistant", content="general kenobi"))]), + start_time=dt.datetime.now(), + end_time=dt.datetime.now(), + ) + + entries: Final = logging_obj.model_call_details["standard_logging_object"]["guardrail_information"] + assert [e["guardrail_mode"] for e in entries] == ["pre_call", "post_call"] + class _ApplyOnlyObserver(CustomGuardrail): """Overrides only apply_guardrail, like panw_prisma_airs; inherits async_logging_hook."""