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refactor(agentic-loop): narrow logging_obj before building the fake stream wrapper
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Browse source 
Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
This commit is contained in:
shivam 2026-08-27 23:19:17 +00:00
parent d556a04286
commit a14daf18d6
1 changed files with 3 additions and 2 deletions
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5
litellm/litellm_core_utils/chat_completion_agentic_loop.py
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@ -10,6 +10,8 @@ from litellm.litellm_core_utils.agentic_loop_settings import (
DEFAULT_MAX_AGENTIC_LOOPS, DEFAULT_MAX_AGENTIC_LOOPS,
validated_max_agentic_loops, validated_max_agentic_loops,
) )
from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObject
from litellm.llms.base_llm.base_model_iterator import MockResponseIterator
from litellm.types.integrations.custom_logger import ( from litellm.types.integrations.custom_logger import (
CHAT_COMPLETION_AGENTIC_SURFACE, CHAT_COMPLETION_AGENTIC_SURFACE,
HEADROOM_CONVERTED_STREAM_KEY, HEADROOM_CONVERTED_STREAM_KEY,
@ -104,9 +106,8 @@ def _wrap_response_as_fake_stream(
) -> object: ) -> object:
if isinstance(response, CustomStreamWrapper): if isinstance(response, CustomStreamWrapper):
return response return response
if not isinstance(response, ModelResponse): if not isinstance(response, ModelResponse) or not isinstance(logging_obj, LiteLLMLoggingObject):
return response return response
from litellm.llms.base_llm.base_model_iterator import MockResponseIterator
return CustomStreamWrapper( return CustomStreamWrapper(
completion_stream=MockResponseIterator(model_response=response), completion_stream=MockResponseIterator(model_response=response),