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fix(logging): prioritize dynamic prompt hooks without prompt ids

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This commit is contained in:
mikemikimike 2026-08-19 21:59:36 +08:00
parent f005afa146
commit 09c757b52c
1 changed files with 33 additions and 9 deletions
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42
tests/test_litellm/responses/test_responses_prompt_management.py
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@ -60,18 +60,15 @@ def _patch_responses_dispatch():
return_value=("gpt-4o", "openai", None, None),
),
patch(
"litellm.responses.mcp.litellm_proxy_mcp_handler."
"LiteLLM_Proxy_MCP_Handler._should_use_litellm_mcp_gateway",
"litellm.responses.mcp.litellm_proxy_mcp_handler.LiteLLM_Proxy_MCP_Handler._should_use_litellm_mcp_gateway",
return_value=False,
),
patch(
"litellm.responses.main.ProviderConfigManager"
".get_provider_responses_api_config",
"litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config",
return_value=None,
),
patch(
"litellm.responses.main.litellm_completion_transformation_handler"
".response_api_handler",
"litellm.responses.main.litellm_completion_transformation_handler.response_api_handler",
return_value=MagicMock(),
),
]
@ -133,6 +130,35 @@ def _make_cache_control_case() -> tuple[
class TestResponsesAPIPromptManagement:
def test_cache_control_hook_wins_over_prompt_manager_without_prompt_id(self):
"""Dynamic hooks must not be shadowed by a generic prompt manager."""
logging_obj = LiteLLMLoggingObj.__new__(LiteLLMLoggingObj)
logging_obj.model_call_details = {}
prompt_manager = MagicMock()
cache_hook = MagicMock(spec=AnthropicCacheControlHook)
with (
patch("litellm.litellm_core_utils.litellm_logging.litellm.logging_callback_manager") as callback_manager,
patch("litellm.litellm_core_utils.litellm_logging.AnthropicCacheControlHook") as hook_class,
):
callback_manager.get_custom_loggers_for_type.return_value = [prompt_manager]
hook_class.get_custom_logger_for_anthropic_cache_control_hook.return_value = cache_hook
result = logging_obj.get_custom_logger_for_prompt_management(
model="anthropic/claude",
non_default_params={"cache_control_injection_points": [{"role": "system", "location": "message"}]},
prompt_id=None,
)
cache_integration = logging_obj.model_call_details["prompt_integration"]
result_with_prompt = logging_obj.get_custom_logger_for_prompt_management(
model="anthropic/claude",
non_default_params={},
prompt_id="managed-prompt",
)
assert result is cache_hook
assert cache_integration == "AnthropicCacheControlHook"
assert result_with_prompt is prompt_manager
def test_str_input_coerced_and_merged(self):
"""[A] str input is wrapped into a message list before being passed to the hook."""
@ -164,9 +190,7 @@ class TestResponsesAPIPromptManagement:
logging_obj.get_chat_completion_prompt.assert_called_once()
call_kwargs = logging_obj.get_chat_completion_prompt.call_args.kwargs
# str was coerced to a single user message before being passed to the hook
assert call_kwargs["messages"] == [
{"role": "user", "content": "Tell me about AI."}
]
assert call_kwargs["messages"] == [{"role": "user", "content": "Tell me about AI."}]
assert call_kwargs["prompt_id"] == "summariser-prompt"
def test_list_input_merged_with_template(self):