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https://github.com/tiennm99/litellm.git
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Merge pull request #18938 from BerriAI/litellm_fix_generate_two_telemetry
[fix] generate two telemetry in responses
This commit is contained in:
YutaSaito
@@ -1853,6 +1853,14 @@ class Logging(LiteLLMLoggingBaseClass):
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cache_hit=cache_hit,
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standard_logging_object=kwargs.get("standard_logging_object", None),
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)
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litellm_params = self.model_call_details.get("litellm_params", {})
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is_sync_request = (
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litellm_params.get(CallTypes.acompletion.value, False) is not True
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and litellm_params.get(CallTypes.aresponses.value, False) is not True
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and litellm_params.get(CallTypes.aembedding.value, False) is not True
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and litellm_params.get(CallTypes.aimage_generation.value, False) is not True
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and litellm_params.get(CallTypes.atranscription.value, False) is not True
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)
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try:
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## BUILD COMPLETE STREAMED RESPONSE
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complete_streaming_response: Optional[
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@@ -1915,7 +1923,6 @@ class Logging(LiteLLMLoggingBaseClass):
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self.has_run_logging(event_type="sync_success")
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for callback in callbacks:
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try:
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litellm_params = self.model_call_details.get("litellm_params", {})
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should_run = self.should_run_callback(
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callback=callback,
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litellm_params=litellm_params,
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@@ -2185,22 +2192,7 @@ class Logging(LiteLLMLoggingBaseClass):
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if (
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callback == "openmeter"
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and self.model_call_details.get("litellm_params", {}).get(
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"acompletion", False
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)
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is not True
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and self.model_call_details.get("litellm_params", {}).get(
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"aembedding", False
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)
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is not True
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and self.model_call_details.get("litellm_params", {}).get(
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"aimage_generation", False
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)
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is not True
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and self.model_call_details.get("litellm_params", {}).get(
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"atranscription", False
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)
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is not True
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and is_sync_request
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):
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global openMeterLogger
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if openMeterLogger is None:
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@@ -2229,22 +2221,7 @@ class Logging(LiteLLMLoggingBaseClass):
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)
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if (
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isinstance(callback, CustomLogger)
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and self.model_call_details.get("litellm_params", {}).get(
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"acompletion", False
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)
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is not True
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and self.model_call_details.get("litellm_params", {}).get(
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"aembedding", False
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)
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is not True
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and self.model_call_details.get("litellm_params", {}).get(
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"aimage_generation", False
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)
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is not True
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and self.model_call_details.get("litellm_params", {}).get(
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"atranscription", False
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)
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is not True
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and is_sync_request
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and self.call_type
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!= CallTypes.pass_through.value # pass-through endpoints call async_log_success_event
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): # custom logger class
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@@ -2272,22 +2249,7 @@ class Logging(LiteLLMLoggingBaseClass):
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)
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if (
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callable(callback) is True
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and self.model_call_details.get("litellm_params", {}).get(
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"acompletion", False
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)
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is not True
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and self.model_call_details.get("litellm_params", {}).get(
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"aembedding", False
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)
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is not True
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and self.model_call_details.get("litellm_params", {}).get(
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"aimage_generation", False
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)
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is not True
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and self.model_call_details.get("litellm_params", {}).get(
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"atranscription", False
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)
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is not True
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and is_sync_request
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and customLogger is not None
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): # custom logger functions
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print_verbose(
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@@ -2737,6 +2699,15 @@ class Logging(LiteLLMLoggingBaseClass):
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event_type="sync_failure"
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): # prevent double logging
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return
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litellm_params = self.model_call_details.get("litellm_params", {})
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is_sync_request = (
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litellm_params.get(CallTypes.acompletion.value, False) is not True
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and litellm_params.get(CallTypes.aresponses.value, False) is not True
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and litellm_params.get(CallTypes.aembedding.value, False) is not True
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and litellm_params.get(CallTypes.aimage_generation.value, False) is not True
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and litellm_params.get(CallTypes.atranscription.value, False) is not True
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)
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try:
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start_time, end_time = self._failure_handler_helper_fn(
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exception=exception,
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@@ -2762,7 +2733,6 @@ class Logging(LiteLLMLoggingBaseClass):
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self.has_run_logging(event_type="sync_failure")
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for callback in callbacks:
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try:
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litellm_params = self.model_call_details.get("litellm_params", {})
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should_run = self.should_run_callback(
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callback=callback,
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litellm_params=litellm_params,
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@@ -2830,14 +2800,7 @@ class Logging(LiteLLMLoggingBaseClass):
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)
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if (
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isinstance(callback, CustomLogger)
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and self.model_call_details.get("litellm_params", {}).get(
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"acompletion", False
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)
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is not True
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and self.model_call_details.get("litellm_params", {}).get(
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"aembedding", False
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)
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is not True
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and is_sync_request
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): # custom logger class
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callback.log_failure_event(
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start_time=start_time,
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@@ -668,6 +668,7 @@ def responses(
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optional_params=dict(responses_api_request_params),
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litellm_params={
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**responses_api_request_params,
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"aresponses": _is_async,
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"litellm_call_id": litellm_call_id,
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"metadata": metadata,
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},
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@@ -14,6 +14,7 @@ import time
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from litellm.constants import SENTRY_DENYLIST, SENTRY_PII_DENYLIST
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from litellm.litellm_core_utils.litellm_logging import Logging as LitellmLogging
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from litellm.litellm_core_utils.litellm_logging import set_callbacks
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from litellm.types.utils import ModelResponse
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@pytest.fixture
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@@ -277,6 +278,87 @@ async def test_logging_non_streaming_request():
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litellm.callbacks = original_callbacks
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@pytest.mark.parametrize("async_flag", ["acompletion", "aresponses"])
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def test_success_handler_skips_sync_callbacks_for_async_requests(logging_obj, async_flag):
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"""Ensure sync success callbacks are skipped when async call type flags are set."""
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from litellm.integrations.custom_logger import CustomLogger
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class DummyLogger(CustomLogger):
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pass
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logging_obj.stream = False # simulate non-streaming request where sync callbacks would normally run
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logging_obj.model_call_details["litellm_params"] = {async_flag: True}
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logging_obj.litellm_params = logging_obj.model_call_details["litellm_params"]
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dummy_logger = DummyLogger()
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dummy_logger.log_success_event = MagicMock()
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dummy_logger.log_stream_event = MagicMock()
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model_response = ModelResponse(
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id="resp-123",
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model="gpt-4o-mini",
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choices=[
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{
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"message": {"role": "assistant", "content": "hello"},
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"finish_reason": "stop",
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"index": 0,
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}
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],
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usage={"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
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)
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with patch.object(
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logging_obj,
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"get_combined_callback_list",
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return_value=[dummy_logger],
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):
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logging_obj.success_handler(result=model_response)
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dummy_logger.log_success_event.assert_not_called()
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dummy_logger.log_stream_event.assert_not_called()
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@pytest.mark.parametrize("call_type", ["completion", "responses"])
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def test_success_handler_runs_sync_callbacks_for_sync_requests(logging_obj, call_type):
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"""Ensure sync success callbacks execute when call type is sync (completion/responses)."""
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from litellm.integrations.custom_logger import CustomLogger
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class DummyLogger(CustomLogger):
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pass
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logging_obj.stream = False
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logging_obj.call_type = call_type
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logging_obj.model_call_details["litellm_params"] = {}
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logging_obj.litellm_params = {}
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dummy_logger = DummyLogger()
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dummy_logger.log_success_event = MagicMock()
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dummy_logger.log_stream_event = MagicMock()
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model_response = ModelResponse(
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id="resp-123",
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model="gpt-4o-mini",
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choices=[
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{
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"message": {"role": "assistant", "content": "hello"},
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"finish_reason": "stop",
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"index": 0,
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}
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],
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usage={"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
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)
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with patch.object(
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logging_obj,
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"get_combined_callback_list",
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return_value=[dummy_logger],
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):
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logging_obj.success_handler(result=model_response)
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dummy_logger.log_success_event.assert_called_once()
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dummy_logger.log_stream_event.assert_not_called()
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def test_get_user_agent_tags():
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from litellm.litellm_core_utils.litellm_logging import StandardLoggingPayloadSetup
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