Fix: output_tokens_details.reasoning_tokens None

litellm/litellm_core_utils/litellm_logging.py

@@ -1638,11 +1638,19 @@ def _transform_usage_objects(self, result):
                     "standard_logging_object"
                 )
             ) is not None:
-                standard_logging_payload["response"] = (
+                response_dict = (
                     result.model_dump()
                     if hasattr(result, "model_dump")
                     else dict(result)
                 )
+                # Ensure usage is properly included with transformed chat format
+                if transformed_usage is not None:
+                    response_dict["usage"] = (
+                        transformed_usage.model_dump()
+                        if hasattr(transformed_usage, "model_dump")
+                        else dict(transformed_usage)
+                    )
+                standard_logging_payload["response"] = response_dict
         elif isinstance(result, TranscriptionResponse):
             from litellm.litellm_core_utils.llm_cost_calc.usage_object_transformation import (
                 TranscriptionUsageObjectTransformation,
@@ -4540,6 +4548,10 @@ def get_usage_from_response_obj(
             )
         elif isinstance(usage, Usage):
             return usage
+        elif isinstance(usage, ResponseAPIUsage):
+            return ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage(
+                usage
+            )
         elif isinstance(usage, dict):
             if ResponseAPILoggingUtils._is_response_api_usage(usage):
                 return (

litellm/llms/anthropic/chat/transformation.py

@@ -1369,7 +1369,7 @@ def calculate_usage(
             else 0
         )
         completion_token_details = CompletionTokensDetailsWrapper(
-            reasoning_tokens=reasoning_tokens if reasoning_tokens > 0 else None,
+            reasoning_tokens=reasoning_tokens if reasoning_tokens > 0 else 0,
             text_tokens=completion_tokens - reasoning_tokens if reasoning_tokens > 0 else completion_tokens,
         )
         total_tokens = prompt_tokens + completion_tokens

litellm/responses/litellm_completion_transformation/transformation.py

@@ -1750,6 +1750,8 @@ def _transform_chat_completion_usage_to_responses_usage(
                 and prompt_details.cached_tokens is not None
             ):
                 input_details_dict["cached_tokens"] = prompt_details.cached_tokens
+            else:
+                input_details_dict["cached_tokens"] = 0
 
             if (
                 hasattr(prompt_details, "text_tokens")
@@ -1782,6 +1784,8 @@ def _transform_chat_completion_usage_to_responses_usage(
                 output_details_dict["reasoning_tokens"] = (
                     completion_details.reasoning_tokens
                 )
+            else:
+                output_details_dict["reasoning_tokens"] = 0
 
             if (
                 hasattr(completion_details, "text_tokens")

litellm/types/llms/openai.py

@@ -1114,7 +1114,7 @@ class ResponsesAPIRequestParams(ResponsesAPIOptionalRequestParams, total=False):
 
 
 class OutputTokensDetails(BaseLiteLLMOpenAIResponseObject):
-    reasoning_tokens: Optional[int] = None
+    reasoning_tokens: int = 0
 
     text_tokens: Optional[int] = None
 
@@ -1123,7 +1123,7 @@ class OutputTokensDetails(BaseLiteLLMOpenAIResponseObject):
 
 class InputTokensDetails(BaseLiteLLMOpenAIResponseObject):
     audio_tokens: Optional[int] = None
-    cached_tokens: Optional[int] = None
+    cached_tokens: int = 0
     text_tokens: Optional[int] = None
 
     model_config = {"extra": "allow"}
@@ -1193,7 +1193,7 @@ class ResponsesAPIResponse(BaseLiteLLMOpenAIResponseObject):
     status: Optional[str] = None
     text: Optional[Union["ResponseText", Dict[str, Any]]] = None
     truncation: Optional[Literal["auto", "disabled"]] = None
-    usage: Optional[Any] = None
+    usage: Optional[ResponseAPIUsage] = None
     user: Optional[str] = None
     store: Optional[bool] = None
     # Define private attributes using PrivateAttr

tests/test_litellm/llms/anthropic/chat/test_anthropic_chat_transformation.py

@@ -1842,7 +1842,7 @@ def test_calculate_usage_completion_tokens_details_always_populated():
 
     # completion_tokens_details should NOT be None
     assert usage.completion_tokens_details is not None
-    assert usage.completion_tokens_details.reasoning_tokens is None
+    assert usage.completion_tokens_details.reasoning_tokens is 0
     assert usage.completion_tokens_details.text_tokens == 248
     assert usage.completion_tokens == 248
     assert usage.prompt_tokens == 37