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Fix usage returned for cache_creation_tokens

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This commit is contained in:
Will Koh 2026-04-30 19:29:17 -07:00
parent bcedf79b0f
commit 3c23038df5
2 changed files with 91 additions and 1 deletions
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12
litellm/responses/litellm_completion_transformation/transformation.py
View file

@ -2101,7 +2101,7 @@ class LiteLLMCompletionResponsesConfig:
and usage.prompt_tokens_details is not None
):
prompt_details = usage.prompt_tokens_details
input_details_dict: Dict[str, int] = {}
input_details_dict: Dict[str, Any] = {}
if (
hasattr(prompt_details, "cached_tokens")
@ -2123,6 +2123,16 @@ class LiteLLMCompletionResponsesConfig:
):
input_details_dict["audio_tokens"] = prompt_details.audio_tokens
# Forward Anthropic prompt-caching fields so callers see cache
# creation token counts on the Responses API usage payload.
for cache_field in (
"cache_creation_tokens",
"cache_creation_token_details",
):
value = getattr(prompt_details, cache_field, None)
if value is not None:
input_details_dict[cache_field] = value
if input_details_dict:
response_usage.input_tokens_details = InputTokensDetails(
**input_details_dict

80
tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py
View file

@ -1565,6 +1565,86 @@ class TestUsageTransformation:
assert response_usage.input_tokens_details.cached_tokens == 3
assert response_usage.input_tokens_details.text_tokens == 6
def test_transform_usage_with_cache_creation_tokens_anthropic(self):
"""Test that Anthropic cache creation token fields are propagated onto input_tokens_details"""
usage = Usage(
prompt_tokens=20,
completion_tokens=10,
total_tokens=30,
prompt_tokens_details=PromptTokensDetailsWrapper(
cached_tokens=4, # cache_read_input_tokens
cache_creation_tokens=12, # cache_creation_input_tokens
text_tokens=4,
),
)
chat_completion_response = ModelResponse(
id="test-response-id",
created=1234567890,
model="claude-sonnet-4",
object="chat.completion",
usage=usage,
choices=[
Choices(
finish_reason="stop",
index=0,
message=Message(content="Hi!", role="assistant"),
)
],
)
response_usage = LiteLLMCompletionResponsesConfig._transform_chat_completion_usage_to_responses_usage(
chat_completion_response=chat_completion_response
)
assert response_usage.input_tokens_details is not None
assert response_usage.input_tokens_details.cached_tokens == 4
assert (
getattr(
response_usage.input_tokens_details, "cache_creation_tokens", None
)
== 12
)
def test_transform_usage_without_cache_creation_tokens(self):
"""Test that cache_creation_tokens is absent when not present on prompt_tokens_details"""
usage = Usage(
prompt_tokens=10,
completion_tokens=5,
total_tokens=15,
prompt_tokens_details=PromptTokensDetailsWrapper(
cached_tokens=0,
text_tokens=10,
),
)
chat_completion_response = ModelResponse(
id="test-response-id",
created=1234567890,
model="gpt-4",
object="chat.completion",
usage=usage,
choices=[
Choices(
finish_reason="stop",
index=0,
message=Message(content="Hi!", role="assistant"),
)
],
)
response_usage = LiteLLMCompletionResponsesConfig._transform_chat_completion_usage_to_responses_usage(
chat_completion_response=chat_completion_response
)
assert response_usage.input_tokens_details is not None
assert (
getattr(
response_usage.input_tokens_details, "cache_creation_tokens", None
)
is None
)
def test_transform_usage_with_reasoning_tokens_gemini(self):
"""Test that reasoning_tokens from Gemini are properly transformed to output_tokens_details"""
# Setup: Simulate Gemini usage with thoughtsTokenCount