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fix(anthropic): preserve prompt cache tokens in messages to responses api usage

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Also map gpt-5.6 flex/priority cache_creation rates into ModelInfo so cache writes are not billed at the standard rate on those service tiers
This commit is contained in:
Devin AI 2026-07-28 16:12:25 +00:00
parent daf22ec871
commit ed366aafbe
8 changed files with 147 additions and 38 deletions
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33
litellm/llms/anthropic/experimental_pass_through/responses_adapters/streaming_iterator.py
View file

@ -7,6 +7,9 @@ from typing import Any, AsyncIterator, Dict
from litellm import verbose_logger
from litellm._uuid import uuid
from litellm.types.llms.anthropic_messages.anthropic_response import AnthropicUsage
from .transformation import LiteLLMAnthropicToResponsesAPIAdapter
class AnthropicResponsesStreamWrapper:
@ -226,24 +229,17 @@ class AnthropicResponsesStreamWrapper:
event.get("response") if isinstance(event, dict) else None
)
stop_reason = "end_turn"
input_tokens = 0
output_tokens = 0
cache_creation_tokens = 0
cache_read_tokens = 0
anthropic_usage: AnthropicUsage = AnthropicUsage(input_tokens=0, output_tokens=0)
if response_obj is not None:
status = getattr(response_obj, "status", None)
if status == "incomplete":
stop_reason = "max_tokens"
usage = getattr(response_obj, "usage", None)
if usage is not None:
input_tokens = getattr(usage, "input_tokens", 0) or 0
output_tokens = getattr(usage, "output_tokens", 0) or 0
cache_creation_tokens = getattr(usage, "input_tokens_details", None) # type: ignore[assignment]
cache_read_tokens = getattr(usage, "output_tokens_details", None) # type: ignore[assignment]
# Prefer direct cache fields if present
cache_creation_tokens = int(getattr(usage, "cache_creation_input_tokens", 0) or 0)
cache_read_tokens = int(getattr(usage, "cache_read_input_tokens", 0) or 0)
anthropic_usage = (
LiteLLMAnthropicToResponsesAPIAdapter.translate_responses_api_usage_to_anthropic_usage(
getattr(response_obj, "usage", None)
)
)
# Check if tool_use was in the output to override stop_reason
if response_obj is not None:
@ -256,20 +252,11 @@ class AnthropicResponsesStreamWrapper:
stop_reason = "tool_use"
break
usage_delta: Dict[str, Any] = {
"input_tokens": input_tokens,
"output_tokens": output_tokens,
}
if cache_creation_tokens:
usage_delta["cache_creation_input_tokens"] = cache_creation_tokens
if cache_read_tokens:
usage_delta["cache_read_input_tokens"] = cache_read_tokens
self._chunk_queue.append(
{
"type": "message_delta",
"delta": {"stop_reason": stop_reason, "stop_sequence": None},
"usage": usage_delta,
"usage": dict(anthropic_usage),
}
)
self._chunk_queue.append({"type": "message_stop"})

32
litellm/llms/anthropic/experimental_pass_through/responses_adapters/transformation.py
View file

@ -29,7 +29,7 @@ from litellm.types.llms.anthropic_messages.anthropic_response import (
AnthropicMessagesResponse,
AnthropicUsage,
)
from litellm.types.llms.openai import ResponsesAPIResponse
from litellm.types.llms.openai import ResponseAPIUsage, ResponsesAPIResponse
class LiteLLMAnthropicToResponsesAPIAdapter:
@ -38,6 +38,24 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
converts Responses API responses back to Anthropic format.
"""
@staticmethod
def translate_responses_api_usage_to_anthropic_usage(
raw_usage: Optional[ResponseAPIUsage],
) -> AnthropicUsage:
"""Map Responses API usage onto Anthropic usage, where ``input_tokens``
excludes the cache-read and cache-write tokens reported alongside it.
"""
if raw_usage is None:
return AnthropicUsage(input_tokens=0, output_tokens=0)
from litellm.llms.anthropic.experimental_pass_through.adapters.transformation import (
LiteLLMAnthropicMessagesAdapter,
)
from litellm.responses.utils import ResponseAPILoggingUtils
chat_usage = ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage(raw_usage)
return LiteLLMAnthropicMessagesAdapter._translate_openai_usage_to_anthropic_usage(chat_usage)
# ------------------------------------------------------------------ #
# Request translation: Anthropic -> Responses API #
# ------------------------------------------------------------------ #
@ -396,8 +414,6 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
ResponseReasoningItem,
)
from litellm.types.llms.openai import ResponseAPIUsage
content: List[Dict[str, Any]] = []
stop_reason: AnthropicFinishReason = "end_turn"
@ -463,15 +479,7 @@ class LiteLLMAnthropicToResponsesAPIAdapter:
if response.status == "incomplete":
stop_reason = "max_tokens"
# usage
raw_usage: Optional[ResponseAPIUsage] = response.usage
input_tokens = int(getattr(raw_usage, "input_tokens", 0) or 0)
output_tokens = int(getattr(raw_usage, "output_tokens", 0) or 0)
anthropic_usage = AnthropicUsage(
input_tokens=input_tokens,
output_tokens=output_tokens,
)
anthropic_usage = self.translate_responses_api_usage_to_anthropic_usage(response.usage)
return AnthropicMessagesResponse(
id=response.id,

4
litellm/types/utils.py
View file

@ -198,6 +198,8 @@ class ModelInfoBase(ProviderSpecificModelInfo, total=False):
input_cost_per_token_flex: Optional[float] # OpenAI flex service tier pricing
input_cost_per_token_priority: Optional[float] # OpenAI priority service tier pricing
cache_creation_input_token_cost: Optional[float]
cache_creation_input_token_cost_flex: Optional[float] # OpenAI flex service tier pricing
cache_creation_input_token_cost_priority: Optional[float] # OpenAI priority service tier pricing
cache_creation_input_token_cost_above_200k_tokens: Optional[float]
cache_creation_input_token_cost_above_1hr: Optional[float]
cache_read_input_token_cost: Optional[float]
@ -3087,6 +3089,8 @@ class CustomPricingLiteLLMParams(BaseModel):
input_cost_per_token_flex: Optional[float] = None
input_cost_per_token_priority: Optional[float] = None
cache_creation_input_token_cost: Optional[float] = None
cache_creation_input_token_cost_flex: Optional[float] = None
cache_creation_input_token_cost_priority: Optional[float] = None
cache_creation_input_token_cost_above_1hr: Optional[float] = None
cache_creation_input_token_cost_above_200k_tokens: Optional[float] = None
cache_creation_input_audio_token_cost: Optional[float] = None

4
litellm/utils.py
View file

@ -5407,6 +5407,10 @@ def _get_model_info_helper(
input_cost_per_token_flex=_model_info.get("input_cost_per_token_flex", None),
input_cost_per_token_priority=_model_info.get("input_cost_per_token_priority", None),
cache_creation_input_token_cost=_model_info.get("cache_creation_input_token_cost", None),
cache_creation_input_token_cost_flex=_model_info.get("cache_creation_input_token_cost_flex", None),
cache_creation_input_token_cost_priority=_model_info.get(
"cache_creation_input_token_cost_priority", None
),
cache_creation_input_token_cost_above_200k_tokens=_model_info.get(
"cache_creation_input_token_cost_above_200k_tokens", None
),

41
tests/test_litellm/litellm_core_utils/llm_cost_calc/test_llm_cost_calc_utils.py
View file

@ -2399,3 +2399,44 @@ def test_generic_cost_per_token_gemini_35_flash_lite():
)
assert prompt_cost == pytest.approx(0.0003)
assert completion_cost == pytest.approx(0.00125)
@pytest.mark.parametrize(
"service_tier,input_rate,cache_read_rate,cache_write_rate,output_rate",
[
("flex", 2.5e-6, 2.5e-7, 3.125e-6, 1.5e-5),
("priority", 1e-5, 1e-6, 1.25e-5, 6e-5),
],
)
def test_service_tier_cache_creation_rates_for_gpt_5_6(
_local_model_cost_map,
service_tier,
input_rate,
cache_read_rate,
cache_write_rate,
output_rate,
):
"""Regression: gpt-5.6 publishes cache_creation_input_token_cost_flex/_priority, so a
flex or priority request must bill cache writes at that tier's rate instead of falling
back to the standard 6.25e-6 rate."""
usage = Usage(
prompt_tokens=10_000,
completion_tokens=500,
total_tokens=10_500,
prompt_tokens_details=PromptTokensDetailsWrapper(
cached_tokens=6_000,
cache_write_tokens=3_000,
text_tokens=1_000,
),
)
prompt_cost, completion_cost = generic_cost_per_token(
model="gpt-5.6-sol",
usage=usage,
custom_llm_provider="openai",
service_tier=service_tier,
)
expected_prompt = 1_000 * input_rate + 6_000 * cache_read_rate + 3_000 * cache_write_rate
assert prompt_cost == pytest.approx(expected_prompt, rel=1e-9)
assert completion_cost == pytest.approx(500 * output_rate, rel=1e-9)

29
tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_streaming_iterator.py
View file

@ -6,6 +6,7 @@ Tests for AnthropicResponsesStreamWrapper
import asyncio
import os
import sys
from types import SimpleNamespace
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "../../../../../..")))
@ -130,3 +131,31 @@ class TestProcessEventTextDeltaWithoutOutputItemAdded:
("content_block_start", 0),
("content_block_delta", 0),
]
class TestResponseCompletedUsage:
"""The Anthropic ``message_delta`` usage must report cache reads/writes and
exclude them from ``input_tokens``, so spend is not billed at the uncached
input rate."""
def test_response_completed_usage_carries_cache_tokens(self):
from litellm.types.llms.openai import ResponseAPIUsage
response = SimpleNamespace(
status="completed",
output=[],
usage=ResponseAPIUsage(
input_tokens=4017,
input_tokens_details={"cached_tokens": 4004, "cache_write_tokens": 10},
output_tokens=5,
total_tokens=4022,
),
)
chunks = _process_all([{"type": "response.completed", "response": response}])
message_delta = next(c for c in chunks if c["type"] == "message_delta")
assert message_delta["usage"] == {
"input_tokens": 3,
"output_tokens": 5,
"cache_creation_input_tokens": 10,
"cache_read_input_tokens": 4004,
}

34
tests/test_litellm/llms/anthropic/experimental_pass_through/responses_adapters/test_responses_adapters_transformation.py
View file

@ -20,6 +20,7 @@ from litellm.llms.anthropic.experimental_pass_through.responses_adapters.transfo
LiteLLMAnthropicToResponsesAPIAdapter,
)
from litellm.types.llms.anthropic import AnthropicMessagesRequest
from litellm.types.llms.openai import ResponseAPIUsage
def _make_request(**overrides) -> AnthropicMessagesRequest:
@ -823,11 +824,19 @@ def _make_mock_response(
model: str = "gpt-4o",
input_tokens: int = 100,
output_tokens: int = 50,
cached_tokens: int = 0,
cache_write_tokens: int = 0,
) -> MagicMock:
"""Build a minimal mock ResponsesAPIResponse."""
usage = MagicMock()
usage.input_tokens = input_tokens
usage.output_tokens = output_tokens
usage = ResponseAPIUsage(
input_tokens=input_tokens,
input_tokens_details={
"cached_tokens": cached_tokens,
"cache_write_tokens": cache_write_tokens,
},
output_tokens=output_tokens,
total_tokens=input_tokens + output_tokens,
)
resp = MagicMock()
resp.id = response_id
@ -961,6 +970,25 @@ class TestTranslateResponse:
assert result["usage"]["input_tokens"] == 200
assert result["usage"]["output_tokens"] == 75
def test_cache_tokens_mapped_to_anthropic_usage(self):
"""Cache reads/writes reported by the Responses API must survive the
Anthropic mapping, and input_tokens must exclude them so spend is not
billed at the uncached input rate."""
response = _make_mock_response(
output=[_make_output_message(["OK"])],
input_tokens=4017,
output_tokens=5,
cached_tokens=4004,
cache_write_tokens=10,
)
result: Any = _ADAPTER.translate_response(response)
assert result["usage"] == {
"input_tokens": 3,
"output_tokens": 5,
"cache_creation_input_tokens": 10,
"cache_read_input_tokens": 4004,
}
def test_model_and_id_preserved(self):
"""Model and response ID from the Responses API are forwarded."""
response = _make_mock_response(

8
ui/litellm-dashboard/src/lib/http/schema.d.ts generated vendored
View file

@ -25822,6 +25822,10 @@ export interface components {
cache_creation_input_token_cost_above_1hr?: number | null;
/** Cache Creation Input Token Cost Above 200K Tokens */
cache_creation_input_token_cost_above_200k_tokens?: number | null;
/** Cache Creation Input Token Cost Flex */
cache_creation_input_token_cost_flex?: number | null;
/** Cache Creation Input Token Cost Priority */
cache_creation_input_token_cost_priority?: number | null;
/** Cache Read Input Audio Token Cost */
cache_read_input_audio_token_cost?: number | null;
/** Cache Read Input Token Cost */
@ -33912,6 +33916,10 @@ export interface components {
cache_creation_input_token_cost_above_1hr?: number | null;
/** Cache Creation Input Token Cost Above 200K Tokens */
cache_creation_input_token_cost_above_200k_tokens?: number | null;
/** Cache Creation Input Token Cost Flex */
cache_creation_input_token_cost_flex?: number | null;
/** Cache Creation Input Token Cost Priority */
cache_creation_input_token_cost_priority?: number | null;
/** Cache Read Input Audio Token Cost */
cache_read_input_audio_token_cost?: number | null;
/** Cache Read Input Token Cost */