fix(bedrock): split Converse 1h vs 5m cache writes by cacheDetails TTL

litellm/llms/bedrock/chat/converse_transformation.py

@@ -57,6 +57,7 @@
     OpenAIMessageContentListBlock,
 )
 from litellm.types.utils import (
+    CacheCreationTokenDetails,
     ChatCompletionMessageToolCall,
     CompletionTokensDetailsWrapper,
     Function,
@@ -1770,6 +1771,23 @@ def _transform_thinking_blocks(
                 thinking_blocks_list.append(_redacted_block)
         return thinking_blocks_list
 
+    @staticmethod
+    def _transform_cache_details(
+        cache_details: list[ConverseCacheDetailBlock] | None,
+    ) -> CacheCreationTokenDetails | None:
+        if not cache_details:
+            return None
+        ephemeral_5m_input_tokens: Final = sum(
+            detail["inputTokens"] for detail in cache_details if detail.get("ttl") == "5m"
+        )
+        ephemeral_1h_input_tokens: Final = sum(
+            detail["inputTokens"] for detail in cache_details if detail.get("ttl") == "1h"
+        )
+        return CacheCreationTokenDetails(
+            ephemeral_5m_input_tokens=ephemeral_5m_input_tokens,
+            ephemeral_1h_input_tokens=ephemeral_1h_input_tokens,
+        )
+
     def _transform_usage(
         self,
         usage: ConverseTokenUsageBlock,
@@ -1789,9 +1807,12 @@ def _transform_usage(
             cache_creation_input_tokens = usage["cacheWriteInputTokens"]
             input_tokens += cache_creation_input_tokens
 
+        cache_creation_token_details: Final = self._transform_cache_details(usage.get("cacheDetails"))
+
         prompt_tokens_details: Final = PromptTokensDetailsWrapper(
             cached_tokens=cache_read_input_tokens,
             cache_creation_tokens=cache_creation_input_tokens,
+            cache_creation_token_details=cache_creation_token_details,
             text_tokens=raw_input_tokens,
         )
         reasoning_tokens = token_counter(text=reasoning_content, count_response_tokens=True) if reasoning_content else 0

litellm/types/llms/bedrock.py

@@ -2,7 +2,7 @@
 from enum import Enum
 from typing import TYPE_CHECKING, Any, Final, Literal
 
-from typing_extensions import Required, TypedDict, override
+from typing_extensions import ReadOnly, Required, TypedDict, override
 
 from .openai import ChatCompletionToolCallChunk
 
@@ -216,6 +216,11 @@ class ConverseResponseOutputBlock(TypedDict):
     message: MessageBlock | None
 
 
+class ConverseCacheDetailBlock(TypedDict):
+    inputTokens: ReadOnly[int]
+    ttl: ReadOnly[Literal["5m", "1h"]]
+
+
 class ConverseTokenUsageBlock(TypedDict):
     inputTokens: int
     outputTokens: int
@@ -224,6 +229,7 @@ class ConverseTokenUsageBlock(TypedDict):
     cacheReadInputTokens: int
     cacheWriteInputTokenCount: int
     cacheWriteInputTokens: int
+    cacheDetails: ReadOnly[list[ConverseCacheDetailBlock]]
 
 
 class ServiceTierBlock(TypedDict):

tests/test_litellm/llms/bedrock/chat/test_converse_transformation.py

@@ -6003,3 +6003,41 @@ def test_adaptive_thinking_dropped_when_max_tokens_too_small_converse():
     )
 
     assert "thinking" not in optional_params
+
+
+def test_transform_usage_splits_cache_writes_by_ttl():
+    config = AmazonConverseConfig()
+    usage: ConverseTokenUsageBlock = {
+        "inputTokens": 100,
+        "outputTokens": 50,
+        "totalTokens": 150,
+        "cacheReadInputTokens": 0,
+        "cacheWriteInputTokens": 4000,
+        "cacheDetails": [
+            {"inputTokens": 3000, "ttl": "1h"},
+            {"inputTokens": 1000, "ttl": "5m"},
+        ],
+    }
+
+    result = config._transform_usage(usage)
+
+    details = result.prompt_tokens_details.cache_creation_token_details
+    assert details is not None
+    assert details.ephemeral_1h_input_tokens == 3000
+    assert details.ephemeral_5m_input_tokens == 1000
+    assert result.cache_creation_input_tokens == 4000
+
+
+def test_transform_usage_without_cache_details_leaves_ttl_split_unset():
+    config = AmazonConverseConfig()
+    usage: ConverseTokenUsageBlock = {
+        "inputTokens": 100,
+        "outputTokens": 50,
+        "totalTokens": 150,
+        "cacheWriteInputTokens": 4000,
+    }
+
+    result = config._transform_usage(usage)
+
+    assert getattr(result.prompt_tokens_details, "cache_creation_token_details", None) is None
+    assert result.cache_creation_input_tokens == 4000