fix(cost_tracking): map cache_write_tokens on Responses API usage path

The Responses API (/v1/responses) usage transform rebuilt prompt token
details and dropped OpenAI's input_tokens_details.cache_write_tokens, so
gpt-5.6 cache-creation tokens were never logged or billed via that route.
Map it in the transform, and make PromptTokensDetailsWrapper keep
cache_write_tokens and cache_creation_tokens in sync on assignment.

Co-Authored-By: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>

litellm/responses/utils.py

@@ -1049,6 +1049,7 @@ class ResponseAPILoggingUtils:
                     audio_tokens=getattr(response_api_usage.input_tokens_details, "audio_tokens", None),
                     text_tokens=getattr(response_api_usage.input_tokens_details, "text_tokens", None),
                     image_tokens=getattr(response_api_usage.input_tokens_details, "image_tokens", None),
+                    cache_write_tokens=getattr(response_api_usage.input_tokens_details, "cache_write_tokens", None),
                 )
         completion_tokens_details: Optional[CompletionTokensDetailsWrapper] = None
         output_tokens_details = getattr(response_api_usage, "output_tokens_details", None)

litellm/types/utils.py

@@ -1538,18 +1538,23 @@ class PromptTokensDetailsWrapper(
     """Number of cache write (creation) tokens sent to the model. OpenAI naming (prompt_tokens_details.cache_write_tokens); this is the canonical field."""
 
     cache_creation_tokens: Optional[int] = None
-    """Number of cache creation tokens sent to the model. Anthropic/Bedrock naming; kept in sync with cache_write_tokens for backwards compatibility."""
+    """Number of cache creation tokens sent to the model. Anthropic/Bedrock naming; kept in sync with cache_write_tokens (assigning either mirrors to the other)."""
 
     cache_creation_token_details: Optional[CacheCreationTokenDetails] = None
     """Details of cache creation tokens sent to the model. Used for tracking 5m/1h cache creation tokens for Anthropic prompt caching."""
 
+    def __setattr__(self, name: str, value: object) -> None:
+        super().__setattr__(name, value)
+        if name == "cache_write_tokens":
+            super().__setattr__("cache_creation_tokens", value)
+        elif name == "cache_creation_tokens":
+            super().__setattr__("cache_write_tokens", value)
+
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
-        cache_write_tokens = (
+        self.cache_write_tokens = (
             self.cache_write_tokens if self.cache_write_tokens is not None else self.cache_creation_tokens
         )
-        self.cache_write_tokens = cache_write_tokens
-        self.cache_creation_tokens = cache_write_tokens
         if self.character_count is None:
             del self.character_count
         if self.image_count is None:
@@ -1676,7 +1681,6 @@ class Usage(SafeAttributeModel, CompletionUsage):
                 )
             else:
                 _prompt_tokens_details.cache_write_tokens = params["cache_creation_input_tokens"]
-                _prompt_tokens_details.cache_creation_tokens = params["cache_creation_input_tokens"]
 
         super().__init__(
             prompt_tokens=prompt_tokens or 0,

tests/test_litellm/responses/test_responses_utils.py

@@ -369,6 +369,32 @@ class TestResponseAPILoggingUtils:
         assert result.completion_tokens_details.image_tokens == 272
         assert result.completion_tokens_details.text_tokens == 100
 
+    def test_transform_response_api_usage_maps_cache_write_tokens(self):
+        """Responses API (/v1/responses) cache-write tokens must survive the usage transform.
+
+        gpt-5.6 returns usage.input_tokens_details.cache_write_tokens (an extra field
+        not typed on InputTokensDetails). Before the fix the transform rebuilt the token
+        details and dropped it, leaving the cache-creation metric empty (LIT-4633).
+        """
+        usage = {
+            "input_tokens": 10062,
+            "output_tokens": 16,
+            "total_tokens": 10078,
+            "input_tokens_details": {
+                "cached_tokens": 0,
+                "cache_write_tokens": 10059,
+            },
+        }
+
+        result = ResponseAPILoggingUtils._transform_response_api_usage_to_chat_usage(
+            usage
+        )
+
+        assert result.prompt_tokens_details is not None
+        assert result.prompt_tokens_details.cache_write_tokens == 10059
+        assert result.prompt_tokens_details.cache_creation_tokens == 10059
+        assert result.prompt_tokens_details.cached_tokens == 0
+
     def test_transform_response_api_usage_mixed_details(self):
         """Test transformation handles mixed token details (cached + image + audio)."""
         # Setup - hypothetical usage with mixed token types

tests/test_litellm/test_utils.py

@@ -74,6 +74,19 @@ def test_prompt_tokens_details_no_cache_write_tokens_when_absent():
     assert not hasattr(details, "cache_creation_tokens")
 
 
+def test_prompt_tokens_details_cache_write_creation_stay_in_sync_on_assignment():
+    """Assigning either name after construction must mirror to the other, so a
+    caller that sets only one field can't leave the pair silently out of sync."""
+    details = PromptTokensDetailsWrapper(cache_write_tokens=100)
+    assert details.cache_write_tokens == details.cache_creation_tokens == 100
+
+    details.cache_write_tokens = 250
+    assert details.cache_write_tokens == details.cache_creation_tokens == 250
+
+    details.cache_creation_tokens = 375
+    assert details.cache_write_tokens == details.cache_creation_tokens == 375
+
+
 @pytest.fixture
 def local_model_cost_map(monkeypatch):
     original_model_cost = litellm.model_cost