Openrouter - filter out cache_control flag for non-anthropic models (allows usage with claude code) (#12850)

* fix(gpt_transformation.py): remove 'cache_control' flag for openai/openai-compatible calls

Fixes https://github.com/BerriAI/litellm/issues/12787

* fix(openrouter/chat/transformation.py): allow passing openrouter cache control flag for claude models

* fix(gpt_transformation.py): fix import

* fix: fix adding tools

litellm/llms/openai/chat/gpt_transformation.py

@@ -1,5 +1,5 @@
 """
-Support for gpt model family 
+Support for gpt model family
 """
 
 from typing import (
@@ -11,6 +11,7 @@ from typing import (
     List,
     Literal,
     Optional,
+    Tuple,
     Union,
     cast,
     overload,
@@ -56,6 +57,7 @@ from ..common_utils import OpenAIError
 
 if TYPE_CHECKING:
     from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+    from litellm.types.llms.openai import ChatCompletionToolParam
 
     LiteLLMLoggingObj = _LiteLLMLoggingObj
 else:
@@ -318,10 +320,12 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
             content_item = content_item_typed
         return content_item
 
+    # fmt: off
+
     @overload
     def _transform_messages(
         self, messages: List[AllMessageValues], model: str, is_async: Literal[True]
-    ) -> Coroutine[Any, Any, List[AllMessageValues]]:
+    ) -> Coroutine[Any, Any, List[AllMessageValues]]: 
         ...
 
     @overload
@@ -333,6 +337,8 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
     ) -> List[AllMessageValues]:
         ...
 
+    # fmt: on
+
     def _transform_messages(
         self, messages: List[AllMessageValues], model: str, is_async: bool = False
     ) -> Union[List[AllMessageValues], Coroutine[Any, Any, List[AllMessageValues]]]:
@@ -351,10 +357,10 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
                         List[OpenAIMessageContentListBlock], message_content
                     )
                     for i, content_item in enumerate(message_content_types):
-                        message_content_types[
-                            i
-                        ] = await self._async_transform_content_item(
-                            cast(OpenAIMessageContentListBlock, content_item),
+                        message_content_types[i] = (
+                            await self._async_transform_content_item(
+                                cast(OpenAIMessageContentListBlock, content_item),
+                            )
                         )
             return messages
 
@@ -378,6 +384,29 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
                         )
             return messages
 
+    def remove_cache_control_flag_from_messages_and_tools(
+        self,
+        model: str,  # allows overrides to selectively run this
+        messages: List[AllMessageValues],
+        tools: Optional[List["ChatCompletionToolParam"]] = None,
+    ) -> Tuple[List[AllMessageValues], Optional[List["ChatCompletionToolParam"]]]:
+        from litellm.litellm_core_utils.prompt_templates.common_utils import (
+            filter_value_from_dict,
+        )
+        from litellm.types.llms.openai import ChatCompletionToolParam
+
+        for message in messages:
+            message = cast(
+                AllMessageValues, filter_value_from_dict(message, "cache_control")  # type: ignore
+            )
+        if tools is not None:
+            for tool in tools:
+                tool = cast(
+                    ChatCompletionToolParam,
+                    filter_value_from_dict(tool, "cache_control"),  # type: ignore
+                )
+        return messages, tools
+
     def transform_request(
         self,
         model: str,
@@ -393,6 +422,12 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
             dict: The transformed request. Sent as the body of the API call.
         """
         messages = self._transform_messages(messages=messages, model=model)
+        messages, tools = self.remove_cache_control_flag_from_messages_and_tools(
+            model=model, messages=messages, tools=optional_params.get("tools", [])
+        )
+        if tools is not None and len(tools) > 0:
+            optional_params["tools"] = tools
+
         return {
             "model": model,
             "messages": messages,
@@ -410,7 +445,15 @@ class OpenAIGPTConfig(BaseLLMModelInfo, BaseConfig):
         transformed_messages = await self._transform_messages(
             messages=messages, model=model, is_async=True
         )
-
+        transformed_messages, tools = (
+            self.remove_cache_control_flag_from_messages_and_tools(
+                model=model,
+                messages=transformed_messages,
+                tools=optional_params.get("tools", []),
+            )
+        )
+        if tools is not None and len(tools) > 0:
+            optional_params["tools"] = tools
         if self.__class__._is_base_class:
             return {
                 "model": model,

litellm/llms/openrouter/chat/transformation.py

@@ -6,13 +6,13 @@ Calls done in OpenAI/openai.py as OpenRouter is openai-compatible.
 Docs: https://openrouter.ai/docs/parameters
 """
 
-from typing import Any, AsyncIterator, Iterator, List, Optional, Union
+from typing import Any, AsyncIterator, Iterator, List, Optional, Tuple, Union
 
 import httpx
 
 from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator
 from litellm.llms.base_llm.chat.transformation import BaseLLMException
-from litellm.types.llms.openai import AllMessageValues
+from litellm.types.llms.openai import AllMessageValues, ChatCompletionToolParam
 from litellm.types.llms.openrouter import OpenRouterErrorMessage
 from litellm.types.utils import ModelResponse, ModelResponseStream
 
@@ -43,11 +43,24 @@ class OpenrouterConfig(OpenAIGPTConfig):
             extra_body["models"] = models
         if route is not None:
             extra_body["route"] = route
-        mapped_openai_params[
-            "extra_body"
-        ] = extra_body  # openai client supports `extra_body` param
+        mapped_openai_params["extra_body"] = (
+            extra_body  # openai client supports `extra_body` param
+        )
         return mapped_openai_params
 
+    def remove_cache_control_flag_from_messages_and_tools(
+        self,
+        model: str,
+        messages: List[AllMessageValues],
+        tools: Optional[List["ChatCompletionToolParam"]] = None,
+    ) -> Tuple[List[AllMessageValues], Optional[List["ChatCompletionToolParam"]]]:
+        if "claude" in model.lower():  # don't remove 'cache_control' flag
+            return messages, tools
+        else:
+            return super().remove_cache_control_flag_from_messages_and_tools(
+                model, messages, tools
+            )
+
     def transform_request(
         self,
         model: str,

tests/test_litellm/llms/openrouter/chat/test_openrouter_chat_transformation.py

@@ -97,3 +97,20 @@ def test_openrouter_extra_body_transformation():
     assert transformed_request["messages"] == [
         {"role": "user", "content": "Hello, world!"}
     ]
+
+
+def test_openrouter_cache_control_flag_removal():
+    transformed_request = OpenrouterConfig().transform_request(
+        model="openrouter/deepseek/deepseek-chat",
+        messages=[
+            {
+                "role": "user",
+                "content": "Hello, world!",
+                "cache_control": {"type": "ephemeral"},
+            }
+        ],
+        optional_params={},
+        litellm_params={},
+        headers={},
+    )
+    assert transformed_request["messages"][0].get("cache_control") is None