add BaseResponsesAPIConfig

litellm/llms/base_llm/responses/transformation.py

@@ -52,17 +52,6 @@ class BaseResponsesAPIConfig(ABC):
 
         pass
 
-    @abstractmethod
-    def validate_environment(
-        self,
-        headers: dict,
-        model: str,
-        optional_params: dict,
-        api_key: Optional[str] = None,
-        api_base: Optional[str] = None,
-    ) -> dict:
-        pass
-
     def get_complete_url(
         self,
         api_base: Optional[str],
@@ -81,18 +70,18 @@ class BaseResponsesAPIConfig(ABC):
             raise ValueError("api_base is required")
         return api_base
 
-    @abstractmethod
-    def transform_request(
-        self,
-        model: str,
-        optional_params: dict,
-        litellm_params: dict,
-        headers: dict,
-    ) -> dict:
-        pass
+    # @abstractmethod
+    # def transform_request(
+    #     self,
+    #     model: str,
+    #     optional_params: dict,
+    #     litellm_params: dict,
+    #     headers: dict,
+    # ) -> dict:
+    #     pass
 
-    @abstractmethod
-    def transform_response(
-        self,
-    ):
-        pass
+    # @abstractmethod
+    # def transform_response(
+    #     self,
+    # ):
+    #     pass

litellm/utils.py

@@ -209,6 +209,7 @@ from litellm.llms.base_llm.image_variations.transformation import (
     BaseImageVariationConfig,
 )
 from litellm.llms.base_llm.rerank.transformation import BaseRerankConfig
+from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig
 
 from ._logging import _is_debugging_on, verbose_logger
 from .caching.caching import (
@@ -5103,7 +5104,7 @@ def prompt_token_calculator(model, messages):
         from anthropic import AI_PROMPT, HUMAN_PROMPT, Anthropic
 
         anthropic_obj = Anthropic()
-        num_tokens = anthropic_obj.count_tokens(text)
+        num_tokens = anthropic_obj.count_tokens(text)  # type: ignore
     else:
         num_tokens = len(encoding.encode(text))
     return num_tokens
@@ -6275,6 +6276,15 @@ class ProviderConfigManager:
             return litellm.DeepgramAudioTranscriptionConfig()
         return None
 
+    @staticmethod
+    def get_provider_responses_api_config(
+        model: str,
+        provider: LlmProviders,
+    ) -> Optional[BaseResponsesAPIConfig]:
+        if litellm.LlmProviders.OPENAI == provider:
+            return litellm.OpenAIResponsesAPIConfig()
+        return None
+
     @staticmethod
     def get_provider_text_completion_config(
         model: str,