add OpenAIResponsesAPIConfig

litellm/llms/base_llm/responses/transformation.py

@@ -0,0 +1,97 @@
+import types
+from abc import ABC, abstractmethod
+from typing import TYPE_CHECKING, Any, Optional
+
+from litellm.types.utils import ModelInfo
+
+from ..chat.transformation import BaseLLMException
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+
+    LiteLLMLoggingObj = _LiteLLMLoggingObj
+else:
+    LiteLLMLoggingObj = Any
+
+
+class BaseResponsesAPIConfig(ABC):
+    def __init__(self):
+        pass
+
+    @classmethod
+    def get_config(cls):
+        return {
+            k: v
+            for k, v in cls.__dict__.items()
+            if not k.startswith("__")
+            and not k.startswith("_abc")
+            and not isinstance(
+                v,
+                (
+                    types.FunctionType,
+                    types.BuiltinFunctionType,
+                    classmethod,
+                    staticmethod,
+                ),
+            )
+            and v is not None
+        }
+
+    @abstractmethod
+    def get_supported_openai_params(self, model: str) -> list:
+        pass
+
+    @abstractmethod
+    def map_openai_params(
+        self,
+        non_default_params: dict,
+        optional_params: dict,
+        model: str,
+        drop_params: bool,
+    ) -> dict:
+        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],
+        model: str,
+        optional_params: dict,
+        stream: Optional[bool] = None,
+    ) -> str:
+        """
+        OPTIONAL
+
+        Get the complete url for the request
+
+        Some providers need `model` in `api_base`
+        """
+        if api_base is None:
+            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_response(
+        self,
+    ):
+        pass