chore: initial public snapshot for github upload

llm-gateway-competitors/litellm-wheel-src/litellm/llms/base_llm/bridges/completion_transformation.py

@@ -0,0 +1,55 @@
+"""
+Bridge for transforming API requests to another API requests
+"""
+
+from abc import ABC, abstractmethod
+from typing import TYPE_CHECKING, Any, AsyncIterator, Iterator, List, Optional, Union
+
+if TYPE_CHECKING:
+    from pydantic import BaseModel
+
+    from litellm import LiteLLMLoggingObj, ModelResponse
+    from litellm.llms.base_llm.base_model_iterator import BaseModelResponseIterator
+    from litellm.types.llms.openai import AllMessageValues
+
+
+class CompletionTransformationBridge(ABC):
+    @abstractmethod
+    def transform_request(
+        self,
+        model: str,
+        messages: List["AllMessageValues"],
+        optional_params: dict,
+        litellm_params: dict,
+        headers: dict,
+        litellm_logging_obj: "LiteLLMLoggingObj",
+    ) -> dict:
+        """Transform /chat/completions api request to another request"""
+        pass
+
+    @abstractmethod
+    def transform_response(
+        self,
+        model: str,
+        raw_response: "BaseModel",  # the response from the other API
+        model_response: "ModelResponse",
+        logging_obj: "LiteLLMLoggingObj",
+        request_data: dict,
+        messages: List["AllMessageValues"],
+        optional_params: dict,
+        litellm_params: dict,
+        encoding: Any,
+        api_key: Optional[str] = None,
+        json_mode: Optional[bool] = None,
+    ) -> "ModelResponse":
+        """Transform another response to /chat/completions api response"""
+        pass
+
+    @abstractmethod
+    def get_model_response_iterator(
+        self,
+        streaming_response: Union[Iterator[str], AsyncIterator[str], "ModelResponse"],
+        sync_stream: bool,
+        json_mode: Optional[bool] = False,
+    ) -> "BaseModelResponseIterator":
+        pass