basic handler for LiteLLMCompletionTransformationHandler

litellm/responses/litellm_completion_transformation/handler.py

@@ -0,0 +1,91 @@
+"""
+Handler for transforming responses api requests to litellm.completion requests
+"""
+
+from typing import Any, Coroutine, Optional, Union
+
+import litellm
+from litellm.responses.litellm_completion_transformation.transformation import (
+    LiteLLMCompletionResponsesConfig,
+)
+from litellm.responses.streaming_iterator import BaseResponsesAPIStreamingIterator
+from litellm.types.llms.openai import (
+    ResponseInputParam,
+    ResponsesAPIOptionalRequestParams,
+    ResponsesAPIResponse,
+)
+from litellm.types.utils import ModelResponse
+
+
+class LiteLLMCompletionTransformationHandler:
+
+    def response_api_handler(
+        self,
+        model: str,
+        input: Union[str, ResponseInputParam],
+        responses_api_request: ResponsesAPIOptionalRequestParams,
+        custom_llm_provider: Optional[str] = None,
+        _is_async: bool = False,
+        **kwargs,
+    ) -> Union[
+        ResponsesAPIResponse,
+        BaseResponsesAPIStreamingIterator,
+        Coroutine[
+            Any, Any, Union[ResponsesAPIResponse, BaseResponsesAPIStreamingIterator]
+        ],
+    ]:
+        litellm_completion_request: dict = (
+            LiteLLMCompletionResponsesConfig.transform_responses_api_request_to_chat_completion_request(
+                model=model,
+                input=input,
+                responses_api_request=responses_api_request,
+                custom_llm_provider=custom_llm_provider,
+            )
+        )
+
+        if _is_async:
+            return self.async_response_api_handler(
+                litellm_completion_request=litellm_completion_request,
+                **kwargs,
+            )
+
+        litellm_completion_response: Union[
+            ModelResponse, litellm.CustomStreamWrapper
+        ] = litellm.completion(
+            **litellm_completion_request,
+            **kwargs,
+        )
+
+        if isinstance(litellm_completion_response, ModelResponse):
+            responses_api_response: ResponsesAPIResponse = (
+                LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
+                    chat_completion_response=litellm_completion_response,
+                )
+            )
+
+            return responses_api_response
+
+        raise ValueError("litellm_completion_response is not a ModelResponse")
+
+    async def async_response_api_handler(
+        self,
+        litellm_completion_request: dict,
+        **kwargs,
+    ) -> Union[ResponsesAPIResponse, BaseResponsesAPIStreamingIterator]:
+        litellm_completion_response: Union[
+            ModelResponse, litellm.CustomStreamWrapper
+        ] = await litellm.acompletion(
+            **litellm_completion_request,
+            **kwargs,
+        )
+
+        if isinstance(litellm_completion_response, ModelResponse):
+            responses_api_response: ResponsesAPIResponse = (
+                LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response(
+                    chat_completion_response=litellm_completion_response,
+                )
+            )
+
+            return responses_api_response
+
+        raise ValueError("litellm_completion_response is not a ModelResponse")

litellm/responses/litellm_completion_transformation/transformation.py

@@ -2,25 +2,8 @@
 Handles transforming from Responses API -> LiteLLM completion  (Chat Completion API)
 """
 
-import asyncio
-import contextvars
-from functools import partial
-from typing import Any, Coroutine, Dict, Iterable, List, Literal, Optional, Union
+from typing import Any, Dict, List, Optional, Union
 
-import httpx
-from openai.types.chat.completion_create_params import CompletionCreateParamsBase
-
-import litellm
-from litellm.constants import request_timeout
-from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
-from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig
-from litellm.llms.custom_httpx.llm_http_handler import BaseLLMHTTPHandler
-from litellm.responses.streaming_iterator import (
-    BaseResponsesAPIStreamingIterator,
-    ResponsesAPIStreamingIterator,
-    SyncResponsesAPIStreamingIterator,
-)
-from litellm.responses.utils import ResponsesAPIRequestUtils
 from litellm.types.llms.openai import (
     AllMessageValues,
     ChatCompletionSystemMessage,
@@ -30,8 +13,7 @@ from litellm.types.llms.openai import (
     ResponsesAPIOptionalRequestParams,
     ResponsesAPIResponse,
 )
-from litellm.types.router import GenericLiteLLMParams
-from litellm.utils import ProviderConfigManager, client
+from litellm.types.utils import ModelResponse
 
 
 class LiteLLMCompletionResponsesConfig:
@@ -149,9 +131,40 @@ class LiteLLMCompletionResponsesConfig:
 
     @staticmethod
     def transform_chat_completion_response_to_responses_api_response(
-        chat_completion_response: dict,
-    ) -> dict:
+        chat_completion_response: ModelResponse,
+    ) -> ResponsesAPIResponse:
         """
         Transform a Chat Completion response into a Responses API response
         """
-        return {}
+        return ResponsesAPIResponse(
+            id=chat_completion_response.id,
+            created_at=chat_completion_response.created,
+            model=chat_completion_response.model,
+            object=chat_completion_response.object,
+            error=getattr(chat_completion_response, "error", None),
+            incomplete_details=getattr(
+                chat_completion_response, "incomplete_details", None
+            ),
+            instructions=getattr(chat_completion_response, "instructions", None),
+            metadata=getattr(chat_completion_response, "metadata", None),
+            output=getattr(chat_completion_response, "output", []),
+            parallel_tool_calls=getattr(
+                chat_completion_response, "parallel_tool_calls", False
+            ),
+            temperature=getattr(chat_completion_response, "temperature", None),
+            tool_choice=getattr(chat_completion_response, "tool_choice", "auto"),
+            tools=getattr(chat_completion_response, "tools", []),
+            top_p=getattr(chat_completion_response, "top_p", None),
+            max_output_tokens=getattr(
+                chat_completion_response, "max_output_tokens", None
+            ),
+            previous_response_id=getattr(
+                chat_completion_response, "previous_response_id", None
+            ),
+            reasoning=getattr(chat_completion_response, "reasoning", None),
+            status=getattr(chat_completion_response, "status", None),
+            text=getattr(chat_completion_response, "text", None),
+            truncation=getattr(chat_completion_response, "truncation", None),
+            usage=getattr(chat_completion_response, "usage", None),
+            user=getattr(chat_completion_response, "user", None),
+        )