two version of R2R are hereHEADmaster

1 files changed, 216 insertions, 0 deletions

diff --git a/.venv/lib/python3.12/site-packages/litellm/llms/openai/responses/transformation.py b/.venv/lib/python3.12/site-packages/litellm/llms/openai/responses/transformation.py
new file mode 100644
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+++ b/.venv/lib/python3.12/site-packages/litellm/llms/openai/responses/transformation.py
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+from typing import TYPE_CHECKING, Any, Dict, Optional, Union, cast
+
+import httpx
+
+import litellm
+from litellm._logging import verbose_logger
+from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig
+from litellm.secret_managers.main import get_secret_str
+from litellm.types.llms.openai import *
+from litellm.types.router import GenericLiteLLMParams
+
+from ..common_utils import OpenAIError
+
+if TYPE_CHECKING:
+    from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
+
+    LiteLLMLoggingObj = _LiteLLMLoggingObj
+else:
+    LiteLLMLoggingObj = Any
+
+
+class OpenAIResponsesAPIConfig(BaseResponsesAPIConfig):
+    def get_supported_openai_params(self, model: str) -> list:
+        """
+        All OpenAI Responses API params are supported
+        """
+        return [
+            "input",
+            "model",
+            "include",
+            "instructions",
+            "max_output_tokens",
+            "metadata",
+            "parallel_tool_calls",
+            "previous_response_id",
+            "reasoning",
+            "store",
+            "stream",
+            "temperature",
+            "text",
+            "tool_choice",
+            "tools",
+            "top_p",
+            "truncation",
+            "user",
+            "extra_headers",
+            "extra_query",
+            "extra_body",
+            "timeout",
+        ]
+
+    def map_openai_params(
+        self,
+        response_api_optional_params: ResponsesAPIOptionalRequestParams,
+        model: str,
+        drop_params: bool,
+    ) -> Dict:
+        """No mapping applied since inputs are in OpenAI spec already"""
+        return dict(response_api_optional_params)
+
+    def transform_responses_api_request(
+        self,
+        model: str,
+        input: Union[str, ResponseInputParam],
+        response_api_optional_request_params: Dict,
+        litellm_params: GenericLiteLLMParams,
+        headers: dict,
+    ) -> Dict:
+        """No transform applied since inputs are in OpenAI spec already"""
+        return dict(
+            ResponsesAPIRequestParams(
+                model=model, input=input, **response_api_optional_request_params
+            )
+        )
+
+    def transform_response_api_response(
+        self,
+        model: str,
+        raw_response: httpx.Response,
+        logging_obj: LiteLLMLoggingObj,
+    ) -> ResponsesAPIResponse:
+        """No transform applied since outputs are in OpenAI spec already"""
+        try:
+            raw_response_json = raw_response.json()
+        except Exception:
+            raise OpenAIError(
+                message=raw_response.text, status_code=raw_response.status_code
+            )
+        return ResponsesAPIResponse(**raw_response_json)
+
+    def validate_environment(
+        self,
+        headers: dict,
+        model: str,
+        api_key: Optional[str] = None,
+    ) -> dict:
+        api_key = (
+            api_key
+            or litellm.api_key
+            or litellm.openai_key
+            or get_secret_str("OPENAI_API_KEY")
+        )
+        headers.update(
+            {
+                "Authorization": f"Bearer {api_key}",
+            }
+        )
+        return headers
+
+    def get_complete_url(
+        self,
+        api_base: Optional[str],
+        model: str,
+        stream: Optional[bool] = None,
+    ) -> str:
+        """
+        Get the endpoint for OpenAI responses API
+        """
+        api_base = (
+            api_base
+            or litellm.api_base
+            or get_secret_str("OPENAI_API_BASE")
+            or "https://api.openai.com/v1"
+        )
+
+        # Remove trailing slashes
+        api_base = api_base.rstrip("/")
+
+        return f"{api_base}/responses"
+
+    def transform_streaming_response(
+        self,
+        model: str,
+        parsed_chunk: dict,
+        logging_obj: LiteLLMLoggingObj,
+    ) -> ResponsesAPIStreamingResponse:
+        """
+        Transform a parsed streaming response chunk into a ResponsesAPIStreamingResponse
+        """
+        # Convert the dictionary to a properly typed ResponsesAPIStreamingResponse
+        verbose_logger.debug("Raw OpenAI Chunk=%s", parsed_chunk)
+        event_type = str(parsed_chunk.get("type"))
+        event_pydantic_model = OpenAIResponsesAPIConfig.get_event_model_class(
+            event_type=event_type
+        )
+        return event_pydantic_model(**parsed_chunk)
+
+    @staticmethod
+    def get_event_model_class(event_type: str) -> Any:
+        """
+        Returns the appropriate event model class based on the event type.
+
+        Args:
+            event_type (str): The type of event from the response chunk
+
+        Returns:
+            Any: The corresponding event model class
+
+        Raises:
+            ValueError: If the event type is unknown
+        """
+        event_models = {
+            ResponsesAPIStreamEvents.RESPONSE_CREATED: ResponseCreatedEvent,
+            ResponsesAPIStreamEvents.RESPONSE_IN_PROGRESS: ResponseInProgressEvent,
+            ResponsesAPIStreamEvents.RESPONSE_COMPLETED: ResponseCompletedEvent,
+            ResponsesAPIStreamEvents.RESPONSE_FAILED: ResponseFailedEvent,
+            ResponsesAPIStreamEvents.RESPONSE_INCOMPLETE: ResponseIncompleteEvent,
+            ResponsesAPIStreamEvents.OUTPUT_ITEM_ADDED: OutputItemAddedEvent,
+            ResponsesAPIStreamEvents.OUTPUT_ITEM_DONE: OutputItemDoneEvent,
+            ResponsesAPIStreamEvents.CONTENT_PART_ADDED: ContentPartAddedEvent,
+            ResponsesAPIStreamEvents.CONTENT_PART_DONE: ContentPartDoneEvent,
+            ResponsesAPIStreamEvents.OUTPUT_TEXT_DELTA: OutputTextDeltaEvent,
+            ResponsesAPIStreamEvents.OUTPUT_TEXT_ANNOTATION_ADDED: OutputTextAnnotationAddedEvent,
+            ResponsesAPIStreamEvents.OUTPUT_TEXT_DONE: OutputTextDoneEvent,
+            ResponsesAPIStreamEvents.REFUSAL_DELTA: RefusalDeltaEvent,
+            ResponsesAPIStreamEvents.REFUSAL_DONE: RefusalDoneEvent,
+            ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DELTA: FunctionCallArgumentsDeltaEvent,
+            ResponsesAPIStreamEvents.FUNCTION_CALL_ARGUMENTS_DONE: FunctionCallArgumentsDoneEvent,
+            ResponsesAPIStreamEvents.FILE_SEARCH_CALL_IN_PROGRESS: FileSearchCallInProgressEvent,
+            ResponsesAPIStreamEvents.FILE_SEARCH_CALL_SEARCHING: FileSearchCallSearchingEvent,
+            ResponsesAPIStreamEvents.FILE_SEARCH_CALL_COMPLETED: FileSearchCallCompletedEvent,
+            ResponsesAPIStreamEvents.WEB_SEARCH_CALL_IN_PROGRESS: WebSearchCallInProgressEvent,
+            ResponsesAPIStreamEvents.WEB_SEARCH_CALL_SEARCHING: WebSearchCallSearchingEvent,
+            ResponsesAPIStreamEvents.WEB_SEARCH_CALL_COMPLETED: WebSearchCallCompletedEvent,
+            ResponsesAPIStreamEvents.ERROR: ErrorEvent,
+        }
+
+        model_class = event_models.get(cast(ResponsesAPIStreamEvents, event_type))
+        if not model_class:
+            raise ValueError(f"Unknown event type: {event_type}")
+
+        return model_class
+
+    def should_fake_stream(
+        self,
+        model: Optional[str],
+        stream: Optional[bool],
+        custom_llm_provider: Optional[str] = None,
+    ) -> bool:
+        if stream is not True:
+            return False
+        if model is not None:
+            try:
+                if (
+                    litellm.utils.supports_native_streaming(
+                        model=model,
+                        custom_llm_provider=custom_llm_provider,
+                    )
+                    is False
+                ):
+                    return True
+            except Exception as e:
+                verbose_logger.debug(
+                    f"Error getting model info in OpenAIResponsesAPIConfig: {e}"
+                )
+        return False