From cce1d2087b9ae997ec406d6d38857642f1461844 Mon Sep 17 00:00:00 2001 From: mateo-berri <277851410+mateo-berri@users.noreply.github.com> Date: Wed, 9 Sep 2026 14:22:22 -0700 Subject: [PATCH] fix(responses): echo a named tool_choice in the Responses API shape on the chat-completions bridge A streamed /v1/responses request with tool_choice {"type": "function", "name": ...} that reaches a chat-completions-only deployment failed with HTTP 500 before the first byte: the synthetic response.created and response.in_progress events copied the chat-shaped tool_choice into ResponsesAPIResponse, whose ToolChoice type expects the flat Responses API shape. The non-streamed path echoed "auto" regardless of the request. Both paths now normalize the request's tool_choice through the existing chat transform and map it back to the Responses API vocabulary, validated by a TypeAdapter(ToolChoice), so a named function is echoed as {"type": "function", "name": ...} and a missing tool_choice is echoed as "auto". Fixes #33689 --- .../streaming_iterator.py | 11 ++-- .../transformation.py | 18 ++++++- .../test_litellm_completion_responses.py | 52 ++++++++++++++++++ .../test_streaming_iterator_transformation.py | 53 +++++++++++++++++++ 4 files changed, 126 insertions(+), 8 deletions(-) diff --git a/litellm/responses/litellm_completion_transformation/streaming_iterator.py b/litellm/responses/litellm_completion_transformation/streaming_iterator.py index d7f8cd8f8bd..660dd8f0c92 100644 --- a/litellm/responses/litellm_completion_transformation/streaming_iterator.py +++ b/litellm/responses/litellm_completion_transformation/streaming_iterator.py @@ -437,14 +437,11 @@ class LiteLLMCompletionStreamingIterator(ResponsesAPIStreamingIterator): response_created_event_data["temperature"] = self.responses_api_request["temperature"] if "text" in self.responses_api_request: response_created_event_data["text"] = self.responses_api_request["text"] - if "tool_choice" in self.responses_api_request: - # Transform tool_choice from dict format (e.g., {"type": "auto"}) to string format - response_created_event_data["tool_choice"] = ( - LiteLLMCompletionResponsesConfig._transform_tool_choice(self.responses_api_request["tool_choice"]) - or "auto" + response_created_event_data["tool_choice"] = ( + LiteLLMCompletionResponsesConfig._transform_tool_choice_for_responses_api_response( + self.responses_api_request.get("tool_choice") ) - else: - response_created_event_data["tool_choice"] = "auto" + ) if "tools" in self.responses_api_request: response_created_event_data["tools"] = self.responses_api_request["tools"] else: diff --git a/litellm/responses/litellm_completion_transformation/transformation.py b/litellm/responses/litellm_completion_transformation/transformation.py index b2d1a69e0d8..878f493b58e 100644 --- a/litellm/responses/litellm_completion_transformation/transformation.py +++ b/litellm/responses/litellm_completion_transformation/transformation.py @@ -27,6 +27,7 @@ from openai.types.chat.chat_completion_named_tool_choice_param import ( ) from openai.types.responses import ResponseFunctionToolCall from openai.types.responses.response_create_params import ResponseInputParam +from openai.types.responses.tool_choice_function_param import ToolChoiceFunctionParam from openai.types.responses.tool_param import FunctionToolParam from pydantic import TypeAdapter from typing_extensions import ReadOnly, TypedDict @@ -68,6 +69,7 @@ from litellm.types.llms.openai import ( ResponsesAPIOptionalRequestParams, ResponsesAPIResponse, ResponsesAPIStatus, + ToolChoice, ValidChatCompletionMessageContentTypes, ValidChatCompletionMessageContentTypesLiteral, ) @@ -126,6 +128,7 @@ _STR_KEY_DICT_ADAPTER: Final = TypeAdapter(dict[str, object]) _OBJECT_LIST_ADAPTER: Final = TypeAdapter(list[object]) _DICT_ITEMS_LIST_ADAPTER: Final = TypeAdapter(list[dict[object, object]]) _TEXT_ADAPTER: Final = TypeAdapter(str) +_RESPONSES_API_TOOL_CHOICE_ADAPTER: Final = TypeAdapter(ToolChoice) @runtime_checkable @@ -267,6 +270,17 @@ class LiteLLMCompletionResponsesConfig: # Return as-is for unknown formats return tool_choice + @staticmethod + def _transform_tool_choice_for_responses_api_response(tool_choice: object) -> ToolChoice: + normalized: Final = LiteLLMCompletionResponsesConfig._transform_tool_choice(tool_choice) + match normalized: + case None: + return "auto" + case {"type": "function", "function": {"name": str(function_name)}}: + return ToolChoiceFunctionParam(type="function", name=function_name) + case _: + return _RESPONSES_API_TOOL_CHOICE_ADAPTER.validate_python(normalized) + @staticmethod def _should_drop_derived_web_search_options(model: str, custom_llm_provider: str | None) -> bool: """ @@ -2263,7 +2277,9 @@ class LiteLLMCompletionResponsesConfig: ), parallel_tool_calls=getattr(chat_completion_response, "parallel_tool_calls", False), temperature=getattr(chat_completion_response, "temperature", 0), - tool_choice=getattr(chat_completion_response, "tool_choice", "auto"), + tool_choice=LiteLLMCompletionResponsesConfig._transform_tool_choice_for_responses_api_response( + responses_api_request.get("tool_choice") + ), 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), diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py index 2068f10ea2d..2aab660b5b7 100644 --- a/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py +++ b/tests/test_litellm/responses/litellm_completion_transformation/test_litellm_completion_responses.py @@ -1421,6 +1421,58 @@ class TestToolChoiceTransformation: ) assert result == "required" + @pytest.mark.parametrize( + "request_tool_choice,expected", + [ + ({"type": "function", "name": "run_command"}, {"type": "function", "name": "run_command"}), + ({"type": "function", "function": {"name": "run_command"}}, {"type": "function", "name": "run_command"}), + ({"type": "custom", "name": "ApplyPatch"}, {"type": "function", "name": "ApplyPatch"}), + ({"type": "tool"}, "required"), + ({"type": "auto"}, "auto"), + ("required", "required"), + ("none", "none"), + (None, "auto"), + ], + ) + def test_transform_tool_choice_for_responses_api_response(self, request_tool_choice, expected): + result = LiteLLMCompletionResponsesConfig._transform_tool_choice_for_responses_api_response( + request_tool_choice + ) + assert result == expected + + def test_non_streamed_response_echoes_named_tool_choice_in_responses_api_shape(self): + chat_completion_response = ModelResponse( + id="chatcmpl-named-tool-choice", + created=1748575031, + model="claude-haiku-4-5", + object="chat.completion", + choices=[ + Choices( + index=0, + finish_reason="tool_calls", + message=Message( + role="assistant", + content=None, + tool_calls=[ + ChatCompletionMessageToolCall( + id="call_pwd", + type="function", + function=Function(name="run_command", arguments='{"command":"pwd"}'), + ) + ], + ), + ) + ], + ) + + responses_api_response = LiteLLMCompletionResponsesConfig.transform_chat_completion_response_to_responses_api_response( + request_input="Run the command pwd.", + responses_api_request={"tool_choice": {"type": "function", "name": "run_command"}}, + chat_completion_response=chat_completion_response, + ) + + assert responses_api_response.tool_choice == {"type": "function", "name": "run_command"} + class TestContentTypeTransformation: """Test content type transformation from Responses API to Chat Completion format""" diff --git a/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py b/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py index 719d51c11e3..d4b565f82a1 100644 --- a/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py +++ b/tests/test_litellm/responses/litellm_completion_transformation/test_streaming_iterator_transformation.py @@ -628,3 +628,56 @@ def test_streamed_anthropic_tool_call_events_correlate_on_normalized_item_id(): assert item_dones[0].item.call_id == "toolu_01AbCdEf" for evt in deltas + dones: assert evt.item_id == added[0].item.id + + +def _tool_call_chunk(finish_reason: str | None = None) -> ModelResponseStream: + return ModelResponseStream( + id=CHAT_COMPLETION_ID, + created=1748575031, + model="claude-haiku-4-5", + object="chat.completion.chunk", + choices=[ + StreamingChoices( + index=0, + delta=Delta( + role="assistant", + content=None, + tool_calls=[ + { + "id": "call_pwd", + "type": "function", + "function": {"name": "run_command", "arguments": '{"command":"pwd"}'}, + "index": 0, + } + ], + ), + finish_reason=finish_reason, + ) + ], + ) + + +def test_streamed_named_tool_choice_is_echoed_in_responses_api_shape(): + iterator = LiteLLMCompletionStreamingIterator( + model="claude-haiku-4-5", + litellm_custom_stream_wrapper=_FakeStreamWrapper([_tool_call_chunk(finish_reason="tool_calls")]), + request_input="Run the command pwd.", + responses_api_request={ + "tools": [{"type": "function", "name": "run_command", "parameters": {"type": "object"}}], + "tool_choice": {"type": "function", "name": "run_command"}, + }, + custom_llm_provider="anthropic", + litellm_metadata={}, + ) + + events = list(iterator) + + response_events = [event for event in events if getattr(event, "type", None) in RESPONSE_ID_EVENT_TYPES] + assert [event.type for event in response_events] == [ + "response.created", + "response.in_progress", + "response.completed", + ] + assert response_events[0].response.tool_choice == {"type": "function", "name": "run_command"} + assert response_events[1].response.tool_choice == {"type": "function", "name": "run_command"} + assert any(getattr(event, "type", None) == "response.output_item.done" for event in events)