diff --git a/litellm/completion_extras/litellm_responses_transformation/transformation.py b/litellm/completion_extras/litellm_responses_transformation/transformation.py index ee3639ac387..bd2f420249c 100644 --- a/litellm/completion_extras/litellm_responses_transformation/transformation.py +++ b/litellm/completion_extras/litellm_responses_transformation/transformation.py @@ -2130,7 +2130,7 @@ class OpenAiResponsesToChatCompletionStreamIterator(BaseModelResponseIterator): return ModelResponseStream( choices=[ StreamingChoices( - index=cast(int, parsed_chunk.get("summary_index")), + index=0, delta=Delta(reasoning_content=content_part), ) ] diff --git a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py index bfbf01d6329..d9f5eb640af 100644 --- a/litellm/litellm_core_utils/streaming_chunk_builder_utils.py +++ b/litellm/litellm_core_utils/streaming_chunk_builder_utils.py @@ -385,8 +385,8 @@ class ChunkProcessor: return "assistant" @staticmethod - def _finish_reason_of_chunks(chunks: Sequence["_BaseChunk"]) -> object: - finish_reason = "stop" + def _finish_reason_of_chunks(chunks: Sequence["_BaseChunk"], unreported: str = "stop") -> object: + finish_reason = unreported for chunk in chunks: if "choices" in chunk and len(chunk["choices"]) > 0: chunk_finish_reason = None @@ -402,7 +402,9 @@ class ChunkProcessor: def build_base_choice(index: int, chunks: Sequence["_BaseChunk"]) -> Choices: return Choices( index=index, - finish_reason=ChunkProcessor._finish_reason_of_chunks(chunks), + finish_reason=ChunkProcessor._finish_reason_of_chunks( + chunks, unreported="tool_calls" if _carries_tool_calls(chunks) else "stop" + ), message={"role": ChunkProcessor._get_role_from_chunks(chunks), "content": ""}, ) @@ -1532,6 +1534,13 @@ def _stream_choice_index(choice: object) -> int: return index if isinstance(index, int) else 0 +def _carries_tool_calls(chunks: Sequence[_BaseChunk]) -> bool: + return any( + "tool_calls" in choice["delta"] and choice["delta"]["tool_calls"] + for choice in chain.from_iterable(chunk.get("choices") or () for chunk in chunks) + ) + + def _choice_streams(chunks: Sequence[_BaseChunk]) -> tuple[tuple[int, Sequence[_BaseChunk]], ...]: indices: Final = sorted( frozenset(map(_stream_choice_index, chain.from_iterable(chunk.get("choices") or () for chunk in chunks))) diff --git a/litellm/llms/openai/chat/guardrail_translation/handler.py b/litellm/llms/openai/chat/guardrail_translation/handler.py index 3070bedd30d..5c5204ef2f4 100644 --- a/litellm/llms/openai/chat/guardrail_translation/handler.py +++ b/litellm/llms/openai/chat/guardrail_translation/handler.py @@ -687,11 +687,6 @@ class OpenAIChatCompletionsHandler(BaseTranslation): responses_so_far: Sequence["ModelResponseStream"], litellm_logging_obj: "LiteLLMLoggingObj | None", ) -> "ModelResponse": - """``stream_chunk_builder`` folds every choice of a stream into one index-0 - choice, so the stream is rebuilt one choice index at a time (every chunk - kept, its choices narrowed to that index, so usage-only chunks still - count) and the rebuilt choices are stitched into one response, each - carrying the index the stream gave it.""" choice_indices: Final = tuple( sorted(frozenset(choice.index for response in responses_so_far for choice in response.choices)) ) diff --git a/tests/unit/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py b/tests/unit/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py index 46f1dbf2e7a..433ef473296 100644 --- a/tests/unit/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py +++ b/tests/unit/completion_extras/litellm_responses_transformation/test_completion_extras_litellm_responses_transformation_transformation.py @@ -418,6 +418,35 @@ def test_openai_responses_chunk_parser_reasoning_summary(): assert delta.function_call is None +def test_bridged_reasoning_summary_parts_rebuild_into_the_one_choice_they_streamed_on(): + from litellm.completion_extras.litellm_responses_transformation.transformation import ( + OpenAiResponsesToChatCompletionStreamIterator, + ) + + iterator = OpenAiResponsesToChatCompletionStreamIterator(streaming_response=None, sync_stream=True) + events = ( + { + "type": "response.reasoning_summary_text.delta", + "delta": "First part.", + "output_index": 0, + "summary_index": 0, + }, + { + "type": "response.reasoning_summary_text.delta", + "delta": "Second part.", + "output_index": 0, + "summary_index": 1, + }, + {"type": "response.output_text.delta", "delta": "Answer", "output_index": 1, "content_index": 0}, + ) + + rebuilt = litellm.stream_chunk_builder(chunks=[iterator.chunk_parser(event) for event in events]) + + assert [(choice.index, choice.message.reasoning_content, choice.message.content) for choice in rebuilt.choices] == [ + (0, "First part.Second part.", "Answer") + ] + + def test_chunk_parser_string_output_text_delta_produces_text(): from litellm.completion_extras.litellm_responses_transformation.transformation import ( OpenAiResponsesToChatCompletionStreamIterator, diff --git a/tests/unit/litellm_core_utils/test_streaming_chunk_builder_utils.py b/tests/unit/litellm_core_utils/test_streaming_chunk_builder_utils.py index 7b1f7a62fd3..d2969295c4d 100644 --- a/tests/unit/litellm_core_utils/test_streaming_chunk_builder_utils.py +++ b/tests/unit/litellm_core_utils/test_streaming_chunk_builder_utils.py @@ -1339,6 +1339,39 @@ def test_stream_chunk_builder_rebuilds_each_choice_of_a_multi_choice_text_stream ] +def test_stream_chunk_builder_gives_a_choice_without_a_finish_chunk_the_finish_reason_its_content_implies(): + def chunk(choice_index: int, delta: Delta, finish_reason: str | None = None) -> ModelResponseStream: + return ModelResponseStream( + id="chatcmpl-123", + object="chat.completion.chunk", + created=1234567890, + model="gpt-4.1-mini", + choices=[StreamingChoices(index=choice_index, delta=delta, finish_reason=finish_reason)], + ) + + def tool_call(call_id: str) -> list[ChatCompletionDeltaToolCall]: + return [ + ChatCompletionDeltaToolCall( + id=call_id, index=0, type="function", function=Function(name="lookup_fruit", arguments="{}") + ) + ] + + response = stream_chunk_builder( + chunks=[ + chunk(0, Delta(tool_calls=tool_call("call_a"))), + chunk(1, Delta(tool_calls=tool_call("call_b"))), + chunk(2, Delta(content="Kiwis are fuzzy.")), + chunk(0, Delta(), finish_reason="tool_calls"), + ] + ) + + assert [(choice.index, choice.finish_reason) for choice in response.choices] == [ + (0, "tool_calls"), + (1, "tool_calls"), + (2, "stop"), + ] + + def test_stream_chunk_builder_keeps_each_choices_function_call_annotations_and_images_on_that_choice(): def chunk(choice_index: int, delta: Delta) -> ModelResponseStream: return ModelResponseStream(