[Frontend] Responses API messages out, just harmony for now (#24985)

Signed-off-by: Alec Solder <alecs@fb.com>
Co-authored-by: Alec Solder <alecs@fb.com>
Co-authored-by: Ye (Charlotte) Qi <yeq@meta.com>

tests/entrypoints/openai/test_response_api_with_harmony.py

@@ -744,3 +744,18 @@ async def test_function_calling_full_history(client: OpenAI, model_name: str):
     assert response_2 is not None
     assert response_2.status == "completed"
     assert response_2.output_text is not None
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize("model_name", [MODEL_NAME])
+async def test_output_messages_enabled(client: OpenAI, model_name: str,
+                                       server):
+    response = await client.responses.create(
+        model=model_name,
+        input="What is the capital of South Korea?",
+        extra_body={"enable_response_messages": True})
+
+    assert response is not None
+    assert response.status == "completed"
+    assert len(response.input_messages) > 0
+    assert len(response.output_messages) > 0

vllm/entrypoints/openai/protocol.py

@@ -328,6 +328,13 @@ class ResponsesRequest(OpenAIBaseModel):
             "access by 3rd parties, and long enough to be "
             "unpredictable (e.g., 43 characters base64-encoded, corresponding "
             "to 256 bit). Not supported by vLLM engine V0."))
+
+    enable_response_messages: bool = Field(
+        default=False,
+        description=(
+            "Dictates whether or not to return messages as part of the "
+            "response object. Currently only supported for non-streaming "
+            "non-background and gpt-oss only. "))
     # --8<-- [end:responses-extra-params]
 
     _DEFAULT_SAMPLING_PARAMS = {
@@ -1831,6 +1838,11 @@ class ResponsesResponse(OpenAIBaseModel):
     model: str
     object: Literal["response"] = "response"
     output: list[ResponseOutputItem]
+    # These are populated when enable_response_messages is set to True
+    # TODO: Currently an issue where content of harmony messages
+    # is not available when these are serialized. Metadata is available
+    input_messages: Optional[list[ChatCompletionMessageParam]] = None
+    output_messages: Optional[list[ChatCompletionMessageParam]] = None
     parallel_tool_calls: bool
     temperature: float
     tool_choice: ToolChoice
@@ -1860,6 +1872,8 @@ class ResponsesResponse(OpenAIBaseModel):
         output: list[ResponseOutputItem],
         status: ResponseStatus,
         usage: Optional[ResponseUsage] = None,
+        input_messages: Optional[list[ChatCompletionMessageParam]] = None,
+        output_messages: Optional[list[ChatCompletionMessageParam]] = None,
     ) -> "ResponsesResponse":
 
         incomplete_details: Optional[IncompleteDetails] = None
@@ -1868,7 +1882,6 @@ class ResponsesResponse(OpenAIBaseModel):
         # TODO: implement the other reason for incomplete_details,
         # which is content_filter
         # incomplete_details = IncompleteDetails(reason='content_filter')
-
         return cls(
             id=request.request_id,
             created_at=created_time,
@@ -1877,6 +1890,8 @@ class ResponsesResponse(OpenAIBaseModel):
             metadata=request.metadata,
             model=model_name,
             output=output,
+            input_messages=input_messages,
+            output_messages=output_messages,
             parallel_tool_calls=request.parallel_tool_calls,
             temperature=sampling_params.temperature,
             tool_choice=request.tool_choice,

vllm/entrypoints/openai/serving_responses.py

@@ -475,9 +475,14 @@ class OpenAIServingResponses(OpenAIServing):
         # "completed" is implemented as the "catch-all" for now.
         status: ResponseStatus = "completed"
 
+        input_messages = None
+        output_messages = None
         if self.use_harmony:
             assert isinstance(context, HarmonyContext)
             output = self._make_response_output_items_with_harmony(context)
+            if request.enable_response_messages:
+                input_messages = context.messages[:context.num_init_messages]
+                output_messages = context.messages[context.num_init_messages:]
             num_tool_output_tokens = context.num_tool_output_tokens
             if len(output) > 0:
                 if context.finish_reason == "length":
@@ -496,6 +501,12 @@ class OpenAIServingResponses(OpenAIServing):
             output = self._make_response_output_items(request, final_output,
                                                       tokenizer)
 
+            # TODO: context for non-gptoss models doesn't use messages
+            # so we can't get them out yet
+            if request.enable_response_messages:
+                raise NotImplementedError(
+                    "enable_response_messages is currently"
+                    " only supported for gpt-oss")
             # Calculate usage.
             assert final_res.prompt_token_ids is not None
             num_tool_output_tokens = 0
@@ -519,6 +530,8 @@ class OpenAIServingResponses(OpenAIServing):
         response = ResponsesResponse.from_request(
             request,
             sampling_params,
+            input_messages=input_messages,
+            output_messages=output_messages,
             model_name=model_name,
             created_time=created_time,
             output=output,