[Frontend] Responses api harmony output

tests/entrypoints/openai/test_response_api_with_harmony.py

@@ -28,6 +28,7 @@ def server(monkeypatch_module: pytest.MonkeyPatch):
 
     with monkeypatch_module.context() as m:
         m.setenv("VLLM_ENABLE_RESPONSES_API_STORE", "1")
+        m.setenv("VLLM_RESPONSES_API_ENABLE_HARMONY_MESSAGES_OUTPUT", "1")
         with RemoteOpenAIServer(MODEL_NAME, args) as remote_server:
             yield remote_server
 
@@ -48,6 +49,11 @@ async def test_basic(client: OpenAI, model_name: str):
     assert response is not None
     print("response: ", response)
     assert response.status == "completed"
+    # For now, just validate that input and output harmony messages exist
+    # To validate that the env flag enables them to be passed through properly
+    # Actual unit tests will need to be implemented on a model specific basis
+    assert len(response.input_harmony_messages) != 0
+    assert len(response.output_harmony_messages) != 0
 
 
 @pytest.mark.asyncio

vllm/entrypoints/context.py

@@ -75,6 +75,7 @@ def __init__(
         available_tools: list[str],
     ):
         self._messages = messages
+        self.input_messages = messages
         self.available_tools = available_tools
         self._tool_sessions: dict[str, Union[ClientSession, Tool]] = {}
 

vllm/entrypoints/openai/protocol.py

@@ -33,6 +33,7 @@
 from openai.types.responses.response import ToolChoice
 from openai.types.responses.tool import Tool
 from openai.types.shared import Metadata, Reasoning
+from openai_harmony import Message
 from pydantic import (BaseModel, ConfigDict, Field, TypeAdapter,
                       ValidationInfo, field_validator, model_validator)
 from typing_extensions import TypeAlias
@@ -1847,6 +1848,10 @@ class ResponseUsage(OpenAIBaseModel):
 class ResponsesResponse(OpenAIBaseModel):
     id: str = Field(default_factory=lambda: f"resp_{random_uuid()}")
     created_at: int = Field(default_factory=lambda: int(time.time()))
+    # These are populated when the env flag
+    # VLLM_RESPONSES_API_ENABLE_HARMONY_MESSAGES_OUTPUT is set
+    input_harmony_messages: Optional[list[Message]] = None
+    output_harmony_messages: Optional[list[Message]] = None
     # error: Optional[ResponseError] = None
     # incomplete_details: Optional[IncompleteDetails] = None
     instructions: Optional[str] = None
@@ -1882,12 +1887,16 @@ def from_request(
         created_time: int,
         output: list[ResponseOutputItem],
         status: ResponseStatus,
+        input_harmony_messages: Optional[list[Message]] = None,
+        output_harmony_messages: Optional[list[Message]] = None,
         usage: Optional[ResponseUsage] = None,
     ) -> "ResponsesResponse":
         return cls(
             id=request.request_id,
             created_at=created_time,
             instructions=request.instructions,
+            input_harmony_messages=input_harmony_messages,
+            output_harmony_messages=output_harmony_messages,
             metadata=request.metadata,
             model=model_name,
             output=output,
@@ -2179,7 +2188,7 @@ class TranscriptionRequest(OpenAIBaseModel):
     to_language: Optional[str] = None
     """The language of the output audio we transcribe to.
 
-    Please note that this is not currently used by supported models at this 
+    Please note that this is not currently used by supported models at this
     time, but it is a placeholder for future use, matching translation api.
     """
 

vllm/entrypoints/openai/serving_responses.py

@@ -439,9 +439,17 @@ async def responses_full_generator(
                 # TODO: Use a vllm-specific Validation Error
                 return self.create_error_response(str(e))
 
+        output_harmony_messages = None
+        input_harmony_messages = None
         if self.use_harmony:
             assert isinstance(context, HarmonyContext)
             output = self._make_response_output_items_with_harmony(context)
+            if envs.VLLM_GPT_OSS_USE_CONTAINER_TOOL:
+                # TODO: Handle leftover parser state?
+                input_harmony_messages = context.input_messages
+                # .messages contains input and output, so just get the output
+                output_harmony_messages = context.messages[
+                    len(input_harmony_messages):]
             # TODO: these are all 0 for now!
             num_prompt_tokens = context.num_prompt_tokens
             num_generated_tokens = context.num_output_tokens
@@ -479,6 +487,8 @@ async def responses_full_generator(
             model_name=model_name,
             created_time=created_time,
             output=output,
+            input_harmony_messages=input_harmony_messages,
+            output_harmony_messages=output_harmony_messages,
             status="completed",
             usage=usage,
         )

vllm/envs.py

@@ -1199,6 +1199,12 @@ def get_vllm_port() -> Optional[int]:
     "VLLM_TUNED_CONFIG_FOLDER":
     lambda: os.getenv("VLLM_TUNED_CONFIG_FOLDER", None),
 
+    # Whether to enable outputting Harmony messages on the
+    # Responses API response object
+    "VLLM_RESPONSES_API_ENABLE_HARMONY_MESSAGES_OUTPUT":
+    lambda: bool(int(
+        os.getenv("VLLM_RESPONSES_API_ENABLE_HARMONY_MESSAGES_OUTPUT",
+        "0"))),
 }
 
 # --8<-- [end:env-vars-definition]