fix(omni): fix disaggregated Qwen2.5-Omni serving pipeline (#8301)

Signed-off-by: Piotr Tarasiewicz <ptarasiewicz@nvidia.com>
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

components/src/dynamo/vllm/omni/stage_worker.py

@@ -13,9 +13,11 @@ from typing import Any, AsyncGenerator
 
 import yaml
 from vllm_omni.distributed.omni_connectors import initialize_orchestrator_connectors
+from vllm_omni.engine.orchestrator import build_engine_core_request_from_tokens
 from vllm_omni.entrypoints.async_omni import AsyncOmni
 from vllm_omni.entrypoints.stage_utils import serialize_obj, shm_write_bytes
 from vllm_omni.entrypoints.utils import load_stage_configs_from_yaml
+from vllm_omni.inputs.data import OmniTokensPrompt
 
 from dynamo import prometheus_names
 from dynamo.llm import ModelType
@@ -64,7 +66,6 @@ class OmniStageWorker:
         self.engine = engine
         self.stage_id = stage_id
         self.connectors = connectors  # {(from_stage, to_stage): vllm_omni connector}
-        self.final_output: bool = getattr(stage_config, "final_output", False)
         self._output_modalities = output_modalities or []
         self._default_video_fps = default_video_fps
         self.stage_config = stage_config
@@ -116,12 +117,28 @@ class OmniStageWorker:
                 if isinstance(prompt, list) and len(prompt) == 1:
                     prompt = prompt[0]
             else:
-                # No processor: use the most recent fetched stage output directly.
-                prompt = stage_list[-1].engine_outputs[0]
+                # No processor: check if the upstream output has the
+                # structure needed to build an OmniEngineCoreRequest
+                # (e.g. code2wav receiving token_ids from talker).
+                # Otherwise fall back to passing the raw data directly.
+                upstream = stage_list[-1].engine_outputs[0]
+                if hasattr(upstream, "outputs") and upstream.outputs:
+                    try:
+                        prompt = self._build_engine_core_request_from_upstream(
+                            stage_list, request_id, sampling_params_list_override
+                        )
+                    except RuntimeError as e:
+                        yield {"error": str(e), "finished": True}
+                        return
+                else:
+                    prompt = upstream
         elif req.request_id is not None:
             # Stage 0 via router: raw request forwarded with request_id — parse it.
-            parsed = parse_omni_request(
-                request, self._output_modalities, self._default_video_fps
+            parsed = await parse_omni_request(
+                request,
+                self._output_modalities,
+                self._default_video_fps,
+                tokenizer_getter=self.engine.get_tokenizer,
             )
             prompt = parsed["engine_inputs"]
             original_prompt = parsed["original_prompt"]
@@ -142,7 +159,7 @@ class OmniStageWorker:
 
         try:
             async for chunk in self.engine.generate(
-                prompt, request_id, sampling_params_list=sp
+                prompt, request_id=request_id, sampling_params_list=sp
             ):
                 last_result = chunk
         except Exception as e:
@@ -157,7 +174,11 @@ class OmniStageWorker:
             return
 
         # --- Write output ---
-        if not self.final_output:
+        # Check for a downstream connector first, regardless of final_output.
+        # In vllm-omni's native mode, multiple stages can set final_output=True
+        # (meaning "produces user-visible output"). In Dynamo's disaggregated
+        # mode the actual pipeline topology — connector edges from the YAML —
+        # determines whether output should go to a connector or to SHM.
         from_s, to_s = _connector_key(self.stage_id, self.stage_id + 1)
         connector = self.connectors.get((from_s, to_s))
         if connector is not None:
@@ -190,12 +211,6 @@ class OmniStageWorker:
                 out["sampling_params_list"] = sampling_params_list_override
             yield out
             return
-            logger.warning(
-                "Stage %d: no connector found for edge (%s→%s), falling through to SHM",
-                self.stage_id,
-                from_s,
-                to_s,
-            )
 
         # Final stage → router: write output to shared memory and return the SHM handle.
         # The router reads it back via shm_deserialize() to format the response.
@@ -207,6 +222,60 @@ class OmniStageWorker:
         shm_meta = shm_write_bytes(serialize_obj(last_result), name=request_id)
         yield {"shm_meta": shm_meta, "finished": True}
 
+    def _build_engine_core_request_from_upstream(
+        self,
+        stage_list: list[_Proxy],
+        request_id: str,
+        sampling_params_list_override: dict | None,
+    ):
+        """Build an OmniEngineCoreRequest from the upstream stage output.
+
+        Used for stages without a custom processor (e.g. code2wav).  Mirrors
+        what the native orchestrator does via ``build_engine_core_request_from_tokens``
+        and ``_forward_to_next_stage``.  Building an ``EngineCoreRequest``
+        bypasses ``InputProcessor.process_inputs()`` which would fail for
+        non-autoregressive stages (``worker_type: generation``) with
+        "This model does not support generation".
+
+        Raises RuntimeError on unexpected upstream output structure.
+        """
+        try:
+            # engine_outputs[0]: first (and only) RequestOutput — Dynamo
+            # processes one request at a time per stage.
+            # outputs[0]: first CompletionOutput (n=1 sampling).
+            # Matches native orchestrator's process_engine_inputs pattern.
+            upstream = stage_list[-1].engine_outputs[0]
+            token_ids = upstream.outputs[0].token_ids
+        except (IndexError, AttributeError) as e:
+            raise RuntimeError(
+                f"Stage {self.stage_id}: cannot extract token_ids from "
+                f"upstream output: {e}"
+            ) from e
+
+        tokens_prompt = OmniTokensPrompt(prompt_token_ids=list(token_ids))
+        sp_list = _build_sampling_params(
+            self.stage_config, sampling_params_list_override
+        )
+        params = sp_list[0] if sp_list else None
+        prompt = build_engine_core_request_from_tokens(
+            request_id=request_id,
+            prompt=tokens_prompt,
+            params=params,
+        )
+        # Pre-built EngineCoreRequests skip the output processor registration
+        # in _build_add_request_message (the isinstance(prompt, EngineCoreRequest)
+        # branch bypasses that block).  Register manually so that the engine's
+        # output processor can match the response back to this request.
+        prompt.external_req_id = prompt.request_id
+        self.engine.engine.output_processors[0].add_request(
+            request=prompt,
+            prompt=None,
+            parent_req=None,
+            request_index=0,
+            queue=None,
+        )
+        return prompt
+
     def _fetch_stage_inputs(
         self, stage_connector_refs: dict[int, Any], request_id: str
     ) -> list[_Proxy]:

components/src/dynamo/vllm/omni/types.py

@@ -15,10 +15,12 @@ from pydantic import BaseModel, ConfigDict, model_validator
 class StageEngine(Protocol):
     """Any engine that can generate outputs for a single pipeline stage.
 
-    Matches AsyncOmni.generate() signature — the only vllm_omni engine
-    with a consistent async generator interface for both LLM and diffusion.
+    Matches AsyncOmni — the only vllm_omni engine with a consistent async
+    generator interface for both LLM and diffusion.
     """
 
+    engine: Any  # AsyncOmniEngine — exposes output_processors for registration
+
     def generate(
         self,
         prompt: Any,
@@ -28,6 +30,10 @@ class StageEngine(Protocol):
     ) -> AsyncGenerator[Any, None]:
         ...
 
+    def get_tokenizer(self) -> Any:
+        """Return the tokenizer (may be async — callers should await)."""
+        ...
+
 
 class StageOutput(BaseModel):
     """Validated output dict from a stage worker.

components/src/dynamo/vllm/omni/utils.py

@@ -37,11 +37,19 @@ def build_original_prompt(request: dict, nvext: dict, height: int, width: int) -
     return prompt
 
 
-def parse_omni_request(
-    request: dict, output_modalities: list, default_video_fps: int = 16
+async def parse_omni_request(
+    request: dict,
+    output_modalities: list,
+    default_video_fps: int = 16,
+    tokenizer_getter=None,
 ) -> dict:
     """Parse a raw frontend request into engine_inputs, original_prompt, sampling_params_list.
 
+    Args:
+      tokenizer_getter: async callable returning a tokenizer (e.g. engine.get_tokenizer).
+          When provided, chat requests are formatted through the model's chat template
+          so the thinker receives the same prompt as native ``vllm serve --omni``.
+
     Returns:
       engine_inputs:        text prompt (str or OmniTextPrompt) for the stage 0 engine
       original_prompt:      rich prompt dict with geometry/params for processor functions
@@ -74,6 +82,22 @@ def parse_omni_request(
         (m.get("content", "") for m in reversed(messages) if m.get("role") == "user"),
         request.get("prompt", ""),
     )
+
+    # Apply chat template when a tokenizer is available.  The native
+    # OpenAI API server applies the template before the engine sees it;
+    # without it the thinker receives bare text instead of the full
+    # chat-formatted prompt.
+    if messages and tokenizer_getter is not None:
+        try:
+            tokenizer = await tokenizer_getter()
+            text = tokenizer.apply_chat_template(
+                messages, tokenize=False, add_generation_prompt=True
+            )
+        except Exception:
+            logging.getLogger(__name__).debug(
+                "Chat template not available, using raw text"
+            )
+
     return {
         "engine_inputs": text,
         "original_prompt": {"prompt": text},

components/src/dynamo/vllm/tests/omni/test_omni_disagg_types.py

@@ -24,12 +24,17 @@ pytestmark = [
 
 
 class _MockEngine:
+    engine = None
+
     def generate(self, prompt, request_id="", *, sampling_params_list=None):
         async def _gen():
             yield {}
 
         return _gen()
 
+    def get_tokenizer(self):
+        return None
+
 
 def test_stage_engine_protocol_satisfied():
     assert isinstance(_MockEngine(), StageEngine)

components/src/dynamo/vllm/tests/omni/test_omni_handler.py

@@ -264,36 +264,39 @@ class TestParseOmniRequest:
     """parse_omni_request: original_prompt only has prompt/negative_prompt,
     geometry goes into sampling_params_list dict."""
 
-    def test_image_sampling_params_has_geometry(self):
+    @pytest.mark.asyncio
+    async def test_image_sampling_params_has_geometry(self):
         request = {
             "prompt": "a sunset",
             "size": "512x512",
             "output_modalities": ["image"],
         }
-        result = parse_omni_request(request, ["image"])
+        result = await parse_omni_request(request, ["image"])
         sp = result["sampling_params_list"]
         assert sp["height"] == 512
         assert sp["width"] == 512
 
-    def test_image_original_prompt_no_geometry(self):
+    @pytest.mark.asyncio
+    async def test_image_original_prompt_no_geometry(self):
         request = {
             "prompt": "a sunset",
             "size": "512x512",
             "output_modalities": ["image"],
         }
-        result = parse_omni_request(request, ["image"])
+        result = await parse_omni_request(request, ["image"])
         op = result["original_prompt"]
         assert op["prompt"] == "a sunset"
         assert "height" not in op
         assert "width" not in op
 
-    def test_nvext_params_go_into_sampling_params_not_prompt(self):
+    @pytest.mark.asyncio
+    async def test_nvext_params_go_into_sampling_params_not_prompt(self):
         request = {
             "prompt": "x",
             "size": "512x512",
             "nvext": {"num_inference_steps": 30, "guidance_scale": 4.0},
         }
-        result = parse_omni_request(request, ["image"])
+        result = await parse_omni_request(request, ["image"])
         sp = result["sampling_params_list"]
         assert sp["num_inference_steps"] == 30
         assert sp["guidance_scale"] == 4.0

components/src/dynamo/vllm/tests/omni/test_omni_stage_worker.py

@@ -26,7 +26,9 @@ pytestmark = [
 
 
 class _MockEngine:
-    """Satisfies StageEngine Protocol — matches AsyncOmni.generate() signature."""
+    """Satisfies StageEngine Protocol — matches AsyncOmni interface."""
+
+    engine = None  # satisfies StageEngine.engine
 
     def __init__(self, output=None):
         self.received_prompt = None
@@ -44,6 +46,9 @@ class _MockEngine:
 
         return _gen()
 
+    async def get_tokenizer(self):
+        return None
+
 
 class _ErrorEngine:
     def generate(self, prompt, request_id="", *, sampling_params_list=None):
@@ -128,6 +133,50 @@ async def test_stage_connector_refs_input_path():
     assert chunks[0]["original_prompt"] == {"prompt": "hello"}
 
 
+@pytest.mark.asyncio
+async def test_stage_connector_refs_builds_engine_core_request():
+    """Stage N>0 without processor: upstream with .outputs builds OmniEngineCoreRequest."""
+    engine = _MockEngine()
+
+    # Mock upstream output that looks like a real RequestOutput (has .outputs[0].token_ids)
+    mock_output = SimpleNamespace(
+        outputs=[SimpleNamespace(token_ids=[100, 200, 300])],
+        prompt_token_ids=[1, 2],
+    )
+
+    in_connector = MagicMock()
+    in_connector.get.return_value = (
+        mock_output  # raw object, not {"engine_inputs": ...}
+    )
+
+    out_connector = MagicMock()
+    out_connector.put.return_value = (True, 0, {"name": "ref1"})
+
+    worker = _make_worker(
+        engine=engine,
+        connectors={("0", "1"): in_connector, ("1", "2"): out_connector},
+        stage_id=1,
+        stage_config=_make_stage_config(
+            default_sampling_params={"temperature": 0.9, "max_tokens": 100},
+        ),
+    )
+    # Mock the engine's output_processors for registration
+    engine.engine = MagicMock()
+    request = {
+        "request_id": "req-ecr",
+        "original_prompt": {"prompt": "hello"},
+        "stage_connector_refs": {"0": {"name": "ref0"}},
+    }
+
+    _ = [chunk async for chunk in worker.generate(request, _MockContext())]
+
+    # The engine should receive an OmniEngineCoreRequest (not the raw dict)
+    assert hasattr(engine.received_prompt, "prompt_token_ids")
+    assert engine.received_prompt.prompt_token_ids == [100, 200, 300]
+    # Output processor should have been registered
+    engine.engine.output_processors[0].add_request.assert_called_once()
+
+
 @pytest.mark.asyncio
 async def test_stage_connector_refs_with_processor():
     """Stage N>0 with processor: processor receives stage_list built from connector output."""