[Core] Retain structured configs through runtime startup (#6849)

Signed-off-by: maithilijoshi20 <97733343+maithilijoshi20@users.noreply.github.com>

tests/entrypoints/openai_api/test_serving_speech.py

@@ -27,6 +27,7 @@ from pydantic import ValidationError
 from pytest_mock import MockerFixture
 from vllm.entrypoints.serve.engine.protocol import ErrorInfo, ErrorResponse
 
+from vllm_omni.config.stage_config import StagePipelineConfig
 from vllm_omni.diffusion.request import OmniDiffusionRequest
 from vllm_omni.diffusion.sched.request_scheduler import RequestScheduler
 from vllm_omni.diffusion.sched.step_scheduler import StepScheduler
@@ -1039,6 +1040,38 @@ class TestTTSMethods:
             asyncio.run(server._prepare_speech_generation(request))
         server.shutdown()
 
+    def test_prepare_speech_rejects_typed_non_tts_omni_model(self, mocker: MockerFixture):
+        """Typed Qwen3-Omni stages must hit the same talker guard as legacy stages."""
+        mock_engine_client = mocker.MagicMock()
+        mock_engine_client.errored = False
+        mock_engine_client.tts_max_instructions_length = None
+        mock_engine_client.stage_configs = [
+            SimpleNamespace(
+                stage_pipeline_config=StagePipelineConfig(stage_id=index, model_stage=model_stage),
+                model_config=SimpleNamespace(model_arch=None),
+                worker_type=worker_type,
+            )
+            for index, (model_stage, worker_type) in enumerate(
+                (
+                    ("thinker", "ar"),
+                    ("talker", "ar"),
+                    ("code2wav", "generation"),
+                )
+            )
+        ]
+
+        mock_models = mocker.MagicMock()
+        mock_models.is_base_model.return_value = True
+        server = OmniOpenAIServingSpeech(
+            engine_client=mock_engine_client,
+            models=mock_models,
+            request_logger=mocker.MagicMock(),
+        )
+        request = OpenAICreateSpeechRequest(input="Hello world")
+        with pytest.raises(ValueError, match="only supported for dedicated TTS models"):
+            asyncio.run(server._prepare_speech_generation(request))
+        server.shutdown()
+
     def test_estimate_prompt_len_fallback(self, speech_server):
         """Test prompt length estimation falls back to 2048 when model is unavailable."""
         tts_params = {"text": ["Hello"], "task_type": ["CustomVoice"]}