[Bugfix] fix: return 400 for unsupported multi-image edits such as Qwen-Image-Layered (#2298)

Signed-off-by: David Chen <530634352@qq.com>

tests/entrypoints/openai_api/test_image_server.py

@@ -740,6 +740,29 @@ def test_image_edit_images_processing(async_omni_test_client):
     assert processed_images[1].size == (24, 24)
 
 
+def test_image_edit_rejects_multiple_images_when_model_does_not_support_them(async_omni_test_client):
+    img_bytes_1 = make_test_image_bytes((16, 16))
+    img_bytes_2 = make_test_image_bytes((32, 32))
+
+    engine = async_omni_test_client.app.state.engine_client
+    engine.get_diffusion_od_config = lambda: SimpleNamespace(supports_multimodal_inputs=False)
+
+    response = async_omni_test_client.post(
+        "/v1/images/edits",
+        files=[
+            ("image", img_bytes_1),
+            ("image", img_bytes_2),
+        ],
+        data={"prompt": "hello world."},
+    )
+
+    assert response.status_code == 400
+    assert (
+        response.json()["detail"] == "Received multiple input images. Only a single image is supported by this model."
+    )
+    assert engine.captured_prompt is None
+
+
 def test_image_edit_parameter_pass(async_omni_test_client):
     img_bytes_1 = make_test_image_bytes((16, 16))
 

tests/entrypoints/test_async_omni_diffusion.py

@@ -0,0 +1,15 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import pytest
+
+from vllm_omni.entrypoints.async_omni_diffusion import AsyncOmniDiffusion
+
+pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
+
+
+def test_get_diffusion_od_config_returns_direct_config():
+    diffusion = object.__new__(AsyncOmniDiffusion)
+    diffusion.od_config = object()
+
+    assert diffusion.get_diffusion_od_config() is diffusion.od_config

tests/entrypoints/test_omni_entrypoints.py

@@ -379,6 +379,19 @@ def test_openai_serving_models_can_consume_async_omni_compat_attrs():
     assert serving_models.input_processor is input_processor
 
 
+def test_get_diffusion_od_config_returns_diffusion_stage_config():
+    diffusion_od_config = object()
+    omni = object.__new__(AsyncOmni)
+    omni.engine = SimpleNamespace(
+        stage_clients=[
+            SimpleNamespace(stage_type="llm"),
+            SimpleNamespace(stage_type="diffusion", _engine=SimpleNamespace(od_config=diffusion_od_config)),
+        ]
+    )
+
+    assert omni.get_diffusion_od_config() is diffusion_od_config
+
+
 @pytest.mark.asyncio
 async def test_async_omni_yields_only_final_stage_outputs(monkeypatch: pytest.MonkeyPatch):
     engine = FakeAsyncOmniEngine(

vllm_omni/entrypoints/async_omni.py

@@ -118,6 +118,23 @@ class AsyncOmni(EngineClient, OmniBase):
         """Compatibility helper for call sites expecting async vllm config access."""
         return self.vllm_config
 
+    def get_diffusion_od_config(self) -> Any | None:
+        """Return the diffusion-stage config when the pipeline has one."""
+        for stage_client in self.engine.stage_clients:
+            if getattr(stage_client, "stage_type", None) != "diffusion":
+                continue
+
+            od_config = getattr(stage_client, "od_config", None)
+            if od_config is not None:
+                return od_config
+
+            inner_engine = getattr(stage_client, "_engine", None)
+            od_config = getattr(inner_engine, "od_config", None)
+            if od_config is not None:
+                return od_config
+
+        return None
+
     @property
     def model_config(self):
         """Return the model config for the comprehension stage when present."""

vllm_omni/entrypoints/async_omni_diffusion.py

@@ -251,6 +251,10 @@ class AsyncOmniDiffusion:
             finished=True,
         )
 
+    def get_diffusion_od_config(self) -> OmniDiffusionConfig:
+        """Return the diffusion config used by this engine."""
+        return self.od_config
+
     # ------------------------------------------------------------------
     # Public generate API
     # ------------------------------------------------------------------

vllm_omni/entrypoints/openai/api_server.py

@@ -1406,6 +1406,11 @@ async def edit_images(
         if not input_images_list:
             raise HTTPException(status_code=422, detail="Field 'image' or 'url' is required")
         pil_images = await _load_input_images(input_images_list)
+        if len(pil_images) > 1 and not _supports_multimodal_image_inputs(raw_request, engine_client):
+            raise HTTPException(
+                status_code=HTTPStatus.BAD_REQUEST.value,
+                detail="Received multiple input images. Only a single image is supported by this model.",
+            )
         prompt["multi_modal_data"] = {}
         prompt["multi_modal_data"]["image"] = pil_images
 
@@ -1584,6 +1589,20 @@ def _get_engine_and_model(raw_request: Request):
     return engine_client, model_name, normalized_stage_configs
 
 
+def _supports_multimodal_image_inputs(raw_request: Request, engine_client: Any) -> bool:
+    diffusion_engine = getattr(raw_request.app.state, "diffusion_engine", None) or engine_client
+    get_diffusion_od_config = getattr(diffusion_engine, "get_diffusion_od_config", None)
+    od_config = (
+        get_diffusion_od_config() if callable(get_diffusion_od_config) else getattr(diffusion_engine, "od_config", None)
+    )
+
+    if od_config is None:
+        # Preserve the existing compatibility behavior when the diffusion
+        # config is not exposed on the serving surface.
+        return True
+    return bool(getattr(od_config, "supports_multimodal_inputs", False))
+
+
 def _get_lora_from_json_str(lora_body):
     if lora_body is None:
         return None