[diffusion][feature] Add LingBot-Video T2I and TI2V generation modes (#5311)

Signed-off-by: wtz2333 <2955110911@qq.com>
Co-authored-by: Claude <noreply@anthropic.com>

tests/entrypoints/openai_api/test_video_server.py

@@ -28,6 +28,7 @@ from vllm_omni.entrypoints.openai.api_server import router
 from vllm_omni.entrypoints.openai.protocol.videos import (
     VideoGenerationRequest,
     VideoGenerationStatus,
+    VideoParams,
     VideoResponse,
 )
 from vllm_omni.entrypoints.openai.serving_video import OmniOpenAIServingVideo
@@ -440,6 +441,75 @@ def test_i2v_video_generation_resizes_input_to_requested_dimensions(test_client,
     assert input_image.size == (96, 64)
 
 
+def test_i2v_extra_params_dimensions_preserve_input_image_geometry(test_client, mocker: MockerFixture):
+    image_bytes = _make_test_image_bytes((48, 48))
+    mocker.patch(
+        "vllm_omni.entrypoints.openai.serving_video._encode_video_bytes",
+        return_value=b"fake-video",
+    )
+    response = test_client.post(
+        "/v1/videos",
+        data={
+            "prompt": "A bear playing with yarn.",
+            "extra_params": json.dumps({"width": 96, "height": 64}),
+        },
+        files={"input_reference": ("input.png", image_bytes, "image/png")},
+    )
+
+    assert response.status_code == 200
+    video_id = response.json()["id"]
+    _wait_for_status(test_client, video_id, VideoGenerationStatus.COMPLETED.value)
+
+    engine = test_client.app.state.openai_serving_video._engine_client
+    input_image = engine.captured_prompt["multi_modal_data"]["image"]
+    assert isinstance(input_image, Image.Image)
+    assert input_image.size == (48, 48)
+    sampling_params = engine.captured_sampling_params_list[0]
+    assert sampling_params.extra_args["width"] == 96
+    assert sampling_params.extra_args["height"] == 64
+
+
+@pytest.mark.parametrize(
+    ("generation_request", "expected_num_frames", "expected_duration"),
+    [
+        (
+            VideoGenerationRequest(prompt="top-level frames", seconds="5", num_frames=9),
+            9,
+            5.0,
+        ),
+        (
+            VideoGenerationRequest(prompt="nested frames", video_params=VideoParams(num_frames=9)),
+            9,
+            None,
+        ),
+        (
+            VideoGenerationRequest(prompt="seconds only", seconds="5"),
+            120,
+            5.0,
+        ),
+    ],
+)
+def test_video_generation_bridges_request_fields(generation_request, expected_num_frames, expected_duration):
+    engine = FakeAsyncOmni()
+    handler = OmniOpenAIServingVideo.for_diffusion(
+        diffusion_engine=engine,
+        model_name="Wan-AI/Wan2.2-T2V-A14B-Diffusers",
+    )
+
+    asyncio.run(handler._run_and_extract(generation_request, "field-bridge"))
+
+    sampling = engine.captured_sampling_params_list[0]
+    # Top-level ``seconds`` bridges into extra_args["duration"]; num_frames is
+    # passed through (or derived as seconds x fps when omitted). No private
+    # provenance channel is injected.
+    assert "_vllm_request_context" not in sampling.extra_args
+    assert sampling.num_frames == expected_num_frames
+    if expected_duration is None:
+        assert "duration" not in sampling.extra_args
+    else:
+        assert sampling.extra_args["duration"] == expected_duration
+
+
 def test_i2v_video_generation_with_image_reference_form(test_client, mocker: MockerFixture):
     mocker.patch(
         "vllm_omni.entrypoints.openai.serving_video._encode_video_bytes",