import pytest

from app.integrations.openai_compatible import OpenAICompatibleGateway


def image_values(profile: str, model_id: str) -> dict:
    return {
        "model_pool": [
            {
                "id": "image",
                "name": "测试生图",
                "model_id": model_id,
                "category": "multimodal",
                "provider": "lingke",
                "base_url": "https://api.lk888.ai",
                "api_key": "secret",
                "capabilities": ["image_generation"],
                "models_path": "/v1/models",
                "image_protocol": "aigc_media",
                "image_parameter_profile": profile,
                "image_generation_path": "/v1/media/generate",
                "image_status_path": "/v1/media/status",
                "enabled": True,
            }
        ],
        "image_routing_mode": "manual",
        "image_model_id": "image",
    }


@pytest.mark.asyncio
@pytest.mark.parametrize(
    ("profile", "model_id", "options", "expected_params"),
    [
        ("gpt_image_2", "gpt-image-2", {"size": "1024x1024", "quality": "low"}, {"size": "1024x1024", "quality": "low"}),
        ("nano_banana_pro", "gemini-3-pro-image-preview", {"aspect_ratio": "1:1", "size": "1K"}, {"aspectRatio": "1:1", "imageSize": "1K"}),
        ("seedream_5_pro", "doubao-seedream-5-0-pro-260628", {"aspectRatio": "1:1", "imageSize": "1K"}, {"aspect_ratio": "1:1", "size": "1K"}),
    ],
)
async def test_aigc_media_profiles_send_documented_parameter_names(
    monkeypatch,
    profile: str,
    model_id: str,
    options: dict,
    expected_params: dict,
) -> None:
    requests: list[dict] = []

    class FakeResponse:
        def raise_for_status(self) -> None:
            return None

        def json(self) -> dict:
            return {"data": [{"url": "https://cdn.example.com/test.png"}]}

    class FakeClient:
        async def __aenter__(self):
            return self

        async def __aexit__(self, *args) -> None:
            return None

        async def post(self, url, **kwargs) -> FakeResponse:
            requests.append({"url": url, **kwargs})
            return FakeResponse()

    monkeypatch.setattr("app.integrations.openai_compatible.httpx.AsyncClient", lambda **kwargs: FakeClient())

    result = await OpenAICompatibleGateway(image_values(profile, model_id)).generate_image("测试", **options)

    assert result["data"][0]["url"].endswith("test.png")
    assert requests[0]["url"] == "https://api.lk888.ai/v1/media/generate"
    assert requests[0]["json"] == {"model": model_id, "prompt": "测试", "params": expected_params}


@pytest.mark.asyncio
async def test_aigc_media_polls_task_until_result_url(monkeypatch) -> None:
    class FakeResponse:
        def __init__(self, payload: dict) -> None:
            self.payload = payload

        def raise_for_status(self) -> None:
            return None

        def json(self) -> dict:
            return self.payload

    class FakeClient:
        async def __aenter__(self):
            return self

        async def __aexit__(self, *args) -> None:
            return None

        async def post(self, *args, **kwargs) -> FakeResponse:
            return FakeResponse({"task_id": 123})

        async def get(self, url, **kwargs) -> FakeResponse:
            assert url == "https://api.lk888.ai/v1/media/status"
            assert kwargs["params"] == {"task_id": 123}
            return FakeResponse({"task_id": 123, "state": "success", "is_final": True, "result_url": "https://cdn.example.com/final.png"})

    async def no_sleep(*args) -> None:
        return None

    monkeypatch.setattr("app.integrations.openai_compatible.httpx.AsyncClient", lambda **kwargs: FakeClient())
    monkeypatch.setattr("app.integrations.openai_compatible.asyncio.sleep", no_sleep)

    result = await OpenAICompatibleGateway(image_values("seedream_5_pro", "doubao-seedream-5-0-pro-260628")).generate_image("测试")

    assert result["state"] == "success"
    assert result["data"] == [{"url": "https://cdn.example.com/final.png"}]