""" Recommended tests of diffusion features that are available in online serving mode and are supported by the following model: - LongCat-Image-Edit: image-to-image edit with a single image + single edit prompt input Coverage: - CPU offloading (model-level sequential offload via --enable-cpu-offload) - Cache-DiT - SP (Ulysses) This validates: - Successful image generation at the expected 1024x1024 resolution with recommended feature combinations """ import pytest from tests.helpers.mark import hardware_marks from tests.helpers.media import generate_synthetic_image from tests.helpers.runtime import ( OmniServer, OmniServerParams, OpenAIClientHandler, dummy_messages_from_mix_data, ) EDIT_PROMPT = "Transform this modern image into a cinematic animation style with vibrant colors and soft lighting." NEGATIVE_PROMPT = "blurry, low quality, distorted, oversaturated" SINGLE_CARD_FEATURE_MARKS = hardware_marks(res={"cuda": "H100"}) def _get_diffusion_feature_cases(model: str): """Return diffusion feature cases for LongCat-Image-Edit.""" return [ pytest.param( OmniServerParams( model=model, ), id="default", marks=SINGLE_CARD_FEATURE_MARKS, ) ] @pytest.mark.advanced_model @pytest.mark.core_model @pytest.mark.diffusion @pytest.mark.parametrize( "omni_server", _get_diffusion_feature_cases("meituan-longcat/LongCat-Image-Edit"), indirect=True, ) def test_longcat_image_edit(omni_server: OmniServer, openai_client: OpenAIClientHandler): """Test the recommended feature combinations for LongCat-Image-Edit.""" image_data_url = f"data:image/jpeg;base64,{generate_synthetic_image(512, 512)['base64']}" messages = dummy_messages_from_mix_data(image_data_url=image_data_url, content_text=EDIT_PROMPT) request_config = { "model": omni_server.model, "messages": messages, "extra_body": { "height": 1024, "width": 1024, "num_inference_steps": 2, "negative_prompt": NEGATIVE_PROMPT, "guidance_scale": 4.0, "seed": 42, }, } openai_client.send_diffusion_request(request_config)