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vllm-omni/tests/e2e/online_serving/test_flux2_klein.py
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"""
Tests for Flux2 Klein; currently Dev is implemented separately,
but ideally these models will fold together in the future.
"""
import pytest
from tests.helpers.mark import hardware_marks
from tests.helpers.runtime import (
OmniServer,
OmniServerParams,
OpenAIClientHandler,
dummy_messages_from_mix_data,
)
FOUR_CARD_FEATURE_MARKS = hardware_marks(res={"cuda": "L4"}, num_cards=4)
POSITIVE_PROMPT = "A cat sitting on a windowsill"
NEGATIVE_PROMPT = "blurry, low quality"
# For now, we only test a good configuration for this model to keep the CI
# light, but in the near future may explore using random models to check
# cross-feature compatibility more generally.
def _get_diffusion_feature_cases(model: str):
return [
# FP8 / Hybrid sequence parallelism
pytest.param(
OmniServerParams(
model=model,
),
id="default",
marks=FOUR_CARD_FEATURE_MARKS,
),
]
@pytest.mark.advanced_model
@pytest.mark.core_model
@pytest.mark.diffusion
@pytest.mark.parametrize(
"omni_server",
_get_diffusion_feature_cases(
model="black-forest-labs/FLUX.2-klein-4B",
),
indirect=True,
)
def test_text_to_image_001(omni_server: OmniServer, openai_client: OpenAIClientHandler):
messages = dummy_messages_from_mix_data(content_text=POSITIVE_PROMPT)
request_config = {
"model": omni_server.model,
"messages": messages,
"extra_body": {
"height": 512,
"width": 512,
"num_inference_steps": 2,
"negative_prompt": NEGATIVE_PROMPT,
"true_cfg_scale": 4.0,
"seed": 42,
},
}
openai_client.send_diffusion_request(request_config)