import os
import unittest
from types import SimpleNamespace

from sglang.srt.utils import kill_process_tree
from sglang.test.ci.ci_register import register_cuda_ci
from sglang.test.run_eval import run_eval
from sglang.test.test_utils import (
    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
    DEFAULT_URL_FOR_TEST,
    CustomTestCase,
    popen_launch_server,
)

register_cuda_ci(est_time=300, suite="nightly-4-gpu-b200", nightly=True)


class TestFlashinferTrtllmGenAttnBackend(CustomTestCase):
    @classmethod
    def setUpClass(cls):
        cls.model = "Qwen/Qwen3-Next-80B-A3B-Instruct"
        cls.base_url = DEFAULT_URL_FOR_TEST
        cls.process = popen_launch_server(
            cls.model,
            cls.base_url,
            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
            env={**os.environ, "SGLANG_ENABLE_JIT_DEEPGEMM": "False"},
            other_args=[
                "--attention-backend",
                "trtllm_mha",
                "--cuda-graph-max-bs-decode",
                "512",
                "--tp-size",
                "4",
                "--ep-size",
                "4",
                "--mem-fraction-static",
                "0.7",
                "--mamba-ssm-dtype",
                "bfloat16",
                "--disable-radix-cache",
            ],
        )

    @classmethod
    def tearDownClass(cls):
        kill_process_tree(cls.process.pid)

    def test_gsm8k(self):
        args = SimpleNamespace(
            base_url=self.base_url,
            model=self.model,
            eval_name="gsm8k",
            api="completion",
            max_tokens=512,
            num_examples=200,
            num_threads=128,
        )
        metrics = run_eval(args)
        print(f"{metrics=}")
        self.assertGreater(metrics["score"], 0.93)


if __name__ == "__main__":
    unittest.main()
