Files
vllm-omni/tests/benchmarks/test_serve_cli.py
T
2026-01-31 10:15:26 +08:00

61 lines
1.8 KiB
Python

import subprocess
from pathlib import Path
import pytest
from tests.conftest import OmniServer
models = ["Qwen/Qwen3-Omni-30B-A3B-Instruct"]
stage_configs = [str(Path(__file__).parent.parent / "e2e" / "stage_configs" / "qwen3_omni_ci.yaml")]
# Create parameter combinations for model and stage config
test_params = [(model, stage_config) for model in models for stage_config in stage_configs]
@pytest.fixture(scope="module")
def omni_server(request):
"""Start vLLM-Omni server as a subprocess with actual model weights.
Uses session scope so the server starts only once for the entire test session.
Multi-stage initialization can take 10-20+ minutes.
"""
model, stage_config_path = request.param
print(f"Starting OmniServer with model: {model}")
print("This may take 10-20+ minutes for initialization...")
with OmniServer(model, ["--stage-configs-path", stage_config_path, "--stage-init-timeout", "120"]) as server:
print("OmniServer started successfully")
yield server
print("OmniServer stopped")
@pytest.mark.parametrize("omni_server", test_params, indirect=True)
def test_bench_serve_chat(omni_server):
command = [
"vllm",
"bench",
"serve",
"--omni",
"--model",
omni_server.model,
"--port",
str(omni_server.port),
"--dataset-name",
"random",
"--random-input-len",
"32",
"--random-output-len",
"4",
"--num-prompts",
"5",
"--endpoint",
"/v1/chat/completions",
"--backend",
"openai-chat-omni",
]
result = subprocess.run(command, capture_output=True, text=True)
print(result.stdout)
print(result.stderr)
assert result.returncode == 0, f"Benchmark failed: {result.stderr}"