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vllm-omni/tests/e2e/online_serving/test_qwen3_tts_base.py
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# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
"""
E2E Online tests for Qwen3-TTS model with text input and audio output.
These tests verify the /v1/audio/speech endpoint works correctly with
actual model inference, not mocks.
"""
import os
os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
os.environ["VLLM_TEST_CLEAN_GPU_MEMORY"] = "0"
import pytest
from tests.helpers.mark import hardware_test
from tests.helpers.media import load_test_audio_data_url
from tests.helpers.runtime import OmniServerParams
from tests.helpers.stage_config import get_deploy_config_path
MODEL = "Qwen/Qwen3-TTS-12Hz-0.6B-Base"
# Vendored under tests/assets/qwen3_tts/clone_2.wav so the server does not need
# to fetch the reference audio over HTTPS at request time (CI runners in some
# regions cannot reach the original Aliyun OSS host; see issue #3263).
REF_AUDIO_URL = load_test_audio_data_url("qwen3_tts/clone_2.wav")
REF_TEXT = "Okay. Yeah. I resent you. I love you. I respect you. But you know what? You blew it! And thanks to you."
def get_prompt(prompt_type="text"):
"""Text prompt for text-to-audio tests (same as test_qwen3_omni - beijing test case)."""
prompts = {
"text": "The weather is nice today, perfect for a walk in the park.",
}
return prompts.get(prompt_type, prompts["text"])
def get_max_batch_size(size_type="few"):
"""Batch size for concurrent requests (same as test_qwen3_omni)."""
batch_sizes = {"few": 5, "medium": 100, "large": 256}
return batch_sizes.get(size_type, 5)
tts_server_params = [
pytest.param(
OmniServerParams(
model=MODEL,
stage_config_path=get_deploy_config_path("qwen3_tts.yaml"),
server_args=["--trust-remote-code", "--disable-log-stats"],
),
id="async_chunk",
)
]
@pytest.mark.advanced_model
@pytest.mark.core_model
@pytest.mark.omni
@hardware_test(res={"cuda": "L4"}, num_cards=1)
@pytest.mark.parametrize("omni_server", tts_server_params, indirect=True)
def test_text_to_audio_001(omni_server, openai_client) -> None:
"""
Test text input processing and audio output via OpenAI API.
Deploy Setting: default yaml
Input Modal: text
Output Modal: audio
Input Setting: stream=False
Datasets: few requests
"""
request_config = {
"model": omni_server.model,
"input": get_prompt(),
"stream": False,
"response_format": "wav",
"task_type": "Base",
"voice": "clone",
"ref_audio": REF_AUDIO_URL,
"ref_text": REF_TEXT,
}
openai_client.send_audio_speech_request(request_config, request_num=get_max_batch_size("few"))
@pytest.mark.advanced_model
@pytest.mark.omni
@hardware_test(res={"cuda": "L4"}, num_cards=1)
@pytest.mark.parametrize("omni_server", tts_server_params, indirect=True)
def test_text_to_audio_002(omni_server, openai_client) -> None:
"""
Test text input processing and audio output via OpenAI API.
Deploy Setting: default yaml
Input Modal: text
Output Modal: audio
Input Setting: stream=True
Datasets: single request
"""
request_config = {
"model": omni_server.model,
"input": get_prompt(),
"stream": True,
"response_format": "wav",
"task_type": "Base",
"voice": "clone",
"ref_audio": REF_AUDIO_URL,
"ref_text": REF_TEXT,
}
openai_client.send_audio_speech_request(request_config)