Signed-off-by: tzhouam <tzhouam@connect.ust.hk> Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
276 lines
9.3 KiB
Python
276 lines
9.3 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
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"""
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E2E online tests for Qwen3-Omni /v1/realtime WebSocket (streaming PCM in, audio out).
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Three scenarios:
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- Ready CI: async_chunk on, smoke only (no send delay, no accuracy check).
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- Merge CI: async_chunk on + send delay, full accuracy check.
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- Merge CI: async_chunk off, no send delay, full accuracy check.
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"""
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from __future__ import annotations
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import asyncio
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import base64
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import io
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import json
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import os
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import wave
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import pytest
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import websockets
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from tests.helpers.mark import hardware_test
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from tests.helpers.media import (
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convert_audio_bytes_to_text,
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cosine_similarity_text,
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generate_synthetic_audio,
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)
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from tests.helpers.runtime import OmniServerParams
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from tests.helpers.stage_config import get_deploy_config_path
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os.environ["VLLM_WORKER_MULTIPROC_METHOD"] = "spawn"
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MODEL = "Qwen/Qwen3-Omni-30B-A3B-Instruct"
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# Synthetic input for realtime E2E (``generate_synthetic_audio``); distinct cache file per phrase.
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REALTIME_SYNTH_PHRASE_TEXT = (
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"Translate into Chinese: Beijing is the Capital of China. It is the center of culture and politics"
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)
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# Simulate realtime upload pacing (``openai_realtime_client.py --send-delay-ms``).
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SEND_DELAY_MS = 200
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# CI overlay bakes in async_chunk: False and covers CUDA/ROCm/XPU via ``platforms:``.
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default_stage_config = get_deploy_config_path("ci/qwen3_omni_moe.yaml")
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realtime_sync_server_params = [
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pytest.param(
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OmniServerParams(
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model=MODEL,
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stage_config_path=default_stage_config,
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use_stage_cli=True,
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),
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id="sync",
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),
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]
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realtime_async_chunk_server_params = [
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pytest.param(
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OmniServerParams(
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model=MODEL,
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stage_config_path=default_stage_config,
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use_stage_cli=True,
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server_args=["--async-chunk"],
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),
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id="async_chunk",
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),
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]
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def _pcm16_mono_16k_from_wav_bytes(wav_bytes: bytes) -> bytes:
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with wave.open(io.BytesIO(wav_bytes), "rb") as wf:
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if wf.getnchannels() != 1:
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raise ValueError(f"Expected mono WAV, got {wf.getnchannels()} channels")
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if wf.getsampwidth() != 2:
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raise ValueError(f"Expected 16-bit PCM, sampwidth={wf.getsampwidth()}")
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if wf.getframerate() != 16000:
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raise ValueError(f"Expected 16 kHz input for /v1/realtime, got {wf.getframerate()} Hz")
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if wf.getcomptype() != "NONE":
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raise ValueError(f"Expected uncompressed PCM, comptype={wf.getcomptype()!r}")
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return wf.readframes(wf.getnframes())
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def _wav_bytes_from_pcm16(pcm: bytes, sample_rate_hz: int) -> bytes:
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buf = io.BytesIO()
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with wave.open(buf, "wb") as wf:
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wf.setnchannels(1)
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wf.setsampwidth(2)
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wf.setframerate(sample_rate_hz)
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wf.writeframes(pcm)
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return buf.getvalue()
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async def _run_realtime_audio_roundtrip(
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host: str,
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port: int,
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model: str,
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pcm16: bytes,
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*,
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chunk_ms: int = 100,
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send_delay_ms: int = 0,
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) -> dict:
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uri = f"ws://{host}:{port}/v1/realtime"
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incremental: list[bytes] = []
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output_sr = 24000
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text_chunks: list[str] = []
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final_text = ""
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delta_events = 0
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bytes_per_ms = 16000 * 2 // 1000
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chunk_bytes = max(bytes_per_ms * chunk_ms, 2)
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async with websockets.connect(uri, max_size=64 * 1024 * 1024) as ws:
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await ws.send(json.dumps({"type": "session.update", "model": model}))
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await ws.send(json.dumps({"type": "input_audio_buffer.commit", "final": False}))
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for i in range(0, len(pcm16), chunk_bytes):
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chunk = pcm16[i : i + chunk_bytes]
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await ws.send(
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json.dumps(
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{
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"type": "input_audio_buffer.append",
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"audio": base64.b64encode(chunk).decode("utf-8"),
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}
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)
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)
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if send_delay_ms > 0:
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await asyncio.sleep(send_delay_ms / 1000.0)
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await ws.send(json.dumps({"type": "input_audio_buffer.commit", "final": True}))
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while True:
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message = await asyncio.wait_for(ws.recv(), timeout=600)
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if isinstance(message, bytes):
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continue
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event = json.loads(message)
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event_type = event.get("type")
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if event_type == "session.created":
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continue
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if event_type == "response.audio.delta":
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delta_events += 1
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sr = event.get("sample_rate_hz")
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if isinstance(sr, int) and sr > 0:
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output_sr = sr
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audio_b64 = event.get("audio", "")
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if audio_b64:
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incremental.append(base64.b64decode(audio_b64))
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continue
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if event_type == "transcription.delta":
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d = event.get("delta", "")
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if d:
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text_chunks.append(d)
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continue
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if event_type == "transcription.done":
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final_text = event.get("text", "") or "".join(text_chunks)
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continue
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if event_type == "response.audio.done":
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break
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if event_type == "error":
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raise AssertionError(f"WebSocket error: {event}")
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raise AssertionError(f"Unexpected WebSocket event: {event}")
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out_pcm = b"".join(incremental)
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return {
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"output_pcm": out_pcm,
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"output_sample_rate": output_sr,
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"transcription_text": final_text if final_text else "".join(text_chunks),
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"delta_events": delta_events,
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}
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def _synthetic_pcm16_input() -> bytes:
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syn = generate_synthetic_audio(
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10,
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1,
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sample_rate=16000,
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phrase_text=REALTIME_SYNTH_PHRASE_TEXT,
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)
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wav_bytes = base64.b64decode(syn["base64"])
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return _pcm16_mono_16k_from_wav_bytes(wav_bytes)
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def _assert_realtime_smoke(result: dict) -> None:
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out_pcm = result["output_pcm"]
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assert result["delta_events"] >= 1
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assert out_pcm, "No output PCM from response.audio.delta"
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assert len(out_pcm) % 2 == 0
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assert len(out_pcm) >= 4096, "Output audio unexpectedly small"
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assert result["output_sample_rate"] > 0
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def _assert_realtime_accuracy(
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result: dict,
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whisper_model_size: str = "large-v3",
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) -> None:
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"""Assert that whisper transcription of audio output matches model text.
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Args:
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result: Roundtrip result dict from ``_run_realtime_audio_roundtrip``.
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whisper_model_size: Whisper model used to transcribe the generated audio
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for the accuracy check. Defaults to ``large-v3``: the default
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``small`` model mishears short Chinese TTS clips (observed:
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北京→韦京 and a dropped leading sentence, sim=0.443), which
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caused spurious sim<0.8 failures under async_chunk codec
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variability even though audio generation was correct. large-v3
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transcribes these clips reliably, so a failure here now points
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at the model, not the ASR grader.
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"""
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final_text = (result["transcription_text"] or "").strip()
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assert final_text, "Expected non-empty transcription (model text stream)"
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wav_out = _wav_bytes_from_pcm16(result["output_pcm"], result["output_sample_rate"])
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whisper_text = convert_audio_bytes_to_text(wav_out, model_size=whisper_model_size).strip()
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assert whisper_text, "Whisper returned empty string for synthesized output audio"
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sim = cosine_similarity_text(whisper_text.lower(), final_text.lower())
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assert sim > 0.8, (
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f"Output audio transcript should match model text (sim={sim:.3f}): "
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f"whisper={whisper_text!r}, model_text={final_text!r}"
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)
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class TestQwen3OmniRealtimeWebSocket:
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@pytest.mark.advanced_model
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@pytest.mark.omni
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@hardware_test(res={"cuda": "H100", "rocm": "MI325"}, num_cards=2)
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@pytest.mark.parametrize("omni_server", realtime_async_chunk_server_params, indirect=True)
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def test_streaming_audio_input_pcm_output_async_chunk(self, omni_server) -> None:
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"""Merge CI: async_chunk on, paced upload, full accuracy check."""
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pcm16 = _synthetic_pcm16_input()
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result = asyncio.run(
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_run_realtime_audio_roundtrip(
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omni_server.host,
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omni_server.port,
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omni_server.model,
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pcm16,
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chunk_ms=100,
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send_delay_ms=SEND_DELAY_MS,
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)
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)
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_assert_realtime_smoke(result)
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_assert_realtime_accuracy(result)
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@pytest.mark.advanced_model
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@pytest.mark.omni
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@hardware_test(res={"cuda": "H100", "rocm": "MI325"}, num_cards=2)
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@pytest.mark.parametrize("omni_server", realtime_sync_server_params, indirect=True)
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def test_streaming_audio_input_pcm_output(self, omni_server) -> None:
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"""Merge CI: async_chunk off, no send delay, full accuracy check."""
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pcm16 = _synthetic_pcm16_input()
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result = asyncio.run(
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_run_realtime_audio_roundtrip(
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omni_server.host,
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omni_server.port,
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omni_server.model,
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pcm16,
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chunk_ms=100,
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send_delay_ms=0,
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)
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)
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_assert_realtime_smoke(result)
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_assert_realtime_accuracy(result)
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