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240 changes: 199 additions & 41 deletions tests/models/multimodal/generation/test_voxtral_streaming.py
Original file line number Diff line number Diff line change
@@ -1,5 +1,6 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import asyncio
from dataclasses import asdict

import pytest
Expand All @@ -9,33 +10,71 @@
StreamingMode,
TranscriptionRequest,
)
from mistral_common.tokens.tokenizers.audio import AudioConfig
from mistral_common.tokens.tokenizers.mistral import MistralTokenizer

from vllm import LLM, EngineArgs, SamplingParams
from vllm.assets.audio import AudioAsset
from vllm.engine.arg_utils import AsyncEngineArgs
from vllm.inputs.data import TokensPrompt
from vllm.v1.engine.async_llm import AsyncLLM, StreamingInput

MODEL_NAME = "mistralai/Voxtral-Mini-3B-Realtime-2602"
ENGINE_CONFIG = dict(
model=MODEL_NAME,
max_model_len=8192,
max_num_seqs=4,
limit_mm_per_prompt={"audio": 1},
config_format="mistral",
load_format="mistral",
tokenizer_mode="mistral",
enforce_eager=True,
gpu_memory_utilization=0.4,
)

def _get_engine(path: str) -> LLM:
engine_args = EngineArgs(
model=path,
max_model_len=8192,
max_num_seqs=1,
limit_mm_per_prompt={"audio": 1},
config_format="mistral",
load_format="mistral",
tokenizer_mode="mistral",
enforce_eager=True,
gpu_memory_utilization=0.4,
)

EXPECTED_TEXT = [
(
" First words I spoke in the original phonograph. "
"A little piece of practical poetry. Mary had a little lamb,"
" its fleece was quite a slow, and everywhere that Mary went, "
"the lamb was sure to go."
),
(
" And the 0-1 pitch on the way to Edgar Martinez. Swung on"
" the line. Down the left field line for OBS. Here comes Joy. "
"Here is Junior to third base. They're going to wave him in. "
"The throw to the plate will be late. The Mariners are going"
" to play. For the American League Championship, "
"I don't believe it. It just continues. My, oh, my."
),
]


@pytest.fixture
def audio_assets() -> list[AudioAsset]:
return [AudioAsset("mary_had_lamb"), AudioAsset("winning_call")]


@pytest.fixture
def tokenizer() -> MistralTokenizer:
return MistralTokenizer.from_hf_hub(MODEL_NAME)


@pytest.fixture
def engine() -> LLM:
engine_args = EngineArgs(**ENGINE_CONFIG)
return LLM(**asdict(engine_args))


@pytest.mark.skip(reason="Voxtral streaming is not yet public")
def test_voxtral_streaming_forward():
audio_assets = [AudioAsset("mary_had_lamb"), AudioAsset("winning_call")]
@pytest.fixture
def async_engine() -> AsyncLLM:
engine_args = AsyncEngineArgs(**ENGINE_CONFIG)
return AsyncLLM.from_engine_args(engine_args)

model_name = "mistralai/Voxtral-Mini-3B-Realtime-2602"
tokenizer = MistralTokenizer.from_hf_hub(model_name)

@pytest.mark.skip(reason="Voxtral streaming is not yet public")

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skip for now

def test_voxtral_streaming_forward(audio_assets, tokenizer, engine):
audio_config = tokenizer.instruct_tokenizer.tokenizer.audio

def from_file(file_path: str):
Expand All @@ -58,11 +97,7 @@ def from_file(file_path: str):

for tokens, audio_array in tokenized_list:
num_samples = audio_array.shape[0]
max_tokens = (
audio_config.num_audio_tokens(num_samples)
- audio_config.num_delay_tokens
- 1
)
max_tokens = audio_config.num_audio_tokens(num_samples) - len(tokens) - 1
sampling_params.append(SamplingParams(temperature=0.0, max_tokens=max_tokens))

input_dict = {
Expand All @@ -71,27 +106,150 @@ def from_file(file_path: str):
}
inputs.append(input_dict)

llm = _get_engine(model_name)
outputs = llm.generate(
outputs = engine.generate(
inputs,
sampling_params=sampling_params,
)

texts = [out.outputs[0].text for out in outputs]
expected = [
(
" First words I spoke in the original phonograph. "
"A little piece of practical poetry. Mary had a little lamb,"
" it sleeps with quite a snow, and everywhere that Mary went, "
"the lamb was sure to go."
),
(
" And the 0-1 pitch on the way to Edgar Martinez. Swung on"
" the line. Down the left field line for OBS. Here comes Joy. "
"Here is Junior to third base. They're going to wave him in. "
"The throw to the plate will be late. The Mariners are going"
" to play. For the American League Championship, "
"I don't believe it. It just continues. My oh, my."
),
]
assert texts == expected
assert texts == EXPECTED_TEXT


class RealTimeAudioInput:
"""
This class is used to stream an audio file just as
if it would be streamed in real-time.
"""

def __init__(self, tokenizer: MistralTokenizer) -> None:
# TODO(Patrick) - put these into the tokenizer config
self._look_ahead_in_ms = 2.5

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audio input takes care of look ahead and look back

self._look_back_in_ms = 52.5

self._tokenizer = tokenizer
self._config: AudioConfig = (
self._tokenizer.instruct_tokenizer.audio_encoder.audio_config
)
self._sampling_rate = self._config.sampling_rate

self._audio: Audio | None = None

# mutable objects
self._start = 0

n_left_pad_samples = (
self._config.raw_audio_length_per_tok * self._config.n_left_pad_tokens
)
self._end = self.streaming_delay + n_left_pad_samples + self.streaming_size
self._queue: asyncio.Queue[StreamingInput | None] = asyncio.Queue()

@classmethod
async def create(cls, audio: Audio, tokenizer: MistralTokenizer):
self = cls(tokenizer)

# we're doing "OFFLINE" encoding here to right & left pad the audio since
# we have access to the whole audio
# if we'd do an actual online realtime streaming application we
# should instead pass `StreamingMode.ONLINE`
req = TranscriptionRequest(
streaming=StreamingMode.OFFLINE,
audio=RawAudio.from_audio(audio),
language=None,
)
audio_enc = self._tokenizer.encode_transcription(req)
self._audio = audio_enc.audios[0]

# add first request
await self.add_tokens(audio_enc.tokens)

return self

@property
def look_ahead(self) -> int:
return self._get_len_in_samples(self._look_ahead_in_ms)

@property
def look_back(self) -> int:
return self._get_len_in_samples(self._look_back_in_ms)

@property
def streaming_delay(self) -> int:
return self._get_len_in_samples(self._config.transcription_delay_ms)

@property
def streaming_size(self) -> int:
stream_size_in_ms = 1000 / self._config.frame_rate
return self._get_len_in_samples(stream_size_in_ms)

def _get_len_in_samples(self, len_in_ms: float) -> int:
_len_in_s = self._sampling_rate * len_in_ms / 1000
assert _len_in_s.is_integer(), _len_in_s
len_in_s = int(_len_in_s)

return len_in_s

async def add_tokens(self, tokens: list[int]) -> None:
assert self._audio is not None
if self._start >= len(self._audio.audio_array):
self.stop()
return

_end = self._end + self.look_ahead
_start = max(0, self._start - self.look_back)

multi_modal_data = {"audio": (self._audio.audio_array[_start:_end], None)}

prompt = TokensPrompt(
prompt_token_ids=tokens, multi_modal_data=multi_modal_data
)

await self._queue.put(StreamingInput(prompt))

# increase
self._start = self._end
self._end = self._end + self.streaming_size

def stop(self):
self._queue.put_nowait(None)

async def generator(self):
while (item := await self._queue.get()) is not None:
yield item


@pytest.mark.asyncio
@pytest.mark.skip(reason="Voxtral streaming is not yet public")

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skip for now - important to make sure async generator works as expected

async def test_voxtral_streaming_generator(audio_assets, tokenizer, async_engine):
sampling_params = SamplingParams(temperature=0.0, max_tokens=1)

output_tokens_list = []
for i, audio_asset in enumerate(audio_assets):
output_tokens = []
audio = Audio.from_file(audio_asset.get_local_path(), strict=False)
streaming_input = await RealTimeAudioInput.create(
audio=audio, tokenizer=tokenizer
)

request_id = f"session-{i}"

async for resp in async_engine.generate(
prompt=streaming_input.generator(),
sampling_params=sampling_params,
request_id=request_id,
):
tokens = resp.outputs[0].token_ids[-1:]

output_tokens.extend(tokens)
await streaming_input.add_tokens(tokens)

output_tokens_list.append(output_tokens)

texts = [tokenizer.decode(output_tokens) for output_tokens in output_tokens_list]

# 'true' streaming and 'offline' streaming differ a bit because log-mels are
# differently noramalized
# TODO(Patrick) - check if we want to align or not
texts[0] = texts[0].replace("He has f", "F")

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small diff because of log-mel

texts[1] = texts[1].replace("a base hit", "OBS").replace("oh my", "oh, my")

assert texts == EXPECTED_TEXT