Support online use_audio_in_video (#36319)

Signed-off-by: Tianyu Guo <guoty9@mail2.sysu.edu.cn>
Signed-off-by: Isotr0py <mozf@mail2.sysu.edu.cn>
Co-authored-by: Isotr0py <mozf@mail2.sysu.edu.cn>

vllm/entrypoints/chat_utils.py

@@ -564,7 +564,9 @@ class BaseMultiModalItemTracker(ABC, Generic[_T]):
         return self.model_cls.get_placeholder_str(modality, num_items)
 
     @abstractmethod
-    def create_parser(self) -> "BaseMultiModalContentParser":
+    def create_parser(
+        self, mm_processor_kwargs: dict[str, Any] | None = None
+    ) -> "BaseMultiModalContentParser":
         raise NotImplementedError
 
 
@@ -690,8 +692,10 @@ class MultiModalItemTracker(BaseMultiModalItemTracker[tuple[object, str | None]]
             dict(self._items_by_modality), self.mm_processor, self._modality_order
         )
 
-    def create_parser(self) -> "BaseMultiModalContentParser":
-        return MultiModalContentParser(self)
+    def create_parser(
+        self, mm_processor_kwargs: dict[str, Any] | None = None
+    ) -> "BaseMultiModalContentParser":
+        return MultiModalContentParser(self, mm_processor_kwargs=mm_processor_kwargs)
 
 
 class AsyncMultiModalItemTracker(
@@ -712,8 +716,12 @@ class AsyncMultiModalItemTracker(
             resolved_items_by_modality, self.mm_processor, self._modality_order
         )
 
-    def create_parser(self) -> "BaseMultiModalContentParser":
-        return AsyncMultiModalContentParser(self)
+    def create_parser(
+        self, mm_processor_kwargs: dict[str, Any] | None = None
+    ) -> "BaseMultiModalContentParser":
+        return AsyncMultiModalContentParser(
+            self, mm_processor_kwargs=mm_processor_kwargs
+        )
 
 
 class BaseMultiModalContentParser(ABC):
@@ -778,7 +786,11 @@ class BaseMultiModalContentParser(ABC):
 
 
 class MultiModalContentParser(BaseMultiModalContentParser):
-    def __init__(self, tracker: MultiModalItemTracker) -> None:
+    def __init__(
+        self,
+        tracker: MultiModalItemTracker,
+        mm_processor_kwargs: dict[str, Any] | None = None,
+    ) -> None:
         super().__init__()
 
         self._tracker = tracker
@@ -790,6 +802,8 @@ class MultiModalContentParser(BaseMultiModalContentParser):
             allowed_media_domains=tracker.allowed_media_domains,
         )
 
+        self._mm_processor_kwargs = mm_processor_kwargs
+
     @property
     def model_config(self) -> ModelConfig:
         return self._tracker.model_config
@@ -886,9 +900,23 @@ class MultiModalContentParser(BaseMultiModalContentParser):
         placeholder = self._tracker.add("video", (video, uuid))
         self._add_placeholder("video", placeholder)
 
+        # Extract audio from video if use_audio_in_video is True
+        if (
+            video_url
+            and self._mm_processor_kwargs
+            and self._mm_processor_kwargs.get("use_audio_in_video", False)
+        ):
+            audio = self._connector.fetch_audio(video_url) if video_url else None
+            audio_placeholder = self._tracker.add("audio", (audio, uuid))
+            self._add_placeholder("audio", audio_placeholder)
+
 
 class AsyncMultiModalContentParser(BaseMultiModalContentParser):
-    def __init__(self, tracker: AsyncMultiModalItemTracker) -> None:
+    def __init__(
+        self,
+        tracker: AsyncMultiModalItemTracker,
+        mm_processor_kwargs: dict[str, Any] | None = None,
+    ) -> None:
         super().__init__()
 
         self._tracker = tracker
@@ -898,6 +926,7 @@ class AsyncMultiModalContentParser(BaseMultiModalContentParser):
             allowed_local_media_path=tracker.allowed_local_media_path,
             allowed_media_domains=tracker.allowed_media_domains,
         )
+        self._mm_processor_kwargs: dict[str, Any] | None = mm_processor_kwargs
 
     @property
     def model_config(self) -> ModelConfig:
@@ -1033,6 +1062,16 @@ class AsyncMultiModalContentParser(BaseMultiModalContentParser):
         placeholder = self._tracker.add("video", coro)
         self._add_placeholder("video", placeholder)
 
+        # Extract audio from video if use_audio_in_video is True
+        if (
+            video_url
+            and self._mm_processor_kwargs
+            and self._mm_processor_kwargs.get("use_audio_in_video", False)
+        ):
+            audio_coro = self._audio_with_uuid_async(video_url, uuid)
+            audio_placeholder = self._tracker.add("audio", audio_coro)
+            self._add_placeholder("audio", audio_placeholder)
+
 
 @dataclass
 class ChatTemplateConfig:
@@ -1343,10 +1382,11 @@ def _parse_chat_message_content_parts(
     *,
     wrap_dicts: bool,
     interleave_strings: bool,
+    mm_processor_kwargs: dict[str, Any] | None = None,
 ) -> list[ConversationMessage]:
     content = list[_ContentPart]()
 
-    mm_parser = mm_tracker.create_parser()
+    mm_parser = mm_tracker.create_parser(mm_processor_kwargs=mm_processor_kwargs)
 
     for part in parts:
         parse_res = _parse_chat_message_content_part(
@@ -1464,6 +1504,7 @@ def _parse_chat_message_content(
     mm_tracker: BaseMultiModalItemTracker,
     content_format: ChatTemplateContentFormat,
     interleave_strings: bool,
+    mm_processor_kwargs: dict[str, Any] | None = None,
 ) -> list[ConversationMessage]:
     role = message["role"]
     content = message.get("content")
@@ -1479,6 +1520,7 @@ def _parse_chat_message_content(
         mm_tracker,
         wrap_dicts=(content_format == "openai"),
         interleave_strings=interleave_strings,
+        mm_processor_kwargs=mm_processor_kwargs,
     )
 
     for result_msg in result:
@@ -1540,6 +1582,7 @@ def parse_chat_messages(
     model_config: ModelConfig,
     content_format: ChatTemplateContentFormat,
     media_io_kwargs: dict[str, dict[str, Any]] | None = None,
+    mm_processor_kwargs: dict[str, Any] | None = None,
 ) -> tuple[
     list[ConversationMessage],
     MultiModalDataDict | None,
@@ -1558,6 +1601,7 @@ def parse_chat_messages(
                 and model_config.multimodal_config is not None
                 and model_config.multimodal_config.interleave_mm_strings
             ),
+            mm_processor_kwargs=mm_processor_kwargs,
         )
 
         conversation.extend(sub_messages)
@@ -1574,6 +1618,7 @@ async def parse_chat_messages_async(
     model_config: ModelConfig,
     content_format: ChatTemplateContentFormat,
     media_io_kwargs: dict[str, dict[str, Any]] | None = None,
+    mm_processor_kwargs: dict[str, Any] | None = None,
 ) -> tuple[
     list[ConversationMessage],
     MultiModalDataDict | None,
@@ -1594,6 +1639,7 @@ async def parse_chat_messages_async(
                 and model_config.multimodal_config is not None
                 and model_config.multimodal_config.interleave_mm_strings
             ),
+            mm_processor_kwargs=mm_processor_kwargs,
         )
 
         conversation.extend(sub_messages)

vllm/entrypoints/openai/engine/serving.py

@@ -892,6 +892,7 @@ class OpenAIServing:
         ).with_defaults(
             default_template_kwargs,
             default_media_io_kwargs=(mm_config.media_io_kwargs if mm_config else None),
+            default_mm_processor_kwargs=getattr(request, "mm_processor_kwargs", None),
         )
 
         (conversation,), (engine_prompt,) = await renderer.render_chat_async(

vllm/model_executor/models/qwen2_5_omni_thinker.py

@@ -78,7 +78,11 @@ from vllm.multimodal.parse import (
     ModalityDataItems,
     MultiModalDataItems,
 )
-from vllm.multimodal.processing import BaseDummyInputsBuilder
+from vllm.multimodal.processing import (
+    BaseDummyInputsBuilder,
+    ProcessorInputs,
+    TimingContext,
+)
 from vllm.multimodal.processing.processor import (
     BaseMultiModalProcessor,
     MultiModalPromptUpdates,
@@ -811,6 +815,16 @@ class Qwen2_5OmniThinkerMultiModalProcessor(
             ),
         ]
 
+    def _cached_apply_hf_processor(
+        self,
+        inputs: ProcessorInputs,
+        timing_ctx: TimingContext,
+    ):
+        mm_processor_kwargs = inputs.hf_processor_mm_kwargs
+        if mm_processor_kwargs.get("use_audio_in_video", False):
+            return self._apply_hf_processor(inputs, timing_ctx)
+        return super()._cached_apply_hf_processor(inputs, timing_ctx)
+
     def _apply_hf_processor_main(
         self,
         prompt: str | list[int],

vllm/multimodal/media/audio.py

@@ -82,6 +82,35 @@ def extract_audio_from_video_bytes(
     return audio, float(native_sr)
 
 
+def is_video(data: bytes) -> bool:
+    """Check if the fetched bytes are video"""
+    if len(data) < 12:
+        return False
+
+    box_type = data[4:8]
+    major_brand = data[8:12]
+
+    MP4_BRANDS = {
+        b"mp41",
+        b"mp42",  # MP4
+        b"isom",  # ISO Base Media
+        b"iso2",
+        b"iso4",
+        b"iso5",
+        b"iso6",
+        b"M4V ",
+        b"M4A ",  # Apple
+        b"avc1",  # H.264
+        b"dash",  # DASH
+        b"mmp4",
+        b"MSNV",
+    }
+
+    is_avi = data[:4] == b"RIFF" and major_brand == b"AVI "
+    is_mp4 = box_type == b"ftyp" and major_brand in MP4_BRANDS
+    return is_mp4 or is_avi
+
+
 class AudioMediaIO(MediaIO[tuple[npt.NDArray, float]]):
     """Configuration values can be user-provided either by --media-io-kwargs or
     by the runtime API field "media_io_kwargs". Ensure proper validation and
@@ -100,6 +129,8 @@ class AudioMediaIO(MediaIO[tuple[npt.NDArray, float]]):
         self.kwargs = kwargs
 
     def load_bytes(self, data: bytes) -> tuple[npt.NDArray, float]:
+        if is_video(data):
+            return extract_audio_from_video_bytes(data)
         return librosa.load(BytesIO(data), sr=None)
 
     def load_base64(

vllm/renderers/deepseek_v32.py

@@ -50,6 +50,7 @@ class DeepseekV32Renderer(BaseRenderer[DeepseekV32Tokenizer]):
             self.model_config,
             content_format="string",
             media_io_kwargs=params.media_io_kwargs,
+            mm_processor_kwargs=params.mm_processor_kwargs,
         )
 
         prompt_raw = tokenizer.apply_chat_template(
@@ -77,6 +78,7 @@ class DeepseekV32Renderer(BaseRenderer[DeepseekV32Tokenizer]):
             self.model_config,
             content_format="string",
             media_io_kwargs=params.media_io_kwargs,
+            mm_processor_kwargs=params.mm_processor_kwargs,
         )
 
         prompt_raw = tokenizer.apply_chat_template(

vllm/renderers/grok2.py

@@ -50,6 +50,7 @@ class Grok2Renderer(BaseRenderer[Grok2Tokenizer]):
             self.model_config,
             content_format="string",
             media_io_kwargs=params.media_io_kwargs,
+            mm_processor_kwargs=params.mm_processor_kwargs,
         )
 
         prompt_raw = tokenizer.apply_chat_template(
@@ -77,6 +78,7 @@ class Grok2Renderer(BaseRenderer[Grok2Tokenizer]):
             self.model_config,
             content_format="string",
             media_io_kwargs=params.media_io_kwargs,
+            mm_processor_kwargs=params.mm_processor_kwargs,
         )
 
         prompt_raw = tokenizer.apply_chat_template(

vllm/renderers/hf.py

@@ -636,6 +636,7 @@ class HfRenderer(BaseRenderer[HfTokenizer]):
                 model_config=model_config,
             ),
             media_io_kwargs=params.media_io_kwargs,
+            mm_processor_kwargs=params.mm_processor_kwargs,
         )
 
         prompt_raw = safe_apply_chat_template(
@@ -691,6 +692,7 @@ class HfRenderer(BaseRenderer[HfTokenizer]):
                 model_config=model_config,
             ),
             media_io_kwargs=params.media_io_kwargs,
+            mm_processor_kwargs=params.mm_processor_kwargs,
         )
 
         prompt_raw = safe_apply_chat_template(

vllm/renderers/mistral.py

@@ -91,6 +91,7 @@ class MistralRenderer(BaseRenderer[MistralTokenizer]):
             self.model_config,
             content_format="string",
             media_io_kwargs=params.media_io_kwargs,
+            mm_processor_kwargs=params.mm_processor_kwargs,
         )
 
         prompt_raw = safe_apply_chat_template(
@@ -118,6 +119,7 @@ class MistralRenderer(BaseRenderer[MistralTokenizer]):
             self.model_config,
             content_format="string",
             media_io_kwargs=params.media_io_kwargs,
+            mm_processor_kwargs=params.mm_processor_kwargs,
         )
 
         prompt_raw = await self._apply_chat_template_async(

vllm/renderers/params.py

@@ -40,6 +40,34 @@ def merge_kwargs(
     return defaults | {k: v for k, v in overrides.items() if v not in unset_values}
 
 
+def recursively_merge_kwargs(
+    defaults: dict[str, Any] | None,
+    overrides: dict[str, Any] | None,
+    /,
+    *,
+    unset_values: tuple[object, ...] = (None, "auto"),
+) -> dict[str, Any]:
+    if defaults is None:
+        defaults = {}
+    if overrides is None:
+        overrides = {}
+
+    merged = dict(defaults)
+
+    for k, v in overrides.items():
+        if v in unset_values:
+            continue
+
+        if k in merged and isinstance(merged[k], dict) and isinstance(v, dict):
+            merged[k] = recursively_merge_kwargs(
+                merged[k], v, unset_values=unset_values
+            )
+        else:
+            merged[k] = v
+
+    return merged
+
+
 @dataclass(frozen=True)
 class ChatParams:
     """Configuration to control how to parse chat messages."""
@@ -56,12 +84,20 @@ class ChatParams:
     media_io_kwargs: dict[str, dict[str, Any]] | None = None
     """Per-modality kwargs for media I/O (loading/decoding images, videos, etc.)."""
 
+    mm_processor_kwargs: dict[str, Any] | None = None
+    """The kwargs to pass to the multi-modal processor."""
+
     def with_defaults(
         self,
         default_chat_template_kwargs: dict[str, Any] | None = None,
         default_media_io_kwargs: dict[str, dict[str, Any]] | None = None,
+        default_mm_processor_kwargs: dict[str, Any] | None = None,
+    ):
+        if (
+            not default_chat_template_kwargs
+            and not default_media_io_kwargs
+            and not default_mm_processor_kwargs
         ):
-        if not default_chat_template_kwargs and not default_media_io_kwargs:
             return self
 
         return ChatParams(
@@ -75,6 +111,10 @@ class ChatParams:
                 default_media_io_kwargs,
                 self.media_io_kwargs,
             ),
+            mm_processor_kwargs=recursively_merge_kwargs(
+                default_mm_processor_kwargs,
+                self.mm_processor_kwargs,
+            ),
         )
 
     def get_apply_chat_template_kwargs(self) -> dict[str, Any]:

vllm/renderers/terratorch.py

@@ -44,6 +44,7 @@ class TerratorchRenderer(BaseRenderer):
             model_config,
             content_format="string",
             media_io_kwargs=params.media_io_kwargs,
+            mm_processor_kwargs=params.mm_processor_kwargs,
         )
 
         prompt = parse_dec_only_prompt([1])  # Dummy token IDs
@@ -66,6 +67,7 @@ class TerratorchRenderer(BaseRenderer):
             model_config,
             content_format="string",
             media_io_kwargs=params.media_io_kwargs,
+            mm_processor_kwargs=params.mm_processor_kwargs,
         )
 
         prompt = parse_dec_only_prompt([1])  # Dummy token IDs