vllm.multimodal.utils ¶

@MEDIA_CONNECTOR_REGISTRY.register("http")
class MediaConnector:
    def __init__(
        self,
        media_io_kwargs: dict[str, dict[str, Any]] | None = None,
        connection: HTTPConnection = global_http_connection,
        *,
        allowed_local_media_path: str = "",
        allowed_media_domains: list[str] | None = None,
    ) -> None:
        """
        Args:
            media_io_kwargs: Additional args passed to process media
                             inputs, keyed by modalities. For example,
                             to set num_frames for video, set
                             `--media-io-kwargs '{"video":{"num_frames":40}}'`
            connection: HTTP connection client to download media contents.
            allowed_local_media_path: A local directory to load media files from.
            allowed_media_domains: If set, only media URLs that belong to this
                                   domain can be used for multi-modal inputs.
        """
        super().__init__()

        self.media_io_kwargs: dict[str, dict[str, Any]] = (
            media_io_kwargs if media_io_kwargs else {}
        )
        self.connection = connection

        if allowed_local_media_path:
            allowed_local_media_path_ = Path(allowed_local_media_path)

            if not allowed_local_media_path_.exists():
                raise ValueError(
                    "Invalid `--allowed-local-media-path`: The path "
                    f"{allowed_local_media_path_} does not exist."
                )
            if not allowed_local_media_path_.is_dir():
                raise ValueError(
                    "Invalid `--allowed-local-media-path`: The path "
                    f"{allowed_local_media_path_} must be a directory."
                )
        else:
            allowed_local_media_path_ = None

        self.allowed_local_media_path = allowed_local_media_path_
        if allowed_media_domains is None:
            allowed_media_domains = []
        self.allowed_media_domains = allowed_media_domains

    def _load_data_url(
        self,
        url_spec: ParseResult,
        media_io: MediaIO[_M],
    ) -> _M:  # type: ignore[type-var]
        data_spec, data = url_spec.path.split(",", 1)
        media_type, data_type = data_spec.split(";", 1)

        if data_type != "base64":
            msg = "Only base64 data URLs are supported for now."
            raise NotImplementedError(msg)

        return media_io.load_base64(media_type, data)

    def _load_file_url(
        self,
        url_spec: ParseResult,
        media_io: MediaIO[_M],
    ) -> _M:  # type: ignore[type-var]
        allowed_local_media_path = self.allowed_local_media_path
        if allowed_local_media_path is None:
            raise RuntimeError(
                "Cannot load local files without `--allowed-local-media-path`."
            )

        filepath = Path(url2pathname(url_spec.netloc + url_spec.path))
        if allowed_local_media_path not in filepath.resolve().parents:
            raise ValueError(
                f"The file path {filepath} must be a subpath "
                f"of `--allowed-local-media-path {allowed_local_media_path}`."
            )

        return media_io.load_file(filepath)

    def _assert_url_in_allowed_media_domains(self, url_spec: ParseResult) -> None:
        if (
            self.allowed_media_domains
            and url_spec.hostname not in self.allowed_media_domains
        ):
            raise ValueError(
                f"The URL must be from one of the allowed domains: "
                f"{self.allowed_media_domains}. Input URL domain: "
                f"{url_spec.hostname}"
            )

    def load_from_url(
        self,
        url: str,
        media_io: MediaIO[_M],
        *,
        fetch_timeout: int | None = None,
    ) -> _M:  # type: ignore[type-var]
        url_spec = urlparse(url)

        if url_spec.scheme.startswith("http"):
            self._assert_url_in_allowed_media_domains(url_spec)

            connection = self.connection
            data = connection.get_bytes(
                url,
                timeout=fetch_timeout,
                allow_redirects=envs.VLLM_MEDIA_URL_ALLOW_REDIRECTS,
            )

            return media_io.load_bytes(data)

        if url_spec.scheme == "data":
            return self._load_data_url(url_spec, media_io)

        if url_spec.scheme == "file":
            return self._load_file_url(url_spec, media_io)

        msg = "The URL must be either a HTTP, data or file URL."
        raise ValueError(msg)

    async def load_from_url_async(
        self,
        url: str,
        media_io: MediaIO[_M],
        *,
        fetch_timeout: int | None = None,
    ) -> _M:
        url_spec = urlparse(url)
        loop = asyncio.get_running_loop()

        if url_spec.scheme.startswith("http"):
            self._assert_url_in_allowed_media_domains(url_spec)

            connection = self.connection
            data = await connection.async_get_bytes(
                url,
                timeout=fetch_timeout,
                allow_redirects=envs.VLLM_MEDIA_URL_ALLOW_REDIRECTS,
            )
            future = loop.run_in_executor(global_thread_pool, media_io.load_bytes, data)
            return await future

        if url_spec.scheme == "data":
            future = loop.run_in_executor(
                global_thread_pool, self._load_data_url, url_spec, media_io
            )
            return await future

        if url_spec.scheme == "file":
            future = loop.run_in_executor(
                global_thread_pool, self._load_file_url, url_spec, media_io
            )
            return await future
        msg = "The URL must be either a HTTP, data or file URL."
        raise ValueError(msg)

    def fetch_audio(
        self,
        audio_url: str,
    ) -> tuple[np.ndarray, int | float]:
        """
        Load audio from a URL.
        """
        audio_io = AudioMediaIO(**self.media_io_kwargs.get("audio", {}))

        return self.load_from_url(
            audio_url,
            audio_io,
            fetch_timeout=envs.VLLM_AUDIO_FETCH_TIMEOUT,
        )

    async def fetch_audio_async(
        self,
        audio_url: str,
    ) -> tuple[np.ndarray, int | float]:
        """
        Asynchronously fetch audio from a URL.
        """
        audio_io = AudioMediaIO(**self.media_io_kwargs.get("audio", {}))

        return await self.load_from_url_async(
            audio_url,
            audio_io,
            fetch_timeout=envs.VLLM_AUDIO_FETCH_TIMEOUT,
        )

    def fetch_image(
        self,
        image_url: str,
        *,
        image_mode: str = "RGB",
    ) -> Image.Image:
        """
        Load a PIL image from an HTTP or base64 data URL.

        By default, the image is converted into RGB format.
        """
        image_io = ImageMediaIO(
            image_mode=image_mode, **self.media_io_kwargs.get("image", {})
        )

        try:
            return self.load_from_url(
                image_url,
                image_io,
                fetch_timeout=envs.VLLM_IMAGE_FETCH_TIMEOUT,
            )
        except UnidentifiedImageError as e:
            # convert to ValueError to be properly caught upstream
            raise ValueError(str(e)) from e

    async def fetch_image_async(
        self,
        image_url: str,
        *,
        image_mode: str = "RGB",
    ) -> Image.Image:
        """
        Asynchronously load a PIL image from an HTTP or base64 data URL.

        By default, the image is converted into RGB format.
        """
        image_io = ImageMediaIO(
            image_mode=image_mode, **self.media_io_kwargs.get("image", {})
        )

        try:
            return await self.load_from_url_async(
                image_url,
                image_io,
                fetch_timeout=envs.VLLM_IMAGE_FETCH_TIMEOUT,
            )
        except UnidentifiedImageError as e:
            # convert to ValueError to be properly caught upstream
            raise ValueError(str(e)) from e

    def fetch_video(
        self,
        video_url: str,
        *,
        image_mode: str = "RGB",
    ) -> tuple[npt.NDArray, dict[str, Any]]:
        """
        Load video from an HTTP or base64 data URL.
        """
        image_io = ImageMediaIO(
            image_mode=image_mode, **self.media_io_kwargs.get("image", {})
        )
        video_io = VideoMediaIO(image_io, **self.media_io_kwargs.get("video", {}))

        return self.load_from_url(
            video_url,
            video_io,
            fetch_timeout=envs.VLLM_VIDEO_FETCH_TIMEOUT,
        )

    async def fetch_video_async(
        self,
        video_url: str,
        *,
        image_mode: str = "RGB",
    ) -> tuple[npt.NDArray, dict[str, Any]]:
        """
        Asynchronously load video from an HTTP or base64 data URL.

        By default, the image is converted into RGB format.
        """
        image_io = ImageMediaIO(
            image_mode=image_mode, **self.media_io_kwargs.get("image", {})
        )
        video_io = VideoMediaIO(image_io, **self.media_io_kwargs.get("video", {}))

        return await self.load_from_url_async(
            video_url,
            video_io,
            fetch_timeout=envs.VLLM_VIDEO_FETCH_TIMEOUT,
        )

    def fetch_image_embedding(
        self,
        data: str,
    ) -> torch.Tensor:
        """
        Load image embedding from a URL.
        """
        image_embedding_io = ImageEmbeddingMediaIO()

        return image_embedding_io.load_base64("", data)

    def fetch_audio_embedding(
        self,
        data: str,
    ) -> torch.Tensor:
        """
        Load audio embedding from a URL.
        """
        audio_embedding_io = AudioEmbeddingMediaIO()

        return audio_embedding_io.load_base64("", data)