vllm.multimodal.utils

class MediaConnector:

    def __init__(
        self,
        media_io_kwargs: Optional[dict[str, dict[str, Any]]] = None,
        connection: HTTPConnection = global_http_connection,
        *,
        allowed_local_media_path: str = "",
    ) -> 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.
        """
        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_

    def _load_data_url(
        self,
        url_spec: ParseResult,
        media_io: MediaIO[_M],
    ) -> _M:
        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:
        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.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 load_from_url(
        self,
        url: str,
        media_io: MediaIO[_M],
        *,
        fetch_timeout: Optional[int] = None,
    ) -> _M:
        url_spec = urlparse(url)

        if url_spec.scheme.startswith("http"):
            connection = self.connection
            data = connection.get_bytes(url, timeout=fetch_timeout)

            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: Optional[int] = None,
    ) -> _M:
        url_spec = urlparse(url)
        loop = asyncio.get_running_loop()

        if url_spec.scheme.startswith("http"):
            connection = self.connection
            data = await connection.async_get_bytes(url, timeout=fetch_timeout)
            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, Union[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, Union[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 a 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 a 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 a 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 a 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)