[Misc] Small: Remove global media connector. Each test should have its own...

[Misc] Small: Remove global media connector. Each test should have its own test connector object. (#20395)
Signed-off-by: Chenheli Hua <huachenheli@outlook.com>

vllm/multimodal/utils.py

@@ -43,6 +43,15 @@ class MediaConnector:
         *,
         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[
@@ -277,15 +286,6 @@ class MediaConnector:
         return image_embedding_io.load_base64("", data)
 
 
-global_media_connector = MediaConnector()
-"""The global [`MediaConnector`][vllm.multimodal.utils.MediaConnector]
-instance used by vLLM."""
-
-fetch_audio = global_media_connector.fetch_audio
-fetch_image = global_media_connector.fetch_image
-fetch_video = global_media_connector.fetch_video
-
-
 def encode_audio_base64(
     audio: np.ndarray,
     sampling_rate: float,
@@ -441,3 +441,51 @@ def run_dp_sharded_vision_model(image_input: torch.Tensor,
                                                          dim=0)
     vision_embeddings = vision_embeddings[:num_chunks, ...]
     return vision_embeddings
+
+
+def fetch_audio(
+    audio_url: str,
+    audio_io_kwargs: Optional[dict[str, Any]] = None,
+) -> tuple[np.ndarray, Union[int, float]]:
+    """
+    Args:
+        audio_url: URL of the audio file to fetch.
+        audio_io_kwargs: Additional kwargs passed to handle audio IO.
+    """
+    media_io_kwargs = None if not audio_io_kwargs else {
+        "audio": audio_io_kwargs
+    }
+    media_connector = MediaConnector(media_io_kwargs=media_io_kwargs)
+    return media_connector.fetch_audio(audio_url)
+
+
+def fetch_image(
+    image_url: str,
+    image_io_kwargs: Optional[dict[str, Any]] = None,
+) -> Image.Image:
+    """
+    Args:
+        image_url: URL of the image file to fetch.
+        image_io_kwargs: Additional kwargs passed to handle image IO.
+    """
+    media_io_kwargs = None if not image_io_kwargs else {
+        "image": image_io_kwargs
+    }
+    media_connector = MediaConnector(media_io_kwargs=media_io_kwargs)
+    return media_connector.fetch_image(image_url)
+
+
+def fetch_video(
+    video_url: str,
+    video_io_kwargs: Optional[dict[str, Any]] = None,
+) -> tuple[npt.NDArray, dict[str, Any]]:
+    """
+    Args:
+        video_url: URL of the video file to fetch.
+        video_io_kwargs: Additional kwargs passed to handle video IO.
+    """
+    media_io_kwargs = None if not video_io_kwargs else {
+        "video": video_io_kwargs
+    }
+    media_connector = MediaConnector(media_io_kwargs=media_io_kwargs)
+    return media_connector.fetch_video(video_url)