Add vLLM plugin support for high-performance ASR serving

vibevoice/processor/audio_utils.py

@@ -1,3 +1,6 @@
+import os
+import threading
+
 import numpy as np
 from subprocess import run
 from typing import List, Optional, Union, Dict, Any
@@ -57,6 +60,7 @@ def load_audio_use_ffmpeg(file: str, resample: bool = False, target_sr: int = 24
     
     cmd = [
         "ffmpeg",
+        "-loglevel", "error",
         "-nostdin",
         "-threads", "0",
         "-i", file,
@@ -64,14 +68,84 @@ def load_audio_use_ffmpeg(file: str, resample: bool = False, target_sr: int = 24
         "-ac", "1",
         "-acodec", "pcm_s16le",
         "-ar", str(sr_to_use),
-        "-"
+        "-",
     ]
     
-    out = run(cmd, capture_output=True, check=True).stdout
+    out = _run_ffmpeg(cmd).stdout
     audio_data = np.frombuffer(out, np.int16).flatten().astype(np.float32) / 32768.0
     
     return audio_data, sr_to_use
 
+
+def _get_ffmpeg_max_concurrency() -> int:
+    """Get the maximum FFmpeg concurrency from environment variable."""
+    v = os.getenv("VIBEVOICE_FFMPEG_MAX_CONCURRENCY", "")
+    try:
+        n = int(v) if v.strip() else 0
+    except Exception:
+        n = 0
+    # 0/negative means no explicit limit.
+    return n
+
+
+_FFMPEG_MAX_CONCURRENCY = _get_ffmpeg_max_concurrency()
+_FFMPEG_SEM = threading.Semaphore(_FFMPEG_MAX_CONCURRENCY) if _FFMPEG_MAX_CONCURRENCY > 0 else None
+
+
+def _run_ffmpeg(cmd: list, *, stdin_bytes: bytes = None):
+    """Run ffmpeg with optional global concurrency limiting.
+
+    This is important for vLLM multi-request concurrency: spawning too many
+    ffmpeg processes can saturate CPU/IO and cause request failures/timeouts.
+    """
+    if _FFMPEG_SEM is None:
+        return run(cmd, capture_output=True, check=True, input=stdin_bytes)
+    with _FFMPEG_SEM:
+        return run(cmd, capture_output=True, check=True, input=stdin_bytes)
+
+
+def load_audio_bytes_use_ffmpeg(data: bytes, *, resample: bool = False, target_sr: int = 24000):
+    """Decode audio bytes via ffmpeg stdin pipe.
+
+    Compared to writing bytes to a temp file, this avoids filesystem IO and
+    reduces contention under high request concurrency.
+    
+    Parameters
+    ----------
+    data: bytes
+        The audio data bytes
+    resample: bool
+        Whether to resample the audio (must be True)
+    target_sr: int
+        The target sample rate if resampling is requested
+
+    Returns
+    -------
+    A tuple containing:
+    - A NumPy array with the audio waveform in float32 dtype
+    - The sample rate
+    """
+    if not resample:
+        # For stdin bytes, we don't have a cheap/robust way to probe original sr.
+        # Keep behavior explicit.
+        raise ValueError("load_audio_bytes_use_ffmpeg requires resample=True")
+
+    cmd = [
+        "ffmpeg",
+        "-loglevel", "error",
+        "-threads", "0",
+        "-i", "pipe:0",
+        "-f", "s16le",
+        "-ac", "1",
+        "-acodec", "pcm_s16le",
+        "-ar", str(target_sr),
+        "-",
+    ]
+    out = _run_ffmpeg(cmd, stdin_bytes=data).stdout
+    audio_data = np.frombuffer(out, np.int16).flatten().astype(np.float32) / 32768.0
+    return audio_data, target_sr
+
+
 class AudioNormalizer:
     """
     Audio normalization class for VibeVoice tokenizer.