feat: containerize VoxCPM2 vLLM-Omni deployment

.containerignore

@@ -0,0 +1,7 @@
+runtime/
+reference-audio/
+*.wav
+*.opus
+*.pcm
+*.safetensors
+resposta.headers

.gitignore

@@ -0,0 +1,9 @@
+hf-cache/
+runtime/
+voices/
+reference-audio/
+*.wav
+*.opus
+*.pcm
+*.safetensors
+resposta.headers

Containerfile

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+FROM vllm/vllm-omni:v0.28.0
+
+RUN python -m pip install --no-cache-dir \
+    voxcpm \
+    soundfile \
+    httpx \
+    ninja
+
+COPY config/voxcpm2-a10-container.yaml /opt/config/voxcpm2.yaml
+
+RUN mkdir -p /opt/vllm-omni/examples/online_serving/text_to_speech/voxcpm2
+
+COPY tools/precompute_custom_voice.py \
+    /opt/vllm-omni/examples/online_serving/text_to_speech/voxcpm2/precompute_custom_voice.py
+
+CMD ["vllm", "serve", "openbmb/VoxCPM2", "--omni", "--deploy-config", "/opt/config/voxcpm2.yaml", "--host", "0.0.0.0", "--port", "8000"]

config/voxcpm2-a10-container.yaml

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+async_chunk: false
+dtype: bfloat16
+
+stages:
+  - stage_id: 0
+    devices: "0"
+    max_num_seqs: 2
+    gpu_memory_utilization: 0.9
+    kv_cache_memory_bytes: 6442450944
+    enforce_eager: true
+    trust_remote_code: true
+    enable_prefix_caching: false
+    max_num_batched_tokens: 4096
+    max_model_len: 4096
+    custom_voice_dir: /opt/voices
+
+    default_sampling_params:
+      temperature: 0.0
+      top_p: 1.0
+      top_k: -1
+      max_tokens: 4096
+      seed: 42
+      repetition_penalty: 1.0

pyproject.toml

@@ -2,4 +2,9 @@
 name = "voxcpm-vllm-poc"
 version = "0.1.0"
 requires-python = ">=3.12"
-dependencies = []
+dependencies = [
+    "httpx>=0.28.1",
+    "ninja>=1.13.2",
+    "soundfile>=0.14.0",
+    "voxcpm>=2.0.3",
+]

tools/precompute_custom_voice.py

@@ -0,0 +1,128 @@
+"""Pre-compute VoxCPM2 custom voice profiles.
+
+The generated directory can be passed to the server via
+``custom_voice_dir`` in ``vllm_omni/deploy/voxcpm2.yaml``. Requests can then
+use ``/v1/audio/speech`` with ``voice="<name>"`` and no per-request ref_audio.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import sys
+from pathlib import Path
+from typing import Any
+
+import torch
+from safetensors.torch import save_file
+
+REPO_ROOT = Path(__file__).resolve().parents[4]
+if str(REPO_ROOT) not in sys.path:
+    sys.path.insert(0, str(REPO_ROOT))
+
+from vllm_omni.utils.custom_voice_io import safe_voice_stem  # noqa: E402
+
+MANIFEST_NAME = "custom_voice_manifest.json"
+
+
+def _load_tts(model: str, device: torch.device):
+    from vllm_omni.model_executor.models.voxcpm2.voxcpm2_import_utils import import_voxcpm2_core
+
+    VoxCPM = import_voxcpm2_core()
+    native = VoxCPM.from_pretrained(model, load_denoiser=False, optimize=False)
+    return native.tts_model.to(device).eval()
+
+
+def _load_manifest(output_dir: Path, model: str) -> dict[str, Any]:
+    path = output_dir / MANIFEST_NAME
+    if path.exists():
+        return json.loads(path.read_text(encoding="utf-8"))
+    return {
+        "schema_version": 1,
+        "model_type": "voxcpm2",
+        "model": model,
+        "voices": {},
+    }
+
+
+def _write_voice(
+    *,
+    model: str,
+    output_dir: Path,
+    voice_name: str,
+    ref_audio: str,
+    prompt_text: str | None,
+    mode: str,
+    speaker_description: str | None,
+    device: torch.device,
+) -> None:
+    if mode in ("continuation", "ref_continuation") and not prompt_text:
+        raise ValueError("--prompt-text is required for continuation/ref_continuation modes")
+
+    tts = _load_tts(model, device)
+    tensors: dict[str, torch.Tensor] = {}
+    with torch.inference_mode():
+        if mode in ("reference", "ref_continuation"):
+            tensors["ref_audio_feat"] = tts._encode_wav(ref_audio, padding_mode="right").float().cpu().contiguous()
+        if mode in ("continuation", "ref_continuation"):
+            tensors["audio_feat"] = tts._encode_wav(ref_audio, padding_mode="left").float().cpu().contiguous()
+
+    output_dir.mkdir(parents=True, exist_ok=True)
+    filename = f"{safe_voice_stem(voice_name)}.safetensors"
+    save_file(tensors, str(output_dir / filename))
+
+    manifest = _load_manifest(output_dir, model)
+    entry: dict[str, Any] = {
+        "name": voice_name,
+        "file": filename,
+        "mode": mode,
+    }
+    if "ref_audio_feat" in tensors:
+        entry["ref_audio_feat_len"] = int(tensors["ref_audio_feat"].shape[0])
+    if "audio_feat" in tensors:
+        entry["audio_feat_len"] = int(tensors["audio_feat"].shape[0])
+    if prompt_text:
+        entry["prompt_text"] = prompt_text
+    if speaker_description:
+        entry["speaker_description"] = speaker_description
+
+    manifest.setdefault("voices", {})[voice_name] = entry
+    (output_dir / MANIFEST_NAME).write_text(json.dumps(manifest, indent=2, ensure_ascii=False), encoding="utf-8")
+    print(f"Wrote {output_dir / filename}")
+    print(f"Updated {output_dir / MANIFEST_NAME}")
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Pre-compute VoxCPM2 custom voice profile")
+    parser.add_argument("--model", default="openbmb/VoxCPM2", help="VoxCPM2 model path or Hugging Face ID")
+    parser.add_argument("--voice-name", required=True)
+    parser.add_argument("--ref-audio", required=True)
+    parser.add_argument(
+        "--prompt-text",
+        default=None,
+        help="Transcript of ref audio for continuation/ref_continuation modes",
+    )
+    parser.add_argument(
+        "--mode",
+        choices=["reference", "continuation", "ref_continuation"],
+        default="reference",
+    )
+    parser.add_argument("--speaker-description", default=None)
+    parser.add_argument("--output-dir", required=True)
+    parser.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu")
+    args = parser.parse_args()
+
+    _write_voice(
+        model=args.model,
+        output_dir=Path(args.output_dir),
+        voice_name=args.voice_name,
+        ref_audio=args.ref_audio,
+        prompt_text=args.prompt_text,
+        mode=args.mode,
+        speaker_description=args.speaker_description,
+        device=torch.device(args.device),
+    )
+
+
+if __name__ == "__main__":
+    main()