Add Mac MPS support for Gradio app

.gitignore

@@ -1,6 +1,7 @@
 launch.json
+.venv/
 __pycache__
 voxcpm.egg-info
 .DS_Store
 ./pretrained_models/
-app_local.py
+app_local.py

app.py

@@ -3,7 +3,6 @@
 import sys
 import logging
 import numpy as np
-import torch
 import gradio as gr
 from typing import Optional, Tuple
 from funasr import AutoModel
@@ -12,6 +11,7 @@
 os.environ["TOKENIZERS_PARALLELISM"] = "false"
 
 import voxcpm
+from voxcpm.model.utils import resolve_runtime_device
 
 logging.basicConfig(
     level=logging.INFO,
@@ -220,17 +220,14 @@
 # ---------- Model ----------
 
 class VoxCPMDemo:
-    def __init__(self, model_id: str = "openbmb/VoxCPM2") -> None:
-        self.device = "cuda" if torch.cuda.is_available() else "cpu"
-        logger.info(f"Running on device: {self.device}")
+    def __init__(self, model_id: str = "openbmb/VoxCPM2", device: str = "auto") -> None:
+        self.device = resolve_runtime_device(device, "cuda")
+        logger.info(f"Running VoxCPM on device: {self.device}")
+        self.optimize = self.device.startswith("cuda")
 
         self.asr_model_id = "iic/SenseVoiceSmall"
-        self.asr_model: Optional[AutoModel] = AutoModel(
-            model=self.asr_model_id,
-            disable_update=True,
-            log_level="DEBUG",
-            device="cuda:0" if self.device == "cuda" else "cpu",
-        )
+        self.asr_device = "cuda:0" if self.device.startswith("cuda") else "cpu"
+        self.asr_model: Optional[AutoModel] = None
 
         self.voxcpm_model: Optional[voxcpm.VoxCPM] = None
         self._model_id = model_id
@@ -239,14 +236,37 @@ def get_or_load_voxcpm(self) -> voxcpm.VoxCPM:
         if self.voxcpm_model is not None:
             return self.voxcpm_model
         logger.info(f"Loading model: {self._model_id}")
-        self.voxcpm_model = voxcpm.VoxCPM.from_pretrained(self._model_id, optimize=True)
+        self.voxcpm_model = voxcpm.VoxCPM.from_pretrained(
+            self._model_id,
+            optimize=self.optimize,
+            device=self.device,
+        )
         logger.info("Model loaded successfully.")
         return self.voxcpm_model
 
+    def get_or_load_asr_model(self) -> AutoModel:
+        if self.asr_model is not None:
+            return self.asr_model
+        logger.info(
+            f"Loading ASR model: {self.asr_model_id} on device: {self.asr_device}"
+        )
+        self.asr_model = AutoModel(
+            model=self.asr_model_id,
+            disable_update=True,
+            log_level="DEBUG",
+            device=self.asr_device,
+        )
+        logger.info("ASR model loaded successfully.")
+        return self.asr_model
+
     def prompt_wav_recognition(self, prompt_wav: Optional[str]) -> str:
         if prompt_wav is None:
             return ""
-        res = self.asr_model.generate(input=prompt_wav, language="auto", use_itn=True)
+        res = self.get_or_load_asr_model().generate(
+            input=prompt_wav,
+            language="auto",
+            use_itn=True,
+        )
         return res[0]["text"].split("|>")[-1]
 
     def _build_generate_kwargs(
@@ -487,8 +507,9 @@ def run_demo(
     server_port: int = 8808,
     show_error: bool = True,
     model_id: str = "openbmb/VoxCPM2",
+    device: str = "auto",
 ):
-    demo = VoxCPMDemo(model_id=model_id)
+    demo = VoxCPMDemo(model_id=model_id, device=device)
     interface = create_demo_interface(demo)
     interface.queue(max_size=10, default_concurrency_limit=1).launch(
         server_name=server_name,
@@ -508,5 +529,11 @@ def run_demo(
         help="Local path or HuggingFace repo ID (default: openbmb/VoxCPM2)",
     )
     parser.add_argument("--port", type=int, default=8808, help="Server port")
+    parser.add_argument(
+        "--device",
+        type=str,
+        default="auto",
+        help="Runtime device: auto, cpu, mps, cuda, or cuda:N (default: auto)",
+    )
     args = parser.parse_args()
-    run_demo(model_id=args.model_id, server_port=args.port)
+    run_demo(model_id=args.model_id, server_port=args.port, device=args.device)

src/voxcpm/cli.py

@@ -11,6 +11,10 @@
 import sys
 from pathlib import Path
 
+import soundfile as sf
+
+from voxcpm.core import VoxCPM
+
 DEFAULT_HF_MODEL_ID = "openbmb/VoxCPM2"
 
 # -----------------------------
@@ -169,8 +173,6 @@ def validate_batch_args(args, parser):
 
 
 def load_model(args):
-    from voxcpm.core import VoxCPM
-
     print("Loading VoxCPM model...", file=sys.stderr)
 
     zipenhancer_path = getattr(args, "zipenhancer_path", None) or os.environ.get(
@@ -263,8 +265,6 @@ def _run_single(args, parser, *, text: str, output: str, prompt_text: str | None
         and (args.prompt_audio is not None or args.reference_audio is not None),
     )
 
-    import soundfile as sf
-
     sf.write(str(output_path), audio_array, model.tts_model.sample_rate)
 
     duration = len(audio_array) / model.tts_model.sample_rate
@@ -306,8 +306,6 @@ def cmd_validate(args, parser):
 
 
 def cmd_batch(args, parser):
-    import soundfile as sf
-
     input_file = require_file_exists(args.input, parser, "input file")
     output_dir = Path(args.output_dir)
     output_dir.mkdir(parents=True, exist_ok=True)