mirror of
https://github.com/modelscope/FunASR.git
synced 2026-10-12 02:19:18 +00:00
feat: add funasr-server CLI command for one-line API deployment
pip install funasr && funasr-server --device cuda Starts OpenAI-compatible /v1/audio/transcriptions endpoint. Verified: import, startup, transcription all work end-to-end.
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游雁
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"""Internal: FastAPI app for funasr-server command."""
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import tempfile
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import time
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import os
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import re
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import logging
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from typing import Optional
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from fastapi import FastAPI, UploadFile, File, Form, HTTPException
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from fastapi.responses import JSONResponse
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logger = logging.getLogger("funasr.server")
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MODEL_CONFIGS = {
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"sensevoice": {
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"model": "iic/SenseVoiceSmall",
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"vad_model": "fsmn-vad",
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"vad_kwargs": {"max_single_segment_time": 30000},
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},
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"paraformer": {
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"model": "paraformer-zh",
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"vad_model": "fsmn-vad",
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"punc_model": "ct-punc",
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},
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"paraformer-en": {
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"model": "paraformer-en",
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"vad_model": "fsmn-vad",
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},
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"fun-asr-nano": {
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"model": "FunAudioLLM/Fun-ASR-Nano-2512",
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"hub": "hf",
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"trust_remote_code": True,
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"vad_model": "fsmn-vad",
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"vad_kwargs": {"max_single_segment_time": 30000},
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},
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}
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def create_app(device: str = "cuda", preload_model: str = "sensevoice") -> FastAPI:
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app = FastAPI(title="FunASR Server", version="1.3.2")
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app.state.models = {}
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app.state.device = device
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def _load_model(name: str):
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if name in app.state.models:
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return app.state.models[name]
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if name not in MODEL_CONFIGS:
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raise ValueError(f"Unknown model: {name}. Available: {list(MODEL_CONFIGS.keys())}")
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from funasr import AutoModel
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cfg = MODEL_CONFIGS[name].copy()
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cfg["device"] = app.state.device
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cfg["disable_update"] = True
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logger.info(f"Loading '{name}' on {device}...")
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t0 = time.time()
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model = AutoModel(**cfg)
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logger.info(f"'{name}' ready in {time.time()-t0:.1f}s")
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app.state.models[name] = model
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return model
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# Pre-load
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_load_model(preload_model)
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@app.post("/v1/audio/transcriptions")
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async def transcribe(
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file: UploadFile = File(...),
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model: str = Form(default="sensevoice"),
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language: Optional[str] = Form(default=None),
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response_format: Optional[str] = Form(default="json"),
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):
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if model not in MODEL_CONFIGS:
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raise HTTPException(400, f"Unknown model '{model}'. Available: {list(MODEL_CONFIGS.keys())}")
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suffix = os.path.splitext(file.filename)[1] if file.filename else ".wav"
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with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as tmp:
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tmp.write(await file.read())
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tmp_path = tmp.name
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try:
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asr = _load_model(model)
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kwargs = {"input": tmp_path, "batch_size": 1}
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if language:
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kwargs["language"] = language
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result = asr.generate(**kwargs)
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text = re.sub(r'<\|[^|]*\|>', '', result[0]["text"]).strip()
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if response_format == "verbose_json":
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segments = []
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if "sentence_info" in result[0]:
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for s in result[0]["sentence_info"]:
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segments.append({"start": s.get("start",0)/1000, "end": s.get("end",0)/1000, "text": re.sub(r'<\|[^|]*\|>','',s.get("text","")).strip(), "speaker": s.get("spk")})
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return JSONResponse({"text": text, "segments": segments, "model": model})
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return JSONResponse({"text": text})
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except Exception as e:
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raise HTTPException(500, str(e))
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finally:
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os.unlink(tmp_path)
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@app.get("/v1/models")
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async def list_models():
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return JSONResponse({"object": "list", "data": [{"id": n, "object": "model", "owned_by": "funasr"} for n in MODEL_CONFIGS]})
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@app.get("/health")
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async def health():
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return {"status": "ok", "device": app.state.device, "models_loaded": list(app.state.models.keys())}
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return app
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@@ -0,0 +1,66 @@
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"""
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FunASR Server — OpenAI-compatible speech recognition API.
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Usage:
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funasr-server # default: sensevoice on cuda:0, port 8000
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funasr-server --device cpu --port 9000
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funasr-server --model paraformer
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"""
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import argparse
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import sys
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def main():
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parser = argparse.ArgumentParser(
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description="FunASR OpenAI-Compatible API Server",
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formatter_class=argparse.RawDescriptionHelpFormatter,
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epilog="""
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Examples:
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funasr-server # Start with SenseVoice on GPU
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funasr-server --device cpu # Start on CPU
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funasr-server --model paraformer # Use Paraformer model
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funasr-server --port 9000 # Custom port
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Then use with OpenAI SDK:
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from openai import OpenAI
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client = OpenAI(base_url="http://localhost:8000/v1", api_key="x")
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result = client.audio.transcriptions.create(model="sensevoice", file=open("a.wav","rb"))
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""",
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)
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parser.add_argument("--host", default="0.0.0.0", help="Bind address (default: 0.0.0.0)")
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parser.add_argument("--port", type=int, default=8000, help="Port (default: 8000)")
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parser.add_argument("--device", default="cuda", help="Device: cuda, cpu, mps (default: cuda)")
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parser.add_argument("--model", default="sensevoice", help="Pre-load model: sensevoice, paraformer, fun-asr-nano (default: sensevoice)")
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args = parser.parse_args()
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try:
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import uvicorn
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import fastapi
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except ImportError:
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print("Error: funasr-server requires additional packages.")
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print("Install with: pip install fastapi uvicorn python-multipart")
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sys.exit(1)
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# Import and configure the app
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import os
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..', 'examples', 'openai_api'))
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# Use inline app to avoid path issues
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from funasr.bin._server_app import create_app
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app = create_app(device=args.device, preload_model=args.model)
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print(f"╔══════════════════════════════════════════════╗")
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print(f"║ FunASR Server v1.3.2 ║")
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print(f"║ Device: {args.device:<8} ║")
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print(f"║ Model: {args.model:<12} ║")
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print(f"║ URL: http://{args.host}:{args.port}/v1 ║")
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print(f"║ Docs: http://{args.host}:{args.port}/docs ║")
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print(f"╚══════════════════════════════════════════════╝")
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uvicorn.run(app, host=args.host, port=args.port)
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if __name__ == "__main__":
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main()
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@@ -154,6 +154,7 @@ setup(
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entry_points={
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"console_scripts": [
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"funasr = funasr.bin.inference:main_hydra",
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"funasr-server = funasr.bin.server:main",
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"funasr-train = funasr.bin.train:main_hydra",
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"funasr-train-ds = funasr.bin.train_ds:main_hydra",
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"funasr-export = funasr.bin.export:main_hydra",
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