add sensevoice & cosevoice (#2562)

Signed-off-by: EthanD <EthanD4869@gmail.com>
Co-authored-by: EthanD <EthanD4869@gmail.com>

python/cosevoice/fastapi/server.py

@@ -0,0 +1,136 @@
+# Set inference model
+# export MODEL_DIR=pretrained_models/CosyVoice-300M-Instruct
+# For development
+# fastapi dev --port 6006 fastapi_server.py
+# For production deployment
+# fastapi run --port 6006 fastapi_server.py
+
+import os
+import sys
+import io,time
+from fastapi import FastAPI, Request, Response, File, UploadFile, Form, Body
+from fastapi.responses import HTMLResponse
+from fastapi.middleware.cors import CORSMiddleware  #引入 CORS中间件模块
+from contextlib import asynccontextmanager
+ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
+sys.path.append('{}/../../..'.format(ROOT_DIR))
+sys.path.append('{}/../../../third_party/Matcha-TTS'.format(ROOT_DIR))
+from cosyvoice.cli.cosyvoice import CosyVoice
+from cosyvoice.utils.file_utils import load_wav
+import numpy as np
+import torch
+import torchaudio
+import logging
+from pydantic import BaseModel
+logging.getLogger('matplotlib').setLevel(logging.WARNING)
+
+class LaunchFailed(Exception):
+    pass
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    model_dir = os.getenv("MODEL_DIR", "pretrained_models/CosyVoice-300M-SFT")
+    if model_dir:
+        logging.info("MODEL_DIR is {}", model_dir)
+        app.cosyvoice = CosyVoice(model_dir)
+        # sft usage
+        logging.info("Avaliable speakers {}", app.cosyvoice.list_avaliable_spks())
+    else:
+        raise LaunchFailed("MODEL_DIR environment must set")
+    yield
+
+app = FastAPI(lifespan=lifespan)
+
+#设置允许访问的域名
+origins = ["*"]  #"*"，即为所有,也可以改为允许的特定ip。
+app.add_middleware(
+    CORSMiddleware, 
+    allow_origins=origins,  #设置允许的origins来源
+    allow_credentials=True,
+    allow_methods=["*"],  # 设置允许跨域的http方法，比如 get、post、put等。
+    allow_headers=["*"])  #允许跨域的headers，可以用来鉴别来源等作用。
+
+def buildResponse(output):
+    buffer = io.BytesIO()
+    torchaudio.save(buffer, output, 22050, format="mp3")
+    buffer.seek(0)
+    return Response(content=buffer.read(-1), media_type="audio/mpeg")
+
+@app.post("/api/inference/sft")
+@app.get("/api/inference/sft")
+async def sft(tts: str = Form(), role: str = Form()):
+    start = time.process_time()
+    output = app.cosyvoice.inference_sft(tts, role)
+    end = time.process_time()
+    logging.info("infer time is {} seconds", end-start)
+    return buildResponse(output['tts_speech'])
+
+class SpeechRequest(BaseModel):
+    model: str
+    input: str
+    voice: str
+
+@app.post("/v1/audio/speech")
+async def sft(request: Request, speech_request: SpeechRequest):
+    # 解析请求体中的JSON数据
+    data = speech_request.dict()
+    
+    start = time.process_time()
+    output = app.cosyvoice.inference_sft(data['input'], data['voice'])
+    end = time.process_time()
+    logging.info("infer time is {} seconds", end-start)
+    return buildResponse(output['tts_speech'])
+
+@app.post("/api/inference/zero-shot")
+async def zeroShot(tts: str = Form(), prompt: str = Form(), audio: UploadFile = File()):
+    start = time.process_time()
+    prompt_speech = load_wav(audio.file, 16000)
+    prompt_audio = (prompt_speech.numpy() * (2**15)).astype(np.int16).tobytes()
+    prompt_speech_16k = torch.from_numpy(np.array(np.frombuffer(prompt_audio, dtype=np.int16))).unsqueeze(dim=0)
+    prompt_speech_16k = prompt_speech_16k.float() / (2**15)
+
+    output = app.cosyvoice.inference_zero_shot(tts, prompt, prompt_speech_16k)
+    end = time.process_time()
+    logging.info("infer time is {} seconds", end-start)
+    return buildResponse(output['tts_speech'])
+
+@app.post("/api/inference/cross-lingual")
+async def crossLingual(tts: str = Form(), audio: UploadFile = File()):
+    start = time.process_time()
+    prompt_speech = load_wav(audio.file, 16000)
+    prompt_audio = (prompt_speech.numpy() * (2**15)).astype(np.int16).tobytes()
+    prompt_speech_16k = torch.from_numpy(np.array(np.frombuffer(prompt_audio, dtype=np.int16))).unsqueeze(dim=0)
+    prompt_speech_16k = prompt_speech_16k.float() / (2**15)
+
+    output = app.cosyvoice.inference_cross_lingual(tts, prompt_speech_16k)
+    end = time.process_time()
+    logging.info("infer time is {} seconds", end-start)
+    return buildResponse(output['tts_speech'])
+
+@app.post("/api/inference/instruct")
+@app.get("/api/inference/instruct")
+async def instruct(tts: str = Form(), role: str = Form(), instruct: str = Form()):
+    start = time.process_time()
+    output = app.cosyvoice.inference_instruct(tts, role, instruct)
+    end = time.process_time()
+    logging.info("infer time is {} seconds", end-start)
+    return buildResponse(output['tts_speech'])
+
+@app.get("/api/roles")
+async def roles():
+    return {"roles": app.cosyvoice.list_avaliable_spks()}
+
+@app.get("/", response_class=HTMLResponse)
+async def root():
+    return """
+    <!DOCTYPE html>
+    <html lang=zh-cn>
+        <head>
+            <meta charset=utf-8>
+            <title>Api information</title>
+        </head>
+        <body>
+            Get the supported tones from the Roles API first, then enter the tones and textual content in the TTS API for synthesis. <a href='./docs'>Documents of API</a>
+        </body>
+    </html>
+    """