add sensevoice & cosevoice (#2562)

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

python/cosevoice/Dockerfile

@@ -0,0 +1,12 @@
+FROM dockerhub.icu/pytorch/pytorch:2.1.0-cuda11.8-cudnn8-runtime
+ENV DEBIAN_FRONTEND=noninteractive
+
+WORKDIR /opt/CosyVoice
+
+RUN chmod 777 /tmp && sed -i 's@//.*archive.ubuntu.com@//mirrors.ustc.edu.cn@g' /etc/apt/sources.list && apt-get update -y && apt-get -y install git unzip git-lfs
+RUN git lfs install && git clone --recursive https://github.com/FunAudioLLM/CosyVoice.git
+# here we use python==3.10 because we cannot find an image which have both python3.8 and torch2.0.1-cu118 installed
+COPY ./requirements.txt CosyVoice
+RUN cd CosyVoice && pip3 install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple
+RUN cd CosyVoice/runtime/python/grpc && python3 -m grpc_tools.protoc -I. --python_out=. --grpc_python_out=. cosyvoice.proto
+COPY fastapi/server.py CosyVoice/runtime/python/fastapi/

python/cosevoice/fastapi/client.py

@@ -0,0 +1,78 @@
+import argparse
+import logging
+import requests
+
+def saveResponse(path, response):
+    # 以二进制写入模式打开文件
+    with open(path, 'wb') as file:
+        # 将响应的二进制内容写入文件
+        file.write(response.content)
+
+def main():
+    api = args.api_base
+    if args.mode == 'sft':
+        url = api + "/api/inference/sft"
+        payload={
+            'tts': args.tts_text,
+            'role': args.spk_id
+        }
+        response = requests.request("POST", url, data=payload)
+        saveResponse(args.tts_wav, response)
+    elif args.mode == 'zero_shot':
+        url = api + "/api/inference/zero-shot"
+        payload={
+            'tts': args.tts_text,
+            'prompt': args.prompt_text
+        }
+        files=[('audio', ('prompt_audio.wav', open(args.prompt_wav,'rb'), 'application/octet-stream'))]
+        response = requests.request("POST", url, data=payload, files=files)
+        saveResponse(args.tts_wav, response)
+    elif args.mode == 'cross_lingual':
+        url = api + "/api/inference/cross-lingual"
+        payload={
+            'tts': args.tts_text,
+        }
+        files=[('audio', ('prompt_audio.wav', open(args.prompt_wav,'rb'), 'application/octet-stream'))]
+        response = requests.request("POST", url, data=payload, files=files)
+        saveResponse(args.tts_wav, response)
+    else:
+        url = api + "/api/inference/instruct"
+        payload = {
+            'tts': args.tts_text,
+            'role': args.spk_id,
+            'instruct': args.instruct_text
+        }
+        response = requests.request("POST", url, data=payload)
+        saveResponse(args.tts_wav, response)
+    logging.info("Response save to {}", args.tts_wav)
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--api_base',
+                        type=str,
+                        default='http://127.0.0.1:50000')
+    parser.add_argument('--mode',
+                        default='sft',
+                        choices=['sft', 'zero_shot', 'cross_lingual', 'instruct'],
+                        help='request mode')
+    parser.add_argument('--tts_text',
+                        type=str,
+                        default='你好，我是通义千问语音合成大模型，请问有什么可以帮您的吗？')
+    parser.add_argument('--spk_id',
+                        type=str,
+                        default='中文男')
+    parser.add_argument('--prompt_text',
+                        type=str,
+                        default='希望你以后能够做的比我还好呦。')
+    parser.add_argument('--prompt_wav',
+                        type=str,
+                        default='../../../zero_shot_prompt.wav')
+    parser.add_argument('--instruct_text',
+                        type=str,
+                        default='Theo \'Crimson\', is a fiery, passionate rebel leader. Fights with fervor for justice, but struggles with impulsiveness.')
+    parser.add_argument('--tts_wav',
+                        type=str,
+                        default='loushiming.mp3')
+    args = parser.parse_args()
+    prompt_sr, target_sr = 16000, 22050
+    main()

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>
+    """

python/cosevoice/grpc/client.py

@@ -0,0 +1,102 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import os
+import sys
+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))
+import logging
+import argparse
+import torchaudio
+import cosyvoice_pb2
+import cosyvoice_pb2_grpc
+import grpc
+import torch
+import numpy as np
+from cosyvoice.utils.file_utils import load_wav
+
+
+def main():
+    with grpc.insecure_channel("{}:{}".format(args.host, args.port)) as channel:
+        stub = cosyvoice_pb2_grpc.CosyVoiceStub(channel)
+        request = cosyvoice_pb2.Request()
+        if args.mode == 'sft':
+            logging.info('send sft request')
+            sft_request = cosyvoice_pb2.sftRequest()
+            sft_request.spk_id = args.spk_id
+            sft_request.tts_text = args.tts_text
+            request.sft_request.CopyFrom(sft_request)
+        elif args.mode == 'zero_shot':
+            logging.info('send zero_shot request')
+            zero_shot_request = cosyvoice_pb2.zeroshotRequest()
+            zero_shot_request.tts_text = args.tts_text
+            zero_shot_request.prompt_text = args.prompt_text
+            prompt_speech = load_wav(args.prompt_wav, 16000)
+            zero_shot_request.prompt_audio = (prompt_speech.numpy() * (2**15)).astype(np.int16).tobytes()
+            request.zero_shot_request.CopyFrom(zero_shot_request)
+        elif args.mode == 'cross_lingual':
+            logging.info('send cross_lingual request')
+            cross_lingual_request = cosyvoice_pb2.crosslingualRequest()
+            cross_lingual_request.tts_text = args.tts_text
+            prompt_speech = load_wav(args.prompt_wav, 16000)
+            cross_lingual_request.prompt_audio = (prompt_speech.numpy() * (2**15)).astype(np.int16).tobytes()
+            request.cross_lingual_request.CopyFrom(cross_lingual_request)
+        else:
+            logging.info('send instruct request')
+            instruct_request = cosyvoice_pb2.instructRequest()
+            instruct_request.tts_text = args.tts_text
+            instruct_request.spk_id = args.spk_id
+            instruct_request.instruct_text = args.instruct_text
+            request.instruct_request.CopyFrom(instruct_request)
+
+        response = stub.Inference(request)
+        logging.info('save response to {}'.format(args.tts_wav))
+        tts_speech = torch.from_numpy(np.array(np.frombuffer(response.tts_audio, dtype=np.int16))).unsqueeze(dim=0)
+        torchaudio.save(args.tts_wav, tts_speech, target_sr)
+        logging.info('get response')
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--host',
+                        type=str,
+                        default='0.0.0.0')
+    parser.add_argument('--port',
+                        type=int,
+                        default='50000')
+    parser.add_argument('--mode',
+                        default='sft',
+                        choices=['sft', 'zero_shot', 'cross_lingual', 'instruct'],
+                        help='request mode')
+    parser.add_argument('--tts_text',
+                        type=str,
+                        default='你好，我是通义千问语音合成大模型，请问有什么可以帮您的吗？')
+    parser.add_argument('--spk_id',
+                        type=str,
+                        default='中文女')
+    parser.add_argument('--prompt_text',
+                        type=str,
+                        default='希望你以后能够做的比我还好呦。')
+    parser.add_argument('--prompt_wav',
+                        type=str,
+                        default='../../../zero_shot_prompt.wav')
+    parser.add_argument('--instruct_text',
+                        type=str,
+                        default='Theo \'Crimson\', is a fiery, passionate rebel leader. Fights with fervor for justice, but struggles with impulsiveness.')
+    parser.add_argument('--tts_wav',
+                        type=str,
+                        default='demo.wav')
+    args = parser.parse_args()
+    prompt_sr, target_sr = 16000, 22050
+    main()

python/cosevoice/grpc/cosyvoice.proto

@@ -0,0 +1,43 @@
+syntax = "proto3";
+
+package cosyvoice;
+option go_package = "protos/";
+
+service CosyVoice{
+  rpc Inference(Request) returns (Response) {}
+}
+
+message Request{
+  oneof RequestPayload {
+    sftRequest sft_request = 1;
+    zeroshotRequest zero_shot_request = 2;
+    crosslingualRequest cross_lingual_request = 3;
+    instructRequest instruct_request = 4;
+  }
+}
+
+message sftRequest{
+  string spk_id = 1;
+  string tts_text = 2;
+}
+
+message zeroshotRequest{
+  string tts_text = 1;
+  string prompt_text = 2;
+  bytes prompt_audio = 3;
+}
+
+message crosslingualRequest{
+  string tts_text = 1;
+  bytes prompt_audio = 2;
+}
+
+message instructRequest{
+  string tts_text = 1;
+  string spk_id = 2;
+  string instruct_text = 3;
+}
+
+message Response{
+  bytes tts_audio = 1;
+}

python/cosevoice/grpc/server.py

@@ -0,0 +1,83 @@
+# Copyright (c) 2024 Alibaba Inc (authors: Xiang Lyu)
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import os
+import sys
+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 concurrent import futures
+import argparse
+import cosyvoice_pb2
+import cosyvoice_pb2_grpc
+import logging
+logging.getLogger('matplotlib').setLevel(logging.WARNING)
+import grpc
+import torch
+import numpy as np
+from cosyvoice.cli.cosyvoice import CosyVoice
+
+logging.basicConfig(level=logging.DEBUG,
+                    format='%(asctime)s %(levelname)s %(message)s')
+
+class CosyVoiceServiceImpl(cosyvoice_pb2_grpc.CosyVoiceServicer):
+    def __init__(self, args):
+        self.cosyvoice = CosyVoice(args.model_dir)
+        logging.info('grpc service initialized')
+
+    def Inference(self, request, context):
+        if request.HasField('sft_request'):
+            logging.info('get sft inference request')
+            model_output = self.cosyvoice.inference_sft(request.sft_request.tts_text, request.sft_request.spk_id)
+        elif request.HasField('zero_shot_request'):
+            logging.info('get zero_shot inference request')
+            prompt_speech_16k = torch.from_numpy(np.array(np.frombuffer(request.zero_shot_request.prompt_audio, dtype=np.int16))).unsqueeze(dim=0)
+            prompt_speech_16k = prompt_speech_16k.float() / (2**15)
+            model_output = self.cosyvoice.inference_zero_shot(request.zero_shot_request.tts_text, request.zero_shot_request.prompt_text, prompt_speech_16k)
+        elif request.HasField('cross_lingual_request'):
+            logging.info('get cross_lingual inference request')
+            prompt_speech_16k = torch.from_numpy(np.array(np.frombuffer(request.cross_lingual_request.prompt_audio, dtype=np.int16))).unsqueeze(dim=0)
+            prompt_speech_16k = prompt_speech_16k.float() / (2**15)
+            model_output = self.cosyvoice.inference_cross_lingual(request.cross_lingual_request.tts_text, prompt_speech_16k)
+        else:
+            logging.info('get instruct inference request')
+            model_output = self.cosyvoice.inference_instruct(request.instruct_request.tts_text, request.instruct_request.spk_id, request.instruct_request.instruct_text)
+
+        logging.info('send inference response')
+        response = cosyvoice_pb2.Response()
+        response.tts_audio = (model_output['tts_speech'].numpy() * (2 ** 15)).astype(np.int16).tobytes()
+        return response
+
+def main():
+    grpcServer = grpc.server(futures.ThreadPoolExecutor(max_workers=args.max_conc), maximum_concurrent_rpcs=args.max_conc)
+    cosyvoice_pb2_grpc.add_CosyVoiceServicer_to_server(CosyVoiceServiceImpl(args), grpcServer)
+    grpcServer.add_insecure_port('0.0.0.0:{}'.format(args.port))
+    grpcServer.start()
+    logging.info("server listening on 0.0.0.0:{}".format(args.port))
+    grpcServer.wait_for_termination()
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--port',
+                        type=int,
+                        default=50000)
+    parser.add_argument('--max_conc',
+                        type=int,
+                        default=4)
+    parser.add_argument('--model_dir',
+                        type=str,
+                        default='iic/CosyVoice-300M',
+                        help='local path or modelscope repo id')
+    args = parser.parse_args()
+    main()

python/cosevoice/requirements.txt

@@ -0,0 +1,29 @@
+--extra-index-url https://download.pytorch.org/whl/cu118
+conformer==0.3.2
+deepspeed==0.14.2; sys_platform == 'linux'
+diffusers==0.27.2
+gdown==5.1.0
+gradio==4.32.2
+grpcio==1.57.0
+grpcio-tools==1.57.0
+hydra-core==1.3.2
+HyperPyYAML==1.2.2
+inflect==7.3.1
+librosa==0.10.2
+lightning==2.2.4
+matplotlib==3.7.5
+modelscope==1.15.0
+networkx==3.1
+omegaconf==2.3.0
+onnxruntime-gpu; sys_platform == 'linux'
+onnxruntime; sys_platform == 'darwin' or sys_platform == 'windows'
+openai-whisper==20231117
+protobuf==4.25
+pydantic==2.7.0
+rich==13.7.1
+soundfile==0.12.1
+tensorboard
+wget==3.2
+fastapi==0.111.0
+fastapi-cli==0.0.4
+WeTextProcessing==1.0.3