mirror of
https://github.com/FunAudioLLM/CosyVoice.git
synced 2026-02-05 01:49:25 +08:00
support upload audio
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iflamed
40
main.py
40
main.py
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import io,time
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from fastapi import FastAPI, Response
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from fastapi.responses import HTMLResponse
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from cosyvoice.cli.cosyvoice import CosyVoice
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import torchaudio
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cosyvoice = CosyVoice('pretrained_models/CosyVoice-300M-SFT')
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# sft usage
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print(cosyvoice.list_avaliable_spks())
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app = FastAPI()
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@app.get("/api/voice/tts")
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async def tts(query: str, role: str):
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start = time.process_time()
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output = cosyvoice.inference_sft(query, role)
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end = time.process_time()
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print("infer time:", end-start, "seconds")
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buffer = io.BytesIO()
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torchaudio.save(buffer, output['tts_speech'], 22050, format="wav")
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buffer.seek(0)
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return Response(content=buffer.read(-1), media_type="audio/wav")
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@app.get("/api/voice/roles")
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async def roles():
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return {"roles": cosyvoice.list_avaliable_spks()}
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@app.get("/", response_class=HTMLResponse)
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async def root():
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return """
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<!DOCTYPE html>
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<html lang=zh-cn>
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<head>
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<meta charset=utf-8>
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<title>Api information</title>
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</head>
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<body>
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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>
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</body>
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</html>
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"""
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102
runtime/python/fastapi_server.py
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102
runtime/python/fastapi_server.py
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import os
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import sys
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import io,time
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from fastapi import FastAPI, Response, File, UploadFile, Form
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from fastapi.responses import HTMLResponse
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from contextlib import asynccontextmanager
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ROOT_DIR = os.path.dirname(os.path.abspath(__file__))
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sys.path.append('{}/../..'.format(ROOT_DIR))
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sys.path.append('{}/../../third_party/Matcha-TTS'.format(ROOT_DIR))
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from cosyvoice.cli.cosyvoice import CosyVoice
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from cosyvoice.utils.file_utils import load_wav
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import numpy as np
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import torch
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import torchaudio
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import logging
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logging.getLogger('matplotlib').setLevel(logging.WARNING)
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class LaunchFailed(Exception):
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pass
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@asynccontextmanager
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async def lifespan(app: FastAPI):
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model_dir = os.getenv("MODEL_DIR", "pretrained_models/CosyVoice-300M-SFT")
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if model_dir:
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logging.info("MODEL_DIR is {}", model_dir)
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app.cosyvoice = CosyVoice('../../'+model_dir)
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# sft usage
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logging.info("Avaliable speakers {}", app.cosyvoice.list_avaliable_spks())
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else:
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raise LaunchFailed("MODEL_DIR environment must set")
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yield
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app = FastAPI(lifespan=lifespan)
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def buildResponse(output):
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buffer = io.BytesIO()
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torchaudio.save(buffer, output, 22050, format="wav")
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buffer.seek(0)
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return Response(content=buffer.read(-1), media_type="audio/wav")
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@app.post("/api/inference/sft")
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@app.get("/api/inference/sft")
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async def sft(tts: str = Form(), role: str = Form()):
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start = time.process_time()
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output = app.cosyvoice.inference_sft(tts, role)
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end = time.process_time()
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logging.info("infer time is {} seconds", end-start)
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return buildResponse(output['tts_speech'])
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@app.post("/api/inference/zero-shot")
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async def zeroShot(tts: str = Form(), prompt: str = Form(), audio: UploadFile = File()):
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start = time.process_time()
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prompt_speech = load_wav(audio.file, 16000)
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prompt_audio = (prompt_speech.numpy() * (2**15)).astype(np.int16).tobytes()
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prompt_speech_16k = torch.from_numpy(np.array(np.frombuffer(prompt_audio, dtype=np.int16))).unsqueeze(dim=0)
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prompt_speech_16k = prompt_speech_16k.float() / (2**15)
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output = app.cosyvoice.inference_zero_shot(tts, prompt, prompt_speech_16k)
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end = time.process_time()
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logging.info("infer time is {} seconds", end-start)
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return buildResponse(output['tts_speech'])
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@app.post("/api/inference/cross-lingual")
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async def crossLingual(tts: str = Form(), audio: UploadFile = File()):
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start = time.process_time()
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prompt_speech = load_wav(audio.file, 16000)
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prompt_audio = (prompt_speech.numpy() * (2**15)).astype(np.int16).tobytes()
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prompt_speech_16k = torch.from_numpy(np.array(np.frombuffer(prompt_audio, dtype=np.int16))).unsqueeze(dim=0)
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prompt_speech_16k = prompt_speech_16k.float() / (2**15)
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output = app.cosyvoice.inference_cross_lingual(tts, prompt_speech_16k)
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end = time.process_time()
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logging.info("infer time is {} seconds", end-start)
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return buildResponse(output['tts_speech'])
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@app.post("/api/inference/instruct")
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@app.get("/api/inference/instruct")
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async def instruct(tts: str = Form(), role: str = Form(), instruct: str = Form()):
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start = time.process_time()
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output = app.cosyvoice.inference_instruct(tts, role, instruct)
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end = time.process_time()
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logging.info("infer time is {} seconds", end-start)
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return buildResponse(output['tts_speech'])
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@app.get("/api/roles")
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async def roles():
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return {"roles": app.cosyvoice.list_avaliable_spks()}
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@app.get("/", response_class=HTMLResponse)
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async def root():
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return """
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<!DOCTYPE html>
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<html lang=zh-cn>
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<head>
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<meta charset=utf-8>
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<title>Api information</title>
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</head>
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<body>
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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>
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</body>
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</html>
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"""
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