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from starlette.responses import StreamingResponse
from texttospeech import MelToWav, TextToMel
from typing import Optional
from pydantic import BaseModel
from fastapi import FastAPI, HTTPException
import uvicorn
import base64
app = FastAPI()
class TextJson(BaseModel):
text: str
lang: Optional[str] = "hi"
gender: Optional[str] = "male"
glow_hi_male = TextToMel(glow_model_dir="", device="")
glow_hi_female = TextToMel(glow_model_dir="", device="")
hifi_hi = MelToWav(hifi_model_dir="", device="")
available_choice = {
"hi_male": [glow_hi_male, hifi_hi],
"hi_female": [glow_hi_female, hifi_hi],
}
@app.post("/TTS/")
async def tts(input: TextJson):
text = input.text
lang = input.lang
gender = input.gender
choice = lang + "_" + gender
if choice in available_choice.keys():
t2s = available_choice[choice]
else:
raise HTTPException(
status_code=400, detail={"error": "Requested model not found"}
)
if text:
mel = t2s[0].generate_mel(text)
data, sr = t2s[1].generate_wav(mel)
t2s.save_audio("out.wav", data, sr)
else:
raise HTTPException(status_code=400, detail={"error": "No text"})
## to return outpur as a file
# audio = open('out.wav', mode='rb')
# return StreamingResponse(audio, media_type="audio/wav")
with open("out.wav", "rb") as audio_file:
encoded_bytes = base64.b64encode(audio_file.read())
encoded_string = encoded_bytes.decode()
return {"encoding": "base64", "data": encoded_string, "sr": sr}
if __name__ == "__main__":
uvicorn.run(
"t2s_fastapi:app", host="127.0.0.1", port=5000, log_level="info", reload=True
)
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