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from fastapi import FastAPI, Query, HTTPException
from fastapi.responses import StreamingResponse
from TTS.api import TTS
import os
from io import BytesIO
from typing import Generator
app = FastAPI()
import os
# By using XTTS you agree to CPML license https://coqui.ai/cpml
os.environ["COQUI_TOS_AGREED"] = "1"
# Initialize the TTS model
tts = TTS("tts_models/multilingual/multi-dataset/xtts_v2", gpu=False) # Set gpu=True if you have GPU support
# Predefined path to the sample voice clone
FIXED_SPEAKER_WAV = "Bible Verses About Community.wav"
# Function to split text into chunks
def split_text(text: str, words_per_chunk: int = 20):
words = text.split()
return [' '.join(words[i:i + words_per_chunk]) for i in range(0, len(words), words_per_chunk)]
@app.post("/generate-audio/")
async def generate_audio(
text: str = Query(..., description="The input text to convert to speech."),
language: str = Query("en", description="Language code for TTS (e.g., 'en' for English).")
):
if not os.path.exists(FIXED_SPEAKER_WAV):
raise HTTPException(status_code=400, detail="Fixed speaker WAV file not found.")
# StreamingResponse to stream audio chunks
def audio_stream():
if tts.is_multi_lingual and not language:
raise ValueError("Language must be specified for multi-lingual models.")
text_chunks = split_text(text, 20)
for idx, chunk in enumerate(text_chunks):
# Generate audio for each chunk and yield as bytes
output_file = f"out_{idx}.wav"
tts.tts_to_file(
text=chunk,
file_path=output_file,
speaker_wav=FIXED_SPEAKER_WAV,
language=language
)
print(output_file)
# Read the file content and yield as binary
with open(output_file, "rb") as audio_file:
yield audio_file.read()
# Optionally delete the file after streaming
os.remove(output_file)
return StreamingResponse(audio_stream(), media_type="audio/wav") |