from fastapi import FastAPI, Query, HTTPException from fastapi.responses import StreamingResponse from fastapi.responses import FileResponse 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.") if tts.is_multi_lingual and not language: raise ValueError("Language must be specified for multi-lingual models.") # Generate audio for each chunk and yield as bytes output_file = f"out.wav" try: tts.tts_to_file( text=text, file_path=output_file, speaker_wav=FIXED_SPEAKER_WAV, language=language ) print(output_file) # Return the generated audio file as a response return FileResponse(output_file, media_type="audio/wav") except Exception as e: raise HTTPException(status_code=500, detail=f"Error generating audio: {str(e)}") # finally: # # Clean up the generated file after the response is sent # if os.path.exists(output_file): # os.remove(output_file) #