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import os
import torch
import time
import logging
from pydub import AudioSegment
from phonemizer.backend.espeak.wrapper import EspeakWrapper
from models import build_model
logger = logging.getLogger(__name__)
# Hugging Face Spaces setup
MODEL_DIR = "./kokoro"
os.makedirs(MODEL_DIR, exist_ok=True)
# Configure espeak-ng for Hugging Face environment
EspeakWrapper.set_library('/usr/lib/x86_64-linux-gnu/libespeak-ng.so.1')
class TTSEngine:
def __init__(self):
logger.info("Initializing TTS Engine")
self.device = "cuda" if torch.cuda.is_available() else "cpu"
logger.debug(f"Using device: {self.device}")
self._verify_model_files()
logger.info("Loading Kokoro model")
self.model = build_model(f"{MODEL_DIR}/kokoro-v0_19.pth", self.device)
logger.info("Loading voice model")
self.voice = torch.load(f"{MODEL_DIR}/voices/af_bella.pt",
map_location=self.device)
logger.info("TTS engine initialized")
def _verify_model_files(self):
"""Ensure required model files exist"""
required_files = [
f"{MODEL_DIR}/kokoro-v0_19.pth",
f"{MODEL_DIR}/voices/af_bella.pt"
]
missing = [f for f in required_files if not os.path.exists(f)]
if missing:
logger.error(f"Missing model files: {missing}")
raise FileNotFoundError(
f"Missing model files: {missing}\n"
"Add this to your Hugging Face Space settings:\n"
"App setup -> Clone Kokoro repository: "
"git clone https://huggingface.co/hexgrad/Kokoro-82M ./kokoro"
)
def generate_speech(self, text: str, language: str = "zh") -> str:
"""Generate speech from Chinese text"""
logger.info(f"Generating speech for text length: {len(text)}")
try:
from kokoro import generate_full
if len(text) > 500:
logger.warning(f"Truncating long text ({len(text)} characters)")
text = text[:495] + "[TRUNCATED]"
logger.debug("Starting audio generation")
audio, _ = generate_full(
self.model,
text,
self.voice,
lang='en-us',
max_len=200 if self.device == "cpu" else 500
)
output_path = f"temp/outputs/output_{int(time.time())}.wav"
logger.debug(f"Saving audio to {output_path}")
AudioSegment(
audio.numpy().tobytes(),
frame_rate=24000,
sample_width=2,
channels=1
).export(output_path, format="wav")
logger.info(f"Audio generation complete: {output_path}")
return output_path
except Exception as e:
logger.error(f"TTS generation failed: {str(e)}", exc_info=True)
raise
# Initialize TTS engine once
@st.cache_resource
def get_tts_engine():
return TTSEngine()
def generate_speech(text: str, language: str = "zh") -> str:
"""Public interface for TTS generation"""
return get_tts_engine().generate_speech(text, language) |