app.py

import io
import transformers
import numpy as np
import streamlit as st
from GPTTTS import GPTTTSTokenizer, GPTTTS
import torch
import torchaudio
import tempfile

# Load your GPTTTSTokenizer
tokenizer = GPTTTSTokenizer()

# Load the GPT-TTS model
model = GPTTTS()

st.title("GPT-TTS Demo")
user_text = st.text_input("Enter text:")

if user_text:
    # Tokenize the input text
    inputs = tokenizer(user_text)["input_ids"]

    with st.spinner("Generating audio..."):
        # Generate the audio tensor
        with torch.no_grad():
            audio = model(inputs)

        # Save the audio tensor to a temporary file
        with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp_wav:
            torchaudio.save(tmp_wav.name, audio, sample_rate=model.sample_rate)

            # Load the temporary file and play the audio
            st.audio(tmp_wav.read(), format="audio/wav")