app.py

import streamlit as st
from transformers import pipeline
import soundfile as sf
import io

# Initialize TTS pipeline
@st.cache_resource
def get_tts_pipeline():
    # Use a valid TTS model from Hugging Face
    return pipeline("text-to-speech", model="microsoft/speecht5_tts")

tts = get_tts_pipeline()

# Streamlit app
st.title("Text-to-Speech (TTS) Application")
st.write("Convert text to speech using Hugging Face models!")

# Input text
input_text = st.text_area("Enter text below:", "Hello! Welcome to our TTS application.")

if st.button("Generate Speech"):
    if input_text.strip():
        # Generate speech
        with st.spinner("Generating speech..."):
            speech = tts(input_text)

        # Convert numpy array to audio file
        audio_data = io.BytesIO()
        sf.write(audio_data, speech["audio"], samplerate=speech["sampling_rate"], format="wav")
        audio_data.seek(0)

        # Play audio
        st.audio(audio_data, format="audio/wav")
    else:
        st.error("Please enter some text!")

st.markdown("**Created by [Your Name]**")