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testing-text-to-speech-app / app.py

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	import streamlit as st
	import scipy

	from transformers import AutoProcessor, BarkModel
	import os
	os.environ["SUNO_OFFLOAD_CPU"] = "True"
	os.environ["SUNO_USE_SMALL_MODELS"] = "True"

	from bark import SAMPLE_RATE, generate_audio, preload_models
	from scipy.io.wavfile import write as write_wav

	from transformers import AutoProcessor, BarkModel


	print("Loading models")
	processor = AutoProcessor.from_pretrained("suno/bark")
	model = BarkModel.from_pretrained("suno/bark")
	# download and load all models
	#preload_models()

	#from streamlit_autorefresh import st_autorefresh

	# Run the autorefresh about every 2000 milliseconds (2 seconds) and stop
	# after it's been refreshed 100 times.
	#count = st_autorefresh(interval=2000, limit=100, key="fizzbuzzcounter")

	st.write('Welcome to Text to Audio generator app')

	def generate_audio_from_text(message):
	audio_array = generate_audio(message)
	scipy.io.wavfile.write("audio.wav", rate=SAMPLE_RATE, data=audio_array)

	def generate_audio_2(message):


	voice_preset = "v2/en_speaker_6"

	inputs = processor(message, voice_preset=voice_preset)

	audio_array = model.generate(**inputs)
	audio_array = audio_array.numpy().squeeze()
	sample_rate = model.generation_config.sample_rate
	scipy.io.wavfile.write("audio.wav", rate=sample_rate, data=audio_array)

	sentence = st.text_input('Input your sentence here:')

	if 'clicked' not in st.session_state:
	st.session_state.clicked = False

	def click_button():
	st.session_state.clicked = True
	generate_audio_2(sentence)
	audio_file = open('audio.wav','rb') #enter the filename with filepath
	audio_bytes = audio_file.read() #reading the file
	st.audio(audio_bytes, format='audio/wav') #displaying the audio


	st.button('Click me', on_click=click_button)