app.py

import streamlit as st
from st_audiorec import st_audiorec

from nameder import init_model_ner, get_entity_labels
from speech2text import init_model_trans, transcribe, translate
# from translation import get_translation
from resources import audit_elapsedtime, set_start
import subprocess

def main ():
    print("------------------------------")
    print(f"Running main")

    #print(subprocess.Popen('pip freeze > requirements_hug.txt', shell=True))
    # text = "Tenho uma proposta para a Caixa Geral de Depositos, para 3 consultores outsystems, 300 euros por dia e um periodo de seis meses."
    # st.write(text)
    # traducao = get_translation(text_to_translate=text, languageCode="pt")
    # st.write(traducao)
    s2t = init_model_trans()
    # ner = init_model_ner() #async

    print("Rendering UI...")
    start_render = set_start()
    wav_audio_data = st_audiorec()
    audit_elapsedtime(function="Rendering UI", start=start_render)

    if wav_audio_data is not None and s2t is not None:
        print("Loading data...")
        start_loading = set_start()
        st.audio(wav_audio_data, format='audio/wav')
        original = transcribe(wav_audio_data, s2t)
        print("translating audio...")
        translation = translate(original)
        st.write(f"Original: {original}/nTranscription: {translation}")

    #     if text is not None and ner is not None:    
    #         st.write('Entities: ', get_entity_labels(model=ner, text=text))
    #     audit_elapsedtime(function="Loading data", start=start_loading)

if __name__ == "__main__":
    print("IN __name__")
    main()