import streamlit as st
from datetime import datetime

from modules.prediction import prepare, predict

STATUS_STOPPED = 120001
STATUS_SUBMIT = 120002
STATUS_ERROR = 120003

has_prepared = False

st.session_state['running_status'] = STATUS_STOPPED

if not has_prepared:
    print('>>> [PREPARE] Preparing...')
    prepare()
    has_prepared = True

st.title('Entity Referring Classifier')
st.caption('It knows exactly when you are calling it. - Version 2.0.1208.01')

st.markdown('---')

livedemo_col1, livedemo_col2, livedemo_col3 = st.columns([12,1,6])

with livedemo_col1:
    st.subheader('Live Demo')

    with st.form("my_form"):
        entity = st.text_input('Entity Name:', 'Jimmy')
        sentence = st.text_input('Sentence Input:', 'Are you feeling good, Jimmy?',
                help='The classifier is going to analyze this sentence.')
        if st.form_submit_button('🚀 Submit'):
            st.session_state['running_status'] = STATUS_SUBMIT

    if st.session_state['running_status'] == STATUS_STOPPED:
        st.info('Type something and submit to start!')
    elif st.session_state['running_status'] == STATUS_SUBMIT:
        if predict(sentence, entity) == 'CALLING':
            st.success('It is a **calling**!')
        else:
            st.success('It is a **mentioning**!')
        st.caption(f'Submitted: `{sentence.lower()}` by `{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}`')

with livedemo_col2:
    st.empty()

with livedemo_col3:
    st.markdown("""
    #### Get Started
    """)
    st.markdown("""
    Hi! I'm the Entity Referring Classifier.
    I can help you find out when you are calling it.
    """)
    st.markdown("""
    #### Terms
    """)
    st.markdown("""
    ##### `Calling`
    """)
    st.markdown("""
    ##### `Mentioning`
    """)