from typing import Sequence
import streamlit as st
from hf_model import classifier_zero,load_model
from utils import plot_result
classifier=load_model()
if __name__ == '__main__':
    st.header("Zero Shot Classification")
    

  
    sequence = st.text_area(label="Input Sequence")
    labels = st.text_input('Possible topics (separated by `,`)', max_chars=1000)
    labels = list(set([x.strip() for x in labels.strip().split(',') if len(x.strip()) > 0]))
    if len(labels) == 0 or len(sequence) == 0:
        st.write('Enter some text and at least one possible topic to see predictions.')

    multi_class = st.checkbox('Allow multiple correct topics', value=True)
    
    with st.spinner('Classifying...'):
      top_topics, scores = classifier_zero(classifier,sequence=sequence,labels=labels,multi_class=multi_class)
      plot_result(top_topics[::-1][-10:], scores[::-1][-10:])