app.py

import streamlit as st
import json

from transformers import pipeline


classifier = pipeline("zero-shot-classification",
                      model="valhalla/distilbart-mnli-12-1")

with st.form('inputs'):
    input_text = st.text_area("Input text")
    input_label = st.text_input("Labels", placeholder="support, help, important")
    input_multi = st.checkbox('Allow multiple true classes', value=False)
    submit_button = st.form_submit_button(label='Submit')

if submit_button:

    labels = list(l.strip() for l in input_label.split(','))
    pred = classifier(input_text, labels, multi_class=input_multi)
    
    if input_multi:
        st.vega_lite_chart(json.dumps(pred),
                           {'mark': 'bar', 'encoding': {'y': 'labels', 'x': 'scores'}} 
                           )
    else:
        out = f"Top predicted labels are {', '.join(p for p in pred['labels'][0:2])}"
    
        st.success(out)
    
    # st.markdown(pred)