app.py

import streamlit as st
import transformers as t
import plotly.express as px
import pandas as pd

st.title("Phrase Emotion Analysis")
with st.spinner(text="Loading model..."):
    classifier = t.pipeline("zero-shot-classification",
                            model="facebook/bart-large-mnli",
                            multi_class=True)
    sentiment_task = t.pipeline("sentiment-analysis",
                                model="cardiffnlp/twitter-xlm-roberta-base-sentiment",
                                tokenizer="cardiffnlp/twitter-xlm-roberta-base-sentiment")


x = st.text_input("Enter your title here:")
candidate_labels = ['anger', 'sadness', 'fear', 'joy', 'interest',
                    'surprise', 'disgust', 'shame', 'compassion', 'other']

if x != "":
    with st.spinner(text="Evaluating your input..."):
        output = classifier(x, candidate_labels)
        sentiment = sentiment_task(x)
    st.write(str(sentiment))

    ordered_results = []
    for lbl in candidate_labels:
        ind = output['labels'].index(lbl)
        ordered_results.append(output['scores'][ind])

    df = pd.DataFrame(dict(r=ordered_results, theta=candidate_labels))
    fig = px.line_polar(df, r='r', theta='theta', line_close=True)
    fig.update_traces(fill='toself')

    st.plotly_chart(fig)