import streamlit as st
from transformers import pipeline

# Initialize the zero-shot classification pipeline
classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")

# Define the candidate labels according to the Enneagram types
labels = ["Peacemaker", "Loyalist", "Achiever", "Reformer", "Individualist", "Helper", "Challenger", "Investigator", "Enthusiast"]

# Streamlit interface
st.title("Resume-based Personality Prediction")
resume_text = st.text_area("Enter Resume Text Here", height=300)
if st.button("Predict Personality"):
    # Make prediction
    result = classifier(resume_text, labels)
    # Display the results
    st.write("Predictions:")
    for label, score in zip(result['labels'], result['scores']):
        st.write(f"{label}: {score*100:.2f}%")