src/streamlit_app.py

import os
from transformers import pipeline
import streamlit as st

'''port = int(os.environ.get("PORT", 7860))
st.set_page_config(page_title="Text Classifier")
st.write(f"Running on port {port} (for Hugging Face)")
'''

# Use local cache directory to avoid permission issues
##os.environ['TRANSFORMERS_CACHE'] = '/app/cache'

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

# Streamlit UI

st.title("Zero-Shot Text Classifier")
text = st.text_area("Enter text to classify")
labels = st.text_input("Enter candidate labels (comma-separated)", "finance, education, health")
'''
if st.button("Classify"):
    if text and labels:
        label_list = [l.strip() for l in labels.split(",")]
        result = classifier(text, candidate_labels=label_list)
        st.write(result)
    else:
        st.warning("Please enter both text and labels.")
'''