app.py

import streamlit as st
from transformers import pipeline 

@st.cache_resource
def load_model():
    model_path = "citizenlab/twitter-xlm-roberta-base-sentiment-finetunned"
    return pipeline("text-classification", model=model_path, tokenizer=model_path)

sentiment_classifier = load_model()

st.title("Sentiment Analysis Web App")
st.write("Enter text to analyze its sentiment (Positive/Negative).")

user_input = st.text_area("Enter your text here:")
if st.button("Analyze Sentiment"):
    if user_input.strip():
        result = sentiment_classifier(user_input)
        label = result[0]['label']
        score = result[0]['score']
        st.write(f"**Sentiment:** {label}")
        st.write(f"**Confidence Score:** {score:.2f}")
    else:
        st.write("Please enter some text to analyze.")