app.py

import streamlit as st
from transformers import pipeline

# Load the sentiment analysis pipeline
sentiment_pipeline = pipeline("sentiment-analysis")

# Streamlit UI
st.title("Sentiment Analysis")
st.write("Enter text below to analyse the sentiment.")
st.write("You can copy and paste a comment from social media for example.")
st.write("Usage idea: Companies can now reach those unhappy customers who leave unhappy comments on social media before they leave a bad review.")
st.write("You can then gather a list of names for your customer services team to prioritise and make that crucial early contact.")
st.write("Be proactive, not reactive")

# Text input
user_input = st.text_area("Text input")

# Button to perform sentiment analysis
if st.button("Analyse Sentiment"):
    if user_input:
        # Perform sentiment analysis
        results = sentiment_pipeline(user_input)
        # Display the results
        sentiment = results[0]['label']
        score = results[0]['score']
        confidence_percentage = score * 100
        st.write(f"Sentiment: {sentiment} (Confidence: {confidence_percentage:.2f}%)")
    else:
        st.write("Please enter some text to proceed.")