src/streamlit_app.py

import streamlit as st
from transformers import pipeline
import os

streamlit_data_dir = "/app/.streamlit"
# Load the sentiment analysis pipeline with your fine-tuned model
@st.cache_resource
def load_model():
    # Replace "johnnas12/sentiment-bert" with your actual model repository ID if different
    model_id = "johnnas12/sentiment-bert"
    sentiment_pipeline = pipeline("sentiment-analysis", model=model_id)
    return sentiment_pipeline

sentiment_analyzer = load_model()

st.title("Eco-Friendly Tweet Sentiment Analyzer")

user_input = st.text_area("Enter your eco-friendly tweet here:")

if st.button("Analyze Sentiment"):
    if user_input:
        result = sentiment_analyzer(user_input)
        label = result[0]['label']
        score = result[0]['score']

        if label == 'LABEL_1':
            st.write(f"Sentiment: Its Positive tweet")
            st.write(f"Confidence Score: {score:.4f}")
        else:
            st.write(f"Sentiment: Its Negative tweet")
            st.write(f"Confidence Score: {score:.4f}")
    else:
        st.write("Please enter some text to analyze.")