import os
import streamlit as st
from transformers import pipeline

auth_token = os.environ.get("TOKEN_FROM_SECRET") or True

pipe = pipeline("text-classification", model="ogozcelik/bert-base-turkish-fake-news", token=auth_token)

st.title("Turkish Fake News Detector")
st.markdown(
    """
    This application determines the accuracy of claims shared on social media since 2020 through Turkish Twitter texts.
    When you test facts that are already known to be true (such as the Earth being round), you may get misleading answers.
    """
)
st.write("\n\n")


def print_result(user_input):
    result = pipe(user_input)
    veracity = result[0]["label"]
    confidence = result[0]["score"]
    return veracity, confidence

st.markdown("Enter a tweet or short statement to detect its truthfulness:")
user_input = st.text_input("")

if st.button('Predict Truthfulness'):
    with st.spinner('Processing...'):
        veracity, confidence = print_result(user_input)
    st.success(f"Truthfulness: {veracity}")
    st.write(f"Confidence: The model is {(confidence*100):.2f}% sure about the result.")