CognitiveScience/FakeNewsDetector

1import streamlit as st2import transformers3import torch4import requests5from PIL import Image6from transformers import AutoTokenizer, AutoModelForSequenceClassification7 8# Setting the page configurations9st.set_page_config(10    page_title="Fake News Detection App", 11    page_icon="fas fa-exclamation-triangle", 12    layout="wide", 13    initial_sidebar_state="auto")14 15# Load the model and tokenizer16model_name = AutoModelForSequenceClassification.from_pretrained("ikoghoemmanuell/finetuned_fake_news_roberta")17tokenizer_name = AutoTokenizer.from_pretrained("ikoghoemmanuell/finetuned_fake_news_roberta")18 19 20# Define the CSS style for the app21st.markdown(22"""23<style>24body {25    background-color: #f5f5f5;26}27h1 {28    color: #4e79a7;29}30</style>31""",32unsafe_allow_html=True33)34 35# Set up sidebar36st.sidebar.header('Navigation')37menu = ['Home', 'About']38choice = st.sidebar.selectbox(39    "Select an option", 40    menu)41 42# Define the function for detecting fake news43@st.cache_resource44def detect_fake_news(text):45    # Load the pipeline.46    pipeline = transformers.pipeline("text-classification", 47                                     model=model_name, 48                                     tokenizer=tokenizer_name)49 50    # Predict the sentiment.51    prediction = pipeline(text)52    sentiment = prediction[0]["label"]53    score = prediction[0]["score"]54 55    return sentiment, score56 57    58# Home section59if choice == 'Home':60    st.markdown("<h1 style='text-align: center;margin-top:0px;'>TRUTH- A fake news detection app</h1>", 61                unsafe_allow_html=True)62 63    # Loading GIF64    gif_url = "https://thumbs.gfycat.com/AnchoredWeeklyGreatwhiteshark-size_restricted.gif"65    st.image(gif_url, 66             use_column_width=True, 67             width=400)68    69    st.markdown("<h1 style='text-align: center;'>Welcome</h1>", 70                unsafe_allow_html=True)71    st.markdown("<p style='text-align: center;'>This is a Fake News Detection App.</p>", 72                unsafe_allow_html=True)73    74    # Get user input75    text = st.text_input("Enter some text and we'll tell you if it's likely to be fake news or not!")76    77    if st.button('Predict'):78        # Show fake news detection output79        if text:80            with st.spinner('Checking if news is Fake...'):81                label, score = detect_fake_news(text)82                if label == "LABEL_1":83                    st.error(f"The text is likely to be fake news with a confidence score of {score*100:.2f}%!")84                else:85                    st.success(f"The text is likely to be genuine with a confidence score of {score*100:.2f}%!")86        else:87            with st.spinner('Checking if news is Fake...'):88                st.warning("Please enter some text to detect fake news.")89 90 91# About section92if choice == 'About':93    # Load the banner image94    banner_image_url = "https://docs.gato.txst.edu/78660/w/2000/a_1dzGZrL3bG/fake-fact.jpg"95 96    # Display the banner image97    st.image(98        banner_image_url, 99        use_column_width=True, 100        width=400)101    st.markdown('''102                    <p style='font-size: 20px; font-style: italic;font-style: bold;'>103                        104                        TRUTH is a cutting-edge application specifically designed to combat the spread of fake 105                        news. Using state-of-the-art algorithms and advanced deep learning techniques, our app 106                        empowers users to detect and verify the authenticity of news articles. TRUTH provides 107                        accurate assessments of the reliability of news content. With its user-friendly 108                        interface and intuitive design, the app enables users to easily navigate and obtain 109                        trustworthy information in real-time. With TRUTH, you can take control of the news you110                        consume and make informed decisions based on verified facts.111                        112                    </p>113                ''', 114                unsafe_allow_html=True)