app.py

import gradio as gr
from transformers import pipeline

# Load the GPT-2 pipeline for text generation
classifier = pipeline("text-classification", model="gpt2")

def analyze_text(text):
    # Use the GPT-2 classifier to predict if the text is fake or true
    result = classifier(text)[0]
    
    # Extract the label and confidence score
    label = result['label']
    score = result['score'] * 100
    
    # Beautify the output
    if label == 'LABEL_0':
        result_text = "This text is likely fake."
    else:
        result_text = "This text is likely true."
    
    return {"Prediction": result_text, "Confidence (%)": f"{score:.2f}"}

# Gradio interface with soft theme, title, description, input examples, and output labels
gr.Interface(analyze_text, 
             inputs=[gr.Textbox(label="Text", placeholder="Enter text here")],
             outputs="text",
             title="Fake vs. True Text Analyzer",
             description="Enter a piece of text to analyze whether it is likely fake or true.",
             examples=["Elon Musk is rich person", "Moon was discovered in 1908 by Cristiano Ronaldo"],
             theme="soft"
             ).launch()