app.py

import gradio as gr
from transformers import pipeline

# Load model
model = pipeline("image-classification", model="Ateeqq/ai-vs-human-image-detector")

# Function for checking AI image
def check_image(image):
    results = model(image)
    label = results[0]['label']
    score = results[0]['score']
    return f"Prediction: {label.capitalize()} (Confidence: {score*100:.2f}%)"

# Gradio interface - EVERYTHING stays inside this Interface(...)
iface = gr.Interface(
    fn=check_image,
    inputs=gr.Image(type="pil"),
    outputs=gr.Textbox(),
    title="Reality - AI Image Detector",
    description="Upload an image to check if it is AI-generated or real."
)

# Launch UI
iface.launch()