app.py

import gradio as gr
from transformers import pipeline

# Use a stable, supported model
clf = pipeline("text-classification", model="roberta-base-openai-detector")

def detect_ai(text):
    if not text.strip():
        return "No text provided."
    try:
        result = clf(text)[0]
        label = result['label']
        score = round(result['score'] * 100, 2)
        return f"{label} ({score}%)"
    except Exception as e:
        return f"Error: {str(e)}"

# Simple Interface to expose API at /api/predict/
demo = gr.Interface(
    fn=detect_ai,
    inputs=gr.Textbox(lines=4, label="Enter text"),
    outputs="text",
    title="AI Text Detector"
)

demo.launch()