import gradio as gr
import requests
import json

# Define API keys (ensure these are securely handled and not exposed in public code repositories)
API_KEY = "565c106133mshb641eb3210436aep10e7fbjsn9b12f087ae76"
API_HOST = "ai-content-identifier2.p.rapidapi.com"

# Code for Text AI Detect
def text_check(user_input):
    url = f"https://{API_HOST}/text"
    payload = {
        "text": user_input,
        "threshold": 10  # Adjust this if needed to test different sensitivity levels
    }
    headers = {
        "x-rapidapi-key": API_KEY,
        "x-rapidapi-host": API_HOST,
        "Content-Type": "application/json"
    }
    try:
        response = requests.post(url, json=payload, headers=headers)
        response.raise_for_status()  # Raises an HTTPError for bad responses
        data = response.json()
        # Format the output to be user-friendly
        if 'success' in data and data['success']:
            ai_status = 'Yes' if data['data']['ai'] else 'No'
            return (f"AI Content Detected: {ai_status}\n"
                    f"Confidence: {data['data']['percentage']}%\n"
                    f"Total Words: {data['data']['stats']['totalWords']}\n"
                    f"AI Words: {data['data']['stats']['aiWords']}\n"
                    f"Human Words: {data['data']['stats']['humanWords']}\n"
                    f"Note: {data['note']}")
        else:
            return "Failed to analyze text. Please try again."
    except requests.exceptions.RequestException as e:
        print(f"Error during API call: {e}")
        return {"error": str(e)}

demo = gr.Interface(fn=text_check, inputs="textbox", outputs="textbox")

if __name__ == "_main_":
    demo.launch()