app.py

import gradio as gr
from transformers import pipeline

print("🔄 Loading CyberGuard Model...")
classifier = pipeline("text-classification", model="Jishnuuuu/cyberguard-v1")
print("✅ Model loaded successfully!")

def analyze_message(text):
    """Analyze message for cyberbullying threats"""
    if not text or len(text.strip()) == 0:
        return {"Label": "ERROR", "Confidence": 0.0}
    
    try:
        result = classifier(text)[0]
        return {
            "Label": result['label'],
            "Confidence": round(result['score'], 3)
        }
    except Exception as e:
        return {"Label": "ERROR", "Confidence": 0.0, "error": str(e)}

demo = gr.Interface(
    fn=analyze_message,
    inputs=gr.Textbox(label="Message", placeholder="Type a message..."),
    outputs=gr.JSON(label="Result"),
    title="🛡️ CyberGuard AI",
    description="Cyberbullying Detection - Model: Jishnuuuu/cyberguard-v1"
)

demo.launch()