app.py

import gradio as gr
import joblib
from huggingface_hub import hf_hub_download

# --- 1. تحميل النموذج الخاص بك من مستودعك ---
REPO_ID = "Ma120/clickbait-detector" 
FILENAME = "clickbait_model.pkl"

print(f"Loading model {FILENAME} from {REPO_ID}...")
model_path = hf_hub_download(repo_id=REPO_ID, filename=FILENAME)
model = joblib.load(model_path)
print("Model loaded successfully.")

# --- 2. تعريف الدالة التي ستنفذ التصنيف ---
def classify_headline(headline):
    prediction = model.predict([headline])[0]
    probabilities = model.predict_proba([headline])[0]

    if prediction == 1:
        confidences = {
            "Clickbait": float(probabilities[1]), 
            "Not Clickbait": float(probabilities[0])
        }
    else:
        confidences = {
            "Not Clickbait": float(probabilities[0]), 
            "Clickbait": float(probabilities[1])
        }
    return confidences

# --- 3. بناء الواجهة الرسومية ---
inputs = gr.Textbox(
    label="Enter a Headline:", 
    placeholder="e.g., You Won't Believe What Happens Next!"
)
outputs = gr.Label(label="Result", num_top_classes=2)

demo = gr.Interface(
    fn=classify_headline,
    inputs=inputs,
    outputs=outputs,
    title="Clickbait Detector",
    description="Enter a news headline to see if it's clickbait or not. Model trained by Ma120."
)

# --- 4. تشغيل الواجهة ---
demo.launch()