Create app.py

app.py

@@ -0,0 +1,47 @@
+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()