Update app.py

app.py

@@ -1,5 +1,8 @@
+# app.py
 import gradio as gr
 import joblib
+import json
+import os
 from src.preprocessing import clean_text
 
 model = joblib.load("model/saved_model.joblib")
@@ -9,14 +12,34 @@ def predict(text):
     clean = clean_text(text)
     vec = vectorizer.transform([clean])
     pred = model.predict(vec)[0]
-    return "🚫 Judi Online" if pred == 1 else "✅ Aman"
+    proba = None
+    if hasattr(model, "predict_proba"):
+        proba = model.predict_proba(vec)[0]
+        proba = { "Aman": round(proba[0]*100, 2), "Judi": round(proba[1]*100, 2) }
 
-demo = gr.Interface(
-    fn=predict,
-    inputs=gr.Textbox(lines=3, placeholder="Masukkan komentar..."),
-    outputs="text",
-    title="Deteksi Komentar Judi Online"
-)
+    label = "🚫 Judi Online" if pred == "judi" or pred == 1 else "✅ Aman"
+    return {"Prediksi": label, "Probabilitas (%)": proba}
+
+def load_metrics():
+    path = "model/metrics_summary.json"
+    if os.path.exists(path):
+        with open(path) as f:
+            return json.load(f)
+    return {}
+
+with gr.Blocks() as demo:
+    with gr.Tab("Inference"):
+        inp = gr.Textbox(lines=3, placeholder="Masukkan komentar...")
+        out = gr.JSON()
+        gr.Button("Prediksi").click(fn=predict, inputs=inp, outputs=out)
+
+    with gr.Tab("Monitoring"):
+        metrics = load_metrics()
+        if metrics:
+            gr.Markdown("### 📊 Model Performance")
+            gr.JSON(metrics)
+        if os.path.exists("model/confusion_matrix.png"):
+            gr.Image("model/confusion_matrix.png", label="Confusion Matrix")
 
 if __name__ == "__main__":
     demo.launch()