Update app.py

app.py

@@ -11,6 +11,31 @@ HF_REPO_ID = "aephidayatuloh/bank-model"
 HF_MODEL_FILENAME = "random_forest_bank_marketing_pipeline.joblib"
 # app.py (atau index.py)
 
+# --- SETUP MODEL (DIJALANKAN SEKALI SAAT STARTUP) ---
+app = FastAPI(title="Bank Deposit Prediction (Docker)")
+
+@app.on_event("startup")
+def load_model():
+    global MODEL_PIPELINE
+    try:
+        # Download model dari HF Hub (direkomendasikan)
+        downloaded_model_path = hf_hub_download(
+            repo_id=HF_REPO_ID, 
+            filename=HF_MODEL_FILENAME
+        )
+        MODEL_PIPELINE = joblib.load(downloaded_model_path)
+        print("✅ Model berhasil dimuat dari Hugging Face Hub.")
+    except Exception as e:
+        print(f"❌ Gagal memuat model: {e}")
+        MODEL_PIPELINE = None
+
+
+# --- ENDPOINT PREDIKSI ---
+
+@app.get("/")
+def home():
+    return {"status": "ok", "message": "FastAPI is running inside Docker on HF Spaces."}
+
 # --- 1. Definisi Skema Fitur (Data Mentah) ---
 # Model ini mendefinisikan struktur objek yang ada di dalam key "features"
 class FeaturesSchema(BaseModel):