Update model artifacts

app.py

@@ -2,40 +2,43 @@
 import gradio as gr
 import joblib
 import json
+import os
 from src.preprocessing import clean_text
 
-model = joblib.load("model/saved_model.joblib")
-vectorizer = joblib.load("model/vectorizer.joblib")
+model = joblib.load("saved_model.joblib")
+vectorizer = joblib.load("vectorizer.joblib")
 
 def predict(text):
     clean = clean_text(text)
     vec = vectorizer.transform([clean])
     pred = model.predict(vec)[0]
-    return "🚫 Judi Online" if pred == "judi" 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) }
+
+    label = "🚫 Judi Online" if pred == "judi" or pred == 1 else "✅ Aman"
+    return {"Prediksi": label, "Probabilitas (%)": proba}
 
 def load_metrics():
-    try:
-        with open("model/metrics_summary.json") as f:
+    path = "model/metrics_summary.json"
+    if os.path.exists(path):
+        with open(path) as f:
             return json.load(f)
-    except:
-        return {"error": "Metrics not available. Run evaluation first."}
+    return {}
 
 with gr.Blocks() as demo:
     with gr.Tab("Inference"):
-        gr.Interface(
-            fn=predict,
-            inputs=gr.Textbox(lines=3, placeholder="Masukkan komentar..."),
-            outputs="text",
-            title="Deteksi Komentar Judi Online"
-        )
+        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"):
-        gr.Markdown("### 📊 Model Performance Metrics")
         metrics = load_metrics()
-        if "error" in metrics:
-            gr.Label(metrics)
-        else:
-            gr.Label({k: round(v, 4) for k, v in metrics.items()})
+        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__":

vectorizer.joblib

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0c2f0281667ac90830c8763c894f12da4fab4c2b5bdce2e3e0971c777130b6f8
+oid sha256:9c0b2299214b99b6449d835a050b80c9b9470ed2fae73f287c08c9391c44288e
 size 2966