Update app.py

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
 
-# ID model klasifikasi yang sudah kamu upload di Hugging Face Hub
+# Ganti dengan model kamu di Hugging Face
 MODEL_ID = "Ranti0603/job-classifier-xlm-roberta-v2"
 
 def respond(message, history, hf_token: gr.OAuthToken):
@@ -12,38 +12,37 @@ def respond(message, history, hf_token: gr.OAuthToken):
     """
     client = InferenceClient(token=hf_token.token, model=MODEL_ID)
 
-    # Panggil model untuk klasifikasi teks
+    # Panggil model klasifikasi
     result = client.text_classification(message)
 
-    # Ambil hasil prediksi
+    # Ambil prediksi terbaik
     best = max(result, key=lambda x: x["score"])
     label = best["label"]
     score = round(best["score"] * 100, 2)
 
-    # Mapping label ke format readable
+    # Mapping label
     if label in ["LABEL_0", "0", "Non-TIK"]:
         label_out = "Non-TIK (0)"
     else:
         label_out = "TIK (1)"
 
-    reply = f"Prediksi: **{label_out}**\n Confidence: {score}%"
+    reply = f"📌 Prediksi: **{label_out}**\n Confidence: {score}%"
     return reply
 
-# === Gradio Chatbot ===
-chatbot = gr.ChatInterface(
-    fn=respond,
-    type="messages",
-    chatbot=gr.Chatbot(height=500),
-    title="Job Classification Chatbot",
-    description="Masukkan deskripsi pekerjaan, sistem akan mengklasifikasikan apakah pekerjaan tersebut termasuk **Non-TIK (0)** atau **TIK (1)**."
-)
-
+# === UI ===
 with gr.Blocks() as demo:
+    gr.Markdown("# Job Classification Chatbot")
+    gr.Markdown("Masukkan deskripsi pekerjaan, sistem akan mengklasifikasikan apakah pekerjaan tersebut termasuk **Non-TIK (0)** atau **TIK (1)**.")
+
     with gr.Row():
         with gr.Column(scale=1):
-            gr.LoginButton()  # login HF
+            gr.LoginButton()  # login HuggingFace
         with gr.Column(scale=5):
-            chatbot.render()
+            chatbot = gr.ChatInterface(
+                respond,
+                type="messages",
+                chatbot=gr.Chatbot(height=400),
+            )
 
 if __name__ == "__main__":
     demo.launch()