Update app.py

app.py

@@ -1,32 +1,29 @@
-import pandas as pd
-import joblib
-import gradio as gr
-from datetime import datetime
-
-# Muat model
-model = joblib.load('random_forest_model.pkl')
-
-# Fungsi untuk memprediksi prioritas tugas
-def predict_task_duration(duration, deadline):
-    start_date = datetime(2024, 10, 20)
-    deadline_days = (pd.to_datetime(deadline) - start_date).days
-    input_data = pd.DataFrame([[duration, deadline_days]], columns=['duration', 'deadline_days'])
-    
-    # Prediksi prioritas
-    priority = model.predict(input_data)
-    return f'Prioritas Tugas: {priority[0]}'
-
-# Buat antarmuka Gradio
-iface = gr.Interface(
-    fn=predict_task_duration,
-    inputs=[
-        gr.inputs.Slider(minimum=1, maximum=10, default=5, label="Durasi Tugas (dalam jam)"),
-        gr.inputs.Textbox(placeholder="Masukkan tanggal deadline (YYYY-MM-DD)", label="Tanggal Deadline")
-    ],
-    outputs="text",
-    title="Prediksi Prioritas Tugas",
-    description="Masukkan durasi dan tanggal deadline tugas untuk memprediksi prioritasnya."
-)
-
-# Jalankan antarmuka
-iface.launch()
+import pandas as pd
+import joblib
+import gradio as gr
+from datetime import datetime
+
+
+model = joblib.load('random_forest_model.pkl')
+
+
+def predict_task_duration(duration, deadline):
+    start_date = datetime(2024, 10, 20)
+    deadline_days = (pd.to_datetime(deadline) - start_date).days
+    input_data = pd.DataFrame([[duration, deadline_days]], columns=['duration', 'deadline_days'])
+    
+
+    priority = model.predict(input_data)
+    return f'Prioritas Tugas: {priority[0]}'
+
+
+iface = gr.Interface(
+    fn=predict_task_duration,
+    inputs=[
+        gr.Dropdown(choices=["Meeting", "Bekerja", "Belajar"], label="Nama Tugas"),
+        gr.Slider(minimum=1, maximum=10, value=5, label="Durasi Tugas (dalam jam)")
+    ],
+    outputs="text"
+)
+
+iface.launch()