app.py

import pandas as pd
import joblib
import gradio as gr
from datetime import datetime, timedelta

# Load model
model = joblib.load('random_forest_model.pkl')

def predict_task_duration(task_name, duration, deadline):
    try:
        start_date = datetime(2024, 10, 20)
        deadline_date = datetime.strptime(deadline, '%Y-%m-%d')
        deadline_days = (deadline_date - start_date).days
        
        input_data = pd.DataFrame({
            'duration': [duration],
            'deadline_days': [deadline_days]
        })
        
        priority = model.predict(input_data)
        priority_map = {
            1: "Rendah",
            2: "Sedang",
            3: "Tinggi"
        }
        
        result = priority_map.get(priority[0], "Tidak diketahui")
        return f'Prioritas Tugas: {result}'
    
    except Exception as e:
        return f"Error: {str(e)}"

# Membuat interface Gradio
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,
            step=0.1,
            label="Durasi Tugas (dalam jam)"
        ),
        gr.Date(label="Deadline")  # Menambahkan input deadline
    ],
    outputs=gr.Text(label="Hasil Prediksi"),
    title="Sistem Prediksi Prioritas Tugas",
    description="Masukkan nama tugas, durasi, dan deadline untuk memprediksi prioritasnya"
)

# Launch the interface
iface.launch()