app.py

import streamlit as st
import pandas as pd
import joblib
from huggingface_hub import hf_hub_download

st.title("Predictive Maintenance - Engine Condition Classifier")

# Load model from Hugging Face
MODEL_REPO = "MohammedSohail/engine_maintenance_model"

model_path = hf_hub_download(
    repo_id=MODEL_REPO,
    filename="model/best_model.pkl"
)

model = joblib.load(model_path)

st.subheader("Enter Engine Sensor Values")

# UI Inputs (same features used during training)
features = {
    "Coolant_Temperature": st.number_input("Coolant Temperature", value=75.0),
    "Lub_Oil_Pressure": st.number_input("Lubricant Oil Pressure", value=3.5),
    "Fuel_Pressure": st.number_input("Fuel Pressure", value=1.2),
    "Engine_RPM": st.number_input("Engine RPM", value=1500),
    "Turbocharger_Speed": st.number_input("Turbocharger Speed", value=9000),
    "Cylinder_Head_Temperature": st.number_input("Cylinder Head Temperature", value=120)
}

if st.button("Predict Engine Condition"):
    input_df = pd.DataFrame([features])
    prediction = model.predict(input_df)[0]
    st.success(f"Predicted Engine Condition: 🚦 {prediction}")