app.py

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

# download model from HuggingFace (force download if needed)
model_path = hf_hub_download(
    repo_id="krishna233/engine-maintenance-model",
    filename="engine_failure_model.pkl"
)

# load model
model = joblib.load(model_path)

# page title
st.title("Engine Predictive Maintenance")

# input fields
rpm = st.number_input("Engine RPM")
oil_pressure = st.number_input("Lub Oil Pressure")
fuel_pressure = st.number_input("Fuel Pressure")
coolant_pressure = st.number_input("Coolant Pressure")
oil_temp = st.number_input("Lub Oil Temp")
coolant_temp = st.number_input("Coolant Temp")

# predict button
if st.button("Predict"):

    input_df = pd.DataFrame({
        "Engine_rpm":[rpm],
        "Lub_oil_pressure":[oil_pressure],
        "Fuel_pressure":[fuel_pressure],
        "Coolant_pressure":[coolant_pressure],
        "lub_oil_temp":[oil_temp],
        "Coolant_temp":[coolant_temp]
    })

    prediction = model.predict(input_df)[0]

    if prediction == 1:
        st.error("Engine needs maintenance")
    else:
        st.success("Engine working normally")