import streamlit as st
import joblib
import numpy as np

# Load the trained model, scaler, and PCA
regressor = joblib.load('slump_regressor.pkl')
scaler = joblib.load('scaler.pkl')

def preprocess_data(X):
    # Load the trained scaler and PCA
    scaler = joblib.load('scaler.pkl')
    pca = joblib.load('pca.pkl')

    # Check if the input has 8 features
    if X.shape[1] != 8:
        raise ValueError("Input data should have 8 features.")

    # Scale the input data using the loaded scaler
    X_scaled = scaler.transform(X)

    # Apply PCA using the loaded PCA transformer
    X_pca = pca.transform(X_scaled)

    return X_pca

def predict_slump_app():
    # Get the input values from the user
    cement = st.number_input("Cement (kg/m^3)", min_value=0.0, step=0.1)
    blast_furnace_slag = st.number_input("Blast Furnace Slag (kg/m^3)", min_value=0.0, step=0.1)
    fly_ash = st.number_input("Fly Ash (kg/m^3)", min_value=0.0, step=0.1)
    water = st.number_input("Water (kg/m^3)", min_value=0.0, step=0.1)
    superplasticizer = st.number_input("Superplasticizer (kg/m^3)", min_value=0.0, step=0.1)
    coarse_aggregate = st.number_input("Coarse Aggregate (kg/m^3)", min_value=0.0, step=0.1)
    fine_aggregate = st.number_input("Fine Aggregate (kg/m^3)", min_value=0.0, step=0.1)
    flow = st.number_input("FLOW (cm)", min_value=0.0, step=0.1)

    # Prepare the input data
    X = np.array([[cement, blast_furnace_slag, fly_ash, water, superplasticizer, coarse_aggregate, fine_aggregate, flow]])

    # Preprocess the data
    X_preprocessed = preprocess_data(X)

    # Make the prediction
    slump_prediction = regressor.predict(X_preprocessed)[0]

    return slump_prediction

def main():
    st.set_page_config(page_title="Concrete Slump Strength Prediction")
    st.title("Concrete Slump Strength Prediction")
    st.write("Enter the concrete mix parameters to predict the slump.")

    slump_prediction = predict_slump_app()
    st.subheader("Predicted Slump Strength:")
    st.write(f"{slump_prediction:.2f} MPA")

if __name__ == '__main__':
    main()