import joblib
import pandas as pd
import streamlit as st 


model = joblib.load('model.joblib')

def main():
    st.title("Wine Quality Analysis")

    with st.form("questionaire"):

        fixed_acidity = st.slider("Fixed Acidity", min_value=0.0, max_value=20.0, step=0.01)
        volatile_acidity = st.slider("Volatile Acidity", min_value=0.0, max_value=20.0, step=0.01)
        citric_acid = st.slider("Citric Acid", min_value=0.0, max_value=1.0, step=0.01)
        residual_sugar = st.slider("Residual Sugar", min_value=0.0, max_value=20.0, step=0.01)
        chlorides = st.slider("Chlorides", min_value=0.0, max_value=1.0, step=0.01)
        free_sulfur_dioxide = st.slider("Free Sulfur Dioxide", min_value=0.0, max_value=100.0, step=0.01)
        total_sulfur_dioxide = st.slider("Total Sulfur Dioxide", min_value=0.0, max_value=500.0, step=0.01)
        density = st.slider("Density", min_value=0.0, max_value=10.0, step=0.01)
        ph = st.slider("pH", min_value=1.0, max_value=14.0, step=0.01)
        sulphates = st.slider("Sulphates", min_value=0.0, max_value=20.0, step=0.01)
        alcohol = st.slider("Alcohol", min_value=0.0, max_value=25.0, step=0.01)

        clicked = st.form_submit_button("Predict quality")
        
        if clicked:
            result = model.predict(pd.DataFrame({
                "fixed acidity": [fixed_acidity],
                "volatile acidity": [volatile_acidity],
                "citric acid": [citric_acid],
                "residual sugar": [residual_sugar],
                "chlorides": [chlorides],
                "free sulfur dioxide": [free_sulfur_dioxide],
                "total sulfur dioxide": [total_sulfur_dioxide],
                "density": [density],
                "pH": [ph],
                "sulphates": [sulphates],
                "alcohol": [alcohol]
            }))

            predicted_quality_rank = result[0]
            st.success('The predicted wine quality ranking is {}'.format(predicted_quality_rank))

if __name__=='__main__':
    main()