import joblib
import pandas as pd
import streamlit as st

model = joblib.load('model.joblib')
unique_values = joblib.load('unique_values.joblib')
    
unique_sex =  unique_values["sex"]
unique_country =  unique_values["country"]
unique_returning =  unique_values["returning"]
unique_GImg1 =  unique_values["GImg1"]
unique_GImg2 =  unique_values["GImg2"]
unique_GImg3 =  unique_values["GImg3"]
unique_PImg1 =  unique_values["PImg1"]
unique_PImg2 =  unique_values["PImg2"]
unique_PImg3 =  unique_values["PImg3"]
unique_PImg4=  unique_values["PImg4"]
unique_PImg5 =  unique_values["PImg5"]
unique_TAudio1  =  unique_values["TAudio1"]
unique_TAudio2  =  unique_values["TAudio2"]
unique_TAudio3  =  unique_values["TAudio3"]
unique_QAudio1  =  unique_values["QAudio1"]
unique_QAudio2  =  unique_values["QAudio2"]
unique_QAudio3  =  unique_values["QAudio3"]
unique_Proxemics  =  unique_values["Proxemics"]


def main():
    st.title("Non verbal tourists data")
    with st.form("questionaire"):
        sex = st.selectbox("Sex", options = unique_sex)
        age = st.slider("Age", min_value = 20, max_value = 90)
        country = st.selectbox("Country of the client United Nations admitted countries", options = unique_country)
        returning =  st.selectbox(" If the client is returning ", options = unique_returning)
        GImg1 = st.selectbox("Handshake Indifferent", options = unique_GImg1)
        GImg2 = st.selectbox("Hug Indifferent", options = unique_GImg2)
        GImg3 = st.selectbox("Kiss Indifferent", options = unique_GImg3)
        PImg1 = st.selectbox("Consent posture Indifferent", options = unique_PImg1)
        PImg2 = st.selectbox("Interest posture Indifferent", options = unique_PImg2)
        PImg3 = st.selectbox("Neutral posture Indifferent", options = unique_PImg3)
        PImg4 = st.selectbox("Reflexive posture Indifferent", options = unique_PImg4)
        PImg5 = st.selectbox("Negative posture Indifferent", options = unique_PImg5)
        Tense= st.slider("Observed emotional clime", min_value = 1, max_value = 10)
        Hostile = st.slider("friendly Observed emotional clime", min_value = 1, max_value = 10)
        Authoritative = st.slider("anarchic Observed emotional clime", min_value = 1, max_value = 10)
        TAudio1 = st.selectbox("Authoritative Indifferent", options = unique_TAudio1)
        TAudio2 = st.selectbox("Sarcastic Indifferent", options = unique_TAudio2)   
        TAudio3 = st.selectbox("Friendly Indifferent", options = unique_TAudio3)   
        QAudio1 = st.selectbox("Spitting Indifferent", options = unique_QAudio1)   
        QAudio2 = st.selectbox("Hum Indifferent", options = unique_QAudio1)   
        QAudio3 = st.selectbox("Sigh Indifferent", options = unique_QAudio1)   
        Proxemics = st.selectbox("Physical distance preferred for the client", options = unique_Proxemics)
        
        
        
        # clicked==True only when the button is clicked
        clicked = st.form_submit_button("Predict Type of Client")
        if clicked:
            result=model.predict(pd.DataFrame({"sex":[sex],
                                               "age":[age],
                                               "country":[country],
                                               "returning":[returning],
                                               "GImg1":[GImg1],
                                               "GImg2":[GImg2],
                                               "GImg3":[GImg3],
                                               "PImg1":[PImg1],
                                               "PImg2":[PImg2],
                                               "PImg3":[PImg3],
                                               "PImg4":[PImg4],
                                               "PImg5":[PImg5],
                                               "Tense.relaxed":[Tense],
                                               "Hostile.friendly":[Hostile],
                                               "Authoritative.anarchic":[Authoritative],
                                               "TAudio1":[TAudio1],
                                               "TAudio2":[TAudio2],
                                               "TAudio3":[TAudio3],
                                               "QAudio1":[QAudio1],  
                                               "QAudio2":[QAudio1],  
                                               "QAudio3":[QAudio1],
                                               "Proxemics":[Proxemics]}))
            # Show prediction
            result = 'low' if result[0] == 1 else 'high'
            st.success("Predict Type of Client is "+result) #แสดงผล
            
# Run main()
if __name__ == "__main__":
    main()