import gradio as gr
import pandas as pd
import joblib


age_input = gr.Number(label="Age")
duration_input = gr.Number(label='Duration(Sec)')
cc_contact_freq_input = gr.Number(label='CC Contact Freq')
days_since_pc_input = gr.Number(label='Days Since PC')
pc_contact_freq_input = gr.Number(label='Pc Contact Freq')
job_input = gr.Dropdown(['admin.', 'blue-collar', 'technician', 'services', 'management',
       'retired', 'entrepreneur', 'self-employed', 'housemaid', 'unemployed',
       'student', 'unknown'],label="Job")
marital_input = gr.Dropdown(['married', 'single', 'divorced', 'unknown'],label='Marital Status')
education_input = gr.Dropdown(['experience', 'university degree', 'high school', 'professional.course',
       'Others', 'illiterate'],label='Education')
defaulter_input = gr.Dropdown(['no', 'unknown', 'yes'],label='Defaulter')
home_loan_input = gr.Dropdown(['yes', 'no', 'unknown'],label='Home Loan')
personal_loan_input = gr.Dropdown(['yes', 'no', 'unknown'],label='Personal Loan')
communication_type_input = gr.Dropdown(['cellular', 'telephone'],label='Communication Type')
last_contacted_input = gr.Dropdown(['may', 'jul', 'aug', 'jun', 'nov', 'apr', 'oct', 'mar', 'sep', 'dec'],label='Last Contacted')
day_of_week_input = gr.Dropdown(['thu', 'mon', 'wed', 'tue', 'fri'],label='Day of Week')
pc_outcome_input = gr.Dropdown(['nonexistent', 'failure', 'success'], label='PC Outcome')

o = gr.Textbox()

# load the model
model = joblib.load('model.joblib')
i2l = ['Not subscribed', 'Subscribed']
def fn(age, duration, cc_contact_freq, days_since_pc, pc_contact_freq, job, marital_status, education, 
                         defaulter, home_loan, personal_loan, communication_type, last_contacted, 
                         day_of_week, pc_outcome):
    sample = {
        'Age': age,
        'Duration(Sec)': duration,
        'CC Contact Freq': cc_contact_freq,
        'Days Since PC': days_since_pc,
        'PC Contact Freq': pc_contact_freq,
        'Job': job,
        'Marital Status': marital_status,
        'Education': education,
        'Defaulter': defaulter,
        'Home Loan': home_loan,
        'Personal Loan': personal_loan,
        'Communication Type': communication_type,
        'Last Contacted': last_contacted,
        'Day of Week': day_of_week,
        'PC Outcome': pc_outcome,
    }
    print(f'sample: {sample}')
    data_point = pd.DataFrame([sample])
    print(f'{data_point}')
    result = model.predict(data_point)
    result = result[0]
    print(result)
    return i2l[result]


interface = gr.Interface(fn, 
                         inputs = [age_input,
                        duration_input,
                        cc_contact_freq_input,
                        days_since_pc_input,
                        pc_contact_freq_input,
                        job_input,
                        marital_input,
                        education_input,
                        defaulter_input,
                        home_loan_input,
                        personal_loan_input,
                        communication_type_input,
                        last_contacted_input,
                        day_of_week_input,
                        pc_outcome_input], 
                         outputs = o)

interface.launch(share=True)