import gradio as gr
import numpy as np
import requests

import hopsworks
import joblib

project = hopsworks.login()
fs = project.get_feature_store()


mr = project.get_model_registry()
model = mr.get_model("titanic_modal", version=5)
model_dir = model.download()
model = joblib.load(model_dir + "/titanic_model.pkl")


def titanic(age, sex, pclass, fare):
    input_list = []
    input_list.append(age)
    input_list.append(sex)
    input_list.append(pclass)
    input_list.append(fare)
    # 'res' is a list of predictions returned as the label.
    res = model.predict(np.asarray(input_list).reshape(1, -1)) 
    # We add '[0]' to the result of the transformed 'res', because 'res' is a list, and we only want 
    # the first element.
    if res == 0:
        output = "This individual probably survived the Titanic."
    else:
        output = "This individual unfortunately probably did not survive the Titanic."
    return output
        
demo = gr.Interface(
    fn=titanic,
    title="Titanic survivor analytics",
    description="Experiment with personal data to predict whether a person would survive the Titanic",
    allow_flagging="never",
    inputs=[
        gr.inputs.Number(default=30.0, label=" Age "),
        gr.inputs.Number(default=1, label=" Sex (0 = Female, 1 = Male) "),
        gr.inputs.Number(default=2, label=" Ticket class (1 = first, 2 = second, 3 = third) "),
        gr.inputs.Number(default=1.0, label=" Passenger fare (Positive real number)"),
        ],
    outputs=gr.outputs.Textbox(label='Prediction'))

demo.launch()