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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=2)
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] == 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()
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