app.py

import gradio as gr
import numpy as np
from PIL import Image
import requests
import os

import hopsworks
import joblib

project = hopsworks.login(api_key_value=os.environ['UNI_HOPSWORKS_API_KEY'])
fs = project.get_feature_store()

mr = project.get_model_registry()
model = mr.get_model("wine_model", version=1)
model_dir = model.download()

model = joblib.load(model_dir + "/wine_model.pkl")


def wine(fixed_acidity,
    volatile_acidity,
    citric_acid,
    residual_sugar,
    chlorides,
    free_sulfur_dioxide,
    total_sulfur_dioxide,
    density,
    pH,
    sulphates,
    alcohol,
    white):
    input_list = []

    input_list.append(fixed_acidity)
    input_list.append(volatile_acidity)
    input_list.append(citric_acid)
    input_list.append(residual_sugar)
    input_list.append(chlorides)
    input_list.append(free_sulfur_dioxide)
    input_list.append(total_sulfur_dioxide)
    input_list.append(density)
    input_list.append(pH)
    input_list.append(sulphates)
    input_list.append(alcohol)
    input_list.append(white)

    res = model.predict(np.asarray(input_list).reshape(1, -1))            
    return res
        
demo = gr.Interface(
    fn=wine,
    title="Wine prediction",
    description="Wine quality prediction",
    allow_flagging="never",
    inputs=[
        gr.inputs.Number(default=1.0, label="fixed_acidity"),
        gr.inputs.Number(default=1.0, label="volatile_acidity"),
        gr.inputs.Number(default=1.0, label="citric_acid"),
        gr.inputs.Number(default=1.0, label="residual_sugar"),
        gr.inputs.Number(default=1.0, label="chlorides"),
        gr.inputs.Number(default=1.0, label="free_sulfur_dioxide"),
        gr.inputs.Number(default=1.0, label="total_sulfur_dioxide"),
        gr.inputs.Number(default=1.0, label="density"),
        gr.inputs.Number(default=1.0, label="pH"),
        gr.inputs.Number(default=1.0, label="sulphates"),
        gr.inputs.Number(default=1.0, label="alcohol"),
        gr.inputs.Number(default=1.0, label="white")
        ],
    outputs=gr.Text(value="none")
    )


demo.launch()