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import gradio as gr
from PIL import Image
import requests
import hopsworks
import joblib
import pandas as pd
project = hopsworks.login()
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")
print("Model downloaded")
def wine(type, fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, free_sulfur_dioxide,
total_sulfur_dioxide, density, ph, sulphates, alcohol):
print("Calling function")
# df = pd.DataFrame([[sepal_length],[sepal_width],[petal_length],[petal_width]],
df = pd.DataFrame([[type, fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, free_sulfur_dioxide,
total_sulfur_dioxide, density, ph, sulphates, alcohol]],
columns=['type', 'fixed_acidity', 'volatile_acidity', 'citric_acid', 'residual_sugar', 'chlorides', 'free_sulfur_dioxide',
'total_sulfur_dioxide', 'density', 'ph', 'sulphates', 'alcohol'])
print("Predicting")
print(df)
# 'res' is a list of predictions returned as the label.
res = "Wine Quality is " + str(model.predict(df))
# We add '[0]' to the result of the transformed 'res', because 'res' is a list, and we only want
# the first element.
# print("Res: {0}").format(res)
return res
# flower_url = "https://raw.githubusercontent.com/featurestoreorg/serverless-ml-course/main/src/01-module/assets/" + res[0] + ".png"
# img = Image.open(requests.get(flower_url, stream=True).raw)
# return img
demo = gr.Interface(
fn=wine,
title="Wine Predictive Analytics",
description="Experiment with various wine components to predict its quality.",
allow_flagging="never",
inputs=[
gr.inputs.Number(default=0, label="Type (0 for red, 1 for white)"),
gr.inputs.Number(default=0.0, label="fixed acidity"),
gr.inputs.Number(default=0.0, label="volatile acidity"),
gr.inputs.Number(default=0.0, label="citric acid"),
gr.inputs.Number(default=0.0, label="residual sugar"),
gr.inputs.Number(default=0.0, label="chlorides"),
gr.inputs.Number(default=0.0, label="free sulfur dioxide"),
gr.inputs.Number(default=0.0, label="total sulfur dioxide"),
gr.inputs.Number(default=0.0, label="density"),
gr.inputs.Number(default=0.0, label="pH"),
gr.inputs.Number(default=0.0, label="sulphates"),
gr.inputs.Number(default=0.0, label="alcohol")
],
outputs="text")
demo.launch(debug=True)
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