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import modal
from PIL import Image
import gradio as gr
MODEL_VERSION = 6
LOCAL = True
if LOCAL == False:
hopsworks_image = modal.Image.debian_slim(python_version='3.9').pip_install(["gradio", "requests", "hopsworks", "joblib", "pandas", "scikit-learn==1.1.1"])
stub = modal.Stub("wine_prediction_user_interface")
@stub.function(image=hopsworks_image, secret=modal.Secret.from_name("HOPSWORKS_API_KEY"))
def f():
g()
def g():
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=MODEL_VERSION)
model_dir = model.download()
model = joblib.load(model_dir + "/wine_model.pkl")
print("Model downloaded")
def wine(fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, free_sulfur_dioxide,
total_sulfar_dioxide, density, ph, sulphates, alcohol, color):
print("Calling function")
# df = pd.DataFrame([[sepal_length],[sepal_width],[petal_length],[petal_width]],
df = pd.DataFrame([[fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, free_sulfur_dioxide,
total_sulfar_dioxide, density, ph, sulphates, alcohol, color]],
columns=['fixed_acidity', 'volatile_acidity', 'citric_aicd', 'residual_sugar', 'chlorides', 'free_sulfur_dioxide',
'total_sulfur_dioxide', 'density', 'ph', 'sulphates', 'alcohol', 'color'])
print("Predicting")
print(df)
# 'res' is a list of predictions returned as the label.
res = 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)
print(res)
return res
demo = gr.Interface(
fn=wine,
title="Wine Quality Predictive Analytics",
description="Experiment with several parameters to predict the quality of wine.",
allow_flagging="never",
inputs=[
gr.Number(value=1.0, label="fixed_acidity [3.8,15.9]"),
gr.Number(value=1.0, label="volatile_acidity [0.1,1.6]"),
gr.Number(value=1.0, label="citric_aicd [0.0,1.6]"),
gr.Number(value=1.0, label="residual_sugar [0.6,65.8]"),
gr.Number(value=1.0, label="chlorides [0.0,0.6]"),
gr.Number(value=1.0, label="free_sulfur_dioxide [1.0,289.0]"),
gr.Number(value=1.0, label="total_sulfur_dioxide [6.0,440.0]"),
gr.Number(value=1.0, label="density [0.9,1.0]"),
gr.Number(value=1.0, label="ph [2.7,4.0]"),
gr.Number(value=1.0, label="sulphates [0.2,2.0]"),
gr.Number(value=1.0, label="alcohol [8.0,14.9]"),
gr.Number(value=1.0, label="color (0:red, 1:white)"),
],
outputs=gr.Number(label="predicted quality"))
demo.launch(debug=True)
if __name__ == "__main__":
if LOCAL == True :
g()
else:
modal.runner.deploy_stub(stub)
with stub.run():
f.remote() |