app.py

import gradio as gr
import hopsworks
import joblib
import pandas as pd

project = hopsworks.login(project="SonyaStern_Lab1")
# fs = project.get_feature_store()

print("trying to dl model")
mr = project.get_model_registry()
model = mr.get_model("diabetes_model", version=1)
model_dir = model.download()
model = joblib.load(model_dir + "/diabetes_model.pkl")
print("Model downloaded")


def diabetes(age, bmi, hba1c_level, blood_glucose_level):
    print("Calling diabetes function")
    df = pd.DataFrame(
        [[age, bmi, hba1c_level, blood_glucose_level]],
        columns=["age", "bmi", "hba1c_level", "blood_glucose_level"],
    )
    print("Predicting")
    print(df)
    res = model.predict(df)
    print(res)
    return res


demo = gr.Interface(
    fn=diabetes,
    title="Diabetes Prediction",
    description="Fill these values with yours",
    allow_flagging="never",
    inputs=[
        gr.Number(label="age"),
        gr.Number(label="bmi"),
        gr.Number(label="hba1c_level"),
        gr.Number(label="blood_glucose_level"),
    ],
    outputs=gr.Number(label="diabetes"),
)

demo.launch(debug=True)