Create app.py

app.py

@@ -0,0 +1,56 @@
+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, 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, density, ph, sulphates, alcohol]],
+                      columns=["type", "fixed_acidity", "volatile_acidity", "citric_acid", "residual_sugar", "chlorides"
+                          , "free_sulfur_dioxide", "density", "ph", "sulphates", "alcohol"])
+    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)
+
+
+demo = gr.Interface(
+    fn=wine,
+    title="Wine quality predictive analytics",
+    description="Experiment with different properties of wine to predict what is its quality.",
+    allow_flagging="never",
+    inputs=[
+        gr.inputs.Number(default=1, label="wine color (1 for red, 0 for white)"),
+        gr.inputs.Number(default=8.0, label="fixed acidity (g/L)"),
+        gr.inputs.Number(default=8.0, label="volatile acidity (g/L)"),
+        gr.inputs.Number(default=8.0, label="citric acid (g/L)"),
+        gr.inputs.Number(default=2.5, label="residual sugar (g/L)"),
+        gr.inputs.Number(default=2.5, label="chlorides (g/L)"),
+        gr.inputs.Number(default=16.0, label="free_sulfur_dioxide (mg/l)"),
+        gr.inputs.Number(default=46.0, label="density (g/mL)"),
+        gr.inputs.Number(default=46.0, label="ph"),
+        gr.inputs.Number(default=46.0, label="sulphates (mg/L)"),
+        gr.inputs.Number(default=10.0, label="alcohol(°)"),
+    ],
+    outputs=gr.Image(type="pil"))
+
+demo.launch(debug=True)