Predict the wine class for the latest added wine

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 from PIL import Image
 import hopsworks
 import pandas as pd
+import joblib
 
 project = hopsworks.login()
 fs = project.get_feature_store()
@@ -11,16 +12,27 @@ dataset_api = project.get_dataset_api()
 dataset_api.download("Resources/images/wine/df_recent.png")
 dataset_api.download("Resources/images/wine/confusion_matrix.png")
 
-monitor_fg = fs.get_feature_group(name="wine", version=1)
-history_df = monitor_fg.read(read_options={"use_hive": True})
-df_latest = history_df.tail(1)
-latest_wine_string = df_latest.to_string(index=False)
+# Read the latest wine added to the feature store
+wine_fg = fs.get_feature_group(name="wine", version=1)
+wine_df = wine_fg.read(read_options={"use_hive": True})
+latest_wine_df = wine_df.tail(1)
+latest_wine_string = latest_wine_df.to_string(index=False)
+
+# Predict the wine class
+mr = project.get_model_registry()
+model = mr.get_model("wine_class_model", version=1)
+model_dir = model.download()
+model = joblib.load(model_dir + "/wine_class_model.pkl")
+y_pred = model.predict(latest_wine_df)
 
 with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column():
             gr.Label("Most Recent Wine Added")
             out = gr.Textbox(latest_wine_string, readonly=True)
+        with gr.Column():
+            gr.Label("Predicted Wine Class")
+            out = gr.Textbox(y_pred[0], readonly=True)
     with gr.Row():
       with gr.Column():
           gr.Label("Recent Prediction History")