Add application file

README.md

@@ -1,12 +1,13 @@
 ---
 title: Wine Quality Prediction
-emoji: 👁
-colorFrom: red
-colorTo: gray
+emoji: 🍷
+colorFrom: purple
+colorTo: green
 sdk: gradio
-sdk_version: 4.4.1
+sdk_version: 3.14.0
 app_file: app.py
 pinned: false
+license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,52 @@
+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_class_model", version=1)
+model_dir = model.download()
+model = joblib.load(model_dir + "/wine_class_model.pkl")
+print("Model downloaded")
+
+def wine_quality_class(wine_type, fixed_acidity, volatile_acidity, citric_acid, residual_sugar, chlorides, free_sulfur_dioxide, density, pH, sulphates, alcohol):
+    print("Calling function")
+    df = pd.DataFrame([[wine_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)
+    return res[0]
+
+
+demo = gr.Interface(
+    fn=wine_quality_class,
+    title="Wine Quality Predictive Analytics",
+    description="Experiment with wine quality to predict which quality it is.",
+    allow_flagging="never",
+    # type,fixed acidity,volatile acidity,citric acid,residual sugar,chlorides,free sulfur dioxide,density,pH,sulphates,alcohol,quality
+    # e.g. white,7,0.27,0.36,20.7,0.045,45,170,1.001,3,0.45,8.8,6
+    inputs=[
+        gr.inputs.Dropdown(["white", "red"], label="Wine type"),
+        gr.inputs.Number(default=7.0, label="fixed acidity"),
+        gr.inputs.Number(default=0.27, label="volatile acidity"),
+        gr.inputs.Number(default=0.36, label="citric acid"),
+        gr.inputs.Number(default=20.7, label="residual sugar"),
+        gr.inputs.Number(default=0.045, label="chlorides"),
+        gr.inputs.Number(default=45, label="free sulfur dioxide"),
+        gr.inputs.Number(default=1.001, label="density"),
+        gr.inputs.Number(default=3.0, label="pH"),
+        gr.inputs.Number(default=0.45, label="sulphates"),
+        gr.inputs.Number(default=8.8, label="alcohol"),
+        ],
+    outputs=gr.Textbox(type="str"))
+
+demo.launch(debug=True)
+

requirements.txt

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+hopsworks
+joblib
+scikit-learn==1.1.1