adding files for running the gradio application

app.py

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+import gradio as gr
+from PIL import Image, ImageDraw, ImageFont
+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")
+
+columns = ['type_white','fixed_acidity','volatile_acidity','citric_acid','residual_sugar','chlorides','free_sulfur_dioxide','total_sulfur_dioxide','density','alcohol']
+
+
+def get_image_with_text(text):
+    img = Image.new(size=(200,200),mode="RGBA", color='white')
+    draw = ImageDraw.Draw(img)
+    font = ImageFont.load_default(size=150)
+    draw.text((50,0), text, font=font, fill=(0, 0, 0, 0))
+    return img
+
+def wine(type_white,fixed_acidity,volatile_acidity,citric_acid,residual_sugar,chlorides,free_sulfur_dioxide,total_sulfur_dioxide,density,alcohol):
+    print("Calling function")
+#     df = pd.DataFrame([[sepal_length],[sepal_width],[petal_length],[petal_width]], 
+    df = pd.DataFrame([[type_white,fixed_acidity,volatile_acidity,citric_acid,residual_sugar,chlorides,free_sulfur_dioxide,total_sulfur_dioxide,density,alcohol]], 
+                      columns=columns)
+    print("Predicting")
+    print(df)
+    res = model.predict(df) 
+    print(res)
+
+    img = get_image_with_text(f'{res}')
+    img = Image.open(requests.get(flower_url, stream=True).raw)            
+    return img
+        
+demo = gr.Interface(
+    fn=iris,
+    title="Wine Quality Predictive Analytics",
+    description="Experiment with the features to predict which quality the wine is.",
+    allow_flagging="never",
+    inputs=[
+        gr.Number(value=1.0, label='is_white_wine (1/0)'),
+        gr.Number(value=7.0, label=columns[1]),
+        gr.Number(value=0.20, label=columns[2]),
+        gr.Number(value=0.25, label=columns[3]),
+        gr.Number(value=9.0, label=columns[4]),
+        gr.Number(value=0.05, label=columns[5]),
+        gr.Number(value=40.0, label=columns[6]),
+        gr.Number(value=150.0, label=columns[7]),
+        gr.Number(value=0.9950, label=columns[8]),
+        gr.Number(value=10.0, label=columns[9]),
+        ],
+    outputs=gr.Image(type="pil"))
+
+demo.launch(debug=True)

requirements.txt

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+gradio==4.4.1
+hopsworks==3.4.3
+joblib==1.3.2
+pandas==2.0.3
+Pillow==10.1.0
+Requests==2.31.0