update app

app.py

@@ -8,7 +8,6 @@ import pandas as pd
 project = hopsworks.login()
 fs = project.get_feature_store()
 
-
 mr = project.get_model_registry()
 model = mr.get_model("iris_model", version=1)
 model_dir = model.download()
@@ -19,23 +18,18 @@ print("Model downloaded")
 def iris(sepal_length, sepal_width, petal_length, petal_width):
     print("Calling function")
     #     df = pd.DataFrame([[sepal_length],[sepal_width],[petal_length],[petal_width]],
-    df = pd.DataFrame(
-        [[sepal_length, sepal_width, petal_length, petal_width]],
-        columns=["sepal_length", "sepal_width", "petal_length", "petal_width"],
-    )
+    df = pd.DataFrame([[sepal_length, sepal_width, petal_length, petal_width]],
+                      columns=['sepal_length', 'sepal_width', 'petal_length', 'petal_width'])
     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
+    # 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)
-    flower_url = (
-        "https://raw.githubusercontent.com/featurestoreorg/serverless-ml-course/main/src/01-module/assets/"
-        + res[0]
-        + ".png"
-    )
+    flower_url = "https://raw.githubusercontent.com/featurestoreorg/serverless-ml-course/main/src/01-module/assets/" + \
+                 res[0] + ".png"
     img = Image.open(requests.get(flower_url, stream=True).raw)
     return img
 
@@ -51,7 +45,6 @@ demo = gr.Interface(
         gr.inputs.Number(default=2.0, label="petal length (cm)"),
         gr.inputs.Number(default=1.0, label="petal width (cm)"),
     ],
-    outputs=gr.Image(type="pil"),
-)
+    outputs=gr.Image(type="pil"))
 
-demo.launch(debug=True)
+demo.launch(debug=True)