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app.py

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+from joblib import load
+import gradio as gr
+
+
+MODEL_NAME = ""
+loaded_model = load("model.joblib")
+
+
+def prediction_function(*args):
+    values_list = []
+
+    for arg in args:
+        values_list.append(int(arg))
+
+    prediction_result = loaded_model.predict([values_list])[0]
+
+    return f"Predicted value: {prediction_result}"
+
+
+def regression_inputs():
+    input_labels = loaded_model.input_feature_names
+
+    inputs = []
+    for input_label in input_labels:
+        value = gr.Textbox(label=input_label, type="text")
+        inputs.append(value)
+
+    return inputs
+
+
+def regression_output():
+    output_label = loaded_model.output_feature_name
+    output = gr.Textbox(label=output_label, type="text")
+
+    return output
+
+
+def create_interface():
+    interface = gr.Interface(
+        fn=prediction_function,
+        inputs=regression_inputs(),
+        outputs=regression_output(),
+        title=MODEL_NAME,
+    )
+
+    interface.launch(debug=True)
+
+
+create_interface()