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| from src.Pipeline.predict_pipe import Predict_Pipeline | |
| import gradio as gr | |
| from src.exception import CustomException | |
| obj = Predict_Pipeline() | |
| demo = gr.Interface(obj.predict, | |
| inputs= [ | |
| gr.Radio(["male","female"],label="Gender"), | |
| gr.Dropdown(['group B' ,'group C' ,'group A' ,'group D' ,'group E'],label="Race"), | |
| gr.Dropdown(["bachelor's degree" ,'some college' ,"master's degree", "associate's degree", | |
| 'high school' ,'some high school'],label="Parent Education"), | |
| gr.Radio(['standard', 'free/reduced'],label="Lunch"), | |
| gr.Radio(['none', 'completed'],label="Coaching"), | |
| gr.Slider(0,100,label="writing Score"), | |
| gr.Slider(0,100,label="reading score")], | |
| outputs = "number" | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() |