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Sleeping
| import random | |
| import os | |
| import gradio as gr | |
| def fraud_detector(card_activity, categories, sensitivity): | |
| activity_range = random.randint(0, 100) | |
| drop_columns = [ | |
| column for column in ["retail", "food", "other"] if column not in categories | |
| ] | |
| if len(drop_columns): | |
| card_activity.drop(columns=drop_columns, inplace=True) | |
| return ( | |
| card_activity, | |
| card_activity, | |
| {"fraud": activity_range / 100.0, "not fraud": 1 - activity_range / 100.0}, | |
| ) | |
| demo = gr.Interface( | |
| fraud_detector, | |
| [ | |
| gr.CheckboxGroup( | |
| ["retail", "food", "other"], value=["retail", "food", "other"] | |
| ), | |
| gr.Slider(1, 3), | |
| ], | |
| [ | |
| "dataframe", | |
| gr.Label(label="Fraud Level"), | |
| ], | |
| examples=[ | |
| [os.path.join(os.path.dirname(__file__), "fraud.csv"), ["retail", "food", "other"], 1.0], | |
| ], | |
| api_name="predict" | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch() | |