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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.Timeseries(x="time", y=["retail", "food", "other"]), | |
gr.CheckboxGroup( | |
["retail", "food", "other"], value=["retail", "food", "other"] | |
), | |
gr.Slider(1, 3), | |
], | |
[ | |
"dataframe", | |
gr.Timeseries(x="time", y=["retail", "food", "other"]), | |
gr.Label(label="Fraud Level"), | |
], | |
examples=[ | |
[os.path.join(os.path.dirname(__file__), "fraud.csv"), ["retail", "food", "other"], 1.0], | |
], | |
) | |
if __name__ == "__main__": | |
demo.launch() | |