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37 lines
1.4 KiB
Python
37 lines
1.4 KiB
Python
# Demo: (Timeseries, CheckboxGroup, Slider) -> (Timeseries, Dataframe, Label)
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import gradio as gr
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import pandas as pd
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import random
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def fraud_detector(card_activity, categories, sensitivity):
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activity_range = random.randint(0, 100)
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drop_columns = [column for column in ["retail", "food", "other"] if column not in categories]
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if len(drop_columns):
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card_activity.drop(columns=drop_columns, inplace=True)
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return card_activity, card_activity, {"fraud": activity_range / 100., "not fraud": 1 - activity_range / 100.}
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iface = gr.Interface(fraud_detector,
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[
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gr.inputs.Timeseries(
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x="time",
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y=["retail", "food", "other"]
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),
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gr.inputs.CheckboxGroup(["retail", "food", "other"], default=[
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"retail", "food", "other"]),
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gr.inputs.Slider(1, 3)
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],
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[
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"dataframe",
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gr.outputs.Timeseries(
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x="time",
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y=["retail", "food", "other"]
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),
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gr.outputs.Label(label="Fraud Level"),
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]
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)
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if __name__ == "__main__":
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iface.launch()
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