text: import gradio as gr
  import pandas as pd
  import random
  
  
  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., "not fraud": 1 - activity_range / 100.}
  
  
  iface = gr.Interface(fraud_detector,
                       [
                           gr.inputs.Timeseries(
                               x="time",
                               y=["retail", "food", "other"]
                           ),
                           gr.inputs.CheckboxGroup(["retail", "food", "other"], default=[
                               "retail", "food", "other"]),
                           gr.inputs.Slider(1, 3)
                       ],
                       [
                           "dataframe",
                           gr.outputs.Timeseries(
                               x="time",
                               y=["retail", "food", "other"]
                           ),
                           gr.outputs.Label(label="Fraud Level"),
                       ]
                       )
  if __name__ == "__main__":
      iface.launch()
  