app.py

import gradio as gr
from huggingface_hub import from_pretrained_keras
import pandas as pd
import numpy as np


model = from_pretrained_keras("keras-io/timeseries_transformer_classification")

def detect_issue(df):
  #df = pd.read_csv('sample.csv',header=None)
  pred = model.predict(df)[0]
  problem = 'No problem'
  if(np.argmax(pred)==1):
    problem = 'Engine problem'
  return problem, pred[1]
  

iface = gr.Interface(detect_issue,"dataframe",
	outputs=[
	        gr.outputs.Textbox(label="Engine issue"),
       		gr.outputs.Textbox(label="Engine issue score")], examples=["sample.csv"]
#	examples = ["sample.csv"],
)


iface.launch()