Update app.py

app.py

@@ -1,23 +1,20 @@
 import streamlit as st
 import pandas as pd
 import torch
-from transformers import TapasConfig, TapasForQuestionAnswering
 from transformers import pipeline
 import datetime
 
 # Load the data
 df = pd.read_excel('discrepantes.xlsx')
 df.fillna(0, inplace=True)
-table_data = df.astype(str)
-print(table_data.head())
 
 # Function to generate a response using the TAPEX model
 def response(user_question, table_data):
     a = datetime.datetime.now()
 
-    model = TapasForQuestionAnswering.from_pretrained("google/tapas-base")
     tqa = pipeline(task="table-question-answering", model="google/tapas-large-finetuned-wtq")
-    answer = tqa(table=table_data, query=user_question)['answer']
+    answer = tqa(table=table, query=question)['cells'][0]
+    
     query_result = {
         "Resposta": answer
     }