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Update app.py
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import streamlit as st
import pandas as pd
from transformers import pipeline
# Load the anomalies data and convert all cells to strings
df = pd.read_csv('anomalies.csv', sep=',', decimal='.')
df['ds'] = pd.to_datetime(df['ds'], format='%Y-%m-%d')
df.fillna("", inplace=True)
print(df.head())
def response(user_question):
tqa = pipeline(task="table-question-answering", model="google/tapas-large-finetuned-wtq")
resposta = tqa(table=df, query=user_question)['cells'][0]
return print(resposta)
# Streamlit interface
st.markdown("""
<div style='display: flex; align-items: center;'>
<div style='width: 40px; height: 40px; background-color: green; border-radius: 50%; margin-right: 5px;'></div>
<div style='width: 40px; height: 40px; background-color: red; border-radius: 50%; margin-right: 5px;'></div>
<div style='width: 40px; height: 40px; background-color: yellow; border-radius: 50%; margin-right: 5px;'></div>
<span style='font-size: 40px; font-weight: bold;'>Chatbot do Tesouro RS</span>
</div>
""", unsafe_allow_html=True)
# Chat history
if 'history' not in st.session_state:
st.session_state['history'] = []
# Input box for user question
user_question = st.text_input("Escreva sua questΓ£o aqui:", "")
if user_question:
# Add person emoji when typing question
st.session_state['history'].append(('πŸ‘€', user_question))
st.markdown(f"**πŸ‘€ {user_question}**")
# Generate the response
bot_response = response(user_question)
# Add robot emoji when generating response and align to the right
st.session_state['history'].append(('πŸ€–', bot_response))
st.markdown(f"<div style='text-align: right'>**πŸ€– {bot_response}**</div>", unsafe_allow_html=True)
# Clear history button
if st.button("Limpar"):
st.session_state['history'] = []
# Display chat history
for sender, message in st.session_state['history']:
if sender == 'πŸ‘€':
st.markdown(f"**πŸ‘€ {message}**")
elif sender == 'πŸ€–':
st.markdown(f"<div style='text-align: right'>**πŸ€– {message}**</div>", unsafe_allow_html=True)