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import streamlit as st | |
import pandas as pd | |
import torch | |
from transformers import pipeline | |
import datetime | |
#from datasets import load_dataset | |
#dataset = load_dataset("wikitablequestions", trust_remote_code=True) | |
#item = dataset["test"][10] # show first test example | |
#def to_pandas(item): | |
#return pd.DataFrame(item['table']["rows"], columns=item['table']["header"]) | |
#df = to_pandas(item) | |
#print(df.head()) | |
df = pd.read_csv("anomalies.csv",quotechar='"',dtype={col: str for col in pd.read_csv('anomalies.csv', nrows=1)}) | |
df = df.fillna('').astype(str) | |
# Function to generate a response using the TAPEX model | |
def response(user_question, df): | |
a = datetime.datetime.now() | |
tqa = pipeline(task="table-question-answering", model="google/tapas-large-finetuned-wtq") | |
print("DataFrame shape:", df.shape) | |
print("DataFrame head:\n", df.head()) | |
print("User question:", user_question) | |
answer = tqa(table=df, query=user_question)['answer'] | |
query_result = { | |
"Resposta": answer | |
} | |
b = datetime.datetime.now() | |
print(b - a) | |
return query_result | |
# 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 human emoji when user asks a question | |
st.session_state['history'].append(('π€', user_question)) | |
st.markdown(f"**π€ {user_question}**") | |
# Generate the response | |
bot_response = response(user_question, df)["Resposta"] | |
# Add robot emoji when generating response and align to the right | |
st.session_state['history'].append(('π€', bot_response)) | |
st.markdown(f"<div style='text-align: right'>**π€ {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 == 'π€': | |
st.markdown(f"**π€ {message}**") | |
elif sender == 'π€': | |
st.markdown(f"<div style='text-align: right'>**π€ {message}**</div>", unsafe_allow_html=True) |