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)})

# 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")
    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 questão aqui:", "")

if user_question:
    # Add human emoji when user asks a question
    st.session_state['history'].append(('👤', user_question))
    st.markdown(f"**👤 {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(('🤖', bot_response))
    st.markdown(f"<div style='text-align: right'>**🤖 {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 == '👤':
        st.markdown(f"**👤 {message}**")
    elif sender == '🤖':
        st.markdown(f"<div style='text-align: right'>**🤖 {message}**</div>", unsafe_allow_html=True)