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import streamlit as st
import pandas as pd
import re
st.set_page_config(layout='wide')
def load_data():
return pd.read_csv(filepath_or_buffer='./Legal_AbstractiveA.csv')
df = load_data()
if 'idx' not in st.session_state:
st.session_state.idx = 0
st.markdown("<h1 style='text-align: center;'>Investigation Legal Documents Dataset Checker</h1>", unsafe_allow_html=True)
col_1, col_2, col_3, col_4, col_5, col_6, col_7, col_8, col_9, col_10 = st.columns([1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
btn_prev = col_1.button(label='Previous sample', use_container_width=True)
btn_next = col_2.button(label='Next sample', use_container_width=True)
btn_save = col_3.button(label='Save changes', use_container_width=True)
if btn_prev:
if st.session_state.idx > 0:
st.session_state.idx -= 1
if btn_next:
if st.session_state.idx < len(df) - 1:
st.session_state.idx += 1
st.markdown(f"<h3 style='text-align: center;'>Sample: {st.session_state.idx+1}/{len(df)}</h3>", unsafe_allow_html=True)
context = st.text_area(label='Your context: ', value=df['context'][st.session_state.idx], height=300)
question = st.text_area(label='Your question: ', value=df['question'][st.session_state.idx], height=100)
answer = st.text_area(label='Your answer: ', value=df['answer'][st.session_state.idx], height=100)
if answer.strip() and context.strip():
highlighted_context = re.sub(re.escape(answer), "<mark>" + answer + "</mark>", context, flags=re.IGNORECASE)
st.markdown(highlighted_context, unsafe_allow_html=True)
if btn_save:
df.loc[st.session_state.idx, 'context'] = context
df.loc[st.session_state.idx, 'question'] = question
df.loc[st.session_state.idx, 'answer'] = answer
df.to_csv('./Legal_AbstractiveA.csv', index=False)
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