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import streamlit as st
import pandas as pd
import re
st.set_page_config(page_icon='🍃', page_title='MRC for Legal Document Dataset checker', layout='wide', initial_sidebar_state="collapsed")
# start processing events
def load_data(file_uploader):
if file_uploader is not None:
return pd.read_csv(file_uploader)
else:
return pd.DataFrame(columns=['context', 'question', 'answer'])
def convert_df(df):
# IMPORTANT: Cache the conversion to prevent computation on every rerun
return df.to_csv().encode("utf-8")
# end processing events
st.markdown("<h1 style='text-align: center;'>Investigation Legal Dataset checker for Machine Reading Comprehension</h1>", unsafe_allow_html=True)
file = st.file_uploader(label='Upload your file here:', type=['csv'], accept_multiple_files=False, label_visibility='hidden')
df = load_data(file_uploader=file)
if 'df' not in st.session_state:
st.session_state.df = df
if 'idx' not in st.session_state:
st.session_state.idx = 0
st.markdown(f"<h3 style='text-align: center;'>Sample {st.session_state.idx + 1}/{len(df)}</h3>", 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_previous = col_1.button(label=':arrow_backward: Previous sample', use_container_width=True)
btn_next = col_2.button(label='Next sample :arrow_forward:', use_container_width=True)
btn_save = col_3.button(label=':heavy_check_mark: Save change', use_container_width=True)
# txt_goto = col_4.selectbox(label='None', options=[np.array(range(len(df)))], label_visibility='collapsed')
if len(df) != 0:
index = st.session_state.idx
txt_context = st.text_area(height=300, label='Your context:', value=st.session_state.df.loc[index, 'context'])
txt_question = st.text_area(height=100, label='Your question:', value=st.session_state.df.loc[index, 'question'])
txt_answer = st.text_area(height=100, label='Your answer:', value=st.session_state.df.loc[index, 'answer'])
if txt_answer.strip() and txt_context.strip():
highlighted_context = re.sub(re.escape(txt_answer), "<mark>" + txt_answer + "</mark>", txt_context, flags=re.IGNORECASE)
st.markdown(highlighted_context, unsafe_allow_html=True)
if btn_next:
if index < len(df) - 1:
st.session_state.idx += 1
st.rerun()
if btn_save:
st.session_state.df.loc[st.session_state.idx, 'context'] = txt_context
st.session_state.df.loc[st.session_state.idx, 'question'] = txt_question
st.session_state.df.loc[st.session_state.idx, 'answer'] = txt_answer
csv_file = convert_df(df=st.session_state.df)
btn_download = col_4.download_button(data=csv_file, label=':arrow_down_small: Download file', use_container_width=True, file_name="large_df.csv", mime="text/csv")
if btn_previous:
if index > 0:
st.session_state.idx -= 1
st.rerun() |