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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['context'][index]) | |
| txt_question = st.text_area(height=100, label='Your question:', value=st.session_state.df['question'][index]) | |
| txt_answer = st.text_area(height=100, label='Your answer:', value=st.session_state.df['answer'][index]) | |
| 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['context'][index] = txt_context | |
| st.session_state.df['question'][index] = txt_question | |
| st.session_state.df['answer'][index] = 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() |