import streamlit as st import pandas as pd import time import os st.set_page_config(page_icon='🧪', page_title='ViQAG for Vietnamese Education', layout='wide', initial_sidebar_state="collapsed") with open(r"./static/styles.css") as f: st.markdown(f"", unsafe_allow_html=True) st.markdown(f"""
""", unsafe_allow_html=True) st.markdown("

ViQAG: An Automate Question Answer Generation System for Vietnamese Education

", unsafe_allow_html=True) # ===================================================================================================== def file_selector(folder_path=r'./Resources/'): filenames = os.listdir(folder_path) return filenames filenames = file_selector() def load_grades(file_name, folder_path=r'./Resources/'): file_path = f"{folder_path}{file_name}" df = pd.read_csv(file_path) list_grades = df['grade'].drop_duplicates().values return list_grades, df def load_chapters(df, grade_name): df_raw = df[df['grade'] == grade_name] list_chapters = df_raw['chapter'].drop_duplicates().values return list_chapters, df def load_lessons(df, grade_name, chapter_name): df_raw = df[(df['grade'] == grade_name) & (df['chapter'] == chapter_name)] return df_raw['lesson'].drop_duplicates().values def load_context(df, grade_name, chapter_name, lesson_name): context = df[(df['grade'] == grade_name) & (df['chapter'] == chapter_name) & (df['lesson'] == lesson_name)]['context'].values return '\n'.join(context.tolist()) # ===================================================================================================== col_1, col_2, col_3, col_4 = st.columns(spec=[1, 1, 3, 4]) col_1.markdown("Select your subject:", unsafe_allow_html=True) subject = col_1.selectbox(label='Select your subject:', options=filenames, label_visibility='collapsed') col_2.markdown("Select your grade:", unsafe_allow_html=True) list_grades, df = load_grades(file_name=subject) grade = col_2.selectbox(label='Select your grade:', options=list_grades, label_visibility='collapsed') col_3.markdown("Select your chapter:", unsafe_allow_html=True) list_chapters, df = load_chapters(df=df, grade_name=grade) chapter = col_3.selectbox(label='Select your chapter:', options=list_chapters, label_visibility='collapsed') col_4.markdown("Select your lesson:", unsafe_allow_html=True) lesson_names = load_lessons(df=df, grade_name=grade, chapter_name=chapter) lesson = col_4.selectbox(label='Select your lesson:', options=lesson_names, label_visibility='collapsed') col_11, col_21 = st.columns(spec=[8, 2]) col_11.markdown("Paragraph related:", unsafe_allow_html=True) context_values = load_context(df=df, grade_name=grade, chapter_name=chapter, lesson_name=lesson) col_11.text_area(label='Paragraph related', label_visibility='collapsed', height=300, value=context_values) col_21.markdown("Choose question generation modes:", unsafe_allow_html=True) col_21.checkbox(label='Question Answer Generation', value=True) col_21.checkbox(label='Multiple Choice Question Generation (Coming soon)', disabled=True) col_21.checkbox(label='Fill-in-the-Blank Question Generation (Coming soon)', disabled=True) col_21.markdown("Options:", unsafe_allow_html=True) btn_show_answer = col_21.toggle(label='Show the answers', disabled=True) btn_generate = col_21.button(label='Generate questions', use_container_width=True) if btn_generate: with st.spinner(text='Generating...'): time.sleep(5) st.markdown("Your questions and answers has been generated:", unsafe_allow_html=True) output = '''question: , answer: [SEP] \nquestion: , answer: [SEP] \nquestion: , answer: [SEP] \nquestion: , answer: [SEP] \nquestion: , answer: [SEP]\nquestion: , answer: [SEP]\nquestion: , answer: [SEP]\nquestion: , answer: [SEP]\nquestion: , answer: [SEP]\nquestion: , answer: [SEP]''' st.code(body=output, language='wiki')