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')