import streamlit as st import pandas as pd from plms.language_model import TransformersQG import time import os import numpy as np st.set_page_config(page_icon='🧪', page_title='ViQAG for Vietnamese Education', layout='centered', 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("

AlphaEdu

", unsafe_allow_html=True) # ===================================================================================================== if 'output' not in st.session_state: st.session_state.output = '' 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 len(context), context def generateQA(context, model_path = 'shnl/vit5-vinewsqa-qg-ae'): unique_qa_pairs = set() model = TransformersQG(model=model_path, max_length=512) output = model.generate_qa(context) qa_pairs = '' for item in output: question, answer = item if (question, answer) not in unique_qa_pairs: qa_pairs += f'question: {question} \nanswer: {answer} [SEP] ' unique_qa_pairs.add((question, answer)) qa = '\n\n'.join(qa_pairs.split(' [SEP] ')) return qa # ===================================================================================================== col_1, col_2 = st.sidebar.columns(spec=[1, 1]) subject = col_1.selectbox(label='Select your subject:', options=filenames, label_visibility='visible') list_grades, df = load_grades(file_name=subject) grade = col_2.selectbox(label='Select your grade:', options=list_grades, label_visibility='visible') list_chapters, df = load_chapters(df=df, grade_name=grade) chapter = st.sidebar.selectbox(label='Select your chapter:', options=list_chapters, label_visibility='visible') lesson_names = load_lessons(df=df, grade_name=grade, chapter_name=chapter) lesson = st.sidebar.selectbox(label='Lesson:', options=lesson_names, label_visibility='visible') total_paragraph, context_values = load_context(df=df, grade_name=grade, chapter_name=chapter, lesson_name=lesson) col_12, col_22 = st.sidebar.columns(spec=[4, 6]) paragraph_idx = col_12.selectbox(label='Paragraph:', options=list(np.arange(1, total_paragraph + 1)), label_visibility='visible') paragraph = st.text_area(label='Paragraph content', label_visibility='visible', height=200, value=context_values[paragraph_idx - 1]) col_22.selectbox(label='QAG model:', options=['ViT5-ViNewsQA'], label_visibility='visible') btn_show_answer = st.sidebar.toggle(label='Show answers', disabled=False) col_14, col_24, col_34, col_44, col_54 = st.columns(spec=[1, 1, 1, 1, 1]) btn_generate = col_34.button(label='Generate', use_container_width=True) if btn_generate == True: with st.spinner(text='Generating QA pairs from the selected paragraph. Please wait ...'): st.session_state.output = generateQA(context=paragraph) if btn_show_answer: if st.session_state.output != '': st.markdown("Generated QA pairs:", unsafe_allow_html=True) st.code(body=st.session_state.output, language='latex') else: pass else: if st.session_state.output != '': st.markdown("Generated QA pairs:", unsafe_allow_html=True) output_no_answer = st.session_state.output.split(' [SEP] ')[0].split(', answer: ')[0].replace('question: ', '') st.code(body=output_no_answer, language='latex') else: pass