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| import os | |
| import gdown as gdown | |
| import nltk | |
| import streamlit as st | |
| import torch | |
| from transformers import AutoTokenizer | |
| from mt5 import MT5 | |
| def download_models(ids): | |
| """ | |
| Download all models. | |
| :param ids: name and links of models | |
| :return: | |
| """ | |
| # Download sentence tokenizer | |
| nltk.download('punkt') | |
| # Download model from drive if not stored locally | |
| for key in ids: | |
| if not os.path.isfile(f"model/{key}.ckpt"): | |
| url = f"https://drive.google.com/u/0/uc?id={ids[key]}" | |
| gdown.download(url=url, output=f"model/{key}.ckpt") | |
| def load_model(model_path): | |
| """ | |
| Load model and cache it. | |
| :param model_path: path to model | |
| :return: | |
| """ | |
| device = 'cuda' if torch.cuda.is_available() else 'cpu' | |
| # Loading model and tokenizer | |
| model = MT5.load_from_checkpoint(model_path).eval().to(device) | |
| model.tokenizer = AutoTokenizer.from_pretrained('tokenizer') | |
| return model | |
| # Page config | |
| st.set_page_config(layout="centered") | |
| st.title("Questions/Answers Pairs Gen.") | |
| st.write("Question Generation, Question Answering and Questions/Answers Generation using Google MT5. ") | |
| # Variables | |
| ids = {'mt5-small': st.secrets['small'], | |
| 'mt5-base': st.secrets['base']} | |
| maintenance = True | |
| if maintenance: | |
| st.write("Unavailable for now (maintenance). ") | |
| else: | |
| # Download all models from drive | |
| download_models(ids) | |
| # Task selection | |
| left, right = st.columns([4, 2]) | |
| task = left.selectbox('Choose the task: ', | |
| options=['Questions/Answers Pairs Generation', 'Question Answering', 'Question Generation'], | |
| help='Choose the task you want to try out') | |
| # Model selection | |
| model_path = right.selectbox('', options=[k for k in ids], index=1, help='Model to use. ') | |
| model = load_model(model_path=f"model/{model_path}.ckpt") | |
| right.write(model.device) | |
| if task == 'Questions/Answers Pairs Generation': | |
| # Input area | |
| inputs = st.text_area('Context:', value="A few years after the First Crusade, in 1107, the Normans under " | |
| "the command of Bohemond, Robert\'s son, landed in Valona and " | |
| "besieged Dyrrachium using the most sophisticated military " | |
| "equipment of the time, but to no avail. Meanwhile, they occupied " | |
| "Petrela, the citadel of Mili at the banks of the river Deabolis, " | |
| "Gllavenica (Ballsh), Kanina and Jericho. This time, " | |
| "the Albanians sided with the Normans, dissatisfied by the heavy " | |
| "taxes the Byzantines had imposed upon them. With their help, " | |
| "the Normans secured the Arbanon passes and opened their way to " | |
| "Dibra. The lack of supplies, disease and Byzantine resistance " | |
| "forced Bohemond to retreat from his campaign and sign a peace " | |
| "treaty with the Byzantines in the city of Deabolis. ", max_chars=2048, | |
| height=250) | |
| split = st.checkbox('Split into sentences', value=True) | |
| if split: | |
| # Split into sentences | |
| sent_tokenized = nltk.sent_tokenize(inputs) | |
| res = {} | |
| with st.spinner('Please wait while the inputs are being processed...'): | |
| # Iterate over sentences | |
| for sentence in sent_tokenized: | |
| predictions = model.multitask([sentence], max_length=512) | |
| questions, answers, answers_bis = predictions['questions'], predictions['answers'], predictions[ | |
| 'answers_bis'] | |
| # Build answer dict | |
| content = {} | |
| for question, answer, answer_bis in zip(questions[0], answers[0], answers_bis[0]): | |
| content[question] = {'answer (extracted)': answer, 'answer (generated)': answer_bis} | |
| res[sentence] = content | |
| # Answer area | |
| st.write(res) | |
| else: | |
| with st.spinner('Please wait while the inputs are being processed...'): | |
| # Prediction | |
| predictions = model.multitask([inputs], max_length=512) | |
| questions, answers, answers_bis = predictions['questions'], predictions['answers'], predictions[ | |
| 'answers_bis'] | |
| # Answer area | |
| zip = zip(questions[0], answers[0], answers_bis[0]) | |
| content = {} | |
| for question, answer, answer_bis in zip: | |
| content[question] = {'answer (extracted)': answer, 'answer (generated)': answer_bis} | |
| st.write(content) | |
| elif task == 'Question Answering': | |
| # Input area | |
| inputs = st.text_area('Context:', value="A few years after the First Crusade, in 1107, the Normans under " | |
| "the command of Bohemond, Robert\'s son, landed in Valona and " | |
| "besieged Dyrrachium using the most sophisticated military " | |
| "equipment of the time, but to no avail. Meanwhile, they occupied " | |
| "Petrela, the citadel of Mili at the banks of the river Deabolis, " | |
| "Gllavenica (Ballsh), Kanina and Jericho. This time, " | |
| "the Albanians sided with the Normans, dissatisfied by the heavy " | |
| "taxes the Byzantines had imposed upon them. With their help, " | |
| "the Normans secured the Arbanon passes and opened their way to " | |
| "Dibra. The lack of supplies, disease and Byzantine resistance " | |
| "forced Bohemond to retreat from his campaign and sign a peace " | |
| "treaty with the Byzantines in the city of Deabolis. ", max_chars=2048, | |
| height=250) | |
| question = st.text_input('Question:', value="What forced Bohemond to retreat from his campaign? ") | |
| # Prediction | |
| with st.spinner('Please wait while the inputs are being processed...'): | |
| predictions = model.qa([{'question': question, 'context': inputs}], max_length=512) | |
| answer = {question: predictions[0]} | |
| # Answer area | |
| st.write(answer) | |
| elif task == 'Question Generation': | |
| # Input area | |
| inputs = st.text_area('Context (highlight answers with <hl> tokens): ', | |
| value="A few years after the First Crusade, in <hl> 1107 <hl>, the <hl> Normans <hl> under " | |
| "the command of <hl> Bohemond <hl>, Robert\'s son, landed in Valona and " | |
| "besieged Dyrrachium using the most sophisticated military " | |
| "equipment of the time, but to no avail. Meanwhile, they occupied " | |
| "Petrela, <hl> the citadel of Mili <hl> at the banks of the river Deabolis, " | |
| "Gllavenica (Ballsh), Kanina and Jericho. This time, " | |
| "the Albanians sided with the Normans, dissatisfied by the heavy " | |
| "taxes the Byzantines had imposed upon them. With their help, " | |
| "the Normans secured the Arbanon passes and opened their way to " | |
| "Dibra. The <hl> lack of supplies, disease and Byzantine resistance <hl> " | |
| "forced Bohemond to retreat from his campaign and sign a peace " | |
| "treaty with the Byzantines in the city of Deabolis. ", max_chars=2048, | |
| height=250) | |
| # Split by highlights | |
| hl_index = [i for i in range(len(inputs)) if inputs.startswith('<hl>', i)] | |
| contexts = [] | |
| answers = [] | |
| # Build a context for each highlight pair | |
| for i in range(0, len(hl_index), 2): | |
| contexts.append(inputs[:hl_index[i]].replace('<hl>', '') + | |
| inputs[hl_index[i]: hl_index[i + 1] + 4] + | |
| inputs[hl_index[i + 1] + 4:].replace('<hl>', '')) | |
| answers.append(inputs[hl_index[i]: hl_index[i + 1] + 4].replace('<hl>', '').strip()) | |
| # Prediction | |
| with st.spinner('Please wait while the inputs are being processed...'): | |
| predictions = model.qg(contexts, max_length=512) | |
| # Answer area | |
| content = {} | |
| for pred, ans in zip(predictions, answers): | |
| content[pred] = ans | |
| st.write(content) | |