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import os | |
import time | |
import re | |
import streamlit as st | |
import requests | |
from wordcloud import WordCloud | |
import matplotlib.pyplot as plt | |
# Установка API URL и заголовков | |
API_URL_TRA = "https://api-inference.huggingface.co" \ | |
"/models/Helsinki-NLP/opus-mt-en-ru" | |
API_URL_KEY = "https://api-inference.huggingface.co" \ | |
"/models/ml6team/keyphrase-extraction-kbir-inspec" | |
API_URL_SUM = "https://api-inference.huggingface.co" \ | |
"/models/facebook/bart-large-cnn" | |
TOKEN = os.getenv('API_TOKEN') | |
HEADERS = {"Authorization": TOKEN} | |
def hugging_api_request(url, payload): | |
response = requests.post(url, headers=HEADERS, json=payload, timeout=120) | |
body = response.json() | |
if 'error' in body: | |
print(response.status_code, body) | |
if 'estimated_time' in body: | |
time.sleep(body['estimated_time']) | |
else: | |
return | |
hugging_api_request(url, payload) | |
return body | |
# Функция для получения ключевых слов | |
def get_key_words(payload): | |
return hugging_api_request(API_URL_KEY, payload) | |
# Функция для перевода слова | |
def translate_key_words(payload): | |
return hugging_api_request(API_URL_TRA, payload) | |
# Функция для составления конспекта | |
def make_summary(payload): | |
return hugging_api_request(API_URL_SUM, payload) | |
# Очищаем список слов | |
def clean_list(words_list): | |
cleaned_words_list = [] | |
for word in words_list: | |
word = word.lower() | |
word = re.sub(r"[^а-яА-Яa-zA-Z\s]", "", word) | |
word = word.lstrip() | |
word = word.rstrip() | |
cleaned_words_list.append(word) | |
return cleaned_words_list | |
# Настраиваем заголовок и название страницы | |
st.set_page_config(layout="wide", page_title="Students' Personal Assistant") | |
st.markdown(' # :female-student: Персональный помощник для студентов') | |
st.divider() | |
st.markdown('# :blue_book: Конспект на английском языке') | |
col1, col2 = st.columns(2) | |
text_from_tarea = col1.text_area('Введите тект статьи на английском языке', | |
key='t_area', height=500) | |
button_start = st.button('Обработать текст') | |
key_words_list = [] | |
if button_start: | |
with st.spinner('Составляем конспект...'): | |
# Составляем конспект | |
summary_text = make_summary({"inputs": text_from_tarea}) | |
col2.text_area('Конспект статьи', height=500, | |
key='sum_area', value=summary_text[0]['summary_text']) | |
with st.spinner('Получаем ключевые слова...'): | |
# Извлекаем ключевые слова | |
kew_words = get_key_words({"inputs": text_from_tarea}) | |
for key_word in kew_words: | |
key_words_list.append(key_word['word'].lower()) | |
sorted_keywords = set(sorted(key_words_list)) | |
sorted_keywords = clean_list(sorted_keywords) | |
with st.spinner('Переводим ключевые слова...'): | |
# Переводим ключевые слова | |
translated_words_dict = translate_key_words( | |
{"inputs": sorted_keywords}) | |
translated_words_list = [ | |
word['translation_text'] for word in translated_words_dict] | |
# Создаем карточки | |
cleaned_words_list_ru = clean_list(translated_words_list) | |
cards_list = [] | |
for item1, item2 in zip(sorted_keywords, cleaned_words_list_ru): | |
cards_list.append([item1, item2]) | |
st.success('Готово') | |
with st.spinner('Создаем WordCloud...'): | |
# Выводим Word Cloud | |
st.set_option('deprecation.showPyplotGlobalUse', False) | |
words_str = ', '.join(sorted_keywords) | |
w = WordCloud(background_color="white", | |
width=1600, height=800).generate(words_str) | |
plt.imshow(w, interpolation='bilinear') | |
plt.imshow(w) | |
plt.axis("off") | |
st.pyplot() | |
# Выводим карточки | |
st.markdown('# :bookmark_tabs: Карточки из ключевых слов') | |
col1, col2, col3 = st.columns(3) | |
columns = [col1, col2, col3] | |
for index, el in enumerate(cards_list): | |
with columns[(index + 1) % 3]: | |
with st.container(border=True): | |
col4, col5 = st.columns([0.1, 0.9]) | |
with col4: | |
st.write("# :flower_playing_cards:") | |
with col5: | |
st.write(f'## :green[{el[0]}]') | |
st.write(f'### :blue[{el[1]}]') | |