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import pandas as pd |
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import streamlit as st |
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from category_classification.models import models as class_models |
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from common import Input |
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from languages import * |
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from results import process_results |
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page_title = {en: "Papers classification", ru: "Классификация статей"} |
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model_label = {en: "Select model", ru: "Выберете модель"} |
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title_label = {en: "Title", ru: "Название статьи"} |
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authors_label = {en: "Author(s)", ru: "Автор(ы)"} |
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abstract_label = {en: "Abstract", ru: "Аннотация"} |
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def text_area_height(line_height: int): |
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return 34 * line_height |
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@st.cache_data |
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def load_class_model(name): |
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model = class_models.get_model(name) |
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return model |
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lang = st.pills(label=langs_str, options=langs, default=en) |
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st.title(page_title[lang]) |
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model_name = st.selectbox( |
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model_label[lang], options=class_models.get_model_names_by_lang(lang) |
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) |
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title = st.text_area(title_label[lang], height=text_area_height(2)) |
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authors = st.text_area(authors_label[lang], height=text_area_height(2)) |
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abstract = st.text_area(abstract_label[lang], height=text_area_height(5)) |
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if title: |
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input = Input(title=title, abstract=abstract, authors=authors) |
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model = load_class_model(model_name) |
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results = model(input) |
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results = process_results(results, lang) |
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st.dataframe(results, hide_index=True) |
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