app.py

import streamlit as st
from inference import InferenceModel


st.set_page_config(layout="wide")

st.title("ArxivTopicPicker")
st.write("This app helps define category of your scientific paper based on its name and abstract.")
name = st.text_input("Paste here name of your paper")
abstract = st.text_area("Paste here abstract of your paper")


@st.cache  # 👈 Add the caching decorator
def load_model():
    return InferenceModel()

model = load_model()
model.inference('load')

# if name != '':
#     st.text("Your paper:\n\tName: " + name + '.\n\tAbstract: ' + abstract)

if st.button("Start processing"):
    if name == '':
        st.write('<p style="font-family:sans-serif; color:Red; font-size: 21px;">Please, provide name of the paper!🙇‍♂️</p>', unsafe_allow_html=True)
    else:
        input_text = name + '. ' + abstract if abstract != '' else name + '.'
        top_topics = model.inference(input_text)
        if len(top_topics) == 0:
            st.text("We don't know yet😰")
        else:
            st.text(top_topics)