import streamlit as st
from src.pager import get_pager
from src.summarizer import Summarizer
import torch


torch.classes.__path__ = []

@st.cache_resource
def GetSummarizer():
    return Summarizer()


url = st.text_input("Please enter your habr article url...")
text = st.text_input("...or paste text here:strawberry:")

def handle_sum_text(sum_text):
    return sorted(set([('#' + x).upper() for x in sum_text.split()]))

def url_callback():
    summarizer = GetSummarizer()
    pager = get_pager(url)
    if pager is not None:
        st.title(pager.title)
        sum_text = summarizer.summarize(pager.text[:1000])
        st.write("Okay, there your tags :sunglasses:")
        for chunk in handle_sum_text(sum_text):
            st.badge(chunk, icon=":material/check:", color="green")
    else:
        st.title(":shit: Слушай ну нормально же общались")

def generator_callback():
    summarizer = GetSummarizer()
    st.title("Your AWESOME:heart: article")
    sum_text = summarizer.summarize(text[:1000])
    st.write("Okay, there your #tags :sunglasses:")
    for chunk in handle_sum_text(sum_text):
        st.badge(chunk, icon=":material/check:", color="green")


st.button("Describe Habr Article", on_click=url_callback)

st.button("Describe text", on_click=generator_callback)