| import streamlit as st | |
| from functions import * | |
| st.set_page_config(page_title="Earnings Summarization", page_icon="📖") | |
| st.sidebar.header("Earnings Summarization") | |
| st.markdown("## Earnings Summarization with FaceBook-Bart") | |
| max_len= st.slider("Maximum length of the summarized text",min_value=50,max_value=200,step=10) | |
| min_len= st.slider("Minimum length of the summarized text",min_value=20,max_value=200,step=10) | |
| st.markdown("####") | |
| st.subheader("Summarized Earnings Call with matched Entities") | |
| if earnings_passages: | |
| text_to_summarize = chunk_and_preprocess_text(earnings_passages) | |
| summarized_text = sum_pipe(text_to_summarize,max_length=max_len,min_length=min_len,clean_up_tokenization_spaces=True,no_repeat_ngram_size=4) | |
| summarized_text = ' '.join([summ['summary_text'] for summ in summarized_text]) | |
| with st.spinner("Summarizing and matching entities, this takes a few seconds..."): | |
| entity_match_html = highlight_entities(text_to_summarize,summarized_text) | |
| st.markdown("####") | |
| with st.expander(label='Summarized Earnings Call',expanded=True): | |
| st.write(entity_match_html, unsafe_allow_html=True) | |
| st.markdown("####") | |
| summary_downloader(summarized_text) | |
| else: | |
| st.write("No text to summarize detected, please ensure you have entered the YouTube URL on the Sentiment Analysis page") |