import appStore.doc_processing as processing import appStore.target as target_extraction from utils.uploadAndExample import add_upload import streamlit as st ####################################### Dashboard ###################################################### # App st.set_page_config(page_title = 'Vulnerable Groups Identification', initial_sidebar_state='expanded', layout="wide") with st.sidebar: # upload and example doc choice = st.sidebar.radio(label = 'Select the Document', help = 'You can upload the document \ or else you can try a example document', options = ('Upload Document', 'Try Example'), horizontal = True) add_upload(choice) with st.container(): st.markdown("

Vulnerable Groups Identification

", unsafe_allow_html=True) st.write(' ') with st.expander("ℹ️ - About this app", expanded=False): st.write( """ The Vulnerable Groups Identification App is an open-source\ digital tool which aims to assist policy analysts and \ other users in extracting and filtering relevant \ information from public documents. """) st.write('**Definitions**') st.caption(""" - **Place holder**: Place holder \ Place holder \ Place holder \ Place holder \ Place holder """) st.write(""" What happens in the background? - Step 1: Once the document is provided to app, it undergoes *Pre-processing*.\ In this step the document is broken into smaller paragraphs \ (based on word/sentence count). - Step 2: The paragraphs are fed to **Target Classifier** which detects if the paragraph contains any *Target* related information or not. - Step 3: The paragraphs which are detected containing some target \ related information are then fed to multiple classifier to enrich the Information Extraction. The Step 2 and 3 are repated then similarly for Action and Policies & Plans. """) st.write("") # if 'key1' in st.session_state: # if st.button("Analyze Document"): # target_identifier.identify_groups() # st.write(st.session_state.key1)