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import appStore.doc_processing as processing |
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import appStore.groups as groups_extraction |
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from utils.uploadAndExample import add_upload |
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import streamlit as st |
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st.set_page_config(page_title = 'Vulnerable Groups Identification', |
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initial_sidebar_state='expanded', layout="wide") |
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with st.sidebar: |
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choice = st.sidebar.radio(label = 'Select the Document', |
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help = 'You can upload the document \ |
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or else you can try a example document', |
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options = ('Upload Document', 'Try Example'), |
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horizontal = True) |
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add_upload(choice) |
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with st.container(): |
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st.markdown("<h2 style='text-align: center; color: black;'> Vulnerable Groups Identification </h2>", unsafe_allow_html=True) |
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st.write(' ') |
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with st.expander("ℹ️ - About this app", expanded=False): |
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st.write( |
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""" |
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The Vulnerable Groups Identification App is an open-source\ |
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digital tool which aims to assist policy analysts and \ |
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other users in extracting and filtering relevant \ |
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information from public documents. |
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""") |
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st.write('**Definitions**') |
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st.caption(""" |
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- **Place holder**: Place holder \ |
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Place holder \ |
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Place holder \ |
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Place holder \ |
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Place holder |
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""") |
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st.write(""" |
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What happens in the background? |
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- Step 1: Once the document is provided to app, it undergoes *Pre-processing*.\ |
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In this step the document is broken into smaller paragraphs \ |
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(based on word/sentence count). |
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- Step 2: The paragraphs are fed to **Target Classifier** which detects if |
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the paragraph contains any *Target* related information or not. |
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- Step 3: The paragraphs which are detected containing some target \ |
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related information are then fed to multiple classifier to enrich the |
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Information Extraction. |
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The Step 2 and 3 are repated then similarly for Action and Policies & Plans. |
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""") |
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st.write("") |
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if st.button("Analyze Document"): |
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groups_extraction.identify_groups() |
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