import streamlit as st

def app():
    
    
    with open('style.css') as f:
        st.markdown(f"<style>{f.read()}</style>", unsafe_allow_html=True)
    
    st.markdown("<h2 style='text-align: center;  \
                      color: black;'> Vulnerability Identifier</h2>", 
                      unsafe_allow_html=True)

    
    st.markdown("<div style='text-align: center; \
                    color: grey;'>The Vulnerability Identifier is an open-source\
                         digital tool which aims to assist policy analysts and \
                          other users in extracting and filtering relevant \
                            information on vulnerable groups from policy documents.</div>",
                        unsafe_allow_html=True)
    footer = """
           <div class="footer-custom">
               Guidance & Feedback - <a href="https://www.linkedin.com/in/maren-bernlöhr-149891222" target="_blank">Robin Nowok</a> |
               Developer - <a href="https://www.linkedin.com/in/lea-voigt/" target="_blank">Lea Voigt</a>  |   
               <a href="https://www.linkedin.com/in/prashantpsingh/" target="_blank">Prashant Singh</a> |
               
           </div>
       """
    st.markdown(footer, unsafe_allow_html=True)

    #c1, c2, c3 =  st.columns([8,1,12])
    #with c1:
     #   st.image("docStore/img/ndc.png")
    #with c3:
    st.markdown('<div style="text-align: justify;">The manual extraction \
    of relevant information from text documents is a \
    time-consuming task for any policy analyst. As the amount and length of \
    public policy documents in relation to sustainable development (such as \
    National Development Plans and Nationally Determined Contributions) \
    continuously increases, a major challenge for policy action tracking – the \
    evaluation of stated goals and targets and their actual implementation on \
    the ground – arises. Luckily, Artificial Intelligence (AI) and Natural \
    Language Processing (NLP) methods can help in shortening and easing this \
    task for policy analysts.</div><br>',
    unsafe_allow_html=True)

    intro = """
    <div style="text-align: justify;">

    For this purpose, the Data Lab and the Data Service Center (DSC) \
    from the Deutsche Gesellschaft für Internationale \
    Zusammenarbeit (GIZ) GmbH have collaborated in the development \
    of this AI-powered open-source web application that helps find and extract \
    relevant information from public policy documents faster to facilitate \
    evidence-based decision-making processes in sustainable development and beyond.  

    This tool allows policy analysts and other users the possibility to rapidly \
    search for relevant information/paragraphs in the document related to different \
    vulnerable groups in the climate context. \


    </div>
    <br>
    """
    st.markdown(intro, unsafe_allow_html=True)
    # st.image("docStore/img/paris.png")