import streamlit as st from utils.uploadAndExample import add_upload ####################################### 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 """) #c1, c2, c3 = st.columns([12,1,10]) #with c1: #image = Image.open('docStore/img/flow.jpg') #st.image(image) #with c3: #st.write(""" #What Happens in background? #st.title("Identify references to vulnerable groups.") #st.write("""Vulnerable groups encompass various communities and individuals who are disproportionately affected by the impacts of climate change #due to their socioeconomic status, geographical location, or inherent characteristics. By incorporating the needs and perspectives of these groups #into national climate policies, governments can ensure equitable outcomes, promote social justice, and strive to build resilience within the most marginalized populations, #fostering a more sustainable and inclusive society as we navigate the challenges posed by climate change.This app allows you to identify whether a text contains any #references to vulnerable groups, for example when talking about policy documents.""") # Document upload #uploaded_file = st.file_uploader("Upload your file here") # Create text input box #input_text = st.text_area(label='Please enter your text here', value="This policy has been implemented to support women.") #st.write('Prediction:', model(input_text)) ######################################### Model ######################################################### # Load the model #model = SetFitModel.from_pretrained("leavoigt/vulnerable_groups") # Define the classes #id2label = { # 0: 'Agricultural communities', # 1: 'Children and Youth', # 2: 'Coastal communities', # 3: 'Drought-prone regions', # 4: 'Economically disadvantaged communities', # 5: 'Elderly population', # 6: 'Ethnic minorities and indigenous people', # 7: 'Informal sector workers', # 8: 'Migrants and Refugees', # 9: 'Other', # 10: 'People with Disabilities', # 11: 'Rural populations', # 12: 'Sexual minorities (LGBTQI+)', # 13: 'Urban populations', # 14: 'Women'} ### Process document to paragraphs # Source: https://blog.jcharistech.com/2021/01/21/how-to-save-uploaded-files-to-directory-in-streamlit-apps/ # Store uploaded file temporarily in directory to get file path (necessary for processing) # def save_uploadedfile(upl_file): # with open(os.path.join("tempDir",upl_file.name),"wb") as f: # f.write(upl_file.getbuffer()) # return st.success("Saved File:{} to tempDir".format(upl_file.name)) # if uploaded_file is not None: # # Save the file # file_details = {"FileName": uploaded_file.name, "FileType": uploaded_file.type} # save_uploadedfile(uploaded_file) # #Get the file path