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import streamlit as st
from utils.uploadAndExample import add_upload
from utils.config import model_dict
from utils.vulnerability_classifier import label_dict
import appStore.doc_processing as processing
import appStore.vulnerability_analysis as vulnerability_analysis
import appStore.target as target_analysis
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)
# Create a list of options for the dropdown
model_options = ['Llama3.1-8B','Llama3.1-70B','Llama3.1-405B','Zephyr 7B β','Mistral-7B','Mixtral-8x7B']
# Dropdown selectbox: model
model_sel = st.selectbox('Select a model:', model_options)
model_sel_name = model_dict[model_sel]
st.session_state['model_sel_name'] = model_sel_name
with st.container():
st.markdown("<h2 style='text-align: center;'> Vulnerability Analysis 3.1 </h2>", unsafe_allow_html=True)
st.write(' ')
with st.expander("ℹ️ - About this app", expanded=False):
st.write(
"""
The Vulnerability Analysis App is an open-source\
digital tool which aims to assist policy analysts and \
other users in extracting and filtering references \
to different groups in vulnerable situations from public documents. \
We use Natural Language Processing (NLP), specifically deep \
learning-based text representations to search context-sensitively \
for mentions of the special needs of groups in vulnerable situations
to cluster them thematically.
For more understanding on Methodology [Click Here](https://vulnerability-analysis.streamlit.app/)
""")
st.write("""
What Happens in 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 then fed to the **Vulnerability Classifier** which detects if
the paragraph contains any or multiple references to vulnerable groups.
""")
st.write("")
# Define the apps used
apps = [processing.app, vulnerability_analysis.app, target_analysis.app]
multiplier_val =1/len(apps)
if st.button("Analyze Document"):
prg = st.progress(0.0)
for i,func in enumerate(apps):
func()
prg.progress((i+1)*multiplier_val)
# If there is data stored
if 'key0' in st.session_state:
vulnerability_analysis.vulnerability_display()
target_analysis.target_display(model_sel_name=model_sel_name) |