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import appStore.target as target_extraction
import appStore.netzero as netzero
import appStore.sector as sector
import appStore.adapmit as adapmit
import appStore.ghg as ghg
import appStore.policyaction as policyaction
import appStore.indicator as indicator
import appStore.doc_processing as processing
from utils.uploadAndExample import add_upload
import streamlit as st
st.set_page_config(page_title = 'Climate Policy Intelligence',
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("<h2 style='text-align: center; color: black;'> Climate Policy Understanding App </h2>", unsafe_allow_html=True)
st.write(' ')
with st.expander("ℹ️ - About this app", expanded=False):
st.write(
"""
Climate Policy Understanding 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.
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 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.
Classifers:
- **Netzero**: Detects if any Netzero commitment is present in paragraph or not.
- **GHG**: Detects if any GHG related information present in paragraph or not.
- **Sector**: Detects which sectors are spoken/discussed about in paragraph.
- **Adaptation-Mitigation**: Detects if the paragraph is related to Adaptation and/or Mitigation.
""")
st.caption("""**Target** (Definition): Targets are an intention to achieve a specific result, \
for example, to reduce GHG emissions to a specific level \
(a GHG target) or increase energy efficiency or renewable \
energy to a specific level (a non-GHG target), typically by \
a certain date""")
st.caption("""**Economy-wide Target** (Definition): Certain Target are applicable \
not at specific Sector level but are applicable at economic \
wide scale. """)
st.write("")
apps = [processing.app, target_extraction.app, netzero.app, ghg.app,
sector.app, adapmit.app]
# policyaction.app, indicator.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)
prg.empty()
if 'key1' in st.session_state:
with st.sidebar:
topic = st.radio(
"Which category you want to explore?",
('Target', 'Action', 'Policies/Plans'))
if topic == 'Target':
target_extraction.target_display()
elif topic == 'Action':
policyaction.action_display()
else:
policyaction.policy_display()
# st.write(st.session_state.key1)
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