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import streamlit as st
import json
import os
# shifted from below - this must be the first streamlit call; otherwise: problems
st.set_page_config(page_title = 'Climate Policy Analysis Assistant',
initial_sidebar_state='expanded', layout="wide")
import logging
logging.getLogger().setLevel(logging.INFO)
from utils.uploadAndExample import add_upload
import appStore.doc_processing as processing
import appStore.target as tapp_extraction
from PIL import Image
import pkg_resources
installed_packages = pkg_resources.working_set
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)
with(open('docStore/sample/files.json','r')) as json_file:
files = json.load(json_file)
add_upload(choice, files)
with st.container():
st.markdown("<h2 style='text-align: center; color: black;'> Climate Policy Analysis Assistant: CPo_droid </h2>", unsafe_allow_html=True)
st.write(' ')
with st.expander("ℹ️ - About this app", expanded=False):
st.write(
"""
CPo_droid 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("""
- **Target**: 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.
- **Economy-wide Target**: Certain Target are applicable \
not at specific Sector level but are applicable at economic \
wide scale.
- **Netzero**: Identifies if its Netzero Target or not.
- 'NET-ZERO target_labels' = ['T_Netzero','T_Netzero_C']
- **GHG Target**: GHG targets refer to contributions framed as targeted \
outcomes in GHG terms.
- 'GHG': ['T_Transport_Unc','T_Transport_C','T_Economy_C','T_Economy_Unc','T_Energy_C','T_Energy_Unc']
- 'NON GHG TARGET': ['T_Adaptation_Unc','T_Adaptation_C', 'T_Transport_O_Unc', 'T_Transport_O_C']
- **Conditionality**: An “unconditional contribution” is what countries \
could implement without any conditions and based on their own \
resources and capabilities. A “conditional contribution” is one \
that countries would undertake if international means of support \
are provided, or other conditions are met.
- **Action**: Actions are an intention to implement specific means of \
achieving GHG reductions, usually in forms of concrete projects.
- **Policies and Plans**: Policies are domestic planning documents \
such as policies, regulations or guidlines, and Plans are broader \
than specific policies or actions, such as a general intention \
to ‘improve efficiency’, ‘develop renewable energy’, etc. \
The terms come from the World Bank's NDC platform and WRI's publication.
""")
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?
- 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 **TAPP(Target/Action/Policy/Plan multilabel) Classifier** which detects if
the paragraph contains any *TAPP* related information or not.
- Step 3: The paragraphs which are detected containing some TAPP \
related information are then fed to multiple classifier to enrich the
Information Extraction.
""")
list_ = ""
for package in installed_packages:
list_ = list_ + f"{package.key}=={package.version}\n"
st.download_button('Download Requirements', list_, file_name='requirements.txt')
st.write("")
# apps to be run
apps = [processing.app, tapp_extraction.app]
#, sector.app, adapmit.app,
# conditional.app, subtarget.app, category.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() |