# set path
import glob, os, sys; 
sys.path.append('../utils')

#import needed libraries
import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import streamlit as st
from utils.groups_classifier import load_groupsClassifier, groups_classification
import logging
logger = logging.getLogger(__name__)
from utils.config import get_classifier_params
from utils.preprocessing import paraLengthCheck
from io import BytesIO
import xlsxwriter
import plotly.express as px


# Declare all the necessary variables
classifier_identifier = 'group_classification'
params  = get_classifier_params(classifier_identifier)

def app():

    ### Main app code ###
    with st.container():

        # Classify groups
        df = group_classification(haystack_doc=df, threshold= params['threshold'])
        
def groups_display():
    if  'key1' in st.session_state:
        df = st.session_state.key1
                
        
        df['Action_check']  = df['Policy-Action Label'].apply(lambda x: True if 'Action' in x else False)
        hits  = df[df['Action_check'] == True]
        # hits['GHG Label'] = hits['GHG Label'].apply(lambda i: _lab_dict[i])
        range_val = min(5,len(hits))
        if range_val !=0:
            count_action = len(hits)

            st.write("")
            st.markdown("###### Top few Action Classified paragraph/text results from list of {} classified paragraphs ######".format(count_action))
            st.markdown("""<hr style="height:10px;border:none;color:#097969;background-color:#097969;" /> """, unsafe_allow_html=True)
            range_val = min(5,len(hits))
            for i in range(range_val):
                # the page number reflects the page that contains the main paragraph 
                # according to split limit, the overlapping part can be on a separate page
                st.write('**Result {}** : `page {}`, `Sector: {}`,\
                            `Indicators: {}`, `Adapt-Mitig :{}`'\
                    .format(i+1,
                            hits.iloc[i]['page'], hits.iloc[i]['Sector Label'],
                            hits.iloc[i]['Indicator Label'],hits.iloc[i]['Adapt-Mitig Label']))                        
                st.write("\t Text: \t{}".format(hits.iloc[i]['text'].replace("\n", " ")))
            hits = hits.reset_index(drop =True)
            st.write('----------------')
            st.write('Explore the data')
            st.write(hits)
            df.drop(columns = ['Action_check'],inplace=True)
            df_xlsx = to_excel(df)
            
            with st.sidebar:
                st.write('-------------')
                st.download_button(label='📥 Download Result',
                            data=df_xlsx ,
                            file_name= 'cpu_analysis.xlsx')

        else:
            st.info("🤔 No Actions found")


def groups_display():
    if  'key1' in st.session_state:
        df = st.session_state.key1
                
        
        df['Policy_check']  = df['Policy-Action Label'].apply(lambda x: True if 'Policies & Plans' in x else False)
        hits  = df[df['Policy_check'] == True]
        # hits['GHG Label'] = hits['GHG Label'].apply(lambda i: _lab_dict[i])
        range_val = min(5,len(hits))
        if range_val !=0:
            count_policy = len(hits)
    
            st.write("")
            st.markdown("###### Top few Policy/Plans Classified paragraph/text results from list of {} classified paragraphs ######".format(count_policy))
            st.markdown("""<hr style="height:10px;border:none;color:#097969;background-color:#097969;" /> """, unsafe_allow_html=True)
            range_val = min(5,len(hits))
            for i in range(range_val):
                # the page number reflects the page that contains the main paragraph 
                # according to split limit, the overlapping part can be on a separate page
                st.write('**Result {}** : `page {}`, `Sector: {}`,\
                            `Indicators: {}`, `Adapt-Mitig :{}`'\
                    .format(i+1,
                            hits.iloc[i]['page'], hits.iloc[i]['Sector Label'],
                            hits.iloc[i]['Indicator Label'],hits.iloc[i]['Adapt-Mitig Label']))                        
                st.write("\t Text: \t{}".format(hits.iloc[i]['text'].replace("\n", " ")))
            hits = hits.reset_index(drop =True)
            st.write('----------------')
            st.write('Explore the data')
            st.write(hits)
            df.drop(columns = ['Policy_check'],inplace=True)
            df_xlsx = to_excel(df)
            
            with st.sidebar:
                st.write('-------------')
                st.download_button(label='📥 Download Result',
                            data=df_xlsx ,
                            file_name= 'vulnerable_groups.xlsx')

        else:
            st.info("🤔 No Groups found")