import os
import sys
import docx
import re
# import textract
from tqdm import tqdm
from collections import Counter
import ntpath
from docx.shared import Inches, Cm, Pt
from docx.enum.text import WD_ALIGN_PARAGRAPH
from docx.enum.table import WD_TABLE_ALIGNMENT, WD_ALIGN_VERTICAL
import requests, uuid, json
import  nltk.translate.bleu_score as bleu
import nltk.translate.gleu_score as gleu
from rouge_score import rouge_scorer
import numpy as np
from indicnlp.tokenize import sentence_tokenize
import nltk

from MNF.settings import BasePath
basePath = BasePath()
from google.cloud import translate
from google.cloud import translate_v2 as Translate

from .script_detector import script_cat
from .buck_2_unicode import buck_2_unicode
from .translation_metric import manual_diff_score, bleu_diff_score, gleu_diff_score, meteor_diff_score, rouge_diff_score, diff_score, critera4_5
from .selection_source import selection_source, function5, function41, function311, function221, function2111, function11111, selection_source_transliteration, two_sources_two_outputs
from .script_writing import addSlugLine, addActionLine, addSpeaker, addParenthetical, addDialogue, dual_script, addTransition, dial_checker,  non_dial_checker
from .script_reading import breaksen, getRefined, getSlugAndNonSlug, getSpeakers, getScenes
from .translation_resources import ibm_watson, google, aws, azure, yandex  #lingvanex
from .transliteration_resources import azure_transliteration, indic_trans, om_transliterator, libindic, indic_transliteration_IAST, indic_transliteration_ITRANS, sheetal,unicode_transliteration_GURMUKHI,indic_transliteration_GURMUKHI,transliteration_LATIN_CYRILLIC,indic_transliteration_TELUGU,unicode_transliteration_GURMUKHI_LATIN,indic_transliteration_GURMUKHI_LATIN,transliteration_CYRILIC_LATIN,ConvertToLatin,readonly
from .detection import language_detector, script_det
# import logging
# from logger import get_module_logger
# log = get_module_logger(__name__)
# log.info('Logger working')


def makeTransliteration_translation(translation_and_transliteration, translated_file, dial_dest_script, dual_dial_script, original_file):
  #os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = rf"{basePath}/conversion/My First Project-2573112d5326.json"
  os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = rf"{basePath}/MNF/json_keys/authentication.json"
  # os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = rf"{basePath}/conversion/gifted-mountain-318504-4f001d5f08db.json"
  translate_client = Translate.Client()
  client = translate.TranslationServiceClient()
  project_id = 'authentic-bongo-272808'
  location = "global"
  parent = f"projects/{project_id}/locations/{location}"
  
  
  translation_and_transliteration = translation_and_transliteration 
  filename1 = translated_file
  dial_dest_script = dial_dest_script
  dual_dial_script = dual_dial_script
  filename2 = original_file
  

  # create an instance of a word document 
  doc = docx.Document() 
  docfile = translated_file
  print(docfile)

  doc2 = docx.Document()
  sections = doc2.sections
  for section in sections:
      section.top_margin = Inches(0.2)
      section.bottom_margin = Inches(0.2)
      section.left_margin = Inches(0.2)
      section.right_margin = Inches(0.2)
  section = doc2.sections[-1]
  new_height = section.page_width
  section.page_width = section.page_height
  section.page_height = new_height
  name = 'Final table '+docfile
  doc2.add_heading(name, 0)
  doc_para = doc2.add_paragraph()
  doc_para.add_run('Translation resources used : Google, IBM watson, AWS, Azure, Lingvanex, Yandex').bold = True
  table2 = doc2.add_table(rows=1,cols=4)
  table2.style = 'TableGrid'
  hdr_Cells = table2.rows[0].cells
  hdr_Cells[0].paragraphs[0].add_run("Input").bold=True
  hdr_Cells[1].paragraphs[0].add_run("Output1").bold=True
  hdr_Cells[2].paragraphs[0].add_run("Output2").bold=True
  hdr_Cells[3].paragraphs[0].add_run("Output3").bold=True

  #scenes for translated file
  refined,total_scenes = getRefined(filename1)
  #print(refined)
  sluglines,without_slug = getSlugAndNonSlug(refined)
  #print(sluglines)
  characters = getSpeakers(without_slug)
  #print(characters)
  scenes,actionline,parenthetical_lis,speakers,dialogues = getScenes(refined,total_scenes,characters)
  #print(scenes)
  
  #scenes1 for original file
  refined,total_scenes = getRefined(filename2)
  sluglines,without_slug = getSlugAndNonSlug(refined)
  characters = getSpeakers(without_slug)
  scenes1,actionline,parenthetical_lis,speakers,dialogues = getScenes(refined,total_scenes,characters)
      

  def punct_remover(string):
    punctuations = '''!()-[]{};:'"\,<>./?@#$%^&*_~…।'''
    for x in string.lower():
      if x in punctuations:
        string = string.replace(x, " ")
    return string

  def space_after_punct(text):
    #text = text.replace('...',' ... ')
    text = text.replace('. . .',' ... ')
    text = re.sub('([,!?()…-])', r'\1 ', text)
    text = re.sub('\s{2,}', ' ', text)
    return text

  def final_transliterated_sentence(original, transliterated):
    original = space_after_punct(original)
    punct_list = ['!', '"', '#', '$', '%', '&', "'", '(', ')', '*', '+', ',', ' ', '-', '.', '/', ':', ';',
          '<', '=', '>', '?', '@', '[', '\\', ']', '^', '_', '`', '{', '|', '}', '~', '…', '...', '।']
    sentence = []
    j = 0

    for i in range(len(original.split())):

      if original.split()[i] in punct_list:
        sentence.append(original.split()[i])
      elif original.split()[i][-1] in punct_list:
        temp = transliterated.split()[j] + original.split()[i][-1]
        sentence.append(temp)
        j = j+1
      elif original.split()[i][-1] not in punct_list:
        temp = transliterated.split()[j]
        sentence.append(temp)
        j = j+1
    
    transliterated_sentence = " ".join(sentence)
    transliterated_sentence.replace(' ... ','...')
    transliterated_sentence.replace('… ', '…')
    return transliterated_sentence

  def MNF_translate(text, dest_lang):
    result = translate_client.translate(text, target_language = dest_lang)
    translated_text = result['translatedText']
    return translated_text     

  def google_length_checker(t, temp_sentence, t0):
    if len(t.split()) >= len(temp_sentence.split()):
      return t
    elif len(t.split()) == len(temp_sentence.split())-1:
      final_t = t+ " " + t0.split()[-1]
      return final_t
    elif len(t.split()) == len(temp_sentence.split())-2:
      final_t = t+ " " + t0.split()[-2] + " " + t0.split()[-1]
      return final_t    
    else:
      return t

  def Halant_remover(T3):
    if T3[-1] == "्":
      return T3[:-1]
    else: return T3    

  def dial_comparison_transliteration_rom_dev_ph1(text, source_lang, source_script, dest_script): 
    source_lang = "hi"
    source_script = "Latin"
    dest_script = "Devanagari"
    sources_name = {'0':'Azure', '1':'indic_trans', '2':'google', '3':'indic_trans_IAST'}
    sentences=sentence_tokenize.sentence_split(text, lang='en')
    priority_list =['Azure', 'indic_trans', 'google', 'indic_trans_IAST', ]

    transliterated_text=[]  
    for sentence in sentences:  
        if sentence == "" or sentence == " . . ." or sentence == " . ." or sentence ==" . . ”":
          continue
        print(sentence)
        OUT=[]
        for word in sentence.split():
          if word==".":
            continue
          print(word)  
          t0 = azure_transliteration(word, source_lang, source_script, dest_script)
          #print(t0)
          t1 = indic_trans(word, source_script, dest_script)
          #print(t1)
          t2 = google(word, 'en', 'hi')
          #print(t2)
          t3 = indic_transliteration_IAST(word)
          #print(t3)
          outputs=[t0, t1, t2, t3]
          out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
          OUT.append(out)
        transliterated_text.append(" ".join(OUT))  
    return " ".join(transliterated_text)


  def dial_comparison_transliteration_rom_dev_ph1_sentence_wise(text, source_lang, source_script, dest_script):
    source_lang = "hi"
    sources_name = {'0':'Azure', '1':'indic_trans', '2':'google', '3':'indic_trans_IAST'}
    etc_punctuation =["", " . . .", " . .", " . . ”"]
    sentences=sentence_tokenize.sentence_split(text, lang='en')
    priority_list =['Azure', 'indic_trans', 'google', 'indic_trans_IAST']

    transliterated_text=[]  
    for sentence in sentences:
      if sentence in etc_punctuation:
        continue

      print("original_sentence", sentence)
      temp_sentence = punct_remover(sentence)
      print("sentence_without_punctuation", temp_sentence)
      
      t00 = azure_transliteration(temp_sentence, source_lang,  source_script, dest_script)
      print(t00)
      t11 = indic_trans(temp_sentence, source_script, dest_script)
      print(t11)
      t = google(temp_sentence, 'en', 'hi')
      #print("btw", t)
      t22 = google_length_checker(t, temp_sentence, t00)
      print("T22 transliteration",t22)
      t33 = indic_transliteration_IAST(temp_sentence)
      print(t33)
        
      Out= []
      outputs = []
      for i in range(len(temp_sentence.split())):
        word = temp_sentence.split()[i]
        # print("test of trasnliteration",i)
        T0 = t00.split()[i]
        # print("test of trasnliteration T0",T0)
        # print("test of trasnliteration T11",t11)
        T1 = t11.split()[i]
        # print("test of trasnliteration T1",T1)
        # print("test of trasnliteration T22",t22)
        T2 = t22.split()[i]
        # print("test of trasnliteration T2",T2)
        T3 = t33.split()[i]
        T3 = Halant_remover(T3)

        outputs=[T0, T1, T2, T3]
        out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
        Out.append(out)
        trans_sent_wo_punct = " ".join(Out)
      print("trans_sent_wo_punct", trans_sent_wo_punct)
        
      transliterated_sentence = final_transliterated_sentence(sentence, trans_sent_wo_punct)  
      print("trans_sent_w_punct", transliterated_sentence)
      transliterated_text.append(transliterated_sentence)
           
    return " ".join(transliterated_text)

  # def dial_comparison_transliteration_dev_rom_ph1(text, source_lang, source_script, dest_script): 
  #   sources_name = {'0':'indic_trans', '1':'Azure', '2':'libindic', '3':'sheetal', '4':'ritwik'} 
  #   sentences=sentence_tokenize.sentence_split(text, lang='hi')
  #   priority_list =['indic_trans', 'Azure', 'ritwik', 'sheetal', 'libindic']

  #   transliterated_text=[]  
  #   for sentence in sentences:  
  #     if sentence == "" or sentence == " . . ." or sentence == " . ." or sentence ==" . . ”":
  #       continue
  #     print("original sentence", sentence)
  #     temp_sentence = punct_remover(sentence)
  #     print("sentence after punctuation", temp_sentence)
      
  #     t0 = indic_trans(temp_sentence, source_script, dest_script)
  #     #print(t0)
  #     t1 = azure_transliteration(temp_sentence, source_lang,  source_script, dest_script)
  #     #print(t1)
  #     t2 = libindic(temp_sentence, dest_script).rstrip()
  #     #print(t2)
  #     t3 = sheetal(temp_sentence).replace('\n','')
  #     #print(t3)
  #     t4 = ritwik(temp_sentence).replace('\n','').rstrip()
  #     #print(t4)

      
  #     Out= []
  #     outputs = []
  #     for i in range(len(temp_sentence.split())):
  #       word = temp_sentence.split()[i]
        
  #       T0 = t0.split()[i]
  #       T1 = t1.split()[i]
  #       T2 = t2.split()[i]
  #       T3 = t3.split()[i]
  #       T4 = t4.split()[i]
        
  #       outputs=[T0, T1, T2, T3, T4]
  #       out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
  #       Out.append(out)
  #       trans_sent_wo_punct = " ".join(Out)
  #       print("trans_sent_wo_punct", trans_sent_wo_punct)
        
  #       transliterated_sentence = final_transliterated_sentence(sentence, trans_sent_wo_punct)
  #       print("trans_sent_with_punct", transliterated_sentence)
  #     transliterated_text.append(transliterated_sentence)
         
  #   return " ".join(transliterated_text)  
  def dial_comparison_transliteration_dev_rom_ph1(text, source_lang, source_script, dest_script): 
    #sources_name = {'0':'indic_trans', '1':'Azure', '2':'libindic', '3':'sheetal', '4':'ritwik'} 
    sources_name = {'0':'indic_trans', '1':'Azure', '2':'libindic', '3':'sheetal'} 
    sentences=sentence_tokenize.sentence_split(text, lang='hi')
    #priority_list =['indic_trans', 'Azure', 'ritwik, 'sheetal', 'libindic']
    priority_list =['indic_trans', 'Azure', 'sheetal', 'libindic']


    transliterated_text=[]  
    for sentence in sentences:  
        if sentence == "" or sentence == " . . ." or sentence == " . ." or sentence ==" . . ”":
          continue
        print(sentence)
        OUT=[]
        for word in sentence.split():
          if word==".":
            continue
          print(word)
          t0 = indic_trans(word, source_script, dest_script)
          #print(t0)
          t1 = azure_transliteration(word, source_lang,  source_script, dest_script)
          #print(t1)
          t2 = libindic(word, dest_script).rstrip()
          #print(t2)
          t3 = sheetal(word).replace('\n','')
          #print(t3)
          #t4 = ritwik(word).replace('\n','').rstrip()
          #print(t4)
          # outputs=[t0, t1, t2, t3, t4]
          outputs=[t0, t1, t2, t3]
          out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
          OUT.append(out)
        transliterated_text.append(" ".join(OUT))  
    return " ".join(transliterated_text)


  def dial_comparison_transliteration_arbic_to_rom_ph1(text, source_lang, source_script, dest_script): 
    print("hello")
    sources_name = {'0':'indic_trans', '1':'Azure', '2':'buck_2_unicode'}
    sentences=sentence_tokenize.sentence_split(text, lang='en')
    priority_list =['indic_trans', 'Azure', 'buck_2_unicode' ]

    transliterated_text=[]  
    for sentence in sentences:  
        if sentence == "" or sentence == " . . ." or sentence == " . ." or sentence ==" . . ”":
          continue
        print(sentence)
        OUT=[]
        for word in sentence.split():
          if word==".":
            continue
          print(word) 
          t0 = indic_trans(word, source_script, dest_script) 
          t1 = azure_transliteration(word, source_lang, source_script, dest_script)
          t2 = buck_2_unicode(word)
          outputs=[t0, t1, t2]
          out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
          OUT.append(out)
        transliterated_text.append(" ".join(OUT))  
    return " ".join(transliterated_text)

  def dial_comparison_transliteration_kann_to_rom_ph1(text, source_lang, source_script, dest_script): 
    print("hello")
    sources_name = {'0':'om_transliteration', '1':'indic_trans', '2':'libindic', '3':'Azure'}
    sentences=sentence_tokenize.sentence_split(text, lang='en')
    priority_list =['om_transliteration', 'indic_trans', 'libindic', 'Azure']

    transliterated_text=[]  
    for sentence in sentences:  
        if sentence == "" or sentence == " . . ." or sentence == " . ." or sentence ==" . . ”":
          continue
        print(sentence)
        OUT=[]
        for word in sentence.split():
          if word==".":
            continue
          print(word) 
          t0 = om_transliterator(word)
          t1 = indic_trans(word, source_script, dest_script) 
          t2 = libindic(word, dest_script)
          t3 = azure_transliteration(word, source_lang, source_script, dest_script)
          outputs=[t0, t1, t2, t3]
          out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
          OUT.append(out)
        transliterated_text.append(" ".join(OUT))  
    return " ".join(transliterated_text)

  def dial_comparison_transliteration_tamil_to_rom_ph1(text, source_lang, source_script, dest_script): 
    print("hello")
    sources_name = {'0':'Azure', '1':'libindic', '2':'indic_trans', }
    sentences=sentence_tokenize.sentence_split(text, lang='en')
    priority_list =['Azure', 'libindic', 'indic_trans']

    transliterated_text=[]  
    for sentence in sentences:  
        if sentence == "" or sentence == " . . ." or sentence == " . ." or sentence ==" . . ”":
          continue
        print(sentence)
        OUT=[]
        for word in sentence.split():
          if word==".":
            continue
          print(word) 
          t0 = azure_transliteration(word, source_lang, source_script, dest_script)
          t2 = libindic(word, dest_script)
          t1 = indic_trans(word, source_script, dest_script)
          outputs=[t0, t1, t2]
          out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
          OUT.append(out)
        transliterated_text.append(" ".join(OUT))  
    return " ".join(transliterated_text)

  def dial_comparison_transliteration_beng_tel_mal_to_rom_ph1(text, source_lang, source_script, dest_script): 
    print("hello gujarati to latin")
    sources_name = {'0':'Azure', '1':'indic_trans', '2':'libindic'}
    sentences=sentence_tokenize.sentence_split(text, lang='en')
    priority_list =['Azure', 'indic_trans', 'libindic']

    transliterated_text=[]  
    for sentence in sentences:  
        if sentence == "" or sentence == " . . ." or sentence == " . ." or sentence ==" . . ”":
          continue
        #print(sentence)
        OUT=[]
        for word in sentence.split():
          if word==".":
            continue
          print(word) 
          t0 = azure_transliteration(word, source_lang, source_script, dest_script)
          t1 = indic_trans(word, source_script, dest_script) 
          t2 = libindic(word, dest_script)
          outputs=[t0, t1, t2]
          out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
          OUT.append(out)
        transliterated_text.append(" ".join(OUT))  
    return " ".join(transliterated_text)

  def dial_comparison_transliteration_latin_gurmukhi(text,source_lang, source_script, dest_script):
    source_lang = "pa"
    sources_name = {'0':'Azure', '1':'indic_trans', '2':'indic_trans_IAST'}
    etc_punctuation =["", " . . .", " . .", " . . ”"]
    sentences=sentence_tokenize.sentence_split(text, lang='en')
    priority_list =['Azure', 'indic_trans', 'indic_trans_IAST']

    transliterated_text=[]  
    for sentence in sentences:
      if sentence in etc_punctuation:
        continue
      temp_sentence = punct_remover(sentence)
      
      t00 = azure_transliteration(temp_sentence, source_lang,  source_script, dest_script)
      t11 = indic_transliteration_GURMUKHI(temp_sentence)
      t22 = unicode_transliteration_GURMUKHI(temp_sentence)
 
      Out= []
      outputs = []
      for i in range(len(temp_sentence.split())):
        word = temp_sentence.split()[i]
        T0 = t00.split()[i]
        T1 = t11.split()[i]
        T2 = t22.split()[i]
        outputs=[T0, T1, T2]
        out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
        Out.append(out)
        trans_sent_wo_punct = " ".join(Out)
      transliterated_sentence = final_transliterated_sentence(sentence, trans_sent_wo_punct)  
      transliterated_text.append(transliterated_sentence)
          
    return " ".join(transliterated_text)

  def dial_comparison_transliteration_latin_cyrillic(text,source_lang, source_script, dest_script):
    source_lang = "bg"
    sources_name = {'0':'Azure', '1':'indic_trans'}
    etc_punctuation =["", " . . .", " . .", " . . ”"]
    sentences=sentence_tokenize.sentence_split(text, lang='en')
    priority_list =['Azure', 'indic_trans']

    transliterated_text=[]  
    for sentence in sentences:
      if sentence in etc_punctuation:
        continue
      temp_sentence = punct_remover(sentence)
      
      t00 = azure_transliteration(temp_sentence, source_lang,  source_script, dest_script)
      t11 = transliteration_LATIN_CYRILLIC(temp_sentence)
      #t22 = polygot(text)
      Out= []
      outputs = []
      for i in range(len(temp_sentence.split())):
        word = temp_sentence.split()[i]
        T0 = t00.split()[i]
        T1 = t11.split()[i]
        #T2 = t22.split()[i]
        outputs=[T0, T1]
        #outputs=[T0, T1, T2]
        out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
        Out.append(out)
        trans_sent_wo_punct = " ".join(Out)
        
      transliterated_sentence = final_transliterated_sentence(sentence, trans_sent_wo_punct)  
      transliterated_text.append(transliterated_sentence)
    return " ".join(transliterated_text)

  def dial_comparison_transliteration_latin_telugu_sentence_wise(text, source_lang, source_script, dest_script): 
    source_lang = "te"
    sources_name = {'0':'indic_trans', '1':'Azure'} 
    priority_list =['indic_trans', 'Azure',]
    etc_punctuation =["", " . . .", " . .", " . . ”"]
    sentences=sentence_tokenize.sentence_split(text, lang='hi')
  
    transliterated_text=[]  
    for sentence in sentences:
        #if sentence == "" or sentence == " . . ." or sentence == " . ." or sentence ==" . . ”":
        if sentence in etc_punctuation:  
          continue

        print("original_sentence", sentence)
        temp_sentence = punct_remover(sentence)
        print("sentence_without_punctuation", temp_sentence)
        
        t0 = indic_transliteration_TELUGU(temp_sentence)
        print(t0)
        t1 = azure_transliteration(temp_sentence, source_lang,  source_script, dest_script)
        print(t1)
        Out= []
        outputs = []
        for i in range(len(temp_sentence.split())):
          word = temp_sentence.split()[i]
          
          T0 = t0.split()[i]
          T1 = t1.split()[i]
        
          outputs=[T0, T1]
          out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
          Out.append(out)
          trans_sent_wo_punct = " ".join(Out)
        print("trans_sent_wo_punct", trans_sent_wo_punct)
          
        transliterated_sentence = final_transliterated_sentence(sentence, trans_sent_wo_punct)  
        print("trans_sent_w_punct", transliterated_sentence)
        transliterated_text.append(transliterated_sentence)
    return " ".join(transliterated_text)


  def dial_comparison_transliteration_gurmukhi_latin_sentence_wise(text, source_lang, source_script, dest_script): 
    source_lang = "pa"
    sources_name = {'0':'indic_trans', '1':'Azure', '2':'unicode'} 
    priority_list =['indic_trans', 'Azure', 'unicode']
    etc_punctuation =["", " . . .", " . .", " . . ”"]
    sentences=sentence_tokenize.sentence_split(text, lang='hi')
  
    transliterated_text=[]  
    for sentence in sentences:
        #if sentence == "" or sentence == " . . ." or sentence == " . ." or sentence ==" . . ”":
        if sentence in etc_punctuation:  
          continue

        print("original_sentence", sentence)
        temp_sentence = punct_remover(sentence)
        print("sentence_without_punctuation", temp_sentence)
        
        t0 = indic_transliteration_GURMUKHI_LATIN(temp_sentence)
        print(t0)
        t1 = azure_transliteration(temp_sentence, source_lang,  source_script, dest_script)
        print(t1)
        t2 = unicode_transliteration_GURMUKHI_LATIN(temp_sentence).rstrip()
        print(t2)
        Out= []
        outputs = []
        for i in range(len(temp_sentence.split())):
          word = temp_sentence.split()[i]
          
          T0 = t0.split()[i]
          T1 = t1.split()[i]
          T2 = t2.split()[i]
        
          outputs=[T0, T1, T2]
          out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
          Out.append(out)
          trans_sent_wo_punct = " ".join(Out)
        print("trans_sent_wo_punct", trans_sent_wo_punct)
          
        transliterated_sentence = final_transliterated_sentence(sentence, trans_sent_wo_punct)  
        print("trans_sent_w_punct", transliterated_sentence)
        transliterated_text.append(transliterated_sentence)
            
    return " ".join(transliterated_text)

  def dial_comparison_transliteration_cyrilic_latin_sentence_wise(text, source_lang, source_script, dest_script): 
    print("cyrillic to latin")
    source_lang = "bg"
    sources_name = {'0':'indic_trans', '1':'Azure', '2':'unicode'} 
    priority_list =['indic_trans', 'Azure', 'unicode']
    etc_punctuation =["", " . . .", " . .", " . . ”"]
    sentences=sentence_tokenize.sentence_split(text, lang='hi')
  
    transliterated_text=[]  
    for sentence in sentences:
        #if sentence == "" or sentence == " . . ." or sentence == " . ." or sentence ==" . . ”":
        if sentence in etc_punctuation:  
          continue

        print("original_sentence", sentence)
        temp_sentence = punct_remover(sentence)
        print("sentence_without_punctuation", temp_sentence)
        
        t0 = azure_transliteration(temp_sentence, source_lang,  source_script, dest_script)
        print("t0",t0)
        t1 = transliteration_CYRILIC_LATIN(temp_sentence)
        print("t1",t1)
        t2 = ConvertToLatin(temp_sentence)
        print("t2",t2)

        Out= []
        outputs = []
        for i in range(len(temp_sentence.split())):
          word = temp_sentence.split()[i]
          T0 = t0.split()[i]
          T1 = t1.split()[i]
          T2 = t2.split()[i]
          outputs=[T0, T1, T2]
          out = compare_outputs_transliteration(word, outputs, sources_name, priority_list)
          Out.append(out)
          trans_sent_wo_punct = " ".join(Out)
        print("trans_sent_wo_punct", trans_sent_wo_punct)
          
        transliterated_sentence = final_transliterated_sentence(sentence, trans_sent_wo_punct)  
        print("trans_sent_w_punct", transliterated_sentence)
        transliterated_text.append(transliterated_sentence)
            
    return " ".join(transliterated_text)




  def compare_outputs_transliteration(word, outputs, sources_name, priority_list):          
        #print(outputs)
        O1ANDS1, O2ANDS2 = selection_source_transliteration(sources_name, outputs, priority_list)
        print(O1ANDS1)
        add_dial_comparison_doc2_transliteration(doc2, table2, word, O1ANDS1, O2ANDS2, sources_name)    
        return O1ANDS1[0]

  def add_dial_comparison_doc2_transliteration(doc2, table2, word, O1ANDS1, O2ANDS2, sources_name):
      row_Cells = table2.add_row().cells
      row_Cells[0].text= word
      row_Cells[1].text= O1ANDS1[0]
      row_Cells[1].paragraphs[0].add_run('(Source : '+str(O1ANDS1[1])+')')
      row_Cells[2].text= O2ANDS2[0]
      row_Cells[2].paragraphs[0].add_run('(Source : '+str(O2ANDS2[1])+')')
  
  
  #store original dialogues for dual dialogue format    
  original_dialogues = []
  for scene in tqdm(scenes1[:]): 
    for i,line in enumerate(scene):
      if i == 0:
        continue
      if type(line)==type(""):
        continue
      
      else:
        print("In dialogue")
        [speaker] = line.keys()
        if speaker == 'Transition': 
          continue

        #if line[speaker][0] != 'NONE':   #cooment
          #continue
           # In parenthitical part
        #   print("parenthitical", line[speaker][0])
   
        if line[speaker][2] == "":
          continue
        print("dialogue", line[speaker][2])
        original_dialogues.append(line[speaker][2])  
          
  print("length of dialogues", len(original_dialogues)) 
  print(original_dialogues)
  #for detection 
  for scene in tqdm(scenes):
      x = "False"
      y = "False"
      for i,line in enumerate(scene):
          if i == 0:
              continue
          if type(line)==type(""):
            x = "True" 
            non_dial_src_lang = language_detector(line)

          else:
              y = "True"
              [speaker] = line.keys()
              if speaker == 'Transition':
                  continue
              if line[speaker][0] != 'NONE':
                  continue
              
              dial_src_lang = language_detector(line[speaker][2])
              dial_src_script = script_det(line[speaker][2])   
              
      if x == "True" and y == "True":
        break 
          
  print("non_dial_src_lang", non_dial_src_lang)
  print("dial_src_lang", dial_src_lang)
  print("dial_src_script", dial_src_script)  
  
  #main for loop            
  j = 0          
  for scene in tqdm(scenes[:]): 
    for i,line in enumerate(scene):
      if i == 0:
        addSlugLine(doc,line)
        continue
      if type(line)==type(""):
        addActionLine(doc, line, non_dial_src_lang)

                   
      else:
        print("In dialogue")
        [speaker] = line.keys()
        if speaker == 'Transition':
          addTransition(doc,line[speaker])
          continue
        addSpeaker(doc,speaker)
        if line[speaker][0] != 'NONE': # In parenthitical part 
          non_dial_translate = "no"    
          if non_dial_translate == "yes":
            out = MNF_translate(line[speaker][0], non_dial_dest_lang)
            addParenthetical(doc,out)  
          else:
            addParenthetical(doc,line[speaker][0])
   
        print("dialogue to be transliterated ", line[speaker][2])
        if line[speaker][2] == "":
          continue
          
        if dial_dest_script == "Latin" and dial_src_script == "Devanagari":
          trans_text = dial_comparison_transliteration_dev_rom_ph1(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script)
        elif dial_dest_script == "Devanagari" and dial_src_script == "Latin":
          trans_text = dial_comparison_transliteration_rom_dev_ph1(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script)
          #trans_text=dial_comparison_transliteration_rom_dev_ph1_sentence_wise(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script)
        elif dial_dest_script == "Latin" and dial_src_script == "Arabic":
          trans_text = dial_comparison_transliteration_arbic_to_rom_ph1(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script )  
        elif dial_dest_script == "Latin" and dial_src_script == "Kannada":
          trans_text = dial_comparison_transliteration_kann_to_rom_ph1(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script )  
        elif dial_dest_script == "Latin" and dial_src_script == "Tamil":
          trans_text = dial_comparison_transliteration_tamil_to_rom_ph1(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script ) 

        elif dial_dest_script == "Latin" and dial_src_script == "Bengali":
          trans_text = dial_comparison_transliteration_beng_tel_mal_to_rom_ph1(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script ) 
        elif dial_dest_script == "Latin" and dial_src_script == "Telugu":
          trans_text = dial_comparison_transliteration_beng_tel_mal_to_rom_ph1(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script ) 
        elif dial_dest_script == "Latin" and dial_src_script == "Malayalam":
          trans_text = dial_comparison_transliteration_beng_tel_mal_to_rom_ph1(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script ) 
        elif dial_dest_script == "Gurmukhi" and dial_src_script == "Latin":
          trans_text = dial_comparison_transliteration_latin_gurmukhi(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script ) 
        elif dial_dest_script == "" and dial_src_script == "Cyrillic":
          trans_text = dial_comparison_transliteration_latin_cyrillic(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script ) 
        elif dial_dest_script == "Telugu" and dial_src_script == "Latin":
          trans_text = dial_comparison_transliteration_latin_telugu_sentence_wise(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script ) 
        elif dial_dest_script == "Latin" and dial_src_script == "Gurmukhi":
          trans_text = dial_comparison_transliteration_gurmukhi_latin_sentence_wise(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script ) 
        elif dial_dest_script == "Latin" and dial_src_script == "Cyrillic":
          trans_text = dial_comparison_transliteration_cyrilic_latin_sentence_wise(line[speaker][2], dial_src_lang, dial_src_script, dial_dest_script ) 
        elif dest_script == "Latin" and src_script == "Gujarati":
          print("Gujarti to latin hoga")
          trans_text = dial_comparison_transliteration_beng_tel_mal_to_rom_ph1(line[speaker][2], src_lang, src_script,dest_script )    
        elif dest_script == "Latin" and src_script == "Oriya":
          trans_text = dial_comparison_transliteration_beng_tel_mal_to_rom_ph1(line[speaker][2], src_lang, src_script,dest_script )                             
                         
        if dual_dial_script == "Yes":
          if translation_and_transliteration == "Yes":
            dual_script(doc, original_dialogues[j], trans_text, dial_src_lang)
            j=j+1
          else:
            dual_script(doc, line[speaker][2], trans_text, dial_src_lang)
            
        else:
          addDialogue(doc, trans_text, dial_src_lang) 
          
  doc.save(docfile)  
  # file_tr = rf"{basePath}/media/scripts/Final_Table" +ss str(forFinal.split('.')[0])+"_trans_to_"+str(dial_dest_lang)+'_'+"final.docx"
  # doc2.save(file_tr)
  print('done file is saved')
  return docfile