import os
from time import perf_counter
from argparse import ArgumentParser
from fun_text_processing.text_normalization.en.graph_utils import generator_main

def parse_args():
    parser = ArgumentParser()
    
    parser.add_argument(
        "--language", help="language", choices=['de', 'en', 'es', 'fr', 'id', 'ja', 'ko', 'pt', 'ru', 'vi', 'zh'], default="en", type=str
    )
    parser.add_argument(
        "--export_dir",
        help="path to export directory. Default to current directory.",
        default="./",
        type=str,
    )
    return parser.parse_args()

def get_grammars(lang: str='en'):
  if lang=='de':
    from fun_text_processing.inverse_text_normalization.de.taggers.tokenize_and_classify import ClassifyFst
    from fun_text_processing.inverse_text_normalization.de.verbalizers.verbalize_final import VerbalizeFinalFst
  elif lang=='en':
    from fun_text_processing.inverse_text_normalization.en.taggers.tokenize_and_classify import ClassifyFst
    from fun_text_processing.inverse_text_normalization.en.verbalizers.verbalize_final import VerbalizeFinalFst
  elif lang=='es':
    from fun_text_processing.inverse_text_normalization.es.taggers.tokenize_and_classify import ClassifyFst
    from fun_text_processing.inverse_text_normalization.es.verbalizers.verbalize_final import VerbalizeFinalFst
  elif lang=='fr':
    from fun_text_processing.inverse_text_normalization.fr.taggers.tokenize_and_classify import ClassifyFst
    from fun_text_processing.inverse_text_normalization.fr.verbalizers.verbalize_final import VerbalizeFinalFst
  elif lang=='id':
    from fun_text_processing.inverse_text_normalization.id.taggers.tokenize_and_classify import ClassifyFst
    from fun_text_processing.inverse_text_normalization.id.verbalizers.verbalize_final import VerbalizeFinalFst
  elif lang=='ja':
    from fun_text_processing.inverse_text_normalization.ja.taggers.tokenize_and_classify import ClassifyFst
    from fun_text_processing.inverse_text_normalization.ja.verbalizers.verbalize_final import VerbalizeFinalFst
  elif lang=='ko':
    from fun_text_processing.inverse_text_normalization.ko.taggers.tokenize_and_classify import ClassifyFst
    from fun_text_processing.inverse_text_normalization.ko.verbalizers.verbalize_final import VerbalizeFinalFst
  elif lang=='pt':
    from fun_text_processing.inverse_text_normalization.pt.taggers.tokenize_and_classify import ClassifyFst
    from fun_text_processing.inverse_text_normalization.pt.verbalizers.verbalize_final import VerbalizeFinalFst
  elif lang=='ru':
    from fun_text_processing.inverse_text_normalization.ru.taggers.tokenize_and_classify import ClassifyFst
    from fun_text_processing.inverse_text_normalization.ru.verbalizers.verbalize_final import VerbalizeFinalFst
  elif lang=='vi':
    from fun_text_processing.inverse_text_normalization.vi.taggers.tokenize_and_classify import ClassifyFst
    from fun_text_processing.inverse_text_normalization.vi.verbalizers.verbalize_final import VerbalizeFinalFst
  elif lang=='zh':
    from fun_text_processing.inverse_text_normalization.zh.taggers.tokenize_and_classify import ClassifyFst
    from fun_text_processing.inverse_text_normalization.zh.verbalizers.verbalize_final import VerbalizeFinalFst
  else:
    from fun_text_processing.inverse_text_normalization.en.taggers.tokenize_and_classify import ClassifyFst
    from fun_text_processing.inverse_text_normalization.en.verbalizers.verbalize_final import VerbalizeFinalFst


  return ClassifyFst().fst, VerbalizeFinalFst().fst

if __name__ == "__main__":
    args = parse_args()

    export_dir = args.export_dir
    os.makedirs(export_dir, exist_ok=True)
    tagger_far_file = os.path.join(export_dir, args.language + "_itn_tagger.far")
    verbalizer_far_file = os.path.join(export_dir, args.language + "_itn_verbalizer.far")

    start_time = perf_counter()
    tagger_fst, verbalizer_fst = get_grammars(args.language)
    generator_main(tagger_far_file, {"tokenize_and_classify": tagger_fst})
    generator_main(verbalizer_far_file, {"verbalize": verbalizer_fst})
    print(f'Time to generate graph: {round(perf_counter() - start_time, 2)} sec')