japanese_tokenizer.py

import re
from typing import Any, Dict, List, Text

from rasa.nlu.components import Component
from rasa.nlu.config import RasaNLUModelConfig
from rasa.nlu.tokenizers import Token, Tokenizer
from rasa.nlu.training_data import Message, TrainingData

class JapaneseTokenizer(Tokenizer, Component):

    provides = ["tokens"]
    
    def __init__(self, component_config: Dict[Text, Any] = None) -> None:
        super(JapaneseTokenizer, self).__init__(component_config)
		
        from sudachipy import dictionary
        from sudachipy import tokenizer
		
        self.tokenizer_obj = dictionary.Dictionary().create()
        self.mode = tokenizer.Tokenizer.SplitMode.A

    @classmethod
    def required_packages(cls) -> List[Text]:
        return ["sudachipy"]
		
    def train(
        self, training_data: TrainingData, config: RasaNLUModelConfig, **kwargs: Any
    ) -> None:

        for example in training_data.training_examples:
            example.set("tokens", self.tokenize(self, example.text))

    def process(self, message: Message, **kwargs: Any) -> None:

        message.set("tokens", self.tokenize(self, message.text))

    @staticmethod
    def tokenize(self, text: Text) -> List[Token]:		
        words = [m.surface() for m in self.tokenizer_obj.tokenize(text, self.mode)]
        running_offset = 0
        tokens = []
        for word in words:
            word_offset = text.index(word, running_offset)
            word_len = len(word)
            running_offset = word_offset + word_len
            tokens.append(Token(word, word_offset))
        return tokens