【勉強メモ】Rasa (1)

Rasa

環境構築

pip install rasa 
pip install ginza ja-ginza

mkdir Rasa
cd Rasa
rasa init --no-prompt

日本語設定

config.yml

recipe: default.v1

assistant_id: placeholder_default

language: ja

pipeline:
  - name: SpacyNLP
    model: 'ja_ginza'
  - name: SpacyTokenizer
  - name: SpacyFeaturizer
  - name: SpacyEntityExtractor
  - name: RegexFeaturizer
  - name: LexicalSyntacticFeaturizer
  - name: CountVectorsFeaturizer
  - name: CountVectorsFeaturizer
    analyzer: "char_wb"
    min_ngram: 1
    max_ngram: 4
  - name: DIETClassifier
    epochs: 100
  - name: EntitySynonymMapper
  - name: ResponseSelector
    epochs: 100
  - name: FallbackClassifier
    threshold: 0.7

policies:
  - name: MemoizationPolicy
  - name: RulePolicy
  - name: TEDPolicy
    max_history: 5
    epochs: 100

設定追加

domain.yml

「intents」に追加

nlu.yml

「intent」を追加、学習させる例文を「examples」に入れる (日本語でも英語でも可)

stories.yml

「rule」を追加、返答する内容等を「steps」に入れる

運用

訓練

rasa train

実行

rasa shell

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参考文献

https://qiita.com/Zect/items/e341e43fa9cf98529942
https://tech-blog.optim.co.jp/entry/2021/11/17/100000