I recently started having an issue where the default fallback intent will be triggered and the bot just repeats the default utterance, even when I use statements that are clearly in the NLU. The fallback seems to be more easily triggered, too.
I’ve pasted my Config.yml below. I’ve read the fallback policy documents and options for different AugmentedMemoizationPolicy, but i’m still pretty confused.
My bot should be designed for long conversations and go between different story types. The most common intent for my bot is
I’m open to using a two-stage fallback policy, but confess that I don’t understand how this could help my particular situation very well.
Open to advice on how to improve it. thank you!
# Configuration for Rasa NLU. # https://rasa.com/docs/rasa/nlu/components/ language: en pipeline: # # No configuration for the NLU pipeline was provided. The following default pipeline was used to train your model. # # If you'd like to customize it, uncomment and adjust the pipeline. # # See https://rasa.com/docs/rasa/tuning-your-model for more information.n - name: WhitespaceTokenizer - name: RegexFeaturizer - name: LexicalSyntacticFeaturizer - name: CountVectorsFeaturizer - name: CountVectorsFeaturizer analyzer: char_wb min_ngram: 1 max_ngram: 4 - name: DIETClassifier epochs: 10 constrain_similarities: true - name: EntitySynonymMapper - name: ResponseSelector epochs: 10 constrain_similarities: true - name: FallbackClassifier threshold: 0.05 ambiguity_threshold: 0.05 policies: # # No configuration for policies was provided. The following default policies were used to train your model. # # If you'd like to customize them, uncomment and adjust the policies. # # See https://rasa.com/docs/rasa/policies for more information. - name: MemoizationPolicy - name: TEDPolicy max_history: 5 epochs: 10 constrain_similarities: true - name: RulePolicy - name: RulePolicy # Confidence threshold for the `core_fallback_action_name` to apply. # The action will apply if no other action was predicted with # a confidence >= core_fallback_threshold core_fallback_threshold: 0.05 core_fallback_action_name: "action_default_fallback" enable_fallback_prediction: True