I’m having one of those moments and finally giving in and asking for help (I may need professional help soon)
I have a new Rasa 2.6.3 project (
rasa init ) I’ve added a single starter conversation, and I have a yes/no question -
Do you need help with that?
and when I choose Yes (/affirm) It displays the out-of-the-box responses to “I’m good” - you know the one
Great, carry on
WHAT?! It’s 100% not following the story below so I’m curious what part of my brain has died to revert my skills back to a first-time-bot-builder.
Here’s my one and only custom story (remember I have the “init bot” code)
- story: Adobe Photoshop Upgrade Issue - YYx - Yes Help with Deflection steps: - intent: adobe_photoshop_upgrade_issue - action: utter_adobe_photoshop_reset_preferences - action: utter_general_support_ask_do_you_need_help_with_that - intent: affirm - action: utter_adobe_photoshop_reset_preferences_url - action: utter_adobe_photoshop_ask_video_helped - intent: affirm - action: utter_general_support_tell_glad_it_helped
Here’s the shell interaction
2021-06-08 17:00:21 INFO root - Rasa server is up and running. Bot loaded. Type a message and press enter (use '/stop' to exit): Your input -> dragging an image onto a canvas no longer center snaps it This could be caused by corrupted preferences. Could you please try resetting the preferences of Photoshop. ? Do you need help with that? 1: Yes I do (/affirm) Great, carry on! Your input ->
Here’s the generated
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. # - name: WhitespaceTokenizer # - name: RegexFeaturizer # - name: LexicalSyntacticFeaturizer # - name: CountVectorsFeaturizer # - name: CountVectorsFeaturizer # analyzer: char_wb # min_ngram: 1 # max_ngram: 4 # - name: DIETClassifier # epochs: 100 # constrain_similarities: true # - name: EntitySynonymMapper # - name: ResponseSelector # epochs: 100 # constrain_similarities: true # - name: FallbackClassifier # threshold: 0.3 # ambiguity_threshold: 0.1 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: 100 # constrain_similarities: true # - name: RulePolicy
Any ideas what the gap in my brain can’t figure out?
rasa interactive and get the exact same story as I manually put together.