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 config.yml
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?
UPDATE
I ran rasa interactive
and get the exact same story as I manually put together.