Hi everyone, Lately have been working on Fallback Policies, and I created a custom action for the fallback action (I didn’t use the default one). I want when the user types any message that is not related to an intent, or an intent with low score, the bot should run the my_fallback_action. In other terms, I want when the intent is None, the bot should be able to run the custom action in tha Fallback Policy. In the interactive learning, things run normally, however when I use the chatbot in the normal way, it usually run the action_default_fallback (when the intent is None) rather than my_fallback_action. Does anyone have an idea about this problem?
could you please show your config file?
for the config.yml:
Configuration for Rasa NLU.
language: en pipeline:
- name: WhitespaceTokenizer
- name: CRFEntityExtractor
- name: EntitySynonymMapper
- name: CountVectorsFeaturizer token_pattern: (?u)\b\w+\b
- name: EmbeddingIntentClassifier
- name: DucklingHTTPExtractor
Configuration for Rasa Core.
- name: MemoizationPolicy
- name: KerasPolicy epochs: 200 max_history: 10
- name: MappingPolicy
- name: “FallbackPolicy” nlu_threshold: 0.4 core_threshold: 0.3 fallback_action_name: “my_action_fallback”
for my_fallback_action here it is:
class ActionDefaultFallback(Action): def name(self): return “my_fallback_action”
def run(self, dispatcher, tracker, domain): i = tracker.get_slot('i') dispatcher.utter_message("okay") if i == 1: dispatcher.utter_message("Handoff, Claudio") return [ConversationPaused()] a = str(i) dispatcher.utter_message(a) if i == None: i = 0 i += 1 return [UserUtteranceReverted(),SlotSet("i", i)]
could you please paste debug logs here?
Hi again and sorry for the late reply. It turned out to be that in the core train I forgot to include the config file as I am using docker commands. So I think my issue is auto-solved. Thank you for your replies.
I need to know something. Do you need to give core config while using docker rasa core training.