I am new to ML & AI / Rasa and trying to develop a company-policy specific faq chatbot.
My requirements are to develop a bot:-
Learn and chat with company-specific policies faq.
Learns and chats with small chitchat conversation.
I am not sure which policies and pipeline so i have used basic settings from weather bot or other tutorials.
# Configuration for Rasa NLU. # https://rasa.com/docs/rasa/nlu/components/ language: en pipeline: supervised_embeddings # Configuration for Rasa Core. # https://rasa.com/docs/rasa/core/policies/ policies: - name: MemoizationPolicy max_history: 5 - name: KerasPolicy epochs: 400 batch_size: 100 validation_split: 0.2 max_history: 5 - name: MappingPolicy
supervised_embeddings internally uses below component.
language: "en" pipeline: - name: "WhitespaceTokenizer" - name: "RegexFeaturizer" - name: "CRFEntityExtractor" - name: "EntitySynonymMapper" - name: "CountVectorsFeaturizer"
How can i choose which component should be used and in which order’s.
when i ask questions for chitchat using the keyword from faq intent NLU choose faq intent for it.
After reading lots of articles i am confused which policy to and pipeline to use.