Cosine similarity, doc2vec in pipeline, QnA csv

Rasa Open Source
1

Prerequisites: I have many-many FAQ questions in my domain. So instead of creating and labeling 1000 intents i thinking of some solution.

  1. Create intent FAQ followed by action_faq which inference faq_model trained on QnA csv file.
  2. Put inference in action_default_fallback if high confidence then utter answer and revert fallback

I’ve seen rasa-demo. Not my case.

Is there solution to put my FAQ model in pipeline?

2

You don’t even have to put it in the pipeline, no? You can just do it like this:

  1. Change your fallback action name to whatever you like in config.yml. E.g.: fallback_action_name: “action_default_faq”
  2. Create custom action in actions.py named “action_default_faq”.
  3. In the class’s run method you manually check cosine similarity of the input against each of your faq candidates. If a similar case has been found, utter it. Else, prompt the user to rephrase and return [UserUtteranceReverted()]
3

Yes, i mentioned this approach in 2).

I doubt to implement it this way because i think FAQ model is NLU component and in this approach it’s located in actions field.

Also, i’m thinking about new feature Knowledge Base. How can i implement using this approach?

4

I’ll gonna try Retrieval Actions. It looks like what i’m looking for.