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Can anyone clarify how to configure follow up intents or prompts like in api.ai ? I am trying to create an application similar to api.ai using rasa nad spacy as backend.

Arpan Mukherjee
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Rasa NLU is just for the intent and entity classification. From their website:

Rasa NLU is an open source tool for intent classification and entity extraction. You can think of it as a set of high level APIs for building your own language parser using existing NLP and ML libraries.

To implement conversation or dialogue you need a different tool or to program your own solution.

Popular ones in the Rasa community are:

Caleb Keller
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As Keller said, it can be done with Rasa-core. DialogFlow supports both (input) parameters and “contexts”. Rasa also supports both (input) parameters and contexts with “Rasa slots”.

There are three steps:

  • 1) In slots section of domain.yml, you can add a context, for example:

slots: zipcode: type: text request_user_affirm: type: text

  • 2) request_user_affirm is the context slot, which will be filled by a customAction

  • 3) use the context in your stories:

* inform{"zipcode": "78733"} - bot_request_affirm * deny{"request_user_affirm": "yes"} - utter_request_info

bot_request_affirm is the custom action which will fill the request_user_affirm slot. if next user intent is deny and request_user_affirm is set, than the bot will response with utter_request_info action.

have fun with rasa-core.

Basile Perrenoud
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Songshan Li
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RASA Core was specifically built for this, rather than creating a dialog flow with simple if-else statements, RASA Core uses machine learning to decide the flow.

More Information here

Kunal Mukherjee
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