Reputation: 45
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.
Upvotes: 0
Views: 2261
Reputation: 2161
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:
Upvotes: 5
Reputation: 46
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:
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.
Upvotes: 1
Reputation: 5853
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.
Upvotes: 0