Choose the folder with the chatbot in English (KI-Campus_en) or in German (KI-Campus_de)
rasa train
NOTE Currently only supported for German chabot (
rasa/KI-Campus_de/
)
Create (or modify) the configuration file kic_recommender.yml
in directory
rasa/KI-Campus_de/
and add/modify configuration entry for Course Recommender Endpoint with the base URL for the endpoint and the access token:
# This file contains the custom service endpoints your bot can use.
# recommender service (DFKI) configuration
recommender_api:
url: "<base URL for recommender service endpoint>"
token: "<recommender access token>"
rasa run --enable-api
rasa run actions
NOTE the actions must not be started from within the actions/
sub-directory,
but the rasa
project's root directory (e.g. rasa/KI-Campus_de/
),
otherwise not all actions may be automatically started.
Change configuration to 'for local development' endpoint in endpoints.yml
in sub-directories
rasa/KI-Campus_de/
rasa/KI-Campus_en/
then (within the respective directory) start the chatbot shell with
rasa shell
for testing logged-in user, get your access-token
from the ki-campus website and start shell with
rasa shell --conversation-id <access-token>
In the outer project structure run:
docker-compose -f docker-compose_de.yml -p kicampus_de up --build
docker-compose -f docker-compose_en.yml -p kicampus_en up --build