machine-learning/hm-rasa/endpoints.yml
# This file contains the different endpoints your bot can use.
# Server where the models are pulled from.
# https://rasa.com/docs/rasa/model-storage#fetching-models-from-a-server
---
# models:
# url: http://my-server.com/models/default_core@latest
# wait_time_between_pulls: 10 # [optional](default: 100)
# Server which runs your custom actions.
# https://rasa.com/docs/rasa/custom-actions
action_endpoint:
url: "http://localhost:5055/webhook"
# Tracker store which is used to store the conversations.
# By default the conversations are stored in memory.
# https://rasa.com/docs/rasa/tracker-stores
# tracker_store:
# type: redis
# url: <host of the redis instance, e.g. localhost>
# port: <port of your redis instance, usually 6379>
# db: <number of your database within redis, e.g. 0>
# password: <password used for authentication>
# use_ssl: <whether or not the communication is encrypted, default false>
# tracker_store:
# type: mongod
# url: <url to your mongo instance, e.g. mongodb://localhost:27017>
# db: <name of the db within your mongo instance, e.g. rasa>
# username: <username used for authentication>
# password: <password used for authentication>
# Event broker which all conversation events should be streamed to.
# https://rasa.com/docs/rasa/event-brokers
# event_broker:
# url: localhost
# username: username
# password: password
# queue: queue