Event Brokers

An event broker allows you to connect your running assistant to other services that process the data coming in from conversations. For example, you could connect your live assistant to Rasa X to review and annotate conversations or forward messages to an external analytics service. The event broker publishes messages to a message streaming service, also known as a message broker, to forward Rasa Events from the Rasa server to other services.

Format

All events are streamed to the broker as serialized dictionaries every time the tracker updates its state. An example event emitted from the default tracker looks like this:

{
    "sender_id": "default",
    "timestamp": 1528402837.617099,
    "event": "bot",
    "text": "what your bot said",
    "data": "some data about e.g. attachments"
    "metadata": {
          "a key": "a value"
     }
}

The event field takes the event’s type_name (for more on event types, check out the Events docs).

Pika Event Broker

The example implementation we’re going to show you here uses Pika, the Python client library for RabbitMQ.

Adding a Pika Event Broker Using the Endpoint Configuration

You can instruct Rasa to stream all events to your Pika event broker by adding an event_broker section to your endpoints.yml:

event_broker:
  type: pika
  url: localhost
  username: username
  password: password
  queues:
    - queue-1
#   you may supply more than one queue to publish to
#   - queue-2
#   - queue-3

Rasa will automatically start streaming events when you restart the Rasa server.

Adding a Pika Event Broker in Python

Here is how you add it using Python code:

from rasa.core.brokers.pika import PikaEventBroker
from rasa.core.tracker_store import InMemoryTrackerStore

pika_broker = PikaEventBroker('localhost',
                              'username',
                              'password',
                              queues=['rasa_events'])

tracker_store = InMemoryTrackerStore(domain=domain, event_broker=pika_broker)

Implementing a Pika Event Consumer

You need to have a RabbitMQ server running, as well as another application that consumes the events. This consumer needs to implement Pika’s start_consuming() method with a callback action. Here’s a simple example:

import json
import pika

def _callback(self, ch, method, properties, body):
        print('Received event {}'.format(json.loads(body)))

if __name__ == '__main__':
    credentials = pika.PlainCredentials('username', 'password')
    connection = pika.BlockingConnection(
        pika.ConnectionParameters('rabbit', credentials=credentials))
    channel = connection.channel()
    channel.basic_consume(_callback,
                          queue='rasa_events',
                          no_ack=True)
    channel.start_consuming()

Kafka Event Broker

It is possible to use Kafka as the main broker for your events. In this example, we will use the python-kafka library.

Adding a Kafka Event Broker Using the Endpoint Configuration

You can instruct Rasa to stream all events to your Kafka event broker by adding an event_broker section to your endpoints.yml:

event_broker:
  url: localhost
  sasl_username: username
  sasl_password: password
  topic: topic
  security_protocol: SASL_PLAINTEXT
  type: kafka

Authentication and Authorization

Rasa’s Kafka producer accepts two types of security protocols - SASL_PLAINTEXT and SSL.

For development environment, you can use simple authentication with SASL_PLAINTEXT. By using this protocol, the credentials exchanged will be sent in plaintext.

kafka_broker = KafkaEventBroker(host='kafka_broker:9092',
                                sasl_plain_username='kafka_username',
                                sasl_plain_password='kafka_password',
                                security_protocol='SASL_PLAINTEXT',
                                topic='rasa_events')

If the clients in the Kafka cluster are located in different machines, it’s recommended to use SSL protocol to ensure the encryption of data and client authentication. After generating valid certificates, the path to the certificate and key must be provided:

kafka_broker = KafkaEventBroker(host='kafka_broker:9092',
                                ssl_cafile='CARoot.pem',
                                ssl_certfile='certificate.pem',
                                ssl_keyfile='key.pem',
                                ssl_check_hostname=True,
                                security_protocol='SSL',
                                topic='rasa_events')

Implementing a Kafka Event Consumer

The parameters used to create a Kafka consumer are the same used on the producer based on the security protocol:

from kafka import KafkaConsumer
from json import loads

consumer = KafkaConsumer('rasa_events',
                          bootstrap_servers=['localhost:29093'],
                          value_deserializer=lambda m: json.loads(m.decode('utf-8')), 
                          security_protocol='SSL',
                          ssl_check_hostname=False,
                          ssl_cafile='CARoot.pem',
                          ssl_certfile='certificate.pem',
                          ssl_keyfile='key.pem')

for message in consumer:
    print(message.value)

SQL Event Broker

It is possible to use an SQL database as an event broker. Connections to databases are established using SQLAlchemy.

Adding a SQL Event Broker Using the Endpoint Configuration

To instruct Rasa to save all events to your SQL event broker, add an event_broker section to your endpoints.yml. An example SQLite configuration:

event_broker:
  type: SQL
  dialect: sqlite
  db: events.db