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 serialised 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 are going to use the python-kafka library, a Kafka client written in Python.

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.

Using SASL_PLAINTEXT protocol the endpoints file must have the following entries:

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

If using SSL protocol, the endpoints file should look like:

event_broker:
  url: localhost
  topic: topic
  security_protocol: SSL
  ssl_cafile: CARoot.pem
  ssl_certfile: certificate.pem
  ssl_keyfile: key.pem
  ssl_check_hostname: True
  type: kafka

Adding a Kafka Broker in Python

The code below shows an example of how to instantiate a Kafka producer in your script:

from rasa.core.brokers.kafka import KafkaEventBroker
from rasa.core.tracker_store import InMemoryTrackerStore

kafka_broker = KafkaEventBroker(host='localhost:9092',
                                topic='rasa_events')

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

Authenticating and Authorizing

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

Implementing a Kafka Event Consumer

The parameters used to create a Kafka consumer are the same used on the producer creation:

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. For example, a valid SQLite configuration could look like the following:

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

PostgreSQL databases can be used as well:

event_broker:
  type: SQL
  host: 127.0.0.1
  port: 5432
  dialect: postgresql
  username: myuser
  password: mypassword
  db: mydatabase

With this configuration applied, Rasa will create a table called events on the database, where all events will be added.