Warning: This document is for an old version of Rasa. The latest version is 1.2.3.

Event Brokers

Rasa Core allows you to stream events to a message broker. The event broker emits events into the event queue. It becomes part of the TrackerStore which you use when starting an Agent or launch rasa.core.run.

All events are streamed to the broker as serialised dictionaries every time the tracker updates it 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"
}

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

Rasa enables two possible brokers producers: Pika Event Broker and Kafka Event Broker.

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 use an endpoint configuration file to instruct Rasa Core to stream all events to your event broker. To do so, add the following section to your endpoint configuration, e.g. endpoints.yml:

event_broker:
  url: localhost
  username: username
  password: password
  queue: queue
  type: pika

Then instruct Rasa Core to use the endpoint configuration and Pika producer by adding --endpoints <path to your endpoint configuration as following example:

rasa run -m models --endpoints endpoints.yml

Adding a Pika Event Broker in Python

Here is how you add it using Python code:

from rasa.core.event_brokers.pika_producer import PikaProducer
from rasa_platform.core.tracker_store import InMemoryTrackerStore

pika_broker = PikaProducer('localhost',
                            'username',
                            'password',
                            queue='rasa_production_events')

tracker_store = InMemoryTrackerStore(db=db, 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 to 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):
        # Do something useful with your incoming message body here, e.g.
        # saving it to a database
        print('Received event {}'.format(json.loads(body)))

if __name__ == '__main__':

    # RabbitMQ credentials with username and password
    credentials = pika.PlainCredentials('username', 'password')

    # pika connection to the RabbitMQ host - typically 'rabbit' in a
    # docker environment, or 'localhost' in a local environment
    connection = pika.BlockingConnection(
        pika.ConnectionParameters('rabbit', credentials=credentials))

    # start consumption of channel
    channel = connection.channel()
    channel.basic_consume(_callback,
                          queue='rasa_production_events',
                          no_ack=True)
    channel.start_consuming()

Kafka Event Broker

It is possible to use Kafka as main broker to you 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

As for the other brokers, you can use an endpoint configuration file to instruct Rasa Core to stream all events to this event broker. To do it, add the following section to your endpoint configuration.

Pass the endpoints.yml file as argument with --endpoints <path to your endpoint configuration> when running Rasa, as following example:

rasa run -m models --endpoints 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

In the case of using SSL protocol the endpoints file must looks 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 on how to instantiate a Kafka producer in you script.

from rasa.core.event_brokers.kafka_producer import KafkaProducer
from rasa.core.tracker_store import InMemoryTrackerStore

kafka_broker = KafkaProducer(host='localhost:9092',
                             topic='rasa_production_events')

tracker_store = InMemoryTrackerStore(event_broker=kafka_broker)

The host variable can be either a list of brokers adresses or a single one. If only one broker address is available, the client will connect to it and request the cluster Metadata. Therefore, the remain brokers in the cluster can be discovered automatically through the data served by the first connected broker.

To pass more than one broker address as argument, they must be passed in a list of strings. e.g.:

kafka_broker = KafkaProducer(host=['kafka_broker_1:9092',
                                   'kafka_broker_2:2030',
                                   'kafka_broker_3:9092'],
                             topic='rasa_production_events')

Authentication and authorization

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

For development environment, or if the brokers servers and clients are located into the same machine, you can use simple authentication with SASL_PLAINTEXT. By using this protocol, the credentials and messages exchanged between the clients and servers will be sent in plaintext. Thus, this is not the most secure approach, but since it’s simple to configure, it is useful for simple cluster configurations. SASL_PLAINTEXT protocol requires the setup of the username and password previously configured in the broker server.

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

If the clients or the brokers in the kafka cluster are located in different machines, it’s important to use ssl protocal to assure encryption of data and client authentication. After generating valid certificates for the brokers and the clients, the path to the certificate and key generated for the producer must be provided as arguments, as well as the CA’s root certificate.

kafka_broker = KafkaProducer(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_production_events')

If the ssl_check_hostname parameter is enabled, the clients will verify if the broker’s hostname matches the certificate. It’s used on client’s connections and inter-broker connections to prevent man-in-the-middle attacks.

Implementing a Kafka Event Consumer

The parameters used to create a Kafka consumer is the same used on the producer creation, according to the security protocol being used. The following implementation shows an example:

from kafka import KafkaConsumer
from json import loads

consumer = KafkaConsumer('rasa_production_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)