Implementation of the Chat Bot for the Magento on Facebook messenger. It uses Wit.AI to parse the context of conversation

2. A Facebook Chat Bot
Using Magento 2 Async
Processing

3. Magento 2 Architect
Eugene Tulika @vrann

4. Use-Case: Store With
Hand-Picked Books

5. Niche Customers With Unusual Requests

6. Facebook Page
• Facebook is the best way to reach larger and targeted audience
• Facebook Page representing the store
• Customers don’t want to leave Facebook to shop in store
• Customers ask questions in Messenger

7. Facebook Chat Bots
• When store Manager cannot handle all communications manually
• Facebook webhooks for messages received in the chat
• Facebook API for responses

8. Facebook POSTs Messages to the Callback
Callback.php
200 OK

9. Callback POSTs Response to Facebook API

10. Understanding the
Conversation

11. How to Convert Messages to Magento API Requests
Input
Classifier
Search catalog by author
Title, image url, description

12. Quadrant of Conversation Parsers
Image from https://www.quora.com/What-is-the-best-way-to-learn-and-write-a-AI-Chat-bot

13. Wit.AI Retrieval Conversation Setup

14. Conversation Parsing
• https://github.com/vrann/phpwit
Do you have a book by Proust?
Intent: catalog_search
Parameters:
 Author: Proust
Invoke: catalogSearch(context)

15. Integration With
Magento
IN/OUT integration Using Web API

16. On average, Magento store has integrations
with 15 different external systems
Integrations Framework:
• API In supported by Web API (CE) and RabbitMQ (EE)
• API Out supported by RabbitMQ (EE)

17. Callback Makes API Request to Magento
Messenger Callback.php
API
Web API Request
Magento POSTs response to Facebook

18. Web API Service Interface

19. Magento API Interfaces
• https://github.com/vrann/magebot

20. Map Service to the Web API Endpoint

21. What Can Go Wrong?
When customer writes in Messenger:
• Blocking request from callback to Magento
• Scalability: Magento can be overloaded processing other requests
• Availability: Magento API is unreachable at that moment
Messages from customer can be lost!

22. API IN Using RabbitMQ

23. Callback Puts Messages to the Queue
• Scripts: https://github.com/vrann/http-rabbitmq-writer
Messenger
API
Callback.php
Magento POSTs response to Facebook
Rabbit MQ

24. Transformation of Web API to Inbound Calls via RabbitMQ
Map message handler to topic in communication.xml
Map consumer to queue in queue_consumer.xml
Run consumer(s):

25. Communication & Queue Configurations
We achieved:
 Non-Blocking request, response to Facebook sent immediately
 Scalability handled by Queue
 Availability handled by Queue
Communication vs Queue:
• Communication Framework is an abstraction around
publisher/subscriber. It can be implemented:
– with database and HTTP requests instead (webhooks)
– in-memory (observers)
• Queue is a Transport layer for Communication
– configuration of RabbitMQ adapter and topology

26. API OUT Using
RabbitMQ

27. Goal: Magento Sends Messages to RabbitMQ
• Scripts: https://github.com/vrann/http-rabbitmq-writer
Messenger
API
callback.php
response.php

28. Before: Sender Interface Using HTTP Request

29. Now: Sender Interface Using RabbitMQ
Replace preference for MessageSenderInterface in di.xml,
Add “Remote” suffix
Interface implementation will be auto-generated:

30. Publisher & Topology
queue_publisher.xml maps generated topic to the exchange
queue_topology.xml configures exchange to queue bindings
• Prior to Magento EE 2.2 these config are in queue.xml

31. Wrap Up
• We covered:
– Reasons behind Magento Web API data structures
– Reasons to use queues
– Switch from Web API to the RabbitMQ
– Code generation of API OUT for RabbitMQ
– Communication framework vs Queue framework
– Separation of publishers, consumers, topology in 2.2
– Input Message Handling
– Facebook bots!
• https://github.com/vrann/facebook-chatbot
• https://github.com/vrann/http-rabbitmq-writer
• https://github.com/vrann/magebot

32. Q&A
Write me @vrann (twitter, github)
etulika@magento.com