Chatbot Meetup

www.neosperience.com | blog.neosperience.com | [email protected] Usergroup

November 2016

Serverless Chatbots

Luca Bianchi, Chief Technology Officer @ NeosperienceJanos Tolgyesi, Team Leader iOS @ Neosperience

github.com/aletheia

https://it.linkedin.com/in/lucabianchipavia

@bianchiluca

github.com/mrtj

https://it.linkedin.com/in/janostolgyesi

Who are we?Working on a lot of bleeding edge technologies. Passionate developers.

Love writing code.

One of us speaks Magyar very well, guess who? :-)

The Neosperience Cloud• Software as a service cloud for Digital Customer Experience processes (couponing, gamification, proximity, etc.)

• Completely built on AWS

• Moved from VMWare, to EC2, to Elastic Beanstalk, to Lambda

• Dozens of micro and nano services

NeosperienceThe Digital Customer Experience Company, aims to change the way brands and customers interact with an

approach of a software vendor targeting Digital Customer Experience as the evolution of Marketing automation.

✓ Functions are the unit of development and scaling

✓ No machine, VMs or containers visible in the programming model

✓ Permanent storage lives elsewhere (stateless code)

✓ Scales per request. Users cannot over or under-provision capacity

✓ Never pay for idle

✓ Implicitly fault tolerant

✓ BYOC - Bring Your Own Code

✓ Metrics and logging are an universal right

The Serverless Manifesto

The Serverless Framework (aka serverless.com)

• Started less than one year ago (was named JAWS) • Fast moving (with a bi-weekly release model) • Funded by a 3M investment • Manages service deployments and provisioning • Vendor independent (in a future release)

• Auto-provision of resources

• Supports for micro-services

• Improved plugin management system

• Production ready

Getting started

• Install Serverless locally (trust me, it’s better) npm install serverless —save

• Create a function in NodeJS (Java and Python supported too)serverless create —template=aws-nodejs

• Deploy serviceserverless deploy

done!

ArchitectureFacebook Bot Messenger

Platform

Messenger HookService

1. send message

2. HTTP methodcall to REST

3. synch HTTP call to api.ai

4.Context and answer

5. message sent backto Facebook

6. Message

Content DataService

3.2 TextualAnswer

3.1 Api.ai Webhook

Introducing Api.ai

• “Conversation UX platform”

• Natural language understanding: intent recognition, entity extraction • Conversational engine

• Optionally speech recognition and TTS • Predefined conversational domain (eg. “Small Talk”)

• Integration with various chat platforms • Free tier

http://api.ai/

Facebook Messenger Platform

• Build chat bots for Messenger

• web-hook based callbacks • relatively complex setup (Page, App, verify token, etc.)

Step 1: Create bot on api.ai

• Create intents: sample phrases (utterances)

• (Optional) Create entities: attributes of intent, to be extracted from user response • Enabled domains if needed (Small Talk)

• api.ai webhooks: content data service • api.ai integration API: we will use this!

http://api.ai/

Step 2: Configure Messenger App

• Create a Facebook Page (chat bots live inside Pages)

• Create a Facebook App • Setup webhooks: Messenger will send here the messages of the user

• Security considerations: verify token and page access token • Subscribe app to page events (eg. new message)

• Receive messages and postbacks, and send structured response

https://developers.facebook.com/docs/messenger-platform/

What’s inside a Service?

JSON Request Event

JSON Response Event

Request to Api.ai

Response from Api.ai

Step 3: Lambda connects the two worlds

• When the webhook is called by facebook, the lambda is invoked

• Parses Messenger payload and extracts user message • Assembles api.ai message requests and sends it to REST api endpoint

• Parses api.ai responds including recognized intent and bot response • Assembles Messenger response and sends it back to Messenger

• + administrative functions (verify token authentication, page subscription)

ArchitectureFacebook Bot Messenger

Platform

Messenger HookService

1. send message

2. HTTP methodcall to REST

3. synch HTTP call to api.ai

4.Context and answer

5. message sent backto Facebook

6. Message

Content DataService

3.2 TextualAnswer

3.1 Api.ai Webhook

The good..

• Fast time to market (the whole project built in 8h)

• Modularity by design • Functions can run locally

• Everything is contained and versioned • Serverless avoids a lot of boilerplate

• Incremental deployments • Supports CI

• Cost-effective • Api.ai acquired by Google (now with support for Italian language)

..the bad

• Architecture has to be enforced (your code is as good as you)

• Testing is unavoidable, TDD is encouraged • Every deploy hits the cloud

• Cannot test offline (no matter how you try) • Avoid Lambda cold start issue

• Not everything is supported by CloudFormation • Many pieces stored in different places (maybe CloudFormation CustomResource?)

Thank you

github.com/aletheia

https://it.linkedin.com/in/lucabianchipavia

@bianchiluca

Slides available on Slideshare

http://bit.ly/2fZMM2Q

Try our Neosperience DCX Bot http://m.me/neosperience

github.com/mrtj

https://it.linkedin.com/in/janostolgyesi

www.neosperience.com | blog.neosperience.com | [email protected]