E.D.D.I.Enhanced Dialog Driven Intelligence

Gregor Jarisch

What is E.D.D.I ? A Platform for creating, running and maintaining customized

Chatbots

Configuration ServerMaintaining Bot-ConfigsWeb UI for configuring Chatbots (Beta)Monitoring ConversationsAutomated Testing of Predefined Conversations (Integration-Tests)

Core ServerLaunching Chatbots based on Bot-Configs Algorithms, extendable by plugins

What is E.D.D.I ? (2) Focus on

Flexibility in connecting to other systems (plugins) Reusability of parts of Chatbots (dictionaries, dialog rules, ) (horizontal) Scalable

Technologies: High-Performance Java Web Application (Embedded Jetty) Dockerized RESTful Microservices NoSQL Database (MongoDB)

Workflow A Bot contains Knowledge-Packages

Knowledge-Packages contain Lifecycle-Tasks (pluggable)

Input Parser

Dialog Behavior

Output Generator

Workflow (2) Input Parser

Translates User Input into Semantic Meanings (Expressions)

Dialog Behavior Rules are clustered in Groups

Rules have Conditions What was the user input now/before

Did another rule succeed

How big is the search result from the external DB

Rules trigger actions

Output Simple Templating von Answer sentences

Example User:

Hallo

Input Parser: greeting(hallo)

Dialog Behavior: Did the user greet? -> greeting(*) action: Greet the user back greet_user

Output Generator Action greet_user Hi, how can I help you?

More Complex Example (flight check-in , choosing seat)

Input Parser

Externalsearch

Dialog Behavior

Output Generator

I dont care where I sit, as long as it is not at thecorridor!

seating(anywhere), not(seating(corridor))

seating(anywhere), not(seating(corridor))

Zb SQL: WHERE seating != corridor

If user input: seating(*)ANDSearch Result: > 0

We have reserved a seat for you, that is not at the corridor.

Action:Reserve_seating_in_DBconfirm_seating_choice

Reusability through Versioning All Bot-Configs (Dictionaries, Dialog Rules, Output, ) are

versioned

read-only

Each change makes another version (comparable to regular VCS)

Therefore less implementation effort with every new Bot e.g.: Greetings from the user will often the same and therefore can be

reused often

Plugins Lifecycle Task (e.g. Parser, Dialog Rules, Output)

Parser Dictionaries (e.g. Greetings, Integer, Time, )

Corrections (e.g. Keyboard Proximity, Phonetic Search, )

Dialog Rules Conditions (Match Input, Dependencies, ResultSize, )

Output Templating

Plugin Extension Points

Input Parser Dialog BehaviorOutput

Generator

Dictionaries Regular Integer Time

Corrections Phonetic Keyboard

Approximity

Conditions Input

Matcher Dependencies Result Size

Templating

}Lifecycle

Two possibilities to write plugins Java Plugin

Inherited from specific Interfaces

Web Hooks REST Call

e.g. to another web services in the same network

Allows the easy integration of other technologies

Default Setup

Configuration Server Core Server

Single-Sign-On (Redhat Keycloak)

Learnings (1) Better many Bots for many Use Cases

Rather than one Bot for all Use Cases

Why? The complexity increases exponentially Many Ambiguities New functions can silently break your Bot

Companies do have as well many employees with different skills Bots should be structured similarly Bots should know about each other and forward request to their

colleagues

Learnings (2) Up to 80 % of all conversation are small talk

User expect a human-like personality

Even if a Bot is functionally outstanding if it cannot small talk with the users, the Bot appears stupid

Small talk takes the most development effort (up to 90%) Customers expect a smart personality But Customers often pay for the functionality only (which is a shame)

If you keep the Chatbot Knowledge & Logic reusable, the effort decreases drastically with each new Bot you create!

Learnings (3) We are missing a Role in Chatbot Development (!)

Developers can create awesome code, but often lack patience to design proper conversation workflows

A Chatbot Team should therefore not only contain DEVs, but

Dialog Designers Profile:

Expertise in Communications Extended understanding about psychological Dynamics Ability to interview customers and experts effectively Sharp minded, technology affine and good at logical thinking

Learnings (4) The BEST This one is my most awesome finding

It took me 4 years to gasper this!!

This is so freaking simple, yet, havent seen it implemented anywhere

Let the Users

UNDOtheir actions!

I have been released on

github.com/labsai/EDDI(Beta)

Contributions & Feedback are Welcomed!

Lead Dev: Gregor Jarisch

E.D.D.I.Slide Number 2What is E.D.D.I ?What is E.D.D.I ? (2)WorkflowWorkflow (2)ExampleMore Complex Example (flight check-in , choosing seat)Reusability through VersioningPluginsPlugin Extension PointsTwo possibilities to write pluginsDefault SetupLearnings (1)Learnings (2)Learnings (3)Learnings (4) The BEST Slide Number 18Slide Number 19