Using Dialogflow to build actions for Google Assistant ‘18 Abdelrahman Omran | Rinvex | @Omranic | [email protected] 

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“ Intent Matching — Match and categorize user utterances to an intent. Entity Extraction — Identify key words and phrases spoken by the user. @ 

Why Dialogflow? Features and benefits of using Dialogflow 

Build natural and rich conversational experiences 

Use machine learning to understand what users are saying 

Across devices Around the world On any platform 

See who's using Dialogflow 

How Dialogflow Works? A high level overview for using dialogflow 

Hey Google, talk to __________. Hey Google, connect me with __________. Hey Google, get __________. 

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In Dialogue Discovery: Explicit Triggering Ok Google, ask Personal Chef for a hot soup recipe Trigger Phrase App Name Developer Specified Action Preposition Action Phrase Developer Specified Working Examples: Let’s speak to Domino’s Ask Dr. Doggy if dogs can eat chocolate Ok Google, let’s talk to Personal Chef Trigger Phrase App Name Developer Specified 

Entities: homemade cannoli “Find me a recipe for homemade cannoli” User Says Response Webhook “Find me a recipe for homemade cannoli” “Here’s the best one I can find” 

Webhook (optional) “Ok Google, talk to personal chef” Dialogflow Invoke “personal chef” action “Well, it’s kind of cold outside, so I’d like something to …” “Sure, here’s your personal chef” “Sure, here’s personal chef. Hi, I’m your personal chef, what are you in the mood for?” “What protein would you like to use?” Speech to Text Text to Speech APP Speech to Text, NLP, Knowledge Graph, ML Ranking, User Profile, Text to Speech 

Ok Google, talk to Personal Chef Well, it’s kind of cold outside, so I’d like... Sure, here’s Personal Chef What are you in the mood for? What protein would you like to use? Speech to Text NLP Knowledge Graph ML Ranking User Profile Speech to Text Text to Speech ... ... ... Trigger WELCOME event ... NLP: Intent Matching Entity Extraction 

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Intent Triggered via a series of “user says” phrases or platform based events. Matched at every turn of conversation. Can collects entity values. 

Important data you want to get from a user's request, will have a corresponding entity. It’s powerful tools used for extracting parameter values from natural language inputs. This helps to bias the speech recognizer to detect the values you are expecting. Defined synonyms will be mapped to each entity value. Entities 

Action Dialogflow specific use of Action compared to Google Assistant Conversation Action. String passed to the webhook that indicates what action is being performed. Can share the same action name across different Intents. 

Input and Output Contexts You can require a context to be available before an Intent is enabled. Implement flow control between some Intents. Intent can set context to enable other Intents. 

Parameters Values that we are trying to capture from the user phrases. Can specify a parameter name and a type of value. Values can be a list of fixed values. Values can be optional. 

Text response Spoken when the Intent is complete. Webhook can dynamically adjust this response. Embed entity values if desired, “I found a recipe for $protein and $vegetable!” 

Specify follow up questions if a user doesn’t specify certain values Read out in random order to make it more natural Prompts 

Fulfillment Dialogflow project interface with business logic through webhook. It’s all built in the web platform, so you can use the programming language and hosting platform of your choice, it’s just HTTP(S) callbacks. 

Dialogflow Example Let’s take a quick Dialogflow example 

Thank you! Abdelrahman Omran | @Omranic | [email protected]