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Google Assistant: Build a Restaurant Locator with the Places API

Google Assistant: Build a Restaurant Locator with the Places API

시간 분 7 크레딧

GSP486

Google Cloud Self-Paced Labs

Overview

Google Assistant is a personal voice assistant that offers a host of actions and integrations. From sending texts and setting reminders, to ordering coffee and playing music, the 1 million+ actions available suit a wide range of voice command needs.

Google Cloud Functions is a lightweight compute solution for developers to create single-purpose, stand-alone functions that respond to Cloud events without the need to manage a server or runtime environment.

The Places API is a service that returns information about points of interest by using HTTP requests. More specifically, you will take advantage of the Place Details and Place Photos services to receive detailed information and photos of establishments.

By utilizing Cloud Functions and the Places API, you will build an Assistant application that takes in a user's current location and restaurant preferences to generate the ideal restaurant for them to visit, complete with names, addresses, and photos.

What you will learn

In this lab, you will learn how to:

  • Build an Assistant application pipeline that consists of an Actions project, a Dialogflow agent with custom intents and entities, a webhook, and a Cloud Function to handle fulfillment.
  • Generate the proper authentication credentials and install necessary dependencies to use the Places API.
  • Add fulfillment logic to the Cloud Function to handle Places API calls.
  • Deploy your application and test it with the Actions Simulator.

Prerequisites

This is an advanced level lab. This assumes familiarity with Dialogflow and Cloud Functions. Basic knowledge of APIs is recommended. Experience with JavaScript and the Node.js runtime is recommended, but not required. If you need to brush up on these skills, please take one of the following labs before attempting this one:

Once you're ready, scroll down and follow the steps below to get your lab environment set up.

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점수

—/100

Create a Dialogflow Agent traverse from Action Project

단계 진행

/ 30

Configure the Default Welcome Intent

단계 진행

/ 10

Build the Custom Intent (name: get_restaurant)

단계 진행

/ 30

Initialize and Configure a Cloud Function

단계 진행

/ 30