Google Cloud Natural Language

Overview

Appian supports the integration of Google AI services in your application. You can use the Google Cloud Natural Language connected system to perform entity and sentiment analysis to collect information from HTML or plain text. Using these capabilities on elements of text allows you to identify key subjects such as people, places, and events, determine a user's opinion or conveyed emotion, and even classify the contents of the text into predefined categories.

To use this connected system, you must have a Google Service Account. For information that pertains to all connected systems, see Connected System Object.

Properties

The Google Cloud Natural Language connected system has the following properties:

Field	Description
Name	The name of the connected system. Use a name that will uniquely identify this connection to the external system.
Description	Supplemental information about the connected system that is displayed in the objects grid of some Designer views and when selecting the system in an integration object.
Project ID	Found in your Google Service Account file.
Private Key ID	Found in your Google Service Account file.
Private Key	Found in your Google Service Account file.
Client Email	Found in your Google Service Account file.
Client ID	Found in your Google Service Account file.

Automating property updates

This object's properties can also be updated programmatically using the Update Connected System endpoint. This lets you change passwords, API keys, and other values without needing to sign in to Appian.

The following properties can be included in the JSON request body of the PATCH /connected-system/<UUID> call.

• projectId
• privateKeyId
• privateKeyId
• clientEmail
• clientId

Operation

Name	Description	Type
Run Analysis	Run analysis on the provided text.	READ

This integration uses the REST Resource documents from the Google Cloud Natural Language API to categorize text and perform entity and sentiment analysis. Using the analysis options available, you can identify common entities, like proper names and common nouns, analyze sentiment in the text or associated with each entity, and categorize text into logical groupings for easier organization.

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