Natural Language Client Libraries

This page shows how to get started with the Cloud Client Libraries for the Cloud Natural Language API. Read more about the client libraries for Cloud APIs, including the older Google APIs Client Libraries, in Client Libraries Explained.

Installing the client library

C#

For more information, see Setting Up a C# Development Environment.

If you are using Visual Studio 2017 or higher, open nuget package manager window and type the following:

Install-Package Google.Apis

If you are using .NET Core command-line interface tools to install your dependencies, run the following command:

dotnet add package Google.Apis

Go

For more information, see Setting Up a Go Development Environment.

go get -u cloud.google.com/go/language/apiv1

Java

For more information, see Setting Up a Java Development Environment.

If you are using Maven, add the following to your pom.xml file. For more information about BOMs, see The Google Cloud Platform Libraries BOM.

<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>com.google.cloud</groupId>
      <artifactId>libraries-bom</artifactId>
      <version>20.6.0</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>

<dependencies>
  <dependency>
    <groupId>com.google.cloud</groupId>
    <artifactId>google-cloud-language</artifactId>
  </dependency>

If you are using Gradle, add the following to your dependencies:

implementation platform('com.google.cloud:libraries-bom:20.6.0')

compile 'com.google.cloud:google-cloud-language'

If you are using sbt, add the following to your dependencies:

libraryDependencies += "com.google.cloud" % "google-cloud-language" % "1.103.1"

If you're using IntelliJ or Eclipse, you can add client libraries to your project using the following IDE plugins:

The plugins provide additional functionality, such as key management for service accounts. Refer to each plugin's documentation for details.

Node.js

For more information, see Setting Up a Node.js Development Environment.

npm install --save @google-cloud/language

PHP

For more information, see Using PHP on Google Cloud.

composer require google/apiclient

Python

For more information, see Setting Up a Python Development Environment.

pip install --upgrade google-cloud-language

Ruby

For more information, see Setting Up a Ruby Development Environment.

gem install google-api-client

Setting up authentication

To run the client library, you must first set up authentication by creating a service account and setting an environment variable. Complete the following steps to set up authentication. For other ways to authenticate, see the GCP authentication documentation.

Cloud Console

Create a service account:

  1. In the Cloud Console, go to the Create service account page.

    Go to Create service account
  2. Select a project.
  3. In the Service account name field, enter a name. The Cloud Console fills in the Service account ID field based on this name.

    In the Service account description field, enter a description. For example, Service account for quickstart.

  4. Click Create.
  5. Click the Select a role field.

    Under Quick access, click Basic, then click Owner.

  6. Click Continue.
  7. Click Done to finish creating the service account.

    Do not close your browser window. You will use it in the next step.

Create a service account key:

  1. In the Cloud Console, click the email address for the service account that you created.
  2. Click Keys.
  3. Click Add key, then click Create new key.
  4. Click Create. A JSON key file is downloaded to your computer.
  5. Click Close.

Command line

You can run the following commands using the Cloud SDK on your local machine, or in Cloud Shell.

  1. Create the service account. Replace NAME with a name for the service account.

    gcloud iam service-accounts create NAME
  2. Grant permissions to the service account. Replace PROJECT_ID with your project ID.

    gcloud projects add-iam-policy-binding PROJECT_ID --member="serviceAccount:NAME@PROJECT_ID.iam.gserviceaccount.com" --role="roles/owner"
  3. Generate the key file. Replace FILE_NAME with a name for the key file.

    gcloud iam service-accounts keys create FILE_NAME.json --iam-account=NAME@PROJECT_ID.iam.gserviceaccount.com

Provide authentication credentials to your application code by setting the environment variable GOOGLE_APPLICATION_CREDENTIALS. This variable only applies to your current shell session, so if you open a new session, set the variable again.

Linux or macOS

export GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

Replace KEY_PATH with the path of the JSON file that contains your service account key.

For example:

export GOOGLE_APPLICATION_CREDENTIALS="/home/user/Downloads/service-account-file.json"

Windows

For PowerShell:

$env:GOOGLE_APPLICATION_CREDENTIALS="KEY_PATH"

Replace KEY_PATH with the path of the JSON file that contains your service account key.

For example:

$env:GOOGLE_APPLICATION_CREDENTIALS="C:\Users\username\Downloads\service-account-file.json"

For command prompt:

set GOOGLE_APPLICATION_CREDENTIALS=KEY_PATH

Replace KEY_PATH with the path of the JSON file that contains your service account key.

Using the client library

The following example shows how to use the client library.

Go


// Sample language-quickstart uses the Google Cloud Natural API to analyze the
// sentiment of "Hello, world!".
package main

import (
	"context"
	"fmt"
	"log"

	language "cloud.google.com/go/language/apiv1"
	languagepb "google.golang.org/genproto/googleapis/cloud/language/v1"
)

func main() {
	ctx := context.Background()

	// Creates a client.
	client, err := language.NewClient(ctx)
	if err != nil {
		log.Fatalf("Failed to create client: %v", err)
	}
	defer client.Close()

	// Sets the text to analyze.
	text := "Hello, world!"

	// Detects the sentiment of the text.
	sentiment, err := client.AnalyzeSentiment(ctx, &languagepb.AnalyzeSentimentRequest{
		Document: &languagepb.Document{
			Source: &languagepb.Document_Content{
				Content: text,
			},
			Type: languagepb.Document_PLAIN_TEXT,
		},
		EncodingType: languagepb.EncodingType_UTF8,
	})
	if err != nil {
		log.Fatalf("Failed to analyze text: %v", err)
	}

	fmt.Printf("Text: %v\n", text)
	if sentiment.DocumentSentiment.Score >= 0 {
		fmt.Println("Sentiment: positive")
	} else {
		fmt.Println("Sentiment: negative")
	}
}

Java

// Imports the Google Cloud client library
import com.google.cloud.language.v1.Document;
import com.google.cloud.language.v1.Document.Type;
import com.google.cloud.language.v1.LanguageServiceClient;
import com.google.cloud.language.v1.Sentiment;

public class QuickstartSample {
  public static void main(String... args) throws Exception {
    // Instantiates a client
    try (LanguageServiceClient language = LanguageServiceClient.create()) {

      // The text to analyze
      String text = "Hello, world!";
      Document doc = Document.newBuilder().setContent(text).setType(Type.PLAIN_TEXT).build();

      // Detects the sentiment of the text
      Sentiment sentiment = language.analyzeSentiment(doc).getDocumentSentiment();

      System.out.printf("Text: %s%n", text);
      System.out.printf("Sentiment: %s, %s%n", sentiment.getScore(), sentiment.getMagnitude());
    }
  }
}

Node.js

async function quickstart() {
  // Imports the Google Cloud client library
  const language = require('@google-cloud/language');

  // Instantiates a client
  const client = new language.LanguageServiceClient();

  // The text to analyze
  const text = 'Hello, world!';

  const document = {
    content: text,
    type: 'PLAIN_TEXT',
  };

  // Detects the sentiment of the text
  const [result] = await client.analyzeSentiment({document: document});
  const sentiment = result.documentSentiment;

  console.log(`Text: ${text}`);
  console.log(`Sentiment score: ${sentiment.score}`);
  console.log(`Sentiment magnitude: ${sentiment.magnitude}`);
}

Python

# Imports the Google Cloud client library
from google.cloud import language_v1


# Instantiates a client
client = language_v1.LanguageServiceClient()

# The text to analyze
text = u"Hello, world!"
document = language_v1.Document(content=text, type_=language_v1.Document.Type.PLAIN_TEXT)

# Detects the sentiment of the text
sentiment = client.analyze_sentiment(request={'document': document}).document_sentiment

print("Text: {}".format(text))
print("Sentiment: {}, {}".format(sentiment.score, sentiment.magnitude))

Additional resources