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Clasificar texto

Analiza texto y muestra una lista de categorías de contenido que se aplican al texto.

Explora más

Para obtener documentación en la que se incluye esta muestra de código, consulta lo siguiente:

Clasifica el contenido

Muestra de código

Go

Para obtener información sobre cómo instalar y usar la biblioteca cliente de Natural Language, consulta Bibliotecas cliente de Natural Language. Para obtener más información, consulta la documentación de referencia de la API de Natural Language Go.

Para autenticarte en Natural Language, configura las credenciales predeterminadas de la aplicación. Si deseas obtener más información, consulta Configura la autenticación para un entorno de desarrollo local.


func classifyText(ctx context.Context, client *language.Client, text string) (*languagepb.ClassifyTextResponse, error) {
	return client.ClassifyText(ctx, &languagepb.ClassifyTextRequest{
		Document: &languagepb.Document{
			Source: &languagepb.Document_Content{
				Content: text,
			},
			Type: languagepb.Document_PLAIN_TEXT,
		},
		ClassificationModelOptions: &languagepb.ClassificationModelOptions{
			ModelType: &languagepb.ClassificationModelOptions_V2Model_{
				V2Model: &languagepb.ClassificationModelOptions_V2Model{
					ContentCategoriesVersion: languagepb.ClassificationModelOptions_V2Model_V2,
				},
			},
		},
	})
}

Java

// Instantiate the Language client com.google.cloud.language.v2.LanguageServiceClient
try (LanguageServiceClient language = LanguageServiceClient.create()) {
  // Set content to the text string
  Document doc = Document.newBuilder().setContent(text).setType(Type.PLAIN_TEXT).build();
  ClassifyTextRequest request = ClassifyTextRequest.newBuilder().setDocument(doc).build();
  // Detect categories in the given text
  ClassifyTextResponse response = language.classifyText(request);

  for (ClassificationCategory category : response.getCategoriesList()) {
    System.out.printf(
        "Category name : %s, Confidence : %.3f\n",
        category.getName(), category.getConfidence());
  }
}

Node.js

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

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

/**
 * TODO(developer): Uncomment the following line to run this code.
 */
// const text = 'Your text to analyze, e.g. Hello, world!';

// Prepares a document, representing the provided text
const document = {
  content: text,
  type: 'PLAIN_TEXT',
};

const classificationModelOptions = {
  v2Model: {
    contentCategoriesVersion: 'V2',
  },
};

// Classifies text in the document
const [classification] = await client.classifyText({
  document,
  classificationModelOptions,
});
console.log('Categories:');
classification.categories.forEach(category => {
  console.log(`Name: ${category.name}, Confidence: ${category.confidence}`);
});

PHP

Para obtener información sobre cómo instalar y usar la biblioteca cliente de Natural Language, consulta Bibliotecas cliente de Natural Language.

use Google\Cloud\Language\V1\ClassifyTextRequest;
use Google\Cloud\Language\V1\Client\LanguageServiceClient;
use Google\Cloud\Language\V1\Document;
use Google\Cloud\Language\V1\Document\Type;

/**
 * @param string $text The text to analyze
 */
function classify_text(string $text): void
{
    // Make sure we have enough words (20+) to call classifyText
    if (str_word_count($text) < 20) {
        printf('20+ words are required to classify text.' . PHP_EOL);
        return;
    }
    $languageServiceClient = new LanguageServiceClient();

    // Create a new Document, add text as content and set type to PLAIN_TEXT
    $document = (new Document())
        ->setContent($text)
        ->setType(Type::PLAIN_TEXT);

    // Call the analyzeSentiment function
    $request = (new ClassifyTextRequest())
        ->setDocument($document);
    $response = $languageServiceClient->classifyText($request);
    $categories = $response->getCategories();
    // Print document information
    foreach ($categories as $category) {
        printf('Category Name: %s' . PHP_EOL, $category->getName());
        printf('Confidence: %s' . PHP_EOL, $category->getConfidence());
        print(PHP_EOL);
    }
}

Python

Si deseas obtener información sobre cómo instalar y usar la biblioteca cliente de Natural Language, consulta Bibliotecas cliente de Natural Language. Para obtener más información, consulta la documentación de referencia de la API de Natural Language Python.

from google.cloud import language_v1


def sample_classify_text(text_content):
    """
    Classifying Content in a String

    Args:
      text_content The text content to analyze.
    """

    client = language_v1.LanguageServiceClient()

    # text_content = "That actor on TV makes movies in Hollywood and also stars in a variety of popular new TV shows."

    # Available types: PLAIN_TEXT, HTML
    type_ = language_v1.Document.Type.PLAIN_TEXT

    # Optional. If not specified, the language is automatically detected.
    # For list of supported languages:
    # https://cloud.google.com/natural-language/docs/languages
    language = "en"
    document = {"content": text_content, "type_": type_, "language": language}

    content_categories_version = (
        language_v1.ClassificationModelOptions.V2Model.ContentCategoriesVersion.V2
    )
    response = client.classify_text(
        request={
            "document": document,
            "classification_model_options": {
                "v2_model": {"content_categories_version": content_categories_version}
            },
        }
    )
    # Loop through classified categories returned from the API
    for category in response.categories:
        # Get the name of the category representing the document.
        # See the predefined taxonomy of categories:
        # https://cloud.google.com/natural-language/docs/categories
        print(f"Category name: {category.name}")
        # Get the confidence. Number representing how certain the classifier
        # is that this category represents the provided text.
        print(f"Confidence: {category.confidence}")

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