Classify content

Analyze a document and return a list of content categories that apply to the text found in the document.

Explore further

For detailed documentation that includes this code sample, see the following:

• Content Classification Tutorial

Code sample

Python

To learn how to install and use the client library for Natural Language, see Natural Language client libraries. For more information, see the Natural Language Python API reference documentation.

To authenticate to Natural Language, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

def classify(text, verbose=True):
    """Classify the input text into categories."""

    language_client = language_v1.LanguageServiceClient()

    document = language_v1.Document(
        content=text, type_=language_v1.Document.Type.PLAIN_TEXT
    )
    response = language_client.classify_text(request={"document": document})
    categories = response.categories

    result = {}

    for category in categories:
        # Turn the categories into a dictionary of the form:
        # {category.name: category.confidence}, so that they can
        # be treated as a sparse vector.
        result[category.name] = category.confidence

    if verbose:
        print(text)
        for category in categories:
            print("=" * 20)
            print("{:<16}: {}".format("category", category.name))
            print("{:<16}: {}".format("confidence", category.confidence))

    return result

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