CODEWITHSUNDEEP
pythongoogle-cloud-platformgoogle-natural-language
snapcrack
snapcrack

Reputation: 1813

AttributeError: 'LanguageServiceClient' object has no attribute 'classify_text'

I'm trying to classify some text and have the following code:

from google.cloud import language
from google.cloud.language import enums
from google.cloud.language import types


def classify_text(text):
    """Classifies content categories of the provided text."""
    client = language.LanguageServiceClient()

    if isinstance(text, six.binary_type):
        text = text.decode('utf-8')

    document = types.Document(
        content=text.encode('utf-8'),
        type=enums.Document.Type.PLAIN_TEXT)

    categories = client.classify_text(document).categories

    for category in categories:
        print(u'=' * 20)
        print(u'{:<16}: {}'.format('name', category.name))
        print(u'{:<16}: {}'.format('confidence', category.confidence))

But when I call: classify_text('Hello'), I get:

AttributeError: 'LanguageServiceClient' object has no attribute 'classify_text'

I can't seem to find any questions here on SO about this error. Does anyone know what's happening here?

Upvotes: 1

Views: 981

Answers (2)

snapcrack
snapcrack

Reputation: 1813

The version I was using, 0.29, was deprecated. The current version is 1.1 and the correct function is the following:

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

    language_client = language.LanguageServiceClient()

    document = language.types.Document(
        content=text,
        type=language.enums.Document.Type.PLAIN_TEXT)
    response = language_client.classify_text(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(u'=' * 20)
            print(u'{:<16}: {}'.format('category', category.name))
            print(u'{:<16}: {}'.format('confidence', category.confidence))

    return result

That function is found here, but the function I mistakenly used is found here

Upvotes: 1

christopher de jesus
christopher de jesus

Reputation: 305

Try:

categories = client.classify_text(document)
cat = categories.categories

That's basic debugging, I know.

You could also comment out the declaration for a document and do this:

document = {}

And check if it's throwing the same error.

Since it should return either way a ClassifyTextResponse, maybe this will start dividing the problem in parts. Better to attack one by one in these cases.

Upvotes: 0

Related Questions