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

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

我正在尝试对一些文本进行分类并具有以下代码:

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))

但是当我调用:classify_text('Hello'),我得到:

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

我似乎在 SO 上找不到关于此错误的任何问题。有人知道这里发生了什么吗?

尝试:

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

这是基本调试,我知道。

您也可以注释掉文档的声明并执行此操作:

document = {}

并检查它是否抛出相同的错误。

因为它应该 return 任何一种方式 ClassifyTextResponse,也许这会开始将问题分成几部分。这种情况最好一一攻击。

我使用的版本 0.29 已弃用。当前版本为1.1,正确的函数如下:

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

找到那个函数here, but the function I mistakenly used is found here