内容分类

分析文档并返回文档中找到的文本所适用的内容分类列表。

代码示例

Python

如需了解如何安装和使用 Natural Language 客户端库，请参阅 Natural Language 客户端库。 有关详情，请参阅 Natural Language Python API 参考文档。

如需向 Natural Language 进行身份验证，请设置应用默认凭据。如需了解详情，请参阅为本地开发环境设置身份验证。

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

后续步骤

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