#

# Copyright 2023 Google LLC

#

# Licensed under the Apache License, Version 2.0 (the "License");

# you may not use this file except in compliance with the License.

# You may obtain a copy of the License at

#

# https://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS,

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

# See the License for the specific language governing permissions and

# limitations under the License.

# To install the latest published package dependency, execute the following:

# pip install google-cloud-language

# sample-metadata

# title: Classify Content

# description: Classifying Content in a String

# [START language_classify_text]

from google.cloud import language_v2

def sample_classify_text(

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

) -> None:

"""

Classifies Content in a string.

Args:

text_content: The text content to analyze.

"""

client = language_v2.LanguageServiceClient()

# Available types: PLAIN_TEXT, HTML

document_type_in_plain_text = language_v2.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_code = "en"

document = {

"content": text_content,

"type_": document_type_in_plain_text,

"language_code": language_code,

}

response = client.classify_text(request={"document": document})

# 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}")

# [END language_classify_text]