feat: Add new gcloud commands, API clients, and third-party libraries across various services.

gcloud auth application-default login/google-cloud-sdk/lib/surface/ml/language/__init__.py

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+# -*- coding: utf-8 -*- #
+# Copyright 2017 Google LLC. All Rights Reserved.
+#
+# 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
+#
+#    http://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.
+
+"""Command group for ml language."""
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import unicode_literals
+
+from googlecloudsdk.calliope import base
+
+
+class Language(base.Group):
+  """Use the Google Cloud Natural Language API to analyze text.
+
+     For more information, please see
+     https://cloud.google.com/natural-language/.
+  """

gcloud auth application-default login/google-cloud-sdk/lib/surface/ml/language/__init__.yaml

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+help_text:
+  language_help: |
+    Currently English, Spanish, Japanese, Chinese (Simplified and Traditional),
+    French, German, Italian, Korean, and Portuguese are supported.
+  language_help_ga: |
+    Currently English, Spanish, and Japanese are supported.
+  language_examples:
+    AE: |
+        To analyze entites in raw content 'puppies':
+
+          $ {command} --content='puppies'
+
+        To analyze entites in file 'myfile.txt':
+
+          $ {command} --content-file='myfile.txt'
+
+        To analyze entites in a remote file 'gs://bucket_name/mycontent.html' for Japanese language using
+        UTF-8 encoding:
+
+          $ {command} --content-file='gs://bucket_name/mycontent.html' --content-type=HTML --encoding-type=utf8 --language=ja-JP
+    AES: |
+        To analyze entity sentiment in raw content 'puppies':
+
+          $ {command} --content='puppies'
+
+        To analyze entity sentiment in file 'myfile.txt':
+
+          $ {command} --content-file='myfile.txt'
+
+        To  analyze entity sentiment in a remote file 'gs://bucket_name/mycontent.html' for Japanese language using
+        UTF-8 encoding:
+
+          $ {command} --content-file='gs://bucket_name/mycontent.html' --content-type=HTML --encoding-type=utf8 --language=ja-JP
+    AS: |
+        To analyze sentiment in raw content 'I love puppies.':
+
+          $ {command} --content='I love puppies.'
+
+        To analyze sentiment in file 'myfile.txt':
+
+          $ {command} --content-file='myfile.txt'
+
+        To analyze sentiment in a remote file 'gs://bucket_name/mycontent.html' for Japanese language using
+        UTF-8 encoding:
+
+          $ {command} --content-file='gs://bucket_name/mycontent.html' --content-type=HTML --encoding-type=utf8 --language=ja-JP
+    ASX: |
+        To analyze syntax in raw content 'They drink.':
+
+          $ {command} --content='They drink'
+
+        To analyze syntax in file 'myfile.txt':
+
+          $ {command} --content-file='myfile.txt'
+
+        To analyze syntax in a remote file 'gs://bucket_name/mycontent.html' for Japanese language using
+        UTF-8 encoding:
+
+          $ {command} --content-file='gs://bucket_name/mycontent.html' --content-type=HTML --encoding-type=utf8 --language=ja-JP
+    CT: |
+        To classify text in raw content 'Long Political Text.':
+
+          $ {command} --content='Long Political Text.'
+
+        To classify text in file 'myfile.txt':
+
+          $ {command} --content-file='myfile.txt'
+
+        To classify text in a remote file 'gs://bucket_name/mycontent.html' for Japanese language:
+
+          $ {command} --content-file='gs://bucket_name/mycontent.html' --content-type=HTML  --language=ja-JP
+
+
+request:
+  collection: language.documents
+  api_version: v1
+  modify_request_hooks:
+  - googlecloudsdk.command_lib.ml.language.util:UpdateRequestWithInput
+
+args:
+  content:
+    api_field: document.type
+    arg_name: content-type
+    default: plain-text
+    choices:
+    - arg_value: plain-text
+      enum_value: PLAIN_TEXT
+    - arg_value: html
+      enum_value: HTML
+    help_text: Specify the format of the input text.
+
+  language:
+    api_field: document.language
+    arg_name: language
+    help_text: |
+      Specify the language of the input text. If omitted, the server will
+      attempt to auto-detect. Both ISO (such as `en` or `es`) and BCP-47 (such
+      as `en-US` or `ja-JP`) language codes are accepted.
+
+  encoding:
+    api_field: encodingType
+    arg_name: encoding-type
+    default: utf8
+    help_text: |
+      The encoding type used by the API to calculate offsets. If set to `none`,
+      encoding-dependent offsets will be set at -1. This is an optional flag
+      only used for the entity mentions in results, and does not affect how the
+      input is read or analyzed.
+
+  content_group:
+    group:
+      mutex: true
+      required: true
+      params:
+      - arg_name: content
+        help_text: |
+          Specify input text on the command line. Useful for experiments, or
+          for extremely short text.
+      - arg_name: content-file
+        help_text: |
+          Specify a local file or Google Cloud Storage (format
+          `gs://bucket/object`) file path containing the text to be analyzed.
+          More useful for longer text or data output from another system.

gcloud auth application-default login/google-cloud-sdk/lib/surface/ml/language/analyze_entities.yaml

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+- release_tracks: [GA]
+
+  help_text:
+    brief: Use Google Cloud Natural Language API to identify entities in text.
+    description: |
+      Entity Analysis inspects the given text for common names or known entities
+      (proper nouns such as public figures, landmarks, etc.), and returns
+      information about those entities.
+
+      {language_help}
+    language_help: !COMMON help_text.language_help_ga
+    examples: !COMMON help_text.language_examples.AE
+
+  request:
+    _COMMON_: request
+    method: analyzeEntities
+
+  arguments:
+    params:
+    - _COMMON_: args.content_group
+    - _COMMON_: args.content
+    - _COMMON_: args.language
+    - _COMMON_: args.encoding
+
+  output:
+    format: json
+
+
+- release_tracks: [ALPHA, BETA]
+
+  help_text:
+    brief: Use Google Cloud Natural Language API to identify entities in text.
+    description: |
+      Entity Analysis inspects the given text for common names or known entities
+      (proper nouns such as public figures, landmarks, etc.), and returns
+      information about those entities.
+
+      {language_help}
+    language_help: !COMMON help_text.language_help
+    examples: !COMMON help_text.language_examples.AE
+
+  request:
+    _COMMON_: request
+    api_version: v1beta2
+    method: analyzeEntities
+
+  arguments:
+    params:
+    - _COMMON_: args.content_group
+    - _COMMON_: args.content
+    - _COMMON_: args.language
+    - _COMMON_: args.encoding
+
+  output:
+    format: json

gcloud auth application-default login/google-cloud-sdk/lib/surface/ml/language/analyze_entity_sentiment.yaml

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+- release_tracks: [GA]
+
+  help_text:
+    brief: Use Google Cloud Natural Language API to identify entity-level sentiment.
+    description: |
+      Entity level sentiment combines both entity analysis and sentiment analysis
+      and attempts to determine the sentiment (positive or negative) expressed
+      about entities within the text.
+
+      Currently only English is supported for this feature.
+    examples: !COMMON help_text.language_examples.AES
+
+  request:
+    _COMMON_: request
+    method: analyzeEntitySentiment
+
+  arguments:
+    params:
+    - _COMMON_: args.content_group
+    - _COMMON_: args.content
+    - _COMMON_: args.language
+    - _COMMON_: args.encoding
+
+  output:
+    format: json
+
+
+- release_tracks: [ALPHA, BETA]
+
+  help_text:
+    brief: Use Google Cloud Natural Language API to identify entity-level sentiment.
+    description: |
+      Entity level sentiment combines both entity analysis and sentiment analysis
+      and attempts to determine the sentiment (positive or negative) expressed
+      about entities within the text.
+
+      Currently only English is supported for this feature.
+    examples: !COMMON help_text.language_examples.AES
+
+  request:
+    _COMMON_: request
+    api_version: v1beta2
+    method: analyzeEntitySentiment
+
+  arguments:
+    params:
+    - _COMMON_: args.content_group
+    - _COMMON_: args.content
+    - _COMMON_: args.language
+    - _COMMON_: args.encoding
+
+  output:
+    format: json

gcloud auth application-default login/google-cloud-sdk/lib/surface/ml/language/analyze_sentiment.yaml

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+- release_tracks: [GA]
+
+  help_text:
+    brief: Use Google Cloud Natural Language API to identify sentiments in a text.
+    description: |
+      Sentiment Analysis inspects the given text and identifies the prevailing
+      emotional opinion within the text, especially to determine a writer's
+      attitude as positive, negative, or neutral.
+
+      {language_help}
+    language_help: !COMMON help_text.language_help_ga
+    examples: !COMMON help_text.language_examples.AS
+
+  request:
+    _COMMON_: request
+    method: analyzeSentiment
+
+  arguments:
+    params:
+    - _COMMON_: args.content_group
+    - _COMMON_: args.content
+    - _COMMON_: args.language
+    - _COMMON_: args.encoding
+
+  output:
+    format: json
+
+
+- release_tracks: [ALPHA, BETA]
+
+  help_text:
+    brief: Use Google Cloud Natural Language API to identify sentiments in a text.
+    description: |
+      Sentiment Analysis inspects the given text and identifies the prevailing
+      emotional opinion within the text, especially to determine a writer's
+      attitude as positive, negative, or neutral.
+
+      {language_help}
+    language_help: !COMMON help_text.language_help
+    examples: !COMMON help_text.language_examples.AS
+
+  request:
+    _COMMON_: request
+    api_version: v1beta2
+    method: analyzeSentiment
+
+  arguments:
+    params:
+    - _COMMON_: args.content_group
+    - _COMMON_: args.content
+    - _COMMON_: args.language
+    - _COMMON_: args.encoding
+
+  output:
+    format: json

gcloud auth application-default login/google-cloud-sdk/lib/surface/ml/language/analyze_syntax.yaml

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+- release_tracks: [GA]
+
+  help_text:
+    brief: Use Google Cloud Natural Language API to identify linguistic information.
+    description: |
+      Syntactic Analysis extracts linguistic information, breaking up the given
+      text into a series of sentences and tokens (generally, word boundaries),
+      providing further analysis on those tokens.
+
+      {language_help}
+    language_help: !COMMON help_text.language_help_ga
+    examples: !COMMON help_text.language_examples.ASX
+
+  request:
+    _COMMON_: request
+    method: analyzeSyntax
+
+  arguments:
+    params:
+    - _COMMON_: args.content_group
+    - _COMMON_: args.content
+    - _COMMON_: args.language
+    - _COMMON_: args.encoding
+
+  output:
+    format: json
+
+
+- release_tracks: [ALPHA, BETA]
+
+  help_text:
+    brief: Use Google Cloud Natural Language API to identify linguistic information.
+    description: |
+      Syntactic Analysis extracts linguistic information, breaking up the given
+      text into a series of sentences and tokens (generally, word boundaries),
+      providing further analysis on those tokens.
+
+      {language_help}
+    language_help: !COMMON help_text.language_help
+    examples: !COMMON help_text.language_examples.ASX
+
+  request:
+    _COMMON_: request
+    api_version: v1beta2
+    method: analyzeSyntax
+
+  arguments:
+    params:
+    - _COMMON_: args.content_group
+    - _COMMON_: args.content
+    - _COMMON_: args.language
+    - _COMMON_: args.encoding
+
+  output:
+    format: json

gcloud auth application-default login/google-cloud-sdk/lib/surface/ml/language/classify_text.yaml

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+- release_tracks: [GA]
+
+  help_text:
+    brief: Classifies input document into categories.
+    description: |
+      Classifies input document into categories. Returns a list of categories
+      representing the document. Only the most relevant categories a document
+      are returned e.g. if  `/Science` and `/Science/Astronomy` both apply to a
+      document, then only the `/Science/Astronomy` category is returned, as it
+      is the more specific result.
+
+      Currently only English is supported for this feature.
+    examples: !COMMON help_text.language_examples.CT
+
+  request:
+    _COMMON_: request
+    api_version: v1
+    method: classifyText
+
+  arguments:
+    params:
+    - _COMMON_: args.content_group
+    - _COMMON_: args.content
+    - _COMMON_: args.language
+
+  output:
+    format: json
+
+- release_tracks: [ALPHA, BETA]
+
+  help_text:
+    brief: Classifies input document into categories.
+    description: |
+      Classifies input document into categories. Returns a list of categories
+      representing the document. Only the most relevant categories a document
+      are returned e.g. if  `/Science` and `/Science/Astronomy` both apply to a
+      document, then only the `/Science/Astronomy` category is returned, as it
+      is the more specific result.
+
+      Currently only English is supported for this feature.
+    examples: !COMMON help_text.language_examples.CT
+
+  request:
+    _COMMON_: request
+    api_version: v1beta2
+    method: classifyText
+
+  arguments:
+    params:
+    - _COMMON_: args.content_group
+    - _COMMON_: args.content
+    - _COMMON_: args.language
+
+  output:
+    format: json