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‎.editorconfig‎

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‎CHANGELOG.md‎

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Change Log
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==========
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## Version 0.14.0
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_2017-07-xx_
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* New: Abstracted `Natural Language Understanding` service.
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## Version 0.13.0
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_2017-01-25_
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‎Config.json.enc‎

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‎Examples/ServiceExamples/Scripts/ExampleNaturalLanguageUnderstandingV1.cs‎

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/**
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* Copyright 2015 IBM Corp. All Rights Reserved.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*
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*/
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using FullSerializer;
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using IBM.Watson.DeveloperCloud.Logging;
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using IBM.Watson.DeveloperCloud.Services.NaturalLanguageUnderstanding.v1;
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using UnityEngine;
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public class ExampleNaturalLanguageUnderstandingV1 : MonoBehaviour
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{
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NaturalLanguageUnderstanding m_NaturalLanguageUnderstanding = new NaturalLanguageUnderstanding();
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private static fsSerializer sm_Serializer = new fsSerializer();
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void Start ()
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{
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LogSystem.InstallDefaultReactors();
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Log.Debug("ExampleNaturalLanguageUnderstandingV1", "attempting to get models...");
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if (!m_NaturalLanguageUnderstanding.GetModels(OnGetModels))
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Log.Debug("ExampleNaturalLanguageUnderstandingV1", "Failed to get models.");
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Parameters parameters = new Parameters()
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{
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text = "Analyze various features of text content at scale. Provide text, raw HTML, or a public URL, and IBM Watson Natural Language Understanding will give you results for the features you request. The service cleans HTML content before analysis by default, so the results can ignore most advertisements and other unwanted content.",
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return_analyzed_text = true,
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language = "en",
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features = new Features()
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{
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entities = new EntitiesOptions()
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{
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limit = 50,
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sentiment = true,
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emotion = true,
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},
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keywords = new KeywordsOptions()
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{
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limit = 50,
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sentiment = true,
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emotion = true
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}
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}
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};
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Log.Debug("ExampleNaturalLanguageUnderstandingV1", "attempting to analyze...");
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if (!m_NaturalLanguageUnderstanding.Analyze(OnAnalyze, parameters))
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Log.Debug("ExampleNaturalLanguageUnderstandingV1", "Failed to get models.");
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}
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private void OnGetModels(ListModelsResults resp, string customData)
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{
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fsData data = null;
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sm_Serializer.TrySerialize(resp, out data).AssertSuccess();
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Log.Debug("ExampleNaturalLanguageUnderstandingV1", "ListModelsResult: {0}", data.ToString());
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}
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private void OnAnalyze(AnalysisResults resp, string customData)
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{
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fsData data = null;
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sm_Serializer.TrySerialize(resp, out data).AssertSuccess();
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Log.Debug("ExampleNaturalLanguageUnderstandingV1", "AnalysisResults: {0}", data.ToString());
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}
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}

‎Examples/ServiceExamples/Scripts/ExampleNaturalLanguageUnderstandingV1.cs.meta‎

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‎Examples/ServiceExamples/ServiceExamples.unity‎

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‎README.md‎

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* [AlchemyData News](#alchemy-data-news)
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* [Retrieve and Rank](#retrieve-and-rank)
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* [Discovery](#discovery)
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* [Natural Language Understanding](#natural-language-understanding)
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* [Developing a basic application in one minute](#developing-a-basic-application-in-one-minute)
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* [Documentation](#documentation)
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* [License](#license)
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Log.Debug("ExampleDiscoveryV1", "resp is null, {0}", data);
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}
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```
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### Natural Language Understanding
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[Natural Language Understanding][natural_language_understanding] uses natural language processing to analyze semantic features of any text. Provide plain text, HTML, or a public URL, and Natural Language Understanding returns results for the features you specify. The service cleans HTML before analysis by default, which removes most advertisements and other unwanted content.
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You can create [custom models][nlu_models] with Watson Knowledge Studio that can be used to detect custom [entities][nlu_entities] and [relations][nlu_relations] in Natural Language Understanding.
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#### Analyze
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Analyze features of natural language content.
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```cs
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NaturalLanguageUnderstanding m_NaturalLanguageUnderstanding = new NaturalLanguageUnderstanding();
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private static fsSerializer sm_Serializer = new fsSerializer();
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void Start ()
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{
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Parameters parameters = new Parameters()
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{
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text = <text-to-analyze>,
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return_analyzed_text = true,
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language = "en",
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features = new Features()
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{
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entities = new EntitiesOptions()
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{
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limit = 50,
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sentiment = true,
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emotion = true,
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},
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keywords = new KeywordsOptions()
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{
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limit = 50,
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sentiment = true,
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emotion = true
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}
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}
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};
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if (!m_NaturalLanguageUnderstanding.Analyze(OnAnalyze, parameters))
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Log.Debug("ExampleNaturalLanguageUnderstandingV1", "Failed to get models.");
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}
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private void OnAnalyze(AnalysisResults resp, string customData)
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{
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fsData data = null;
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sm_Serializer.TrySerialize(resp, out data).AssertSuccess();
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Log.Debug("ExampleNaturalLanguageUnderstandingV1", "AnalysisResults: {0}", data.ToString());
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}
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```
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#### Get models
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List available custom models.
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```cs
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NaturalLanguageUnderstanding m_NaturalLanguageUnderstanding = new NaturalLanguageUnderstanding();
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private static fsSerializer sm_Serializer = new fsSerializer();
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void Start ()
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{
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if (!m_NaturalLanguageUnderstanding.GetModels(OnGetModels))
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Log.Debug("ExampleNaturalLanguageUnderstandingV1", "Failed to get models.");
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}
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private void OnGetModels(ListModelsResults resp, string customData)
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{
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fsData data = null;
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sm_Serializer.TrySerialize(resp, out data).AssertSuccess();
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Log.Debug("ExampleNaturalLanguageUnderstandingV1", "ListModelsResult: {0}", data.ToString());
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}
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```
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#### Delete model
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Delete a custom model.
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```cs
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NaturalLanguageUnderstanding m_NaturalLanguageUnderstanding = new NaturalLanguageUnderstanding();
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private static fsSerializer sm_Serializer = new fsSerializer();
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void Start ()
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{
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if (!m_NaturalLanguageUnderstanding.DeleteModel(OnDeleteModel, <model-id>))
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Log.Debug("ExampleNaturalLanguageUnderstandingV1", "Failed to delete model.");
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}
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private void OnDeleteModel(bool success, string customData)
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{
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Log.Debug("ExampleNaturalLanguageUnderstandingV1", "DeleteModelResult: {0}", success);
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}
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```
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## Developing a basic application in one minute
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You can quickly develop a basic application that uses the Speech to Text service and the Natural Language Classifier service by using the prefabs that come with the SDK. Ensure that you prepare the test data before you complete the the following steps:
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[expressive_ssml]: http://www.ibm.com/watson/developercloud/doc/text-to-speech/http.shtml#expressive
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[ssml]: http://www.ibm.com/watson/developercloud/doc/text-to-speech/SSML.shtml
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[discovery-query]: http://www.ibm.com/watson/developercloud/doc/discovery/using.shtml
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[natural_language_understanding]: https://www.ibm.com/watson/developercloud/natural-language-understanding.html
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[nlu_models]: https://www.ibm.com/watson/developercloud/doc/natural-language-understanding/customizing.html
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[nlu_entities]: https://www.ibm.com/watson/developercloud/natural-language-understanding/api/v1/#entities
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[nlu_relations]: https://www.ibm.com/watson/developercloud/natural-language-understanding/api/v1/#relations
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[dialog_service]: http://www.ibm.com/watson/developercloud/doc/dialog/
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[dialog_migration]: https://www.ibm.com/watson/developercloud/doc/conversation/migration.shtml

‎Scripts/Services/Discovery/v1/DataModels.cs‎

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/// <summary>
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/// Number of bytes used on the environment's disk capacity.
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/// </summary>
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public uint used_bytes { get; set; }
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public long used_bytes { get; set; }
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/// <summary>
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/// Total number of bytes available in the environment's disk capacity.
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/// </summary>
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public uint total_bytes { get; set; }
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public long total_bytes { get; set; }
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/// <summary>
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/// Amount of disk capacity used, in KB or GB format.
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/// </summary>
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/// <summary>
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/// Number of bytes used in the environment's memory capacity.
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/// </summary>
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public uint used_bytes { get; set; }
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public long used_bytes { get; set; }
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/// <summary>
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/// Total number of bytes available in the environment's memory capacity.
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/// </summary>
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public uint total_bytes { get; set; }
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public long total_bytes { get; set; }
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/// <summary>
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/// Amount of memory capacity used, in KB or GB format.
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/// </summary>

‎Scripts/Services/NaturalLanguageUnderstanding.meta‎

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