Uri endpoint = new Uri("{endpoint}");
AzureKeyCredential credential = new AzureKeyCredential("{api-key}");
TextAnalyticsClient client = new(endpoint, credential);

Uri endpoint = new Uri("{endpoint}");
AzureKeyCredential credential = new AzureKeyCredential("{api-key}");
TextAnalysisClientOptions options = new TextAnalysisClientOptions(TextAnalysisClientOptions.ServiceVersion.V2023_04_01);
var client = new TextAnalysisClient(endpoint, credential, options);

string documentA =
    "Este documento está escrito en un lenguaje diferente al inglés. Su objectivo es demostrar cómo"
    + " invocar el método de detección de lenguaje del servicio de Text Analytics en Microsoft Azure."
    + " También muestra cómo acceder a la información retornada por el servicio. Esta funcionalidad es"
    + " útil para las aplicaciones que recopilan texto arbitrario donde el lenguaje no se conoce de"
    + " antemano. Puede usarse para detectar una amplia gama de lenguajes, variantes, dialectos y"
    + " algunos idiomas regionales o culturales.";

string documentB =
    "This document is written in English. Its objective is to demonstrate how to call the language"
    + " detection method of the Text Analytics service in Microsoft Azure. It also shows how to access the"
    + " information returned by the service. This functionality is useful for applications that collect"
    + " arbitrary text where the language is not known beforehand. It can be used to detect a wide range"
    + " of languages, variants, dialects, and some regional or cultural languages.";

string documentC =
    "Ce document est rédigé dans une langue autre que l'anglais. Son objectif est de montrer comment"
    + " appeler la méthode de détection de langue du service Text Analytics dans Microsoft Azure. Il"
    + " montre également comment accéder aux informations renvoyées par le service. Cette fonctionnalité"
    + " est utile pour les applications qui collectent du texte arbitraire dont la langue n'est pas connue"
    + " à l'avance. Il peut être utilisé pour détecter un large éventail de langues, de variantes, de"
    + " dialectes et certaines langues régionales ou culturelles.";

string documentD = string.Empty;

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
List<string> batchedDocuments = new()
{
    documentA,
    documentB,
    documentC,
    documentD
};

Response<DetectLanguageResultCollection> response = await client.DetectLanguageBatchAsync(batchedDocuments);
DetectLanguageResultCollection documentsLanguage = response.Value;

int i = 0;
Console.WriteLine($"Detect Language, model version: \"{documentsLanguage.ModelVersion}\"");
Console.WriteLine();

foreach (DetectLanguageResult documentResult in documentsLanguage)
{
    Console.WriteLine($"Result for document with Text = \"{batchedDocuments[i++]}\"");

    if (documentResult.HasError)
    {
        Console.WriteLine($"  Error!");
        Console.WriteLine($"  Document error code: {documentResult.Error.ErrorCode}");
        Console.WriteLine($"  Message: {documentResult.Error.Message}");
        Console.WriteLine();
        continue;
    }

    Console.WriteLine($"  Detected language: {documentResult.PrimaryLanguage.Name}");
    Console.WriteLine($"  Confidence score: {documentResult.PrimaryLanguage.ConfidenceScore}");
    Console.WriteLine();
}

string textA =
    "Este documento está escrito en un lenguaje diferente al inglés. Su objectivo es demostrar cómo"
    + " invocar el método de detección de lenguaje del servicio de Text Analytics en Microsoft Azure."
    + " También muestra cómo acceder a la información retornada por el servicio. Esta funcionalidad es"
    + " útil para las aplicaciones que recopilan texto arbitrario donde el lenguaje no se conoce de"
    + " antemano. Puede usarse para detectar una amplia gama de lenguajes, variantes, dialectos y"
    + " algunos idiomas regionales o culturales.";

string textB =
    "This document is written in English. Its objective is to demonstrate how to call the language"
    + " detection method of the Text Analytics service in Microsoft Azure. It also shows how to access the"
    + " information returned by the service. This functionality is useful for applications that collect"
    + " arbitrary text where the language is not known beforehand. It can be used to detect a wide range"
    + " of languages, variants, dialects, and some regional or cultural languages.";

string textC =
    "Ce document est rédigé dans une langue autre que l'anglais. Son objectif est de montrer comment"
    + " appeler la méthode de détection de langue du service Text Analytics dans Microsoft Azure. Il"
    + " montre également comment accéder aux informations renvoyées par le service. Cette fonctionnalité"
    + " est utile pour les applications qui collectent du texte arbitraire dont la langue n'est pas connue"
    + " à l'avance. Il peut être utilisé pour détecter un large éventail de langues, de variantes, de"
    + " dialectes et certaines langues régionales ou culturelles.";

try
{
    AnalyzeTextInput body = new TextLanguageDetectionInput()
    {
        TextInput = new LanguageDetectionTextInput()
        {
            LanguageInputs =
            {
                new LanguageInput("A", textA),
                new LanguageInput("B", textB),
                new LanguageInput("C", textC),
            }
        }
    };

    Response<AnalyzeTextResult> response = await client.AnalyzeTextAsync(body);
    AnalyzeTextLanguageDetectionResult AnalyzeTextLanguageDetectionResult = (AnalyzeTextLanguageDetectionResult)response.Value;

    foreach (LanguageDetectionDocumentResult document in AnalyzeTextLanguageDetectionResult.Results.Documents)
    {
        Console.WriteLine($"Result for document with Id = \"{document.Id}\":");
        Console.WriteLine($"    Name: {document.DetectedLanguage.Name}");
        Console.WriteLine($"    Iso6391Name: {document.DetectedLanguage.Iso6391Name}");
        if (document.DetectedLanguage.ScriptName != null)
        {
            Console.WriteLine($"    ScriptName: {document.DetectedLanguage.ScriptName}");
            Console.WriteLine($"    ScriptIso15924Code: {document.DetectedLanguage.ScriptIso15924Code}");
        }
        Console.WriteLine($"    ConfidenceScore: {document.DetectedLanguage.ConfidenceScore}");
    }
}
catch (RequestFailedException exception)
{
    Console.WriteLine($"Error DocumentWarningCode: {exception.ErrorCode}");
    Console.WriteLine($"Message: {exception.Message}");
}

string documentA =
    "The food and service were unacceptable, but the concierge were nice. After talking to them about the"
    + " quality of the food and the process to get room service they refunded the money we spent at the"
    + " restaurant and gave us a voucher for nearby restaurants.";

string documentB =
    "Nice rooms! I had a great unobstructed view of the Microsoft campus but bathrooms were old and the"
    + " toilet was dirty when we arrived. It was close to bus stops and groceries stores. If you want to"
    + " be close to campus I will recommend it, otherwise, might be better to stay in a cleaner one";

string documentC =
    "The rooms were beautiful. The AC was good and quiet, which was key for us as outside it was 100F and"
    + " our baby was getting uncomfortable because of the heat. The breakfast was good too with good"
    + " options and good servicing times. The thing we didn't like was that the toilet in our bathroom was"
    + " smelly. It could have been that the toilet was not cleaned before we arrived.";

string documentD = string.Empty;

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
List<string> batchedDocuments = new()
{
    documentA,
    documentB,
    documentC,
    documentD
};

Response<AnalyzeSentimentResultCollection> response = await client.AnalyzeSentimentBatchAsync(batchedDocuments);
AnalyzeSentimentResultCollection sentimentPerDocuments = response.Value;

int i = 0;
Console.WriteLine($"Analyze Sentiment, model version: \"{sentimentPerDocuments.ModelVersion}\"");
Console.WriteLine();

foreach (AnalyzeSentimentResult documentResult in sentimentPerDocuments)
{
    Console.WriteLine($"Result for document with Text = \"{batchedDocuments[i++]}\"");

    if (documentResult.HasError)
    {
        Console.WriteLine($"  Error!");
        Console.WriteLine($"  Document error code: {documentResult.Error.ErrorCode}");
        Console.WriteLine($"  Message: {documentResult.Error.Message}");
        Console.WriteLine();
        continue;
    }

    Console.WriteLine($"  Document sentiment is {documentResult.DocumentSentiment.Sentiment} with: ");
    Console.WriteLine($"    Positive confidence score: {documentResult.DocumentSentiment.ConfidenceScores.Positive}");
    Console.WriteLine($"    Neutral confidence score: {documentResult.DocumentSentiment.ConfidenceScores.Neutral}");
    Console.WriteLine($"    Negative confidence score: {documentResult.DocumentSentiment.ConfidenceScores.Negative}");
    Console.WriteLine();
    Console.WriteLine($"  Sentence sentiment results:");

    foreach (SentenceSentiment sentimentInSentence in documentResult.DocumentSentiment.Sentences)
    {
        Console.WriteLine($"  * For sentence: \"{sentimentInSentence.Text}\"");
        Console.WriteLine($"    Sentiment is {sentimentInSentence.Sentiment} with: ");
        Console.WriteLine($"      Positive confidence score: {sentimentInSentence.ConfidenceScores.Positive}");
        Console.WriteLine($"      Neutral confidence score: {sentimentInSentence.ConfidenceScores.Neutral}");
        Console.WriteLine($"      Negative confidence score: {sentimentInSentence.ConfidenceScores.Negative}");
        Console.WriteLine();
    }
}

string textA =
    "The food and service were unacceptable, but the concierge were nice. After talking to them about the"
    + " quality of the food and the process to get room service they refunded the money we spent at the"
    + " restaurant and gave us a voucher for nearby restaurants.";

string textB =
    "Nos hospedamos en el Hotel Foo la semana pasada por nuestro aniversario. La gerencia sab�a de nuestra"
    + " celebraci�n y me ayudaron a tenerle una sorpresa a mi pareja. La habitaci�n estaba limpia y"
    + " decorada como yo hab�a pedido. Una gran experiencia. El pr�ximo a�o volveremos.";

string textC =
    "The rooms were beautiful. The AC was good and quiet, which was key for us as outside it was 100F and"
    + " our baby was getting uncomfortable because of the heat. The breakfast was good too with good"
    + " options and good servicing times. The thing we didn't like was that the toilet in our bathroom was"
    + " smelly. It could have been that the toilet was not cleaned before we arrived.";

try
{
    AnalyzeTextInput body = new TextSentimentAnalysisInput()
    {
        TextInput = new MultiLanguageTextInput()
        {
            MultiLanguageInputs =
            {
                new MultiLanguageInput("A", textA) { Language = "en" },
                new MultiLanguageInput("B", textB) { Language = "es" },
                new MultiLanguageInput("C", textC) { Language = "en" },
            }
        }
    };

    Response<AnalyzeTextResult> response = await client.AnalyzeTextAsync(body);
    AnalyzeTextSentimentResult AnalyzeTextSentimentResult = (AnalyzeTextSentimentResult)response.Value;

    foreach (SentimentActionResult sentimentResponseWithDocumentDetectedLanguage in AnalyzeTextSentimentResult.Results.Documents)
    {
        Console.WriteLine($"Document {sentimentResponseWithDocumentDetectedLanguage.Id} sentiment is {sentimentResponseWithDocumentDetectedLanguage.Sentiment} with: ");
        Console.WriteLine($"  Positive confidence score: {sentimentResponseWithDocumentDetectedLanguage.ConfidenceScores.Positive}");
        Console.WriteLine($"  Neutral confidence score: {sentimentResponseWithDocumentDetectedLanguage.ConfidenceScores.Neutral}");
        Console.WriteLine($"  Negative confidence score: {sentimentResponseWithDocumentDetectedLanguage.ConfidenceScores.Negative}");
    }

    foreach (DocumentError analyzeTextDocumentError in AnalyzeTextSentimentResult.Results.Errors)
    {
        Console.WriteLine($"  Error on document {analyzeTextDocumentError.Id}!");
        Console.WriteLine($"  Document error code: {analyzeTextDocumentError.Error.Code}");
        Console.WriteLine($"  Message: {analyzeTextDocumentError.Error.Message}");
        Console.WriteLine();
        continue;
    }
}
catch (RequestFailedException exception)
{
    Console.WriteLine($"Error DocumentWarningCode: {exception.ErrorCode}");
    Console.WriteLine($"Message: {exception.Message}");
}

string documentA =
    "We love this trail and make the trip every year. The views are breathtaking and well worth the hike!"
    + " Yesterday was foggy though, so we missed the spectacular views. We tried again today and it was"
    + " amazing. Everyone in my family liked the trail although it was too challenging for the less"
    + " athletic among us. Not necessarily recommended for small children. A hotel close to the trail"
    + " offers services for childcare in case you want that.";

string documentB =
    "Last week we stayed at Hotel Foo to celebrate our anniversary. The staff knew about our anniversary"
    + " so they helped me organize a little surprise for my partner. The room was clean and with the"
    + " decoration I requested. It was perfect!";

string documentC =
    "That was the best day of my life! We went on a 4 day trip where we stayed at Hotel Foo. They had"
    + " great amenities that included an indoor pool, a spa, and a bar. The spa offered couples massages"
    + " which were really good. The spa was clean and felt very peaceful. Overall the whole experience was"
    + " great. We will definitely come back.";

string documentD = string.Empty;

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
List<string> batchedDocuments = new()
{
    documentA,
    documentB,
    documentC,
    documentD
};

Response<ExtractKeyPhrasesResultCollection> response = await client.ExtractKeyPhrasesBatchAsync(batchedDocuments);
ExtractKeyPhrasesResultCollection keyPhrasesInDocuments = response.Value;

int i = 0;
Console.WriteLine($"Extract Key Phrases, model version: \"{keyPhrasesInDocuments.ModelVersion}\"");
Console.WriteLine();

foreach (ExtractKeyPhrasesResult documentResult in keyPhrasesInDocuments)
{
    Console.WriteLine($"Result for document with Text = \"{batchedDocuments[i++]}\"");

    if (documentResult.HasError)
    {
        Console.WriteLine($"  Error!");
        Console.WriteLine($"  Document error code: {documentResult.Error.ErrorCode}");
        Console.WriteLine($"  Message: {documentResult.Error.Message}");
        Console.WriteLine();
        continue;
    }

    Console.WriteLine($"  Extracted {documentResult.KeyPhrases.Count()} key phrases:");

    foreach (string keyPhrase in documentResult.KeyPhrases)
    {
        Console.WriteLine($"    {keyPhrase}");
    }
    Console.WriteLine();
}

string textA =
    "We love this trail and make the trip every year. The views are breathtaking and well worth the hike!"
    + " Yesterday was foggy though, so we missed the spectacular views. We tried again today and it was"
    + " amazing. Everyone in my family liked the trail although it was too challenging for the less"
    + " athletic among us. Not necessarily recommended for small children. A hotel close to the trail"
    + " offers services for childcare in case you want that.";

string textB =
"Nos hospedamos en el Hotel Foo la semana pasada por nuestro aniversario. La gerencia sabía de nuestra"
    + " celebración y me ayudaron a tenerle una sorpresa a mi pareja. La habitación estaba limpia y"
    + " decorada como yo había pedido. Una gran experiencia. El próximo año volveremos.";

string textC =
    "That was the best day of my life! We went on a 4 day trip where we stayed at Hotel Foo. They had"
    + " great amenities that included an indoor pool, a spa, and a bar. The spa offered couples massages"
    + " which were really good. The spa was clean and felt very peaceful. Overall the whole experience was"
    + " great. We will definitely come back.";

string textD = string.Empty;

AnalyzeTextInput body = new TextKeyPhraseExtractionInput()
{
    TextInput = new MultiLanguageTextInput()
    {
        MultiLanguageInputs =
        {
            new MultiLanguageInput("A", textA) { Language = "en" },
            new MultiLanguageInput("B", textB) { Language = "es" },
            new MultiLanguageInput("C", textC) { Language = "en" },
            new MultiLanguageInput("D", textD),
        }
    },
    ActionContent = new KeyPhraseActionContent()
    {
        ModelVersion = "latest",
    }
};

Response<AnalyzeTextResult> response = await client.AnalyzeTextAsync(body);
AnalyzeTextKeyPhraseResult keyPhraseTaskResult = (AnalyzeTextKeyPhraseResult)response.Value;

foreach (KeyPhrasesActionResult kpeResult in keyPhraseTaskResult.Results.Documents)
{
    Console.WriteLine($"Result for document with Id = \"{kpeResult.Id}\":");
    foreach (string keyPhrase in kpeResult.KeyPhrases)
    {
        Console.WriteLine($"    {keyPhrase}");
    }
    Console.WriteLine();
}

foreach (DocumentError analyzeTextDocumentError in keyPhraseTaskResult.Results.Errors)
{
    Console.WriteLine($"  Error on document {analyzeTextDocumentError.Id}!");
    Console.WriteLine($"  Document error code: {analyzeTextDocumentError.Error.Code}");
    Console.WriteLine($"  Message: {analyzeTextDocumentError.Error.Message}");
    Console.WriteLine();
    continue;
}

string documentA =
    "We love this trail and make the trip every year. The views are breathtaking and well worth the hike!"
    + " Yesterday was foggy though, so we missed the spectacular views. We tried again today and it was"
    + " amazing. Everyone in my family liked the trail although it was too challenging for the less"
    + " athletic among us. Not necessarily recommended for small children. A hotel close to the trail"
    + " offers services for childcare in case you want that.";

string documentB =
    "Nos hospedamos en el Hotel Foo la semana pasada por nuestro aniversario. La gerencia sabía de nuestra"
    + " celebración y me ayudaron a tenerle una sorpresa a mi pareja. La habitación estaba limpia y"
    + " decorada como yo había pedido. Una gran experiencia. El próximo año volveremos.";

string documentC =
    "That was the best day of my life! We went on a 4 day trip where we stayed at Hotel Foo. They had"
    + " great amenities that included an indoor pool, a spa, and a bar. The spa offered couples massages"
    + " which were really good. The spa was clean and felt very peaceful. Overall the whole experience was"
    + " great. We will definitely come back.";

string documentD = string.Empty;

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
List<string> batchedDocuments = new()
{
    documentA,
    documentB,
    documentC,
    documentD
};

Response<RecognizeEntitiesResultCollection> response = await client.RecognizeEntitiesBatchAsync(batchedDocuments);
RecognizeEntitiesResultCollection entititesPerDocuments = response.Value;

int i = 0;
Console.WriteLine($"Recognize Entities, model version: \"{entititesPerDocuments.ModelVersion}\"");
Console.WriteLine();

foreach (RecognizeEntitiesResult documentResult in entititesPerDocuments)
{
    Console.WriteLine($"Result for document with Text = \"{batchedDocuments[i++]}\"");

    if (documentResult.HasError)
    {
        Console.WriteLine($"  Error!");
        Console.WriteLine($"  Document error code: {documentResult.Error.ErrorCode}");
        Console.WriteLine($"  Message: {documentResult.Error.Message}");
        Console.WriteLine();
        continue;
    }

    Console.WriteLine($"  Recognized {documentResult.Entities.Count} entities:");

    foreach (CategorizedEntity entity in documentResult.Entities)
    {
        Console.WriteLine($"    Text: {entity.Text}");
        Console.WriteLine($"    Offset: {entity.Offset}");
        Console.WriteLine($"    Length: {entity.Length}");
        Console.WriteLine($"    Category: {entity.Category}");
        if (!string.IsNullOrEmpty(entity.SubCategory))
            Console.WriteLine($"    SubCategory: {entity.SubCategory}");
        Console.WriteLine($"    Confidence score: {entity.ConfidenceScore}");
        Console.WriteLine();
    }
    Console.WriteLine();
}

string textA =
    "We love this trail and make the trip every year. The views are breathtaking and well worth the hike!"
    + " Yesterday was foggy though, so we missed the spectacular views. We tried again today and it was"
    + " amazing. Everyone in my family liked the trail although it was too challenging for the less"
    + " athletic among us. Not necessarily recommended for small children. A hotel close to the trail"
    + " offers services for childcare in case you want that.";

string textB =
    "Nos hospedamos en el Hotel Foo la semana pasada por nuestro aniversario. La gerencia sabía de nuestra"
    + " celebración y me ayudaron a tenerle una sorpresa a mi pareja. La habitación estaba limpia y"
    + " decorada como yo había pedido. Una gran experiencia. El próximo año volveremos.";

string textC =
    "That was the best day of my life! We went on a 4 day trip where we stayed at Hotel Foo. They had"
    + " great amenities that included an indoor pool, a spa, and a bar. The spa offered couples massages"
    + " which were really good. The spa was clean and felt very peaceful. Overall the whole experience was"
    + " great. We will definitely come back.";

string textD = string.Empty;

AnalyzeTextInput body = new TextEntityRecognitionInput()
{
    TextInput = new MultiLanguageTextInput()
    {
        MultiLanguageInputs =
        {
            new MultiLanguageInput("A", textA) { Language = "en" },
            new MultiLanguageInput("B", textB) { Language = "es" },
            new MultiLanguageInput("C", textC) { Language = "en" },
            new MultiLanguageInput("D", textD),
        }
    },
    ActionContent = new EntitiesActionContent()
    {
        ModelVersion = "latest",
    }
};

Response<AnalyzeTextResult> response = await client.AnalyzeTextAsync(body);
AnalyzeTextEntitiesResult entitiesTaskResult = (AnalyzeTextEntitiesResult)response.Value;

foreach (EntityActionResult nerResult in entitiesTaskResult.Results.Documents)
{
    Console.WriteLine($"Result for document with Id = \"{nerResult.Id}\":");

    Console.WriteLine($"  Recognized {nerResult.Entities.Count} entities:");

    foreach (NamedEntityWithMetadata entity in nerResult.Entities)
    {
        Console.WriteLine($"    Text: {entity.Text}");
        Console.WriteLine($"    Offset: {entity.Offset}");
        Console.WriteLine($"    Length: {entity.Length}");
        Console.WriteLine($"    Category: {entity.Category}");
        Console.WriteLine($"    Type: {entity.Type}");
        Console.WriteLine($"    Tags:");
        foreach (EntityTag tag in entity.Tags)
        {
            Console.WriteLine($"            TagName: {tag.Name}");
            Console.WriteLine($"            TagConfidenceScore: {tag.ConfidenceScore}");
        }
        Console.WriteLine($"    Confidence score: {entity.ConfidenceScore}");
        Console.WriteLine();
    }
    Console.WriteLine();
}

foreach (DocumentError analyzeTextDocumentError in entitiesTaskResult.Results.Errors)
{
    Console.WriteLine($"  Error on document {analyzeTextDocumentError.Id}!");
    Console.WriteLine($"  Document error code: {analyzeTextDocumentError.Error.Code}");
    Console.WriteLine($"  Message: {analyzeTextDocumentError.Error.Message}");
    Console.WriteLine();
    continue;
}

string documentA =
    "Parker Doe has repaid all of their loans as of 2020-04-25. Their SSN is 859-98-0987. To contact them,"
    + " use their phone number 800-102-1100. They are originally from Brazil and have document ID number"
    + " 998.214.865-68.";

string documentB =
    "Yesterday, Dan Doe was asking where they could find the ABA number. I explained that it is the first"
    + " 9 digits in the lower left hand corner of their personal check. After looking at their account"
    + " they confirmed the number was 111000025.";

string documentC = string.Empty;

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
List<string> batchedDocuments = new()
{
    documentA,
    documentB,
    documentC
};

Response<RecognizePiiEntitiesResultCollection> response = await client.RecognizePiiEntitiesBatchAsync(batchedDocuments);
RecognizePiiEntitiesResultCollection entititesPerDocuments = response.Value;

int i = 0;
Console.WriteLine($"Recognize PII Entities, model version: \"{entititesPerDocuments.ModelVersion}\"");
Console.WriteLine();

foreach (RecognizePiiEntitiesResult documentResult in entititesPerDocuments)
{
    Console.WriteLine($"Result for document with Text = \"{batchedDocuments[i++]}\"");

    if (documentResult.HasError)
    {
        Console.WriteLine($"  Error!");
        Console.WriteLine($"  Document error code: {documentResult.Error.ErrorCode}");
        Console.WriteLine($"  Message: {documentResult.Error.Message}");
        Console.WriteLine();
        continue;
    }

    Console.WriteLine($"  Redacted Text: {documentResult.Entities.RedactedText}");
    Console.WriteLine();
    Console.WriteLine($"  Recognized {documentResult.Entities.Count} PII entities:");
    foreach (PiiEntity piiEntity in documentResult.Entities)
    {
        Console.WriteLine($"    Text: {piiEntity.Text}");
        Console.WriteLine($"    Category: {piiEntity.Category}");
        if (!string.IsNullOrEmpty(piiEntity.SubCategory))
            Console.WriteLine($"    SubCategory: {piiEntity.SubCategory}");
        Console.WriteLine($"    Confidence score: {piiEntity.ConfidenceScore}");
        Console.WriteLine();
    }
    Console.WriteLine();
}

string textA =
    "Parker Doe has repaid all of their loans as of 2020-04-25. Their SSN is 859-98-0987. To contact them,"
    + " use their phone number 800-102-1100. They are originally from Brazil and have document ID number"
    + " 998.214.865-68.";

string textB =
    "Yesterday, Dan Doe was asking where they could find the ABA number. I explained that it is the first"
    + " 9 digits in the lower left hand corner of their personal check. After looking at their account"
    + " they confirmed the number was 111000025.";

string textC = string.Empty;

AnalyzeTextInput body = new TextPiiEntitiesRecognitionInput()
{
    TextInput = new MultiLanguageTextInput()
    {
        MultiLanguageInputs =
        {
            new MultiLanguageInput("A", textA) { Language = "en" },
            new MultiLanguageInput("B", textB) { Language = "es" },
            new MultiLanguageInput("C", textC),
        }
    },
    ActionContent = new PiiActionContent()
    {
        ModelVersion = "latest",
    }
};

Response<AnalyzeTextResult> response = await client.AnalyzeTextAsync(body);
AnalyzeTextPiiResult piiTaskResult = (AnalyzeTextPiiResult)response.Value;

foreach (PiiResultWithDetectedLanguage piiResult in piiTaskResult.Results.Documents)
{
    Console.WriteLine($"Result for document with Id = \"{piiResult.Id}\":");
    Console.WriteLine($"  Redacted Text: \"{piiResult.RedactedText}\":");
    Console.WriteLine($"  Recognized {piiResult.Entities.Count} entities:");

    foreach (PiiEntity entity in piiResult.Entities)
    {
        Console.WriteLine($"    Text: {entity.Text}");
        Console.WriteLine($"    Offset: {entity.Offset}");
        Console.WriteLine($"    Length: {entity.Length}");
        Console.WriteLine($"    Category: {entity.Category}");
        if (!string.IsNullOrEmpty(entity.Subcategory))
            Console.WriteLine($"    SubCategory: {entity.Subcategory}");
        Console.WriteLine($"    Confidence score: {entity.ConfidenceScore}");
        Console.WriteLine();
    }
    Console.WriteLine();
}

foreach (DocumentError analyzeTextDocumentError in piiTaskResult.Results.Errors)
{
    Console.WriteLine($"  Error on document {analyzeTextDocumentError.Id}!");
    Console.WriteLine($"  Document error code: {analyzeTextDocumentError.Error.Code}");
    Console.WriteLine($"  Message: {analyzeTextDocumentError.Error.Message}");
    Console.WriteLine();
    continue;
}

string documentA =
    "Microsoft was founded by Bill Gates with some friends he met at Harvard. One of his friends, Steve"
    + " Ballmer, eventually became CEO after Bill Gates as well.Steve Ballmer eventually stepped down as"
    + " CEO of Microsoft, and was succeeded by Satya Nadella. Microsoft originally moved its headquarters"
    + " to Bellevue, Washington in Januaray 1979, but is now headquartered in Redmond";

string documentB =
    "Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975, to develop and sell BASIC"
    + " interpreters for the Altair 8800. During his career at Microsoft, Gates held the positions of"
    + " chairman chief executive officer, president and chief software architect while also being the"
    + " largest individual shareholder until May 2014.";

string documentC = string.Empty;

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
List<string> batchedDocuments = new()
{
    documentA,
    documentB,
    documentC
};

Response<RecognizeLinkedEntitiesResultCollection> response = await client.RecognizeLinkedEntitiesBatchAsync(batchedDocuments);
RecognizeLinkedEntitiesResultCollection entitiesInDocuments = response.Value;

int i = 0;
Console.WriteLine($"Recognize Linked Entities, model version: \"{entitiesInDocuments.ModelVersion}\"");
Console.WriteLine();

foreach (RecognizeLinkedEntitiesResult documentResult in entitiesInDocuments)
{
    Console.WriteLine($"Result for document with Text = \"{batchedDocuments[i++]}\"");

    if (documentResult.HasError)
    {
        Console.WriteLine($"  Error!");
        Console.WriteLine($"  Document error code: {documentResult.Error.ErrorCode}");
        Console.WriteLine($"  Message: {documentResult.Error.Message}");
        Console.WriteLine();
        continue;
    }

    Console.WriteLine($"Recognized {documentResult.Entities.Count} entities:");
    foreach (LinkedEntity linkedEntity in documentResult.Entities)
    {
        Console.WriteLine($"  Name: {linkedEntity.Name}");
        Console.WriteLine($"  Language: {linkedEntity.Language}");
        Console.WriteLine($"  Data Source: {linkedEntity.DataSource}");
        Console.WriteLine($"  URL: {linkedEntity.Url}");
        Console.WriteLine($"  Entity Id in Data Source: {linkedEntity.DataSourceEntityId}");
        foreach (LinkedEntityMatch match in linkedEntity.Matches)
        {
            Console.WriteLine($"    Match Text: {match.Text}");
            Console.WriteLine($"    Offset: {match.Offset}");
            Console.WriteLine($"    Length: {match.Length}");
            Console.WriteLine($"    Confidence score: {match.ConfidenceScore}");
        }
        Console.WriteLine();
    }
    Console.WriteLine();
}

string textA =
    "Microsoft was founded by Bill Gates with some friends he met at Harvard. One of his friends, Steve"
    + " Ballmer, eventually became CEO after Bill Gates as well.Steve Ballmer eventually stepped down as"
    + " CEO of Microsoft, and was succeeded by Satya Nadella. Microsoft originally moved its headquarters"
    + " to Bellevue, Washington in Januaray 1979, but is now headquartered in Redmond";

string textB =
    "Microsoft was founded by Bill Gates and Paul Allen on April 4, 1975, to develop and sell BASIC"
    + " interpreters for the Altair 8800. During his career at Microsoft, Gates held the positions of"
    + " chairman chief executive officer, president and chief software architect while also being the"
    + " largest individual shareholder until May 2014.";

string textC =
    "El CEO de Microsoft es Satya Nadella, quien asumió esta posición en Febrero de 2014. Él empezó como"
    + " Ingeniero de Software en el año 1992.";

string textD = string.Empty;

AnalyzeTextInput body = new TextEntityLinkingInput()
{
    TextInput = new MultiLanguageTextInput()
    {
        MultiLanguageInputs =
        {
            new MultiLanguageInput("A", textA) { Language = "en" },
            new MultiLanguageInput("B", textB) { Language = "en" },
            new MultiLanguageInput("C", textC) { Language = "es" },
            new MultiLanguageInput("D", textD),
        }
    },
    ActionContent = new EntityLinkingActionContent()
    {
        ModelVersion = "latest",
    }
};

Response<AnalyzeTextResult> response = await client.AnalyzeTextAsync(body);
AnalyzeTextEntityLinkingResult entityLinkingTaskResult = (AnalyzeTextEntityLinkingResult)response.Value;

foreach (EntityLinkingActionResult entityLinkingResult in entityLinkingTaskResult.Results.Documents)
{
    Console.WriteLine($"Result for document with Id = \"{entityLinkingResult.Id}\":");
    Console.WriteLine($"Recognized {entityLinkingResult.Entities.Count} entities:");
    foreach (LinkedEntity linkedEntity in entityLinkingResult.Entities)
    {
        Console.WriteLine($"  Name: {linkedEntity.Name}");
        Console.WriteLine($"  LanguageClient: {linkedEntity.Language}");
        Console.WriteLine($"  Data Source: {linkedEntity.DataSource}");
        Console.WriteLine($"  URL: {linkedEntity.Url}");
        Console.WriteLine($"  NamedEntity Id in Data Source: {linkedEntity.Id}");
        foreach (EntityLinkingMatch match in linkedEntity.Matches)
        {
            Console.WriteLine($"    EntityLinkingMatch Text: {match.Text}");
            Console.WriteLine($"    Offset: {match.Offset}");
            Console.WriteLine($"    Length: {match.Length}");
            Console.WriteLine($"    Confidence score: {match.ConfidenceScore}");
        }
    }
    Console.WriteLine();
}

foreach (DocumentError analyzeTextDocumentError in entityLinkingTaskResult.Results.Errors)
{
    Console.WriteLine($"  Error on document {analyzeTextDocumentError.Id}!");
    Console.WriteLine($"  Document error code: {analyzeTextDocumentError.Error.Code}");
    Console.WriteLine($"  Message: {analyzeTextDocumentError.Error.Message}");
    Console.WriteLine();
    continue;
}

string documentA =
    "RECORD #333582770390100 | MH | 85986313 | | 054351 | 2/14/2001 12:00:00 AM |"
    + " CORONARY ARTERY DISEASE | Signed | DIS |"
    + Environment.NewLine
    + " Admission Date: 5/22/2001 Report Status: Signed Discharge Date: 4/24/2001"
    + " ADMISSION DIAGNOSIS: CORONARY ARTERY DISEASE."
    + Environment.NewLine
    + " HISTORY OF PRESENT ILLNESS: The patient is a 54-year-old gentleman with a history of progressive"
    + " angina over the past several months. The patient had a cardiac catheterization in July of this"
    + " year revealing total occlusion of the RCA and 50% left main disease, with a strong family history"
    + " of coronary artery disease with a brother dying at the age of 52 from a myocardial infarction and"
    + " another brother who is status post coronary artery bypass grafting. The patient had a stress"
    + " echocardiogram done on July, 2001, which showed no wall motion abnormalities, but this was a"
    + " difficult study due to body habitus. The patient went for six minutes with minimal ST depressions"
    + " in the anterior lateral leads, thought due to fatigue and wrist pain, his anginal equivalent. Due"
    + " to the patient'sincreased symptoms and family history and history left main disease with total"
    + " occasional of his RCA was referred for revascularization with open heart surgery.";

string documentB = "Prescribed 100mg ibuprofen, taken twice daily.";

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
List<string> batchedDocuments = new()
{
    documentA,
    documentB
};

// Perform the text analysis operation.
AnalyzeHealthcareEntitiesOperation operation = await client.AnalyzeHealthcareEntitiesAsync(WaitUntil.Completed, batchedDocuments);
// View the operation results.
await foreach (AnalyzeHealthcareEntitiesResultCollection documentsInPage in operation.Value)
{
    Console.WriteLine($"Analyze Healthcare Entities, model version: \"{documentsInPage.ModelVersion}\"");
    Console.WriteLine();

    foreach (AnalyzeHealthcareEntitiesResult documentResult in documentsInPage)
    {
        if (documentResult.HasError)
        {
            Console.WriteLine($"  Error!");
            Console.WriteLine($"  Document error code: {documentResult.Error.ErrorCode}");
            Console.WriteLine($"  Message: {documentResult.Error.Message}");
            continue;
        }

        Console.WriteLine($"  Recognized the following {documentResult.Entities.Count} healthcare entities:");
        Console.WriteLine();

        // View the healthcare entities that were recognized.
        foreach (HealthcareEntity entity in documentResult.Entities)
        {
            Console.WriteLine($"  Entity: {entity.Text}");
            Console.WriteLine($"  Category: {entity.Category}");
            Console.WriteLine($"  Offset: {entity.Offset}");
            Console.WriteLine($"  Length: {entity.Length}");
            Console.WriteLine($"  NormalizedText: {entity.NormalizedText}");
            Console.WriteLine($"  Links:");

            // View the entity data sources.
            foreach (EntityDataSource entityDataSource in entity.DataSources)
            {
                Console.WriteLine($"    Entity ID in Data Source: {entityDataSource.EntityId}");
                Console.WriteLine($"    DataSource: {entityDataSource.Name}");
            }

            // View the entity assertions.
            if (entity.Assertion is not null)
            {
                Console.WriteLine($"  Assertions:");

                if (entity.Assertion?.Association is not null)
                {
                    Console.WriteLine($"    Association: {entity.Assertion?.Association}");
                }

                if (entity.Assertion?.Certainty is not null)
                {
                    Console.WriteLine($"    Certainty: {entity.Assertion?.Certainty}");
                }

                if (entity.Assertion?.Conditionality is not null)
                {
                    Console.WriteLine($"    Conditionality: {entity.Assertion?.Conditionality}");
                }
            }
        }

        Console.WriteLine($"  We found {documentResult.EntityRelations.Count} relations in the current document:");
        Console.WriteLine();

        // View the healthcare entity relations that were recognized.
        foreach (HealthcareEntityRelation relation in documentResult.EntityRelations)
        {
            Console.WriteLine($"    Relation: {relation.RelationType}");
            if (relation.ConfidenceScore is not null)
            {
                Console.WriteLine($"    ConfidenceScore: {relation.ConfidenceScore}");
            }
            Console.WriteLine($"    For this relation there are {relation.Roles.Count} roles");

            // View the relation roles.
            foreach (HealthcareEntityRelationRole role in relation.Roles)
            {
                Console.WriteLine($"      Role Name: {role.Name}");

                Console.WriteLine($"      Associated Entity Text: {role.Entity.Text}");
                Console.WriteLine($"      Associated Entity Category: {role.Entity.Category}");
                Console.WriteLine();
            }

            Console.WriteLine();
        }

        Console.WriteLine();
    }
}

string textA =
    "RECORD #333582770390100 | MH | 85986313 | | 054351 | 2/14/2001 12:00:00 AM |"
    + " CORONARY ARTERY DISEASE | Signed | DIS |"
    + Environment.NewLine
    + " Admission Date: 5/22/2001 Report Status: Signed Discharge Date: 4/24/2001"
    + " ADMISSION DIAGNOSIS: CORONARY ARTERY DISEASE."
    + Environment.NewLine
    + " HISTORY OF PRESENT ILLNESS: The patient is a 54-year-old gentleman with a history of progressive"
    + " angina over the past several months. The patient had a cardiac catheterization in July of this"
    + " year revealing total occlusion of the RCA and 50% left main disease, with a strong family history"
    + " of coronary artery disease with a brother dying at the age of 52 from a myocardial infarction and"
    + " another brother who is status post coronary artery bypass grafting. The patient had a stress"
    + " echocardiogram done on July, 2001, which showed no wall motion abnormalities, but this was a"
    + " difficult study due to body habitus. The patient went for six minutes with minimal ST depressions"
    + " in the anterior lateral leads, thought due to fatigue and wrist pain, his anginal equivalent. Due"
    + " to the patient'sincreased symptoms and family history and history left main disease with total"
    + " occasional of his RCA was referred for revascularization with open heart surgery.";

string textB = "Prescribed 100mg ibuprofen, taken twice daily.";

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
MultiLanguageTextInput multiLanguageTextInput = new MultiLanguageTextInput()
{
    MultiLanguageInputs =
    {
        new MultiLanguageInput("A", textA) { Language = "en" },
        new MultiLanguageInput("B", textB) { Language = "en" },
    }
};

var analyzeTextOperationActions = new AnalyzeTextOperationAction[]
{
    new HealthcareOperationAction
    {
        Name = "HealthcareOperationActionSample", // Optional string for humans to identify action by name.
    },
};

Response<AnalyzeTextJobState> response = await client.AnalyzeTextOperationAsync(multiLanguageTextInput, analyzeTextOperationActions);

AnalyzeTextJobState analyzeTextJobState = response.Value;

foreach (AnalyzeTextOperationResult taskResult in analyzeTextJobState.Tasks.Items)
{
    if (taskResult is HealthcareOperationResult)
    {
        HealthcareOperationResult healthcareOperationResult = (HealthcareOperationResult)taskResult;
        Console.WriteLine($"Analyze Healthcare Entities, model version: \"{healthcareOperationResult.Results.ModelVersion}\"");
        Console.WriteLine();

        // View the healthcare entities recognized in the input documents.
        foreach (HealthcareActionResult healthcareEntitiesDocument in healthcareOperationResult.Results.Documents)
        {
            Console.WriteLine($"Result for document with Id = \"{healthcareEntitiesDocument.Id}\":");
            Console.WriteLine($"  Recognized the following {healthcareEntitiesDocument.Entities.Count} healthcare entities:");
            foreach (HealthcareEntity healthcareEntity in healthcareEntitiesDocument.Entities)
            {
                Console.WriteLine($"  NamedEntity: {healthcareEntity.Text}");
                Console.WriteLine($"  Category: {healthcareEntity.Category}");
                Console.WriteLine($"  Offset: {healthcareEntity.Offset}");
                Console.WriteLine($"  Length: {healthcareEntity.Length}");
                Console.WriteLine($"  Name: {healthcareEntity.Name}");
                Console.WriteLine($"  Links:");

                // View the entity data sources.
                foreach (HealthcareEntityLink healthcareEntityLink in healthcareEntity.Links)
                {
                    Console.WriteLine($"    NamedEntity ID in Data Source: {healthcareEntityLink.Id}");
                    Console.WriteLine($"    DataSource: {healthcareEntityLink.DataSource}");
                }

                // View the entity assertions.
                if (healthcareEntity.Assertion is not null)
                {
                    Console.WriteLine($"  Assertions:");
                    if (healthcareEntity.Assertion?.Association is not null)
                    {
                        Console.WriteLine($"    HealthcareAssociation: {healthcareEntity.Assertion?.Association}");
                    }
                    if (healthcareEntity.Assertion?.Certainty is not null)
                    {
                        Console.WriteLine($"    HealthcareCertainty: {healthcareEntity.Assertion?.Certainty}");
                    }
                    if (healthcareEntity.Assertion?.Conditionality is not null)
                    {
                        Console.WriteLine($"    HealthcareConditionality: {healthcareEntity.Assertion?.Conditionality}");
                    }
                }
            }

            Console.WriteLine($"  We found {healthcareEntitiesDocument.Relations.Count} relations in the current document:");
            Console.WriteLine();

            // View the healthcare entity relations that were recognized.
            foreach (HealthcareRelation relation in healthcareEntitiesDocument.Relations)
            {
                Console.WriteLine($"    Relation: {relation.RelationType}");
                if (relation.ConfidenceScore is not null)
                {
                    Console.WriteLine($"    ConfidenceScore: {relation.ConfidenceScore}");
                }
                Console.WriteLine($"    For this relation there are {relation.Entities.Count} roles");

                // View the relations
                foreach (HealthcareRelationEntity healthcareRelationEntity in relation.Entities)
                {
                    Console.WriteLine($"      Role: {healthcareRelationEntity.Role}");
                    Console.WriteLine($"      Refrence: {healthcareRelationEntity.Ref}");
                    Console.WriteLine();
                }

                Console.WriteLine();
            }

            // View the errors in the document
            foreach (DocumentError error in healthcareOperationResult.Results.Errors)
            {
                Console.WriteLine($"  Error in document: {error.Id}!");
                Console.WriteLine($"  Document error code: {error.Error.Code}");
                Console.WriteLine($"  Message: {error.Error.Message}");
                continue;
            }
        }
    }
}

string documentA =
    "We love this trail and make the trip every year. The views are breathtaking and well worth the hike!"
    + " Yesterday was foggy though, so we missed the spectacular views. We tried again today and it was"
    + " amazing. Everyone in my family liked the trail although it was too challenging for the less"
    + " athletic among us.";

string documentB =
    "Last week we stayed at Hotel Foo to celebrate our anniversary. The staff knew about our anniversary"
    + " so they helped me organize a little surprise for my partner. The room was clean and with the"
    + " decoration I requested. It was perfect!";

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
List<TextDocumentInput> batchedDocuments = new()
{
    new TextDocumentInput("1", documentA)
    {
         Language = "en",
    },
    new TextDocumentInput("2", documentB)
    {
         Language = "en",
    }
};

// Specify the project and deployment names of the desired custom model. To train your own custom model to
// recognize custom entities, see https://aka.ms/azsdk/textanalytics/customentityrecognition.
string projectName = "<projectName>";
string deploymentName = "<deploymentName>";

// Perform the text analysis operation.
RecognizeCustomEntitiesOperation operation = await client.RecognizeCustomEntitiesAsync(WaitUntil.Completed, batchedDocuments, projectName, deploymentName);

await foreach (RecognizeCustomEntitiesResultCollection documentsInPage in operation.Value)
{
    foreach (RecognizeEntitiesResult documentResult in documentsInPage)
    {
        Console.WriteLine($"Result for document with Id = \"{documentResult.Id}\":");

        if (documentResult.HasError)
        {
            Console.WriteLine($"  Error!");
            Console.WriteLine($"  Document error code: {documentResult.Error.ErrorCode}");
            Console.WriteLine($"  Message: {documentResult.Error.Message}");
            Console.WriteLine();
            continue;
        }

        Console.WriteLine($"  Recognized {documentResult.Entities.Count} entities:");

        foreach (CategorizedEntity entity in documentResult.Entities)
        {
            Console.WriteLine($"  Entity: {entity.Text}");
            Console.WriteLine($"  Category: {entity.Category}");
            Console.WriteLine($"  Offset: {entity.Offset}");
            Console.WriteLine($"  Length: {entity.Length}");
            Console.WriteLine($"  ConfidenceScore: {entity.ConfidenceScore}");
            Console.WriteLine($"  SubCategory: {entity.SubCategory}");
            Console.WriteLine();
        }

        Console.WriteLine();
    }
}

string textA =
    "We love this trail and make the trip every year. The views are breathtaking and well worth the hike!"
    + " Yesterday was foggy though, so we missed the spectacular views. We tried again today and it was"
    + " amazing. Everyone in my family liked the trail although it was too challenging for the less"
    + " athletic among us.";

string textB =
    "Last week we stayed at Hotel Foo to celebrate our anniversary. The staff knew about our anniversary"
    + " so they helped me organize a little surprise for my partner. The room was clean and with the"
    + " decoration I requested. It was perfect!";

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
MultiLanguageTextInput multiLanguageTextInput = new MultiLanguageTextInput()
{
    MultiLanguageInputs =
    {
        new MultiLanguageInput("A", textA) { Language = "en" },
        new MultiLanguageInput("B", textB) { Language = "en" },
    }
};

// Specify the project and deployment names of the desired custom model. To train your own custom model to
// recognize custom entities, see https://aka.ms/azsdk/textanalytics/customentityrecognition.
string projectName = "<projectName>";
string deploymentName = "<deploymentName>";

CustomEntitiesActionContent customEntitiesActionContent = new CustomEntitiesActionContent(projectName, deploymentName);

// Perform the text analysis operation.
var analyzeTextOperationActions = new AnalyzeTextOperationAction[]
{
    new CustomEntitiesOperationAction
    {
        Name = "CustomEntitiesOperationActionSample", // Optional string for humans to identify action by name.
        Parameters = customEntitiesActionContent
    },
};

Response<AnalyzeTextJobState> response = await client.AnalyzeTextOperationAsync(multiLanguageTextInput, analyzeTextOperationActions);

AnalyzeTextJobState analyzeTextJobState = response.Value;

foreach (AnalyzeTextOperationResult taskResult in analyzeTextJobState.Tasks.Items)
{
    if (taskResult is CustomEntityRecognitionOperationResult)
    {
        CustomEntityRecognitionOperationResult customClassificationResult = (CustomEntityRecognitionOperationResult)taskResult;

        // View the classifications recognized in the input documents.
        foreach (CustomEntityActionResult entitiesDocument in customClassificationResult.Results.Documents)
        {
            Console.WriteLine($"Result for document with Id = \"{entitiesDocument.Id}\":");
            Console.WriteLine($"  Recognized {entitiesDocument.Entities.Count} Entities:");

            foreach (NamedEntity entity in entitiesDocument.Entities)
            {
                Console.WriteLine($"  NamedEntity: {entity.Text}");
                Console.WriteLine($"  Category: {entity.Category}");
                Console.WriteLine($"  Offset: {entity.Offset}");
                Console.WriteLine($"  Length: {entity.Length}");
                Console.WriteLine($"  ConfidenceScore: {entity.ConfidenceScore}");
                Console.WriteLine($"  Subcategory: {entity.Subcategory}");
                Console.WriteLine();
            }
        }
        // View the errors in the document
        foreach (DocumentError error in customClassificationResult.Results.Errors)
        {
            Console.WriteLine($"  Error in document: {error.Id}!");
            Console.WriteLine($"  Document error: {error.Error}");
            continue;
        }
        Console.WriteLine();
    }
}

string document =
    "I need a reservation for an indoor restaurant in China. Please don't stop the music. Play music and"
    + " add it to my playlist.";

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
List<string> batchedDocuments = new()
{
    document
};

// Specify the project and deployment names of the desired custom model. To train your own custom model to
// classify your documents, see https://aka.ms/azsdk/textanalytics/customfunctionalities.
string projectName = "<projectName>";
string deploymentName = "<deploymentName>";

// Perform the text analysis operation.
ClassifyDocumentOperation operation = await client.SingleLabelClassifyAsync(WaitUntil.Completed, batchedDocuments, projectName, deploymentName);

// View the operation results.
await foreach (ClassifyDocumentResultCollection documentsInPage in operation.Value)
{
    foreach (ClassifyDocumentResult documentResult in documentsInPage)
    {
        if (documentResult.HasError)
        {
            Console.WriteLine($"  Error!");
            Console.WriteLine($"  Document error code: {documentResult.Error.ErrorCode}");
            Console.WriteLine($"  Message: {documentResult.Error.Message}");
            continue;
        }

        Console.WriteLine($"  Predicted the following class:");
        Console.WriteLine();

        foreach (ClassificationCategory classification in documentResult.ClassificationCategories)
        {
            Console.WriteLine($"  Category: {classification.Category}");
            Console.WriteLine($"  Confidence score: {classification.ConfidenceScore}");
            Console.WriteLine();
        }
    }
}

string textA =
    "I need a reservation for an indoor restaurant in China. Please don't stop the music. Play music and"
    + " add it to my playlist.";

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
MultiLanguageTextInput multiLanguageTextInput = new MultiLanguageTextInput()
{
    MultiLanguageInputs =
    {
        new MultiLanguageInput("A", textA)
        {
            Language = "en"
        },
    }
};

// Specify the project and deployment names of the desired custom model. To train your own custom model to
// recognize custom entities, see https://aka.ms/azsdk/textanalytics/customentityrecognition.
string projectName = "<projectName>";
string deploymentName = "<deploymentName>";

CustomSingleLabelClassificationActionContent customSingleLabelClassificationActionContent = new CustomSingleLabelClassificationActionContent(projectName, deploymentName);

var analyzeTextOperationActions = new AnalyzeTextOperationAction[]
{
    new CustomSingleLabelClassificationOperationAction
    {
        Name = "CSCOperationActionSample", // Optional string for humans to identify action by name.
        ActionContent = customSingleLabelClassificationActionContent
    },
};

Response<AnalyzeTextJobState> response = await client.AnalyzeTextOperationAsync(multiLanguageTextInput, analyzeTextOperationActions);

AnalyzeTextJobState analyzeTextJobState = response.Value;

foreach (AnalyzeTextOperationResult taskResult in analyzeTextJobState.Tasks.Items)
{
    if (taskResult is CustomSingleLabelClassificationOperationResult)
    {
        CustomSingleLabelClassificationOperationResult customClassificationResult = (CustomSingleLabelClassificationOperationResult)taskResult;

        // View the classifications recognized in the input documents.
        foreach (ClassificationActionResult customClassificationDocument in customClassificationResult.Results.Documents)
        {
            Console.WriteLine($"Result for document with Id = \"{customClassificationDocument.Id}\":");
            Console.WriteLine($"  Recognized {customClassificationDocument.Class.Count} classifications:");

            foreach (ClassificationResult classification in customClassificationDocument.Class)
            {
                Console.WriteLine($"  Classification: {classification.Category}");
                Console.WriteLine($"  ConfidenceScore: {classification.ConfidenceScore}");
                Console.WriteLine();
            }
        }
        // View the errors in the document
        foreach (DocumentError error in customClassificationResult.Results.Errors)
        {
            Console.WriteLine($"  Error in document: {error.Id}!");
            Console.WriteLine($"  Document error: {error.Error}");
            continue;
        }
    }
}

string document =
    "I need a reservation for an indoor restaurant in China. Please don't stop the music. Play music and"
    + " add it to my playlist.";

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
List<string> batchedDocuments = new()
{
    document
};

// Specify the project and deployment names of the desired custom model. To train your own custom model to
// classify your documents, see https://aka.ms/azsdk/textanalytics/customfunctionalities.
string projectName = "<projectName>";
string deploymentName = "<deploymentName>";

// Perform the text analysis operation.
ClassifyDocumentOperation operation = await client.MultiLabelClassifyAsync(WaitUntil.Completed, batchedDocuments, projectName, deploymentName);

// View the operation results.
await foreach (ClassifyDocumentResultCollection documentsInPage in operation.Value)
{
    foreach (ClassifyDocumentResult documentResult in documentsInPage)
    {
        if (documentResult.HasError)
        {
            Console.WriteLine($"  Error!");
            Console.WriteLine($"  Document error code: {documentResult.Error.ErrorCode}");
            Console.WriteLine($"  Message: {documentResult.Error.Message}");
            continue;
        }

        Console.WriteLine($"  Predicted the following classes:");
        Console.WriteLine();

        foreach (ClassificationCategory classification in documentResult.ClassificationCategories)
        {
            Console.WriteLine($"  Category: {classification.Category}");
            Console.WriteLine($"  Confidence score: {classification.ConfidenceScore}");
            Console.WriteLine();
        }
    }
}

string textA =
    "I need a reservation for an indoor restaurant in China. Please don't stop the music. Play music and"
    + " add it to my playlist.";

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
MultiLanguageTextInput multiLanguageTextInput = new MultiLanguageTextInput()
{
    MultiLanguageInputs =
    {
        new MultiLanguageInput("A", textA)
        {
            Language = "en"
        },
    }
};

// Specify the project and deployment names of the desired custom model. To train your own custom model to
// recognize custom entities, see https://aka.ms/azsdk/textanalytics/customentityrecognition.
string projectName = "<projectName>";
string deploymentName = "<deploymentName>";

CustomMultiLabelClassificationActionContent customMultiLabelClassificationActionContent = new CustomMultiLabelClassificationActionContent(projectName, deploymentName);

var analyzeTextOperationActions = new AnalyzeTextOperationAction[]
{
    new CustomMultiLabelClassificationOperationAction
    {
        Name = "CMCOperationActionSample",
        ActionContent = customMultiLabelClassificationActionContent,
    },
};

Response<AnalyzeTextJobState> response = await client.AnalyzeTextOperationAsync(multiLanguageTextInput, analyzeTextOperationActions);

AnalyzeTextJobState analyzeTextJobState = response.Value;

foreach (AnalyzeTextOperationResult taskResult in analyzeTextJobState.Tasks.Items)
{
    if (taskResult is CustomMultiLabelClassificationOperationResult)
    {
        CustomMultiLabelClassificationOperationResult customClassificationResult = (CustomMultiLabelClassificationOperationResult)taskResult;

        // View the classifications recognized in the input documents.
        foreach (ClassificationActionResult customClassificationDocument in customClassificationResult.Results.Documents)
        {
            Console.WriteLine($"Result for document with Id = \"{customClassificationDocument.Id}\":");
            Console.WriteLine($"  Recognized {customClassificationDocument.Class.Count} classifications:");

            foreach (ClassificationResult classification in customClassificationDocument.Class)
            {
                Console.WriteLine($"  Classification: {classification.Category}");
                Console.WriteLine($"  ConfidenceScore: {classification.ConfidenceScore}");
                Console.WriteLine();
            }
        }
        // View the errors in the document
        foreach (DocumentError error in customClassificationResult.Results.Errors)
        {
            Console.WriteLine($"  Error in document: {error.Id}!");
            Console.WriteLine($"  Document error: {error.Error}");
            continue;
        }
    }
}

string document =
    "Windows 365 was in the works before COVID-19 sent companies around the world on a scramble to secure"
    + " solutions to support employees suddenly forced to work from home, but “what really put the"
    + " firecracker behind it was the pandemic, it accelerated everything,” McKelvey said. She explained"
    + " that customers were asking, “How do we create an experience for people that makes them still feel"
    + " connected to the company without the physical presence of being there?” In this new world of"
    + " Windows 365, remote workers flip the lid on their laptop, boot up the family workstation or clip a"
    + " keyboard onto a tablet, launch a native app or modern web browser and login to their Windows 365"
    + " account. From there, their Cloud PC appears with their background, apps, settings and content just"
    + " as they left it when they last were last there – in the office, at home or a coffee shop. And"
    + " then, when you’re done, you’re done. You won’t have any issues around security because you’re not"
    + " saving anything on your device,” McKelvey said, noting that all the data is stored in the cloud."
    + " The ability to login to a Cloud PC from anywhere on any device is part of Microsoft’s larger"
    + " strategy around tailoring products such as Microsoft Teams and Microsoft 365 for the post-pandemic"
    + " hybrid workforce of the future, she added. It enables employees accustomed to working from home to"
    + " continue working from home; it enables companies to hire interns from halfway around the world; it"
    + " allows startups to scale without requiring IT expertise. “I think this will be interesting for"
    + " those organizations who, for whatever reason, have shied away from virtualization. This is giving"
    + " them an opportunity to try it in a way that their regular, everyday endpoint admin could manage,”"
    + " McKelvey said. The simplicity of Windows 365 won over Dean Wells, the corporate chief information"
    + " officer for the Government of Nunavut. His team previously attempted to deploy a traditional"
    + " virtual desktop infrastructure and found it inefficient and unsustainable given the limitations of"
    + " low-bandwidth satellite internet and the constant need for IT staff to manage the network and"
    + " infrastructure. We didn’t run it for very long,” he said. “It didn’t turn out the way we had"
    + " hoped. So, we actually had terminated the project and rolled back out to just regular PCs.” He"
    + " re-evaluated this decision after the Government of Nunavut was hit by a ransomware attack in"
    + " November 2019 that took down everything from the phone system to the government’s servers."
    + " Microsoft helped rebuild the system, moving the government to Teams, SharePoint, OneDrive and"
    + " Microsoft 365. Manchester’s team recruited the Government of Nunavut to pilot Windows 365. Wells"
    + " was intrigued, especially by the ability to manage the elastic workforce securely and seamlessly."
    + " “The impact that I believe we are finding, and the impact that we’re going to find going forward,"
    + " is being able to access specialists from outside the territory and organizations outside the"
    + " territory to come in and help us with our projects, being able to get people on staff with us to"
    + " help us deliver the day-to-day expertise that we need to run the government,” he said. “Being able"
    + " to improve healthcare, being able to improve education, economic development is going to improve"
    + " the quality of life in the communities.”";

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
List<string> batchedDocuments = new()
{
    document
};

// Perform the text analysis operation.
ExtractiveSummarizeOperation operation = await client.ExtractiveSummarizeAsync(WaitUntil.Completed, batchedDocuments);

// View the operation results.
await foreach (ExtractiveSummarizeResultCollection documentsInPage in operation.Value)
{
    Console.WriteLine($"Extractive Summarize, version: \"{documentsInPage.ModelVersion}\"");
    Console.WriteLine();

    foreach (ExtractiveSummarizeResult documentResult in documentsInPage)
    {
        if (documentResult.HasError)
        {
            Console.WriteLine($"  Error!");
            Console.WriteLine($"  Document error code: {documentResult.Error.ErrorCode}");
            Console.WriteLine($"  Message: {documentResult.Error.Message}");
            continue;
        }

        Console.WriteLine($"  Extracted {documentResult.Sentences.Count} sentence(s):");
        Console.WriteLine();

        foreach (ExtractiveSummarySentence sentence in documentResult.Sentences)
        {
            Console.WriteLine($"  Sentence: {sentence.Text}");
            Console.WriteLine($"  Rank Score: {sentence.RankScore}");
            Console.WriteLine($"  Offset: {sentence.Offset}");
            Console.WriteLine($"  Length: {sentence.Length}");
            Console.WriteLine();
        }
    }
}

string textA =
    "Windows 365 was in the works before COVID-19 sent companies around the world on a scramble to secure"
    + " solutions to support employees suddenly forced to work from home, but “what really put the"
    + " firecracker behind it was the pandemic, it accelerated everything,” McKelvey said. She explained"
    + " that customers were asking, “How do we create an experience for people that makes them still feel"
    + " connected to the company without the physical presence of being there?” In this new world of"
    + " Windows 365, remote workers flip the lid on their laptop, boot up the family workstation or clip a"
    + " keyboard onto a tablet, launch a native app or modern web browser and login to their Windows 365"
    + " account. From there, their Cloud PC appears with their background, apps, settings and content just"
    + " as they left it when they last were last there – in the office, at home or a coffee shop. And"
    + " then, when you’re done, you’re done. You won’t have any issues around security because you’re not"
    + " saving anything on your device,” McKelvey said, noting that all the data is stored in the cloud."
    + " The ability to login to a Cloud PC from anywhere on any device is part of Microsoft’s larger"
    + " strategy around tailoring products such as Microsoft Teams and Microsoft 365 for the post-pandemic"
    + " hybrid workforce of the future, she added. It enables employees accustomed to working from home to"
    + " continue working from home; it enables companies to hire interns from halfway around the world; it"
    + " allows startups to scale without requiring IT expertise. “I think this will be interesting for"
    + " those organizations who, for whatever reason, have shied away from virtualization. This is giving"
    + " them an opportunity to try it in a way that their regular, everyday endpoint admin could manage,”"
    + " McKelvey said. The simplicity of Windows 365 won over Dean Wells, the corporate chief information"
    + " officer for the Government of Nunavut. His team previously attempted to deploy a traditional"
    + " virtual desktop infrastructure and found it inefficient and unsustainable given the limitations of"
    + " low-bandwidth satellite internet and the constant need for IT staff to manage the network and"
    + " infrastructure. We didn’t run it for very long,” he said. “It didn’t turn out the way we had"
    + " hoped. So, we actually had terminated the project and rolled back out to just regular PCs.” He"
    + " re-evaluated this decision after the Government of Nunavut was hit by a ransomware attack in"
    + " November 2019 that took down everything from the phone system to the government’s servers."
    + " Microsoft helped rebuild the system, moving the government to Teams, SharePoint, OneDrive and"
    + " Microsoft 365. Manchester’s team recruited the Government of Nunavut to pilot Windows 365. Wells"
    + " was intrigued, especially by the ability to manage the elastic workforce securely and seamlessly."
    + " “The impact that I believe we are finding, and the impact that we’re going to find going forward,"
    + " is being able to access specialists from outside the territory and organizations outside the"
    + " territory to come in and help us with our projects, being able to get people on staff with us to"
    + " help us deliver the day-to-day expertise that we need to run the government,” he said. “Being able"
    + " to improve healthcare, being able to improve education, economic development is going to improve"
    + " the quality of life in the communities.”";

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
MultiLanguageTextInput multiLanguageTextInput = new MultiLanguageTextInput()
{
    MultiLanguageInputs =
    {
        new MultiLanguageInput("A", textA) { Language = "en" },
    }
};

var analyzeTextOperationActions = new AnalyzeTextOperationAction[]
{
    new ExtractiveSummarizationOperationAction
    {
        Name = "ExtractiveSummarizationOperationActionSample", // Optional string for humans to identify action by name.
    },
};

Response<AnalyzeTextJobState> response = await client.AnalyzeTextOperationAsync(multiLanguageTextInput, analyzeTextOperationActions);

AnalyzeTextJobState analyzeTextJobState = response.Value;

foreach (AnalyzeTextOperationResult analyzeTextOperationResult in analyzeTextJobState.Tasks.Items)
{
    if (analyzeTextOperationResult is ExtractiveSummarizationOperationResult)
    {
        ExtractiveSummarizationOperationResult extractiveSummarizationLROResult = (ExtractiveSummarizationOperationResult)analyzeTextOperationResult;

        // View the classifications recognized in the input documents.
        foreach (ExtractedSummaryActionResult extractedSummyDocument in extractiveSummarizationLROResult.Results.Documents)
        {
            Console.WriteLine($"Result for document with Id = \"{extractedSummyDocument.Id}\":");
            Console.WriteLine($"  Extracted {extractedSummyDocument.Sentences.Count} sentence(s):");
            Console.WriteLine();

            foreach (ExtractedSummarySentence sentence in extractedSummyDocument.Sentences)
            {
                Console.WriteLine($"  Sentence: {sentence.Text}");
                Console.WriteLine($"  Rank Score: {sentence.RankScore}");
                Console.WriteLine($"  Offset: {sentence.Offset}");
                Console.WriteLine($"  Length: {sentence.Length}");
                Console.WriteLine();
            }
        }
        // View the errors in the document
        foreach (DocumentError error in extractiveSummarizationLROResult.Results.Errors)
        {
            Console.WriteLine($"  Error in document: {error.Id}!");
            Console.WriteLine($"  Document error: {error.Error}");
            continue;
        }
    }
}

string document =
    "Windows 365 was in the works before COVID-19 sent companies around the world on a scramble to secure"
    + " solutions to support employees suddenly forced to work from home, but “what really put the"
    + " firecracker behind it was the pandemic, it accelerated everything,” McKelvey said. She explained"
    + " that customers were asking, “How do we create an experience for people that makes them still feel"
    + " connected to the company without the physical presence of being there?” In this new world of"
    + " Windows 365, remote workers flip the lid on their laptop, boot up the family workstation or clip a"
    + " keyboard onto a tablet, launch a native app or modern web browser and login to their Windows 365"
    + " account. From there, their Cloud PC appears with their background, apps, settings and content just"
    + " as they left it when they last were last there – in the office, at home or a coffee shop. And"
    + " then, when you’re done, you’re done. You won’t have any issues around security because you’re not"
    + " saving anything on your device,” McKelvey said, noting that all the data is stored in the cloud."
    + " The ability to login to a Cloud PC from anywhere on any device is part of Microsoft’s larger"
    + " strategy around tailoring products such as Microsoft Teams and Microsoft 365 for the post-pandemic"
    + " hybrid workforce of the future, she added. It enables employees accustomed to working from home to"
    + " continue working from home; it enables companies to hire interns from halfway around the world; it"
    + " allows startups to scale without requiring IT expertise. “I think this will be interesting for"
    + " those organizations who, for whatever reason, have shied away from virtualization. This is giving"
    + " them an opportunity to try it in a way that their regular, everyday endpoint admin could manage,”"
    + " McKelvey said. The simplicity of Windows 365 won over Dean Wells, the corporate chief information"
    + " officer for the Government of Nunavut. His team previously attempted to deploy a traditional"
    + " virtual desktop infrastructure and found it inefficient and unsustainable given the limitations of"
    + " low-bandwidth satellite internet and the constant need for IT staff to manage the network and"
    + " infrastructure. We didn’t run it for very long,” he said. “It didn’t turn out the way we had"
    + " hoped. So, we actually had terminated the project and rolled back out to just regular PCs.” He"
    + " re-evaluated this decision after the Government of Nunavut was hit by a ransomware attack in"
    + " November 2019 that took down everything from the phone system to the government’s servers."
    + " Microsoft helped rebuild the system, moving the government to Teams, SharePoint, OneDrive and"
    + " Microsoft 365. Manchester’s team recruited the Government of Nunavut to pilot Windows 365. Wells"
    + " was intrigued, especially by the ability to manage the elastic workforce securely and seamlessly."
    + " “The impact that I believe we are finding, and the impact that we’re going to find going forward,"
    + " is being able to access specialists from outside the territory and organizations outside the"
    + " territory to come in and help us with our projects, being able to get people on staff with us to"
    + " help us deliver the day-to-day expertise that we need to run the government,” he said. “Being able"
    + " to improve healthcare, being able to improve education, economic development is going to improve"
    + " the quality of life in the communities.”";

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
List<string> batchedDocuments = new()
{
    document
};

// Perform the text analysis operation.
AbstractiveSummarizeOperation operation = await client.AbstractiveSummarizeAsync(WaitUntil.Completed, batchedDocuments);

// View the operation results.
await foreach (AbstractiveSummarizeResultCollection documentsInPage in operation.Value)
{
    Console.WriteLine($"Abstractive Summarize, model version: \"{documentsInPage.ModelVersion}\"");
    Console.WriteLine();

    foreach (AbstractiveSummarizeResult documentResult in documentsInPage)
    {
        if (documentResult.HasError)
        {
            Console.WriteLine($"  Error!");
            Console.WriteLine($"  Document error code: {documentResult.Error.ErrorCode}");
            Console.WriteLine($"  Message: {documentResult.Error.Message}");
            continue;
        }

        Console.WriteLine($"  Produced the following abstractive summaries:");
        Console.WriteLine();

        foreach (AbstractiveSummary summary in documentResult.Summaries)
        {
            Console.WriteLine($"  Text: {summary.Text.Replace("\n", " ")}");
            Console.WriteLine($"  Contexts:");

            foreach (AbstractiveSummaryContext context in summary.Contexts)
            {
                Console.WriteLine($"    Offset: {context.Offset}");
                Console.WriteLine($"    Length: {context.Length}");
            }

            Console.WriteLine();
        }
    }
}

string textA =
    "Windows 365 was in the works before COVID-19 sent companies around the world on a scramble to secure"
    + " solutions to support employees suddenly forced to work from home, but “what really put the"
    + " firecracker behind it was the pandemic, it accelerated everything,” McKelvey said. She explained"
    + " that customers were asking, “How do we create an experience for people that makes them still feel"
    + " connected to the company without the physical presence of being there?” In this new world of"
    + " Windows 365, remote workers flip the lid on their laptop, boot up the family workstation or clip a"
    + " keyboard onto a tablet, launch a native app or modern web browser and login to their Windows 365"
    + " account. From there, their Cloud PC appears with their background, apps, settings and content just"
    + " as they left it when they last were last there – in the office, at home or a coffee shop. And"
    + " then, when you’re done, you’re done. You won’t have any issues around security because you’re not"
    + " saving anything on your device,” McKelvey said, noting that all the data is stored in the cloud."
    + " The ability to login to a Cloud PC from anywhere on any device is part of Microsoft’s larger"
    + " strategy around tailoring products such as Microsoft Teams and Microsoft 365 for the post-pandemic"
    + " hybrid workforce of the future, she added. It enables employees accustomed to working from home to"
    + " continue working from home; it enables companies to hire interns from halfway around the world; it"
    + " allows startups to scale without requiring IT expertise. “I think this will be interesting for"
    + " those organizations who, for whatever reason, have shied away from virtualization. This is giving"
    + " them an opportunity to try it in a way that their regular, everyday endpoint admin could manage,”"
    + " McKelvey said. The simplicity of Windows 365 won over Dean Wells, the corporate chief information"
    + " officer for the Government of Nunavut. His team previously attempted to deploy a traditional"
    + " virtual desktop infrastructure and found it inefficient and unsustainable given the limitations of"
    + " low-bandwidth satellite internet and the constant need for IT staff to manage the network and"
    + " infrastructure. We didn’t run it for very long,” he said. “It didn’t turn out the way we had"
    + " hoped. So, we actually had terminated the project and rolled back out to just regular PCs.” He"
    + " re-evaluated this decision after the Government of Nunavut was hit by a ransomware attack in"
    + " November 2019 that took down everything from the phone system to the government’s servers."
    + " Microsoft helped rebuild the system, moving the government to Teams, SharePoint, OneDrive and"
    + " Microsoft 365. Manchester’s team recruited the Government of Nunavut to pilot Windows 365. Wells"
    + " was intrigued, especially by the ability to manage the elastic workforce securely and seamlessly."
    + " “The impact that I believe we are finding, and the impact that we’re going to find going forward,"
    + " is being able to access specialists from outside the territory and organizations outside the"
    + " territory to come in and help us with our projects, being able to get people on staff with us to"
    + " help us deliver the day-to-day expertise that we need to run the government,” he said. “Being able"
    + " to improve healthcare, being able to improve education, economic development is going to improve"
    + " the quality of life in the communities.”";

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
MultiLanguageTextInput multiLanguageTextInput = new MultiLanguageTextInput()
{
    MultiLanguageInputs =
    {
        new MultiLanguageInput("A", textA) { Language = "en" },
    }
};

var analyzeTextOperationActions = new AnalyzeTextOperationAction[]
{
    new AbstractiveSummarizationOperationAction
    {
        Name = "AbsractiveSummarizationOperationActionSample", // Optional string for humans to identify action by name.
    },
};

Response<AnalyzeTextJobState> response = await client.AnalyzeTextOperationAsync(multiLanguageTextInput, analyzeTextOperationActions);

AnalyzeTextJobState analyzeTextJobState = response.Value;

foreach (AnalyzeTextOperationResult analyzeTextOperationResult in analyzeTextJobState.Tasks.Items)
{
    if (analyzeTextOperationResult is AbstractiveSummarizationOperationResult)
    {
        AbstractiveSummarizationOperationResult abstractiveSummarizationLROResult = (AbstractiveSummarizationOperationResult)analyzeTextOperationResult;

        // View the classifications recognized in the input documents.
        foreach (AbstractiveSummaryActionResult extractedSummaryDocument in abstractiveSummarizationLROResult.Results.Documents)
        {
            Console.WriteLine($"Result for document with Id = \"{extractedSummaryDocument.Id}\":");
            Console.WriteLine($"  Produced the following abstractive summaries:");
            Console.WriteLine();

            foreach (AbstractiveSummary summary in extractedSummaryDocument.Summaries)
            {
                Console.WriteLine($"  Text: {summary.Text.Replace("\n", " ")}");
                Console.WriteLine($"  Contexts:");

                foreach (SummaryContext context in summary.Contexts)
                {
                    Console.WriteLine($"    Offset: {context.Offset}");
                    Console.WriteLine($"    Length: {context.Length}");
                }

                Console.WriteLine();
            }
        }
        // View the errors in the document
        foreach (DocumentError error in abstractiveSummarizationLROResult.Results.Errors)
        {
            Console.WriteLine($"  Error in document: {error.Id}!");
            Console.WriteLine($"  Document error: {error.Error}");
            continue;
        }
    }
}

    string documentA =
        "We love this trail and make the trip every year. The views are breathtaking and well worth the hike!"
        + " Yesterday was foggy though, so we missed the spectacular views. We tried again today and it was"
        + " amazing. Everyone in my family liked the trail although it was too challenging for the less"
        + " athletic among us.";

    string documentB =
        "Last week we stayed at Hotel Foo to celebrate our anniversary. The staff knew about our anniversary"
        + " so they helped me organize a little surprise for my partner. The room was clean and with the"
        + " decoration I requested. It was perfect!";

    // Prepare the input of the text analysis operation. You can add multiple documents to this list and
    // perform the same operation on all of them simultaneously.
    List<string> batchedDocuments = new()
    {
        documentA,
        documentB
    };

    TextAnalyticsActions actions = new()
    {
        ExtractKeyPhrasesActions = new List<ExtractKeyPhrasesAction>() { new ExtractKeyPhrasesAction() { ActionName = "ExtractKeyPhrasesSample" } },
        RecognizeEntitiesActions = new List<RecognizeEntitiesAction>() { new RecognizeEntitiesAction() { ActionName = "RecognizeEntitiesSample" } },
        DisplayName = "AnalyzeOperationSample"
    };

    // Perform the text analysis operation.
    AnalyzeActionsOperation operation = await client.AnalyzeActionsAsync(WaitUntil.Completed, batchedDocuments, actions);

    // View the operation status.
    Console.WriteLine($"Created On   : {operation.CreatedOn}");
    Console.WriteLine($"Expires On   : {operation.ExpiresOn}");
    Console.WriteLine($"Id           : {operation.Id}");
    Console.WriteLine($"Status       : {operation.Status}");
    Console.WriteLine($"Last Modified: {operation.LastModified}");
    Console.WriteLine();

    if (!string.IsNullOrEmpty(operation.DisplayName))
    {
        Console.WriteLine($"Display name: {operation.DisplayName}");
        Console.WriteLine();
    }

    Console.WriteLine($"Total actions: {operation.ActionsTotal}");
    Console.WriteLine($"  Succeeded actions: {operation.ActionsSucceeded}");
    Console.WriteLine($"  Failed actions: {operation.ActionsFailed}");
    Console.WriteLine($"  In progress actions: {operation.ActionsInProgress}");
    Console.WriteLine();

    await foreach (AnalyzeActionsResult documentsInPage in operation.Value)
    {
        IReadOnlyCollection<ExtractKeyPhrasesActionResult> keyPhrasesResults = documentsInPage.ExtractKeyPhrasesResults;
        IReadOnlyCollection<RecognizeEntitiesActionResult> entitiesResults = documentsInPage.RecognizeEntitiesResults;

        Console.WriteLine("Recognized Entities");
        int docNumber = 1;
        foreach (RecognizeEntitiesActionResult entitiesActionResults in entitiesResults)
        {
            Console.WriteLine($" Action name: {entitiesActionResults.ActionName}");
            Console.WriteLine();
            foreach (RecognizeEntitiesResult documentResult in entitiesActionResults.DocumentsResults)
            {
                Console.WriteLine($" Document #{docNumber++}");
                Console.WriteLine($"  Recognized {documentResult.Entities.Count} entities:");

                foreach (CategorizedEntity entity in documentResult.Entities)
                {
                    Console.WriteLine();
                    Console.WriteLine($"    Entity: {entity.Text}");
                    Console.WriteLine($"    Category: {entity.Category}");
                    Console.WriteLine($"    Offset: {entity.Offset}");
                    Console.WriteLine($"    Length: {entity.Length}");
                    Console.WriteLine($"    ConfidenceScore: {entity.ConfidenceScore}");
                    Console.WriteLine($"    SubCategory: {entity.SubCategory}");
                }
                Console.WriteLine();
            }
        }

        Console.WriteLine("Extracted Key Phrases");
        docNumber = 1;
        foreach (ExtractKeyPhrasesActionResult keyPhrasesActionResult in keyPhrasesResults)
        {
            Console.WriteLine($" Action name: {keyPhrasesActionResult.ActionName}");
            Console.WriteLine();
            foreach (ExtractKeyPhrasesResult documentResults in keyPhrasesActionResult.DocumentsResults)
            {
                Console.WriteLine($" Document #{docNumber++}");
                Console.WriteLine($"  Recognized the following {documentResults.KeyPhrases.Count} Keyphrases:");

                foreach (string keyphrase in documentResults.KeyPhrases)
                {
                    Console.WriteLine($"    {keyphrase}");
                }
                Console.WriteLine();
            }
        }
    }
}

string textA =
    "We love this trail and make the trip every year. The views are breathtaking and well worth the hike!"
    + " Yesterday was foggy though, so we missed the spectacular views. We tried again today and it was"
    + " amazing. Everyone in my family liked the trail although it was too challenging for the less"
    + " athletic among us. Not necessarily recommended for small children. A hotel close to the trail"
    + " offers services for childcare in case you want that.";

string textB =
    "Nos hospedamos en el Hotel Foo la semana pasada por nuestro aniversario. La gerencia sabía de nuestra"
    + " celebración y me ayudaron a tenerle una sorpresa a mi pareja. La habitación estaba limpia y"
    + " decorada como yo había pedido. Una gran experiencia. El próximo año volveremos.";

string textC =
    "That was the best day of my life! We went on a 4 day trip where we stayed at Hotel Foo. They had"
    + " great amenities that included an indoor pool, a spa, and a bar. The spa offered couples massages"
    + " which were really good. The spa was clean and felt very peaceful. Overall the whole experience was"
    + " great. We will definitely come back.";

string textD = string.Empty;

// Prepare the input of the text analysis operation. You can add multiple documents to this list and
// perform the same operation on all of them simultaneously.
MultiLanguageTextInput multiLanguageTextInput = new MultiLanguageTextInput()
{
    MultiLanguageInputs =
    {
        new MultiLanguageInput("A", textA) { Language = "en" },
        new MultiLanguageInput("B", textB) { Language = "es" },
        new MultiLanguageInput("C", textC) { Language = "en" },
        new MultiLanguageInput("D", textD),
    }
};

var analyzeTextOperationActions = new AnalyzeTextOperationAction[]
{
    new EntitiesOperationAction
    {
        Name = "EntitiesOperationActionSample", // Optional string for humans to identify action by name.
    },
    new KeyPhraseOperationAction
    {
        Name = "KeyPhraseOperationActionSample", // Optional string for humans to identify action by name.
    },
};

Response<AnalyzeTextJobState> response = await client.AnalyzeTextOperationAsync(multiLanguageTextInput, analyzeTextOperationActions);

AnalyzeTextJobState analyzeTextJobState = response.Value;

foreach (AnalyzeTextOperationResult taskResult in analyzeTextJobState.Tasks.Items)
{
    if (taskResult is EntityRecognitionOperationResult)
    {
        EntityRecognitionOperationResult EntityRecognitionOperationResult = (EntityRecognitionOperationResult)taskResult;

        // View the classifications recognized in the input documents.
        foreach (EntityActionResultWithMetadata nerResult in EntityRecognitionOperationResult.Results.Documents)
        {
            Console.WriteLine($"Result for document with Id = \"{nerResult.Id}\":");

            Console.WriteLine($"  Recognized {nerResult.Entities.Count} entities:");

            foreach (NamedEntityWithMetadata entity in nerResult.Entities)
            {
                Console.WriteLine($"    Text: {entity.Text}");
                Console.WriteLine($"    Offset: {entity.Offset}");
                Console.WriteLine($"    Length: {entity.Length}");
                Console.WriteLine($"    Category: {entity.Category}");
                Console.WriteLine($"    Type: {entity.Type}");
                Console.WriteLine($"    Tags:");
                foreach (EntityTag tag in entity.Tags)
                {
                    Console.WriteLine($"            TagName: {tag.Name}");
                    Console.WriteLine($"            TagConfidenceScore: {tag.ConfidenceScore}");
                }
                Console.WriteLine();
            }
            Console.WriteLine();
        }
        // View the errors in the document
        foreach (DocumentError error in EntityRecognitionOperationResult.Results.Errors)
        {
            Console.WriteLine($"  Error in document: {error.Id}!");
            Console.WriteLine($"  Document error: {error.Error}");
            continue;
        }
    }

    if (taskResult is KeyPhraseExtractionOperationResult)
    {
        KeyPhraseExtractionOperationResult keyPhraseExtractionLROResult = (KeyPhraseExtractionOperationResult)taskResult;

        // View the classifications recognized in the input documents.
        foreach (KeyPhrasesActionResult kpeResult in keyPhraseExtractionLROResult.Results.Documents)
        {
            Console.WriteLine($"Result for document with Id = \"{kpeResult.Id}\":");
            foreach (string keyPhrase in kpeResult.KeyPhrases)
            {
                Console.WriteLine($"    {keyPhrase}");
            }
            Console.WriteLine();
        }
        // View the errors in the document
        foreach (DocumentError error in keyPhraseExtractionLROResult.Results.Errors)
        {
            Console.WriteLine($"  Error in document: {error.Id}!");
            Console.WriteLine($"  Document error: {error.Error}");
            continue;
        }
    }
}