TextAnalysisClient.AnalyzeText Method

Definition

Namespace:

Azure.AI.Language.Text

Assembly:

Azure.AI.Language.Text.dll

Package:

Azure.AI.Language.Text v1.0.0-beta.2

Overloads

AnalyzeText(AnalyzeTextInput, Nullable<Boolean>, CancellationToken)	Request text analysis over a collection of documents.
AnalyzeText(RequestContent, Nullable<Boolean>, RequestContext)	[Protocol Method] Request text analysis over a collection of documents. This protocol method allows explicit creation of the request and processing of the response for advanced scenarios. Please try the simpler AnalyzeText(AnalyzeTextInput, Nullable<Boolean>, CancellationToken) convenience overload with strongly typed models first.

AnalyzeText(AnalyzeTextInput, Nullable<Boolean>, CancellationToken)

Source:

TextAnalysisClient.cs

Request text analysis over a collection of documents.

public virtual Azure.Response<Azure.AI.Language.Text.AnalyzeTextResult> AnalyzeText (Azure.AI.Language.Text.AnalyzeTextInput analyzeTextInput, bool? showStatistics = default, System.Threading.CancellationToken cancellationToken = default);

abstract member AnalyzeText : Azure.AI.Language.Text.AnalyzeTextInput * Nullable<bool> * System.Threading.CancellationToken -> Azure.Response<Azure.AI.Language.Text.AnalyzeTextResult>
override this.AnalyzeText : Azure.AI.Language.Text.AnalyzeTextInput * Nullable<bool> * System.Threading.CancellationToken -> Azure.Response<Azure.AI.Language.Text.AnalyzeTextResult>

Public Overridable Function AnalyzeText (analyzeTextInput As AnalyzeTextInput, Optional showStatistics As Nullable(Of Boolean) = Nothing, Optional cancellationToken As CancellationToken = Nothing) As Response(Of AnalyzeTextResult)

Parameters

analyzeTextInput

AnalyzeTextInput

The input documents to analyze.

showStatistics

Nullable<Boolean>

(Optional) if set to true, response will contain request and document level statistics.

cancellationToken

CancellationToken

The cancellation token to use.

Returns

Response<AnalyzeTextResult>

Exceptions

ArgumentNullException

analyzeTextInput is null.

Examples

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextEntityLinkingInput
{
    TextInput = new MultiLanguageTextInput
    {
        MultiLanguageInputs = {new MultiLanguageInput("1", "Microsoft was founded by Bill Gates and Paul Allen.")
        {
            Language = "en",
        }, new MultiLanguageInput("2", "Pike place market is my favorite Seattle attraction.")
        {
            Language = "en",
        }},
    },
    ActionContent = new EntityLinkingActionContent
    {
        ModelVersion = "latest",
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextEntityRecognitionInput
{
    TextInput = new MultiLanguageTextInput
    {
        MultiLanguageInputs = {new MultiLanguageInput("2", "When I was 5 years old I had $90.00 dollars to my name.")
        {
            Language = "en",
        }, new MultiLanguageInput("3", "When we flew from LAX it seemed like we were moving at 10 meters per second. I was lucky to see Amsterdam, Effile Tower, and the Nile.")
        {
            Language = "en",
        }},
    },
    ActionContent = new EntitiesActionContent
    {
        ModelVersion = "latest",
        Exclusions = { EntityCategory.Numeric },
        OverlapPolicy = new AllowOverlapEntityPolicyType(),
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextEntityRecognitionInput
{
    TextInput = new MultiLanguageTextInput
    {
        MultiLanguageInputs = {new MultiLanguageInput("2", "When I was 5 years old I had $90.00 dollars to my name.")
        {
            Language = "en",
        }, new MultiLanguageInput("3", "When we flew from LAX it seemed like we were moving at 10 meters per second. I was lucky to see Amsterdam, Effile Tower, and the Nile.")
        {
            Language = "en",
        }},
    },
    ActionContent = new EntitiesActionContent
    {
        ModelVersion = "latest",
        Inclusions = { EntityCategory.Location },
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextEntityRecognitionInput
{
    TextInput = new MultiLanguageTextInput
    {
        MultiLanguageInputs = {new MultiLanguageInput("1", "When I was 5 years old I had $90.00 dollars to my name.")
        {
            Language = "en",
        }},
    },
    ActionContent = new EntitiesActionContent
    {
        ModelVersion = "latest",
        InferenceOptions = new EntityInferenceConfig
        {
            ExcludeNormalizedValues = true,
        },
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextEntityRecognitionInput
{
    TextInput = new MultiLanguageTextInput
    {
        MultiLanguageInputs = {new MultiLanguageInput("4", "25th April Meeting was an intresting one. At least we gont to experience the WorldCup")
        {
            Language = "en",
        }},
    },
    ActionContent = new EntitiesActionContent
    {
        ModelVersion = "latest",
        OverlapPolicy = new MatchLongestEntityPolicyType(),
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextEntityRecognitionInput
{
    TextInput = new MultiLanguageTextInput
    {
        MultiLanguageInputs = {new MultiLanguageInput("2", "When I was 5 years old I had $90.00 dollars to my name.")
        {
            Language = "en",
        }, new MultiLanguageInput("3", "When we flew from LAX it seemed like we were moving at 10 meters per second. I was lucky to see Amsterdam, Effile Tower, and the Nile.")
        {
            Language = "en",
        }, new MultiLanguageInput("4", "25th April Meeting was an intresting one. At least we gont to experience the WorldCup")
        {
            Language = "en",
        }, new MultiLanguageInput("5", "My IP is 127.12.1.1 and my phone   number is 5555555555")
        {
            Language = "en",
        }},
    },
    ActionContent = new EntitiesActionContent
    {
        ModelVersion = "latest",
        OverlapPolicy = new AllowOverlapEntityPolicyType(),
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextKeyPhraseExtractionInput
{
    TextInput = new MultiLanguageTextInput
    {
        MultiLanguageInputs = {new MultiLanguageInput("1", "Microsoft was founded by Bill Gates and Paul Allen.")
        {
            Language = "en",
        }, new MultiLanguageInput("2", "Text Analytics is one of the Azure Cognitive Services.")
        {
            Language = "en",
        }, new MultiLanguageInput("3", "My cat might need to see a veterinarian.")
        {
            Language = "en",
        }},
    },
    ActionContent = new KeyPhraseActionContent
    {
        ModelVersion = "latest",
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextLanguageDetectionInput
{
    TextInput = new LanguageDetectionTextInput
    {
        LanguageInputs = { new LanguageInput("1", "Hello world"), new LanguageInput("2", "Bonjour tout le monde"), new LanguageInput("3", "Hola mundo"), new LanguageInput("4", "Tumhara naam kya hai?") },
    },
    ActionContent = new LanguageDetectionActionContent
    {
        ModelVersion = "latest",
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextPiiEntitiesRecognitionInput
{
    TextInput = new MultiLanguageTextInput
    {
        MultiLanguageInputs = {new MultiLanguageInput("1", "My SSN is 859-98-0987")
        {
            Language = "en",
        }, new MultiLanguageInput("2", "Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check.")
        {
            Language = "en",
        }, new MultiLanguageInput("3", "Is 998.214.865-68 your Brazilian CPF number?")
        {
            Language = "en",
        }},
    },
    ActionContent = new PiiActionContent
    {
        ModelVersion = "latest",
        ExcludePiiCategories = { PiiCategoriesExclude.UsSocialSecurityNumber },
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextPiiEntitiesRecognitionInput
{
    TextInput = new MultiLanguageTextInput
    {
        MultiLanguageInputs = {new MultiLanguageInput("1", "My name is John Doe My phone number is 424 878 9192")
        {
            Language = "en",
        }},
    },
    ActionContent = new PiiActionContent
    {
        ModelVersion = "latest",
        RedactionPolicy = new EntityMaskPolicyType(),
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextPiiEntitiesRecognitionInput
{
    TextInput = new MultiLanguageTextInput
    {
        MultiLanguageInputs = {new MultiLanguageInput("1", "My SSN is 859-98-0987")
        {
            Language = "en",
        }, new MultiLanguageInput("2", "Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check.")
        {
            Language = "en",
        }, new MultiLanguageInput("3", "Is 998.214.865-68 your Brazilian CPF number?")
        {
            Language = "en",
        }},
    },
    ActionContent = new PiiActionContent
    {
        ModelVersion = "latest",
        RedactionPolicy = new CharacterMaskPolicyType
        {
            RedactionCharacter = RedactionCharacter.Minus,
        },
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextPiiEntitiesRecognitionInput
{
    TextInput = new MultiLanguageTextInput
    {
        MultiLanguageInputs = {new MultiLanguageInput("1", "My SSN is 859-98-0987")
        {
            Language = "en",
        }, new MultiLanguageInput("2", "Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check.")
        {
            Language = "en",
        }, new MultiLanguageInput("3", "Is 998.214.865-68 your Brazilian CPF number?")
        {
            Language = "en",
        }},
    },
    ActionContent = new PiiActionContent
    {
        ModelVersion = "latest",
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

This sample shows how to call AnalyzeText.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

AnalyzeTextInput analyzeTextInput = new TextSentimentAnalysisInput
{
    TextInput = new MultiLanguageTextInput
    {
        MultiLanguageInputs = {new MultiLanguageInput("1", "Great atmosphere. Close to plenty of restaurants, hotels, and transit! Staff are friendly and helpful.")
        {
            Language = "en",
        }},
    },
    ActionContent = new SentimentAnalysisActionContent
    {
        ModelVersion = "latest",
    },
};
Response<AnalyzeTextResult> response = client.AnalyzeText(analyzeTextInput);

AnalyzeText(RequestContent, Nullable<Boolean>, RequestContext)

Source:

TextAnalysisClient.cs

[Protocol Method] Request text analysis over a collection of documents.

• This protocol method allows explicit creation of the request and processing of the response for advanced scenarios.
• Please try the simpler AnalyzeText(AnalyzeTextInput, Nullable<Boolean>, CancellationToken) convenience overload with strongly typed models first.

public virtual Azure.Response AnalyzeText (Azure.Core.RequestContent content, bool? showStatistics = default, Azure.RequestContext context = default);

abstract member AnalyzeText : Azure.Core.RequestContent * Nullable<bool> * Azure.RequestContext -> Azure.Response
override this.AnalyzeText : Azure.Core.RequestContent * Nullable<bool> * Azure.RequestContext -> Azure.Response

Public Overridable Function AnalyzeText (content As RequestContent, Optional showStatistics As Nullable(Of Boolean) = Nothing, Optional context As RequestContext = Nothing) As Response

Parameters

content

RequestContent

The content to send as the body of the request.

showStatistics

Nullable<Boolean>

(Optional) if set to true, response will contain request and document level statistics.

context

RequestContext

The request context, which can override default behaviors of the client pipeline on a per-call basis.

Returns

Response

The response returned from the service.

Exceptions

ArgumentNullException

content is null.

RequestFailedException

Service returned a non-success status code.

Examples

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "EntityLinking",
    parameters = new
    {
        modelVersion = "latest",
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "1",
                language = "en",
                text = "Microsoft was founded by Bill Gates and Paul Allen.",
            },
            new
            {
                id = "2",
                language = "en",
                text = "Pike place market is my favorite Seattle attraction.",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "EntityRecognition",
    parameters = new
    {
        modelVersion = "latest",
        exclusionList = new object[]
        {
            "Numeric"
        },
        overlapPolicy = new
        {
            policyKind = "allowOverlap",
        },
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "2",
                language = "en",
                text = "When I was 5 years old I had $90.00 dollars to my name.",
            },
            new
            {
                id = "3",
                language = "en",
                text = "When we flew from LAX it seemed like we were moving at 10 meters per second. I was lucky to see Amsterdam, Effile Tower, and the Nile.",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "EntityRecognition",
    parameters = new
    {
        modelVersion = "latest",
        inclusionList = new object[]
        {
            "Location"
        },
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "2",
                language = "en",
                text = "When I was 5 years old I had $90.00 dollars to my name.",
            },
            new
            {
                id = "3",
                language = "en",
                text = "When we flew from LAX it seemed like we were moving at 10 meters per second. I was lucky to see Amsterdam, Effile Tower, and the Nile.",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "EntityRecognition",
    parameters = new
    {
        modelVersion = "latest",
        inferenceOptions = new
        {
            excludeNormalizedValues = true,
        },
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "1",
                language = "en",
                text = "When I was 5 years old I had $90.00 dollars to my name.",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "EntityRecognition",
    parameters = new
    {
        modelVersion = "latest",
        overlapPolicy = new
        {
            policyKind = "matchLongest",
        },
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "4",
                language = "en",
                text = "25th April Meeting was an intresting one. At least we gont to experience the WorldCup",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "EntityRecognition",
    parameters = new
    {
        modelVersion = "latest",
        overlapPolicy = new
        {
            policyKind = "allowOverlap",
        },
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "2",
                language = "en",
                text = "When I was 5 years old I had $90.00 dollars to my name.",
            },
            new
            {
                id = "3",
                language = "en",
                text = "When we flew from LAX it seemed like we were moving at 10 meters per second. I was lucky to see Amsterdam, Effile Tower, and the Nile.",
            },
            new
            {
                id = "4",
                language = "en",
                text = "25th April Meeting was an intresting one. At least we gont to experience the WorldCup",
            },
            new
            {
                id = "5",
                language = "en",
                text = "My IP is 127.12.1.1 and my phone   number is 5555555555",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "KeyPhraseExtraction",
    parameters = new
    {
        modelVersion = "latest",
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "1",
                language = "en",
                text = "Microsoft was founded by Bill Gates and Paul Allen.",
            },
            new
            {
                id = "2",
                language = "en",
                text = "Text Analytics is one of the Azure Cognitive Services.",
            },
            new
            {
                id = "3",
                language = "en",
                text = "My cat might need to see a veterinarian.",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "LanguageDetection",
    parameters = new
    {
        modelVersion = "latest",
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "1",
                text = "Hello world",
            },
            new
            {
                id = "2",
                text = "Bonjour tout le monde",
            },
            new
            {
                id = "3",
                text = "Hola mundo",
            },
            new
            {
                id = "4",
                text = "Tumhara naam kya hai?",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "PiiEntityRecognition",
    parameters = new
    {
        modelVersion = "latest",
        excludePiiCategories = new object[]
        {
            "USSocialSecurityNumber"
        },
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "1",
                language = "en",
                text = "My SSN is 859-98-0987",
            },
            new
            {
                id = "2",
                language = "en",
                text = "Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check.",
            },
            new
            {
                id = "3",
                language = "en",
                text = "Is 998.214.865-68 your Brazilian CPF number?",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "PiiEntityRecognition",
    parameters = new
    {
        modelVersion = "latest",
        redactionPolicy = new
        {
            policyKind = "entityMask",
        },
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "1",
                language = "en",
                text = "My name is John Doe My phone number is 424 878 9192",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "PiiEntityRecognition",
    parameters = new
    {
        modelVersion = "latest",
        redactionPolicy = new
        {
            policyKind = "characterMask",
            redactionCharacter = "-",
        },
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "1",
                language = "en",
                text = "My SSN is 859-98-0987",
            },
            new
            {
                id = "2",
                language = "en",
                text = "Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check.",
            },
            new
            {
                id = "3",
                language = "en",
                text = "Is 998.214.865-68 your Brazilian CPF number?",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "PiiEntityRecognition",
    parameters = new
    {
        modelVersion = "latest",
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "1",
                language = "en",
                text = "My SSN is 859-98-0987",
            },
            new
            {
                id = "2",
                language = "en",
                text = "Your ABA number - 111000025 - is the first 9 digits in the lower left hand corner of your personal check.",
            },
            new
            {
                id = "3",
                language = "en",
                text = "Is 998.214.865-68 your Brazilian CPF number?",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());

This sample shows how to call AnalyzeText and parse the result.

Uri endpoint = new Uri("<endpoint>");
AzureKeyCredential credential = new AzureKeyCredential("<key>");
TextAnalysisClient client = new TextAnalysisClient(endpoint, credential);

using RequestContent content = RequestContent.Create(new
{
    kind = "SentimentAnalysis",
    parameters = new
    {
        modelVersion = "latest",
    },
    analysisInput = new
    {
        documents = new object[]
        {
            new
            {
                id = "1",
                language = "en",
                text = "Great atmosphere. Close to plenty of restaurants, hotels, and transit! Staff are friendly and helpful.",
            }
        },
    },
});
Response response = client.AnalyzeText(content);

JsonElement result = JsonDocument.Parse(response.ContentStream).RootElement;
Console.WriteLine(result.GetProperty("kind").ToString());