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if (!response.IsSuccessStatusCode)

            {

                throw new Exception("Call to get key phrases failed with HTTP status code: " +

                                    response.StatusCode + " and contents: " + content);

            }

Based on the information in the comments, I created an account at this link: https://datamarket.azure.com/account/keys and used the key that is provided, but I am getting the above error.

Here is the code in case you do not want to download from github:

 class Program

    {

        static string searchServiceName = "<removed>";     // Learn more here: https://azure.microsoft.com/en-us/documentation/articles/search-what-is-azure-search/

        static string searchServiceAPIKey = "<removed>";

        static string azureMLTextAnalyticsKey = "<removed>";     // Learn more here: https://azure.microsoft.com/en-us/documentation/articles/machine-learning-apps-text-analytics/

        static string indexName = "textanalytics";

        static SearchServiceClient serviceClient = new SearchServiceClient(searchServiceName, new SearchCredentials(searchServiceAPIKey));

        static SearchIndexClient indexClient = serviceClient.Indexes.GetClient(indexName);

       static void Main(string[] args)

        {

            string filetext = "Build great search experiences for your web and mobile apps. " +

                "Many applications use search as the primary interaction pattern for their users. When it comes to search, user expectations are high. They expect great relevance, suggestions, near-instantaneous responses, multiple languages, faceting, and more. Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. The integrated Microsoft natural language stack, also used in Bing and Office, has been improved over 16 years of development. Quickly and easily tune search results, and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios. " +

                "Reduce complexity with a fully managed service. " +

                "Azure Search removes the complexity of setting up and managing your own search index. This fully managed service helps you avoid the hassle of dealing with index corruption, service availability, scaling, and service updates. Create multiple indexes with no incremental cost per index. Easily scale up or down as the traffic and data volume of your application changes.";

            // Note, this will create a new Azure Search Index for the text and the key phrases

            Console.WriteLine("Creating Azure Search index...");

            AzureSearch.CreateIndex(serviceClient, indexName);

           // Apply the Machine Learning Text Extraction to retrieve only the key phrases

            Console.WriteLine("Extracting key phrases from processed text... \r\n");

            KeyPhraseResult keyPhraseResult = TextExtraction.ProcessText(azureMLTextAnalyticsKey, filetext);

            Console.WriteLine("Found the following phrases... \r\n");

            foreach (var phrase in keyPhraseResult.KeyPhrases)

                Console.WriteLine(phrase);

            // Take the resulting key phrases to a new Azure Search Index

            // It is highly recommended that you upload documents in batches rather 

            // individually like is done here

            Console.WriteLine("Uploading extracted text to Azure Search...\r\n");

            AzureSearch.UploadDocuments(indexClient, "1", keyPhraseResult);

            Console.WriteLine("Wait 5 seconds for content to become searchable...\r\n");

            Thread.Sleep(5000);

            // Execute a test search 

            Console.WriteLine("Execute Search...");

            AzureSearch.SearchDocuments(indexClient, "Azure Search");

            Console.WriteLine("All done.  Press any key to continue.");

            Console.ReadLine();

        }

    }

The below is in the TextExtractionHelper class:

/// <summary>

/// This is a sample program that shows how to use the Azure ML Text Analytics app (https://datamarket.azure.com/dataset/amla/text-analytics)

/// </summary>

public class TextExtraction

{

    private const string ServiceBaseUri = "https://api.datamarket.azure.com/";

    public static KeyPhraseResult ProcessText(string accountKey, string inputText)

    {

        KeyPhraseResult keyPhraseResult = new KeyPhraseResult();

        using (var httpClient = new HttpClient())

        {

            string inputTextEncoded = HttpUtility.UrlEncode(inputText);

            httpClient.BaseAddress = new Uri(ServiceBaseUri);

            string creds = "AccountKey:" + accountKey;

            string authorizationHeader = "Basic " + Convert.ToBase64String(Encoding.ASCII.GetBytes(creds));

            httpClient.DefaultRequestHeaders.Add("Authorization", authorizationHeader);

            httpClient.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));

            // get key phrases

            string keyPhrasesRequest = "data.ashx/amla/text-analytics/v1/GetKeyPhrases?Text=" + inputTextEncoded;

            Task<HttpResponseMessage> responseTask = httpClient.GetAsync(keyPhrasesRequest);

            responseTask.Wait();

            HttpResponseMessage response = responseTask.Result;

            Task<string> contentTask = response.Content.ReadAsStringAsync();

            contentTask.Wait();

            string content = contentTask.Result;

            if (!response.IsSuccessStatusCode)

            {

                throw new Exception("Call to get key phrases failed with HTTP status code: " +

                                    response.StatusCode + " and contents: " + content);

            }

            keyPhraseResult = JsonConvert.DeserializeObject<KeyPhraseResult>(content);

        }

        return keyPhraseResult;

    }

}

/// <summary>

/// Class to hold result of Key Phrases call

/// </summary>

public class KeyPhraseResult

{

    public List<string> KeyPhrases { get; set; }

}

/// <summary>

/// Class to hold result of Sentiment call

/// </summary>

public class SentimentResult

{

    public double Score { get; set; }

}

/// <summary>

/// Class to hold result of Language detection call

/// </summary>

public class LanguageResult

{

    public bool UnknownLanguage { get; set; }

    public IList<DetectedLanguage> DetectedLanguages { get; set; }

}

/// <summary>

/// Class to hold information about a single detected language

/// </summary>

public class DetectedLanguage

{

    public string Name { get; set; }

    /// <summary>

    /// This is the short ISO 639-1 standard form of representing

    /// all languages. The short form is a 2 letter representation of the language.

    /// en = English, fr = French for example

    /// </summary>

    public string Iso6391Name { get; set; }

    public double Score { get; set; }

}

UPDATE

After many hours of taking different sample code and trying to put them together, I finally got something "kind of" working. Here is all my code:

class Program

{

    static string searchServiceName = "<removed>";     // Learn more here: https://azure.microsoft.com/en-us/documentation/articles/search-what-is-azure-search/

    static string searchServiceAPIKey = "<removed>";

    //static string azureMLTextAnalyticsKey = "<removed>";     // Learn more here: https://azure.microsoft.com/en-us/documentation/articles/machine-learning-apps-text-analytics/

    static string indexName = "textanalytics";

    static SearchServiceClient serviceClient = new SearchServiceClient(searchServiceName, new SearchCredentials(searchServiceAPIKey));

    static SearchIndexClient indexClient = serviceClient.Indexes.GetClient(indexName);

    static void Main()

    {

        MakeRequests();

        Console.WriteLine("Hit ENTER to exit...");

        Console.ReadLine();

    }

    static async void MakeRequests()

    {

        // Note, this will create a new Azure Search Index for the text and the key phrases

        Console.WriteLine("Creating Azure Search index...");

        AzureSearch.CreateIndex(serviceClient, indexName);

        // Apply the Machine Learning Text Extraction to retrieve only the key phrases

        Console.WriteLine("Extracting key phrases from processed text... \r\n");

        KeyPhraseResult keyPhraseResult = await TextExtraction.ProcessText();

        Console.WriteLine("Found the following phrases... \r\n");

        foreach (var phrase in keyPhraseResult.KeyPhrases)

            Console.WriteLine(phrase);

        // Take the resulting key phrases to a new Azure Search Index

        // It is highly recommended that you upload documents in batches rather 

        // individually like is done here

        Console.WriteLine("Uploading extracted text to Azure Search...\r\n");

        AzureSearch.UploadDocuments(indexClient, "1", keyPhraseResult);

        Console.WriteLine("Wait 5 seconds for content to become searchable...\r\n");

        Thread.Sleep(5000);

        // Execute a test search 

        Console.WriteLine("Execute Search...");

        AzureSearch.SearchDocuments(indexClient, "Azure Search");

        Console.WriteLine("All done.  Press any key to continue.");

        Console.ReadLine();

    }

}

Here is my TextExtractionHelper class:

public class TextExtraction

{

    static string azureMLTextAnalyticsKey = "<Removed>";     // Learn more here: https://azure.microsoft.com/en-us/documentation/articles/machine-learning-apps-text-analytics/

    private const string ServiceBaseUri = "https://westus.api.cognitive.microsoft.com/";

    public static async Task<KeyPhraseResult> ProcessText()

    {

        string filetext = "Build great search experiences for your web and mobile apps. " +

            "Many applications use search as the primary interaction pattern for their users. When it comes to search, user expectations are high. They expect great relevance, suggestions, near-instantaneous responses, multiple languages, faceting, and more. Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. The integrated Microsoft natural language stack, also used in Bing and Office, has been improved over 16 years of development. Quickly and easily tune search results, and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios. " +

            "Reduce complexity with a fully managed service. " +

            "Azure Search removes the complexity of setting up and managing your own search index. This fully managed service helps you avoid the hassle of dealing with index corruption, service availability, scaling, and service updates. Create multiple indexes with no incremental cost per index. Easily scale up or down as the traffic and data volume of your application changes.";

        KeyPhraseResult keyPhraseResult = new KeyPhraseResult();

        using (var httpClient = new HttpClient())

        {

            httpClient.BaseAddress = new Uri(ServiceBaseUri);

            // Request headers.

            httpClient.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", azureMLTextAnalyticsKey);         httpClient.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));

            byte[] byteData = Encoding.UTF8.GetBytes("{\"documents\":[" +

               "{\"id\":\"1\",\"text\":\"" + filetext + "\"},]}");

            //byte[] byteData = Encoding.UTF8.GetBytes("{\"documents\":[" +

            //   "{\"id\":\"1\",\"text\":\"Build great search experiences for your web and mobile apps." +

            //   "Many applications use search as the primary interaction pattern for their users. When it comes to search, user expectations are high. They expect great relevance, suggestions, near-instantaneous responses, multiple languages, faceting, and more. Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. The integrated Microsoft natural language stack, also used in Bing and Office, has been improved over 16 years of development. Quickly and easily tune search results, and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios." +

            //   "Reduce complexity with a fully managed service. " +

            //   "Azure Search removes the complexity of setting up and managing your own search index. This fully managed service helps you avoid the hassle of dealing with index corruption, service availability, scaling, and service updates. Create multiple indexes with no incremental cost per index. Easily scale up or down as the traffic and data volume of your application changes.\"}," +

            //   "]}");

            // Detect key phrases:

            var keyPhrasesRequest = "text/analytics/v2.0/keyPhrases";

            //var response = await CallEndpoint(httpClient, uri, byteData);

            // get key phrases

            using (var getcontent = new ByteArrayContent(byteData))

            {

                getcontent.Headers.ContentType = new MediaTypeHeaderValue("application/json");

                var response = await httpClient.PostAsync(keyPhrasesRequest, getcontent);

                Task<string> contentTask = response.Content.ReadAsStringAsync();

                string content = contentTask.Result;

                if (!response.IsSuccessStatusCode)

                {

                    throw new Exception("Call to get key phrases failed with HTTP status code: " +

                                        response.StatusCode + " and contents: " + content);

                }

                keyPhraseResult = JsonConvert.DeserializeObject<KeyPhraseResult>(content);

                //return await response.Content.ReadAsStringAsync();

            }

        }

        return keyPhraseResult;

    }

}

/// <summary>

/// Class to hold result of Key Phrases call

/// </summary>

public class KeyPhraseResult

{

    public List<string> KeyPhrases { get; set; }

}

/// <summary>

/// Class to hold result of Sentiment call

/// </summary>

public class SentimentResult

{

    public double Score { get; set; }

}

/// <summary>

/// Class to hold result of Language detection call

/// </summary>

public class LanguageResult

{

    public bool UnknownLanguage { get; set; }

    public IList<DetectedLanguage> DetectedLanguages { get; set; }

}

/// <summary>

/// Class to hold information about a single detected language

/// </summary>

public class DetectedLanguage

{

    public string Name { get; set; }

    /// <summary>

    /// This is the short ISO 639-1 standard form of representing

    /// all languages. The short form is a 2 letter representation of the language.

    /// en = English, fr = French for example

    /// </summary>

    public string Iso6391Name { get; set; }

    public double Score { get; set; }

}

So I am now able to pull the KeyPhrases from the text! But, now I am sitting with a problem where it doesn't seem like the JSON string is being deserialized and my keyPhraseResult is now getting a null value.

What am I missing?

If anyone is able to help, I would greatly appreciate it.

1 Answer

0 votes
by (9.6k points)

Hope this works:

using Microsoft.Azure.Search;

using System;

using System.Configuration;

using System.IO;

using System.Threading;

namespace AzureSearchTextAnalytics

{

class Program

{

    static string searchServiceName = "<removed>";     // This is the Azure Search service name that you create in Azure

    static string searchServiceAPIKey = "<removed>";   // This is the Primary key that is provided after creating a Azure Search Service

    static string indexName = "textanalytics";

    static SearchServiceClient serviceClient = new SearchServiceClient(searchServiceName, new SearchCredentials(searchServiceAPIKey));

    static SearchIndexClient indexClient = serviceClient.Indexes.GetClient(indexName);

    static void Main()

    {

        MakeRequests();

        Console.WriteLine("Hit ENTER to exit...");

        Console.ReadLine();

    }

    static async void MakeRequests()

    {

        // Note, this will create a new Azure Search Index for the text and the key phrases

        Console.WriteLine("Creating Azure Search index...");

        AzureSearch.CreateIndex(serviceClient, indexName);

        // Apply the Machine Learning Text Extraction to retrieve only the key phrases

        Console.WriteLine("Extracting key phrases from processed text... \r\n");

        KeyPhraseResult keyPhraseResult = await TextExtraction.ProcessText();

        Console.WriteLine("Found the following phrases... \r\n");

        foreach (var phrase in keyPhraseResult.KeyPhrases)

            Console.WriteLine(phrase);

        // Take the resulting key phrases to a new Azure Search Index

        // It is highly recommended that you upload documents in batches rather 

        // individually like is done here

        Console.WriteLine("Uploading extracted text to Azure Search...\r\n");

        AzureSearch.UploadDocuments(indexClient, "1", keyPhraseResult);

        Console.WriteLine("Wait 5 seconds for content to become searchable...\r\n");

        Thread.Sleep(5000);

        // Execute a test search 

        Console.WriteLine("Execute Search...");

        AzureSearch.SearchDocuments(indexClient, "Azure Search");

        Console.WriteLine("All done.  Press any key to continue.");

        Console.ReadLine();

    }

}

}

My TextExtractionHelper.cs:

using System;

using System.Collections.Generic;

using System.Linq;

using System.Net.Http;

using System.Net.Http.Headers;

using System.Text;

using System.Threading.Tasks;

using System.Web;

using Newtonsoft.Json;

using System.Configuration; // get it from http://www.newtonsoft.com/json

using Newtonsoft.Json.Linq;

namespace AzureSearchTextAnalytics

{

/// </summary>

public class TextExtraction

{

    static string azureMLTextAnalyticsKey = "<removed>";     // This key you will get when you have added TextAnalytics in Azure.

    private const string ServiceBaseUri = "https://westus.api.cognitive.microsoft.com/"; //This you will get when you have added TextAnalytics in Azure

    public static async Task<KeyPhraseResult> ProcessText()

    {

        string filetext = "Build great search experiences for your web and mobile apps. " +

            "Many applications use search as the primary interaction pattern for their users. When it comes to search, user expectations are high. They expect great relevance, suggestions, near-instantaneous responses, multiple languages, faceting, and more. Azure Search makes it easy to add powerful and sophisticated search capabilities to your website or application. The integrated Microsoft natural language stack, also used in Bing and Office, has been improved over 16 years of development. Quickly and easily tune search results, and construct rich, fine-tuned ranking models to tie search results to business goals. Reliable throughput and storage provide fast search indexing and querying to support time-sensitive search scenarios. " +

            "Reduce complexity with a fully managed service. " +

            "Azure Search removes the complexity of setting up and managing your own search index. This fully managed service helps you avoid the hassle of dealing with index corruption, service availability, scaling, and service updates. Create multiple indexes with no incremental cost per index. Easily scale up or down as the traffic and data volume of your application changes.";

        KeyPhraseResult keyPhraseResult = new KeyPhraseResult();

        using (var httpClient = new HttpClient())

        {

            httpClient.BaseAddress = new Uri(ServiceBaseUri);

            // Request headers.

            httpClient.DefaultRequestHeaders.Add("Ocp-Apim-Subscription-Key", azureMLTextAnalyticsKey);

            httpClient.DefaultRequestHeaders.Accept.Add(new MediaTypeWithQualityHeaderValue("application/json"));

           byte[] byteData = Encoding.UTF8.GetBytes("{\"documents\":[" +

               "{\"id\":\"1\",\"text\":\"" + filetext + "\"},]}");

            // Detect key phrases:

            var keyPhrasesRequest = "text/analytics/v2.0/keyPhrases";

            // get key phrases

            using (var getcontent = new ByteArrayContent(byteData))

            {

                getcontent.Headers.ContentType = new MediaTypeHeaderValue("application/json");

                var response = await httpClient.PostAsync(keyPhrasesRequest, getcontent);

                Task<string> contentTask = response.Content.ReadAsStringAsync();

                string content = contentTask.Result;

                if (!response.IsSuccessStatusCode)

                {

                    throw new Exception("Call to get key phrases failed with HTTP status code: " +                                        response.StatusCode + " and contents: " + content);

                }

                var result = JsonConvert.DeserializeObject<RootObject>(content);

                keyPhraseResult.KeyPhrases = result.documents[0].keyPhrases;

            }

        }

        return keyPhraseResult;

    }

}

public class Documents

{

    public List<string> keyPhrases { get; set; }

    public string id { get; set; }

}

public class RootObject

{

    public List<Documents> documents { get; set; }

    public List<object> errors { get; set; }

}

/// <summary>

/// Class to hold result of Key Phrases call

/// </summary>

public class KeyPhraseResult

{

    public List<string> KeyPhrases { get; set; }

}

}

AzureSearch.cs:

using Microsoft.Azure.Search;

using Microsoft.Azure.Search.Models;

using System;

using System.Collections.Generic;

using System.Configuration;

using System.Linq;

using System.Text;

using System.Threading.Tasks;

namespace AzureSearchTextAnalytics

{

public class AzureSearch

{

    public static void CreateIndex(SearchServiceClient serviceClient, string indexName)

    {

        if (serviceClient.Indexes.Exists(indexName))

        {

            serviceClient.Indexes.Delete(indexName);

        }

        var definition = new Index()

        {

            Name = indexName,

            Fields = new[]

            {

                new Field("fileId", DataType.String)                       { IsKey = true },

                new Field("fileText", DataType.String)                      { IsSearchable = true, IsFilterable = false, IsSortable = false, IsFacetable = false },

                new Field("keyPhrases", DataType.Collection(DataType.String)) { IsSearchable = true, IsFilterable = true,  IsFacetable = true }

            }

        };

        serviceClient.Indexes.Create(definition);

    }

    public static void UploadDocuments(SearchIndexClient indexClient, string fileId, KeyPhraseResult keyPhraseResult)

    {

        List<IndexAction> indexOperations = new List<IndexAction>();

        var doc = new Document();

        doc.Add("fileId", fileId);

        doc.Add("keyPhrases", keyPhraseResult.KeyPhrases.ToList());

        indexOperations.Add(IndexAction.Upload(doc));

        try

        {

            indexClient.Documents.Index(new IndexBatch(indexOperations));

        }

        catch (IndexBatchException e)

        {

            // Sometimes when your Search service is under load, indexing will fail for some of the documents in

            // the batch. Depending on your application, you can take compensating actions like delaying and

            // retrying. For this simple demo, we just log the failed document keys and continue.

            Console.WriteLine(

            "Failed to index some of the documents: {0}",

                   String.Join(", ", e.IndexingResults.Where(r => !r.Succeeded).Select(r => r.Key)));

        }

    }

    public static void SearchDocuments(SearchIndexClient indexClient, string searchText)

    {

        // Search using the supplied searchText and output documents that match 

        try

        {

            var sp = new SearchParameters();

            DocumentSearchResult<OCRTextIndex> response = indexClient.Documents.Search<OCRTextIndex>(searchText, sp);

            foreach (SearchResult<OCRTextIndex> result in response.Results)

            {

                Console.WriteLine("File ID: {0}", result.Document.fileId);

                Console.WriteLine("Key Phrases: {0}", string.Join(",", result.Document.keyPhrases));

            }

        }

        catch (Exception e)

        {

            Console.WriteLine("Failed search: {0}", e.Message.ToString());

        }

    }

}

}

DataModel.cs:

using Microsoft.Azure.Search.Models;

using System;

using System.Collections.Generic;

using System.Linq;

using System.Text;

using System.Threading.Tasks;

namespace AzureSearchTextAnalytics

{

[SerializePropertyNamesAsCamelCase]

public class OCRTextIndex

{

    public string fileId { get; set; }

    public string[] keyPhrases { get; set; }

}

}

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