class Azure::CognitiveServices::TextAnalytics::V2_1::TextAnalyticsClient

A service client - single point of access to the REST API.

Attributes

accept_language[RW]

@return [String] The preferred language for the response.

base_url[R]

@return [String] the base URI of the service.

credentials[RW]

@return Subscription credentials which uniquely identify client subscription.

credentials1[R]

@return Credentials needed for the client to connect to Azure.

endpoint[RW]

@return [String] Supported Cognitive Services endpoints (protocol and hostname, for example: westus.api.cognitive.microsoft.com).

generate_client_request_id[RW]

@return [Boolean] Whether a unique x-ms-client-request-id should be generated. When set to true a unique x-ms-client-request-id value is generated and included in each request. Default is true.

long_running_operation_retry_timeout[RW]

@return [Integer] The retry timeout in seconds for Long Running Operations. Default value is 30.

Public Class Methods

new(credentials = nil, options = nil) click to toggle source

Creates initializes a new instance of the TextAnalyticsClient class. @param credentials [MsRest::ServiceClientCredentials] credentials to authorize HTTP requests made by the service client. @param options [Array] filters to be applied to the HTTP requests.

Calls superclass method
# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 45
def initialize(credentials = nil, options = nil)
  super(credentials, options)
  @base_url = '{Endpoint}/text/analytics/v2.1'

  fail ArgumentError, 'invalid type of credentials input parameter' unless credentials.is_a?(MsRest::ServiceClientCredentials) unless credentials.nil?
  @credentials = credentials

  @accept_language = 'en-US'
  @long_running_operation_retry_timeout = 30
  @generate_client_request_id = true
  add_telemetry
end

Public Instance Methods

detect_language(show_stats:nil, language_batch_input:nil, custom_headers:nil) click to toggle source

The API returns the detected language and a numeric score between 0 and 1.

Scores close to 1 indicate 100% certainty that the identified language is true. A total of 120 languages are supported.

@param show_stats [Boolean] (optional) if set to true, response will contain input and document level statistics. @param language_batch_input [LanguageBatchInput] Collection of documents to analyze. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.

@return [LanguageBatchResult] operation results.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 131
def detect_language(show_stats:nil, language_batch_input:nil, custom_headers:nil)
  response = detect_language_async(show_stats:show_stats, language_batch_input:language_batch_input, custom_headers:custom_headers).value!
  response.body unless response.nil?
end
detect_language_async(show_stats:nil, language_batch_input:nil, custom_headers:nil) click to toggle source

The API returns the detected language and a numeric score between 0 and 1.

Scores close to 1 indicate 100% certainty that the identified language is true. A total of 120 languages are supported.

@param show_stats [Boolean] (optional) if set to true, response will contain input and document level statistics. @param language_batch_input [LanguageBatchInput] Collection of documents to analyze. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.

@return [Concurrent::Promise] Promise object which holds the HTTP response.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 170
def detect_language_async(show_stats:nil, language_batch_input:nil, custom_headers:nil)
  fail ArgumentError, 'endpoint is nil' if endpoint.nil?


  request_headers = {}
  request_headers['Content-Type'] = 'application/json; charset=utf-8'

  # Set Headers
  request_headers['x-ms-client-request-id'] = SecureRandom.uuid
  request_headers['accept-language'] = accept_language unless accept_language.nil?

  # Serialize Request
  request_mapper = Azure::CognitiveServices::TextAnalytics::V2_1::Models::LanguageBatchInput.mapper()
  request_content = self.serialize(request_mapper,  language_batch_input)
  request_content = request_content != nil ? JSON.generate(request_content, quirks_mode: true) : nil

  path_template = 'languages'

  request_url = @base_url || self.base_url
request_url = request_url.gsub('{Endpoint}', endpoint)

  options = {
      middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]],
      query_params: {'showStats' => show_stats},
      body: request_content,
      headers: request_headers.merge(custom_headers || {}),
      base_url: request_url
  }
  promise = self.make_request_async(:post, path_template, options)

  promise = promise.then do |result|
    http_response = result.response
    status_code = http_response.status
    response_content = http_response.body
    unless status_code == 200
      error_model = JSON.load(response_content)
      fail MsRest::HttpOperationError.new(result.request, http_response, error_model)
    end

    result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil?
    # Deserialize Response
    if status_code == 200
      begin
        parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content)
        result_mapper = Azure::CognitiveServices::TextAnalytics::V2_1::Models::LanguageBatchResult.mapper()
        result.body = self.deserialize(result_mapper, parsed_response)
      rescue Exception => e
        fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result)
      end
    end

    result
  end

  promise.execute
end
detect_language_with_http_info(show_stats:nil, language_batch_input:nil, custom_headers:nil) click to toggle source

The API returns the detected language and a numeric score between 0 and 1.

Scores close to 1 indicate 100% certainty that the identified language is true. A total of 120 languages are supported.

@param show_stats [Boolean] (optional) if set to true, response will contain input and document level statistics. @param language_batch_input [LanguageBatchInput] Collection of documents to analyze. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.

@return [MsRestAzure::AzureOperationResponse] HTTP response information.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 151
def detect_language_with_http_info(show_stats:nil, language_batch_input:nil, custom_headers:nil)
  detect_language_async(show_stats:show_stats, language_batch_input:language_batch_input, custom_headers:custom_headers).value!
end
entities(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil) click to toggle source

The API returns a list of recognized entities in a given document.

To get even more information on each recognized entity we recommend using the Bing Entity Search API by querying for the recognized entities names. See the <a href=“Supported”>docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/text-analytics-supported-languages“>Supported languages in Text Analytics API</a> for the list of enabled languages.

@param show_stats [Boolean] (optional) if set to true, response will contain input and document level statistics. @param multi_language_batch_input [MultiLanguageBatchInput] Collection of documents to analyze. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.

@return [EntitiesBatchResult] operation results.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 245
def entities(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil)
  response = entities_async(show_stats:show_stats, multi_language_batch_input:multi_language_batch_input, custom_headers:custom_headers).value!
  response.body unless response.nil?
end
entities_async(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil) click to toggle source

The API returns a list of recognized entities in a given document.

To get even more information on each recognized entity we recommend using the Bing Entity Search API by querying for the recognized entities names. See the <a href=“Supported”>docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/text-analytics-supported-languages“>Supported languages in Text Analytics API</a> for the list of enabled languages.

@param show_stats [Boolean] (optional) if set to true, response will contain input and document level statistics. @param multi_language_batch_input [MultiLanguageBatchInput] Collection of documents to analyze. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.

@return [Concurrent::Promise] Promise object which holds the HTTP response.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 290
def entities_async(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil)
  fail ArgumentError, 'endpoint is nil' if endpoint.nil?


  request_headers = {}
  request_headers['Content-Type'] = 'application/json; charset=utf-8'

  # Set Headers
  request_headers['x-ms-client-request-id'] = SecureRandom.uuid
  request_headers['accept-language'] = accept_language unless accept_language.nil?

  # Serialize Request
  request_mapper = Azure::CognitiveServices::TextAnalytics::V2_1::Models::MultiLanguageBatchInput.mapper()
  request_content = self.serialize(request_mapper,  multi_language_batch_input)
  request_content = request_content != nil ? JSON.generate(request_content, quirks_mode: true) : nil

  path_template = 'entities'

  request_url = @base_url || self.base_url
request_url = request_url.gsub('{Endpoint}', endpoint)

  options = {
      middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]],
      query_params: {'showStats' => show_stats},
      body: request_content,
      headers: request_headers.merge(custom_headers || {}),
      base_url: request_url
  }
  promise = self.make_request_async(:post, path_template, options)

  promise = promise.then do |result|
    http_response = result.response
    status_code = http_response.status
    response_content = http_response.body
    unless status_code == 200
      error_model = JSON.load(response_content)
      fail MsRest::HttpOperationError.new(result.request, http_response, error_model)
    end

    result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil?
    # Deserialize Response
    if status_code == 200
      begin
        parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content)
        result_mapper = Azure::CognitiveServices::TextAnalytics::V2_1::Models::EntitiesBatchResult.mapper()
        result.body = self.deserialize(result_mapper, parsed_response)
      rescue Exception => e
        fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result)
      end
    end

    result
  end

  promise.execute
end
entities_with_http_info(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil) click to toggle source

The API returns a list of recognized entities in a given document.

To get even more information on each recognized entity we recommend using the Bing Entity Search API by querying for the recognized entities names. See the <a href=“Supported”>docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/text-analytics-supported-languages“>Supported languages in Text Analytics API</a> for the list of enabled languages.

@param show_stats [Boolean] (optional) if set to true, response will contain input and document level statistics. @param multi_language_batch_input [MultiLanguageBatchInput] Collection of documents to analyze. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.

@return [MsRestAzure::AzureOperationResponse] HTTP response information.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 268
def entities_with_http_info(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil)
  entities_async(show_stats:show_stats, multi_language_batch_input:multi_language_batch_input, custom_headers:custom_headers).value!
end
key_phrases(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil) click to toggle source

The API returns a list of strings denoting the key talking points in the input text.

See the <a href=“Text”>docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview#supported-languages“>Text Analytics Documentation</a> for details about the languages that are supported by key phrase extraction.

@param show_stats [Boolean] (optional) if set to true, response will contain input and document level statistics. @param multi_language_batch_input [MultiLanguageBatchInput] Collection of documents to analyze. Documents can now contain a language field to indicate the text language @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.

@return [KeyPhraseBatchResult] operation results.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 366
def key_phrases(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil)
  response = key_phrases_async(show_stats:show_stats, multi_language_batch_input:multi_language_batch_input, custom_headers:custom_headers).value!
  response.body unless response.nil?
end
key_phrases_async(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil) click to toggle source

The API returns a list of strings denoting the key talking points in the input text.

See the <a href=“Text”>docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview#supported-languages“>Text Analytics Documentation</a> for details about the languages that are supported by key phrase extraction.

@param show_stats [Boolean] (optional) if set to true, response will contain input and document level statistics. @param multi_language_batch_input [MultiLanguageBatchInput] Collection of documents to analyze. Documents can now contain a language field to indicate the text language @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.

@return [Concurrent::Promise] Promise object which holds the HTTP response.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 413
def key_phrases_async(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil)
  fail ArgumentError, 'endpoint is nil' if endpoint.nil?


  request_headers = {}
  request_headers['Content-Type'] = 'application/json; charset=utf-8'

  # Set Headers
  request_headers['x-ms-client-request-id'] = SecureRandom.uuid
  request_headers['accept-language'] = accept_language unless accept_language.nil?

  # Serialize Request
  request_mapper = Azure::CognitiveServices::TextAnalytics::V2_1::Models::MultiLanguageBatchInput.mapper()
  request_content = self.serialize(request_mapper,  multi_language_batch_input)
  request_content = request_content != nil ? JSON.generate(request_content, quirks_mode: true) : nil

  path_template = 'keyPhrases'

  request_url = @base_url || self.base_url
request_url = request_url.gsub('{Endpoint}', endpoint)

  options = {
      middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]],
      query_params: {'showStats' => show_stats},
      body: request_content,
      headers: request_headers.merge(custom_headers || {}),
      base_url: request_url
  }
  promise = self.make_request_async(:post, path_template, options)

  promise = promise.then do |result|
    http_response = result.response
    status_code = http_response.status
    response_content = http_response.body
    unless status_code == 200
      error_model = JSON.load(response_content)
      fail MsRest::HttpOperationError.new(result.request, http_response, error_model)
    end

    result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil?
    # Deserialize Response
    if status_code == 200
      begin
        parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content)
        result_mapper = Azure::CognitiveServices::TextAnalytics::V2_1::Models::KeyPhraseBatchResult.mapper()
        result.body = self.deserialize(result_mapper, parsed_response)
      rescue Exception => e
        fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result)
      end
    end

    result
  end

  promise.execute
end
key_phrases_with_http_info(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil) click to toggle source

The API returns a list of strings denoting the key talking points in the input text.

See the <a href=“Text”>docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview#supported-languages“>Text Analytics Documentation</a> for details about the languages that are supported by key phrase extraction.

@param show_stats [Boolean] (optional) if set to true, response will contain input and document level statistics. @param multi_language_batch_input [MultiLanguageBatchInput] Collection of documents to analyze. Documents can now contain a language field to indicate the text language @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.

@return [MsRestAzure::AzureOperationResponse] HTTP response information.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 390
def key_phrases_with_http_info(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil)
  key_phrases_async(show_stats:show_stats, multi_language_batch_input:multi_language_batch_input, custom_headers:custom_headers).value!
end
make_request(method, path, options = {}) click to toggle source

Makes a request and returns the body of the response. @param method [Symbol] with any of the following values :get, :put, :post, :patch, :delete. @param path [String] the path, relative to {base_url}. @param options [Hash{String=>String}] specifying any request options like :body. @return [Hash{String=>String}] containing the body of the response. Example:

request_content = "{'location':'westus','tags':{'tag1':'val1','tag2':'val2'}}"
path = "/path"
options = {
  body: request_content,
  query_params: {'api-version' => '2016-02-01'}
}
result = @client.make_request(:put, path, options)
# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 74
def make_request(method, path, options = {})
  result = make_request_with_http_info(method, path, options)
  result.body unless result.nil?
end
make_request_async(method, path, options = {}) click to toggle source

Makes a request asynchronously. @param method [Symbol] with any of the following values :get, :put, :post, :patch, :delete. @param path [String] the path, relative to {base_url}. @param options [Hash{String=>String}] specifying any request options like :body. @return [Concurrent::Promise] Promise object which holds the HTTP response.

Calls superclass method
# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 99
def make_request_async(method, path, options = {})
  fail ArgumentError, 'method is nil' if method.nil?
  fail ArgumentError, 'path is nil' if path.nil?

  request_url = options[:base_url] || @base_url
  if(!options[:headers].nil? && !options[:headers]['Content-Type'].nil?)
    @request_headers['Content-Type'] = options[:headers]['Content-Type']
  end

  request_headers = @request_headers
  request_headers.merge!({'accept-language' => @accept_language}) unless @accept_language.nil?
  options.merge!({headers: request_headers.merge(options[:headers] || {})})
  options.merge!({credentials: @credentials}) unless @credentials.nil?

  super(request_url, method, path, options)
end
make_request_with_http_info(method, path, options = {}) click to toggle source

Makes a request and returns the operation response. @param method [Symbol] with any of the following values :get, :put, :post, :patch, :delete. @param path [String] the path, relative to {base_url}. @param options [Hash{String=>String}] specifying any request options like :body. @return [MsRestAzure::AzureOperationResponse] Operation response containing the request, response and status.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 86
def make_request_with_http_info(method, path, options = {})
  result = make_request_async(method, path, options).value!
  result.body = result.response.body.to_s.empty? ? nil : JSON.load(result.response.body)
  result
end
sentiment(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil) click to toggle source

The API returns a numeric score between 0 and 1.

Scores close to 1 indicate positive sentiment, while scores close to 0 indicate negative sentiment. A score of 0.5 indicates the lack of sentiment (e.g. a factoid statement). See the <a href=“Text”>docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview#supported-languages“>Text Analytics Documentation</a> for details about the languages that are supported by sentiment analysis.

@param show_stats [Boolean] (optional) if set to true, response will contain input and document level statistics. @param multi_language_batch_input [MultiLanguageBatchInput] Collection of documents to analyze. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.

@return [Object] operation results.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 489
def sentiment(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil)
  response = sentiment_async(show_stats:show_stats, multi_language_batch_input:multi_language_batch_input, custom_headers:custom_headers).value!
  response.body unless response.nil?
end
sentiment_async(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil) click to toggle source

The API returns a numeric score between 0 and 1.

Scores close to 1 indicate positive sentiment, while scores close to 0 indicate negative sentiment. A score of 0.5 indicates the lack of sentiment (e.g. a factoid statement). See the <a href=“Text”>docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview#supported-languages“>Text Analytics Documentation</a> for details about the languages that are supported by sentiment analysis.

@param show_stats [Boolean] (optional) if set to true, response will contain input and document level statistics. @param multi_language_batch_input [MultiLanguageBatchInput] Collection of documents to analyze. @param [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.

@return [Concurrent::Promise] Promise object which holds the HTTP response.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 536
def sentiment_async(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil)
  fail ArgumentError, 'endpoint is nil' if endpoint.nil?


  request_headers = {}
  request_headers['Content-Type'] = 'application/json; charset=utf-8'

  # Set Headers
  request_headers['x-ms-client-request-id'] = SecureRandom.uuid
  request_headers['accept-language'] = accept_language unless accept_language.nil?

  # Serialize Request
  request_mapper = Azure::CognitiveServices::TextAnalytics::V2_1::Models::MultiLanguageBatchInput.mapper()
  request_content = self.serialize(request_mapper,  multi_language_batch_input)
  request_content = request_content != nil ? JSON.generate(request_content, quirks_mode: true) : nil

  path_template = 'sentiment'

  request_url = @base_url || self.base_url
request_url = request_url.gsub('{Endpoint}', endpoint)

  options = {
      middlewares: [[MsRest::RetryPolicyMiddleware, times: 3, retry: 0.02], [:cookie_jar]],
      query_params: {'showStats' => show_stats},
      body: request_content,
      headers: request_headers.merge(custom_headers || {}),
      base_url: request_url
  }
  promise = self.make_request_async(:post, path_template, options)

  promise = promise.then do |result|
    http_response = result.response
    status_code = http_response.status
    response_content = http_response.body
    unless status_code == 200 || status_code == 500
      error_model = JSON.load(response_content)
      fail MsRestAzure::AzureOperationError.new(result.request, http_response, error_model)
    end

    result.request_id = http_response['x-ms-request-id'] unless http_response['x-ms-request-id'].nil?
    # Deserialize Response
    if status_code == 200
      begin
        parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content)
        result_mapper = Azure::CognitiveServices::TextAnalytics::V2_1::Models::SentimentBatchResult.mapper()
        result.body = self.deserialize(result_mapper, parsed_response)
      rescue Exception => e
        fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result)
      end
    end
    # Deserialize Response
    if status_code == 500
      begin
        parsed_response = response_content.to_s.empty? ? nil : JSON.load(response_content)
        result_mapper = Azure::CognitiveServices::TextAnalytics::V2_1::Models::ErrorResponse.mapper()
        result.body = self.deserialize(result_mapper, parsed_response)
      rescue Exception => e
        fail MsRest::DeserializationError.new('Error occurred in deserializing the response', e.message, e.backtrace, result)
      end
    end

    result
  end

  promise.execute
end
sentiment_with_http_info(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil) click to toggle source

The API returns a numeric score between 0 and 1.

Scores close to 1 indicate positive sentiment, while scores close to 0 indicate negative sentiment. A score of 0.5 indicates the lack of sentiment (e.g. a factoid statement). See the <a href=“Text”>docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview#supported-languages“>Text Analytics Documentation</a> for details about the languages that are supported by sentiment analysis.

@param show_stats [Boolean] (optional) if set to true, response will contain input and document level statistics. @param multi_language_batch_input [MultiLanguageBatchInput] Collection of documents to analyze. @param custom_headers [Hash{String => String}] A hash of custom headers that will be added to the HTTP request.

@return [MsRestAzure::AzureOperationResponse] HTTP response information.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 513
def sentiment_with_http_info(show_stats:nil, multi_language_batch_input:nil, custom_headers:nil)
  sentiment_async(show_stats:show_stats, multi_language_batch_input:multi_language_batch_input, custom_headers:custom_headers).value!
end

Private Instance Methods

add_telemetry() click to toggle source

Adds telemetry information.

# File lib/v2.1/generated/azure_cognitiveservices_textanalytics/text_analytics_client.rb, line 608
def add_telemetry
    sdk_information = 'azure_cognitiveservices_textanalytics'
    sdk_information = "#{sdk_information}/0.17.4"
    add_user_agent_information(sdk_information)
end