watson_developer_cloud.tone_analyzer_v3 module

### Service Overview The IBM Watson Tone Analyzer service uses linguistic analysis to detect emotional and language tones in written text. The service can analyze tone at both the document and sentence levels. You can use the service to understand how your written communications are perceived and then to improve the tone of your communications. Businesses can use the service to learn the tone of their customers’ communications and to respond to each customer appropriately, or to understand and improve their customer conversations. ### API Usage The following information provides details about using the service to analyze tone: * The tone method: The service offers GET and POST /v3/tone methods that use the general purpose endpoint to analyze the tone of input content. The methods accept content in JSON, plain text, or HTML format. * The tone_chat method: The service offers a POST /v3/tone_chat method that uses the customer engagement endpoint to analyze the tone of customer service and customer support conversations. The method accepts content in JSON format. * Authentication: You authenticate to the service by using your service credentials. You can use your credentials to authenticate via a proxy server that resides in Bluemix, or you can use your credentials to obtain a token and contact the service directly. See [Service credentials for Watson services](https://console.bluemix.net/docs/services/watson/getting-started-credentials.html) and [Tokens for authentication](https://console.bluemix.net/docs/services/watson/getting-started-tokens.html). * Request Logging: By default, all Watson services log requests and their results. Data is collected only to improve the Watson services. If you do not want to share your data, set the header parameter X-Watson-Learning-Opt-Out to true for each request. Data is collected for any request that omits this header. See [Controlling request logging for Watson services](https://console.bluemix.net/docs/services/watson/getting-started-logging.html).

For more information about the service, see [About Tone Analyzer](https://console.bluemix.net/docs/services/tone-analyzer/index.html).

Note: Method descriptions apply to the latest version of the interface, 2017-09-21. Where necessary, parameters and models describe differences between versions 2017-09-21 and 2016-05-19.

class ToneAnalyzerV3(version, url='https://gateway.watsonplatform.net/tone-analyzer/api', username=None, password=None)[source]

Bases: watson_developer_cloud.watson_service.WatsonService

The Tone Analyzer V3 service.

default_url = 'https://gateway.watsonplatform.net/tone-analyzer/api'
tone(tone_input, content_type='application/json', sentences=None, tones=None, content_language=None, accept_language=None)[source]

Analyze general purpose tone.

Uses the general purpose endpoint to analyze the tone of your input content. The service analyzes the content for emotional and language tones. The method always analyzes the tone of the full document; by default, it also analyzes the tone of each individual sentence of the content. You can submit no more than 128 KB of total input content and no more than 1000 individual sentences in JSON, plain text, or HTML format. The service analyzes the first 1000 sentences for document-level analysis and only the first 100 sentences for sentence-level analysis. Use the POST request method to analyze larger amounts of content in any of the available formats. Use the GET request method to analyze smaller quantities of plain text content. Per the JSON specification, the default character encoding for JSON content is effectively always UTF-8; per the HTTP specification, the default encoding for plain text and HTML is ISO-8859-1 (effectively, the ASCII character set). When specifying a content type of plain text or HTML, include the charset parameter to indicate the character encoding of the input text; for example: Content-Type: text/plain;charset=utf-8. For text/html, the service removes HTML tags and analyzes only the textual content.

Parameters:
  • tone_input (ToneInput) – JSON, plain text, or HTML input that contains the content to be analyzed. For JSON input, provide an object of type ToneInput.
  • content_type (str) – The type of the input: application/json, text/plain, or text/html. A character encoding can be specified by including a charset parameter. For example, ‘text/plain;charset=utf-8’.
  • sentences (bool) – Indicates whether the service is to return an analysis of each individual sentence in addition to its analysis of the full document. If true (the default), the service returns results for each sentence.
  • tones (list[str]) – `2017-09-21`: Deprecated. The service continues to accept the parameter for backward-compatibility, but the parameter no longer affects the response. `2016-05-19`: A comma-separated list of tones for which the service is to return its analysis of the input; the indicated tones apply both to the full document and to individual sentences of the document. You can specify one or more of the valid values. Omit the parameter to request results for all three tones.
  • content_language (str) – The language of the input text for the request: English or French. Regional variants are treated as their parent language; for example, en-US is interpreted as en. The input content must match the specified language. Do not submit content that contains both languages. You can specify any combination of languages for content_language and Accept-Language. * `2017-09-21`: Accepts en or fr. * `2016-05-19`: Accepts only en.
  • accept_language (str) – The desired language of the response. For two-character arguments, regional variants are treated as their parent language; for example, en-US is interpreted as en. You can specify any combination of languages for Content-Language and accept_language.
Returns:

A dict containing the ToneAnalysis response.
Return type:

dict
tone_chat(utterances, accept_language=None)[source]

Analyze customer engagement tone.

Use the customer engagement endpoint to analyze the tone of customer service and customer support conversations. For each utterance of a conversation, the method reports the most prevalent subset of the following seven tones: sad, frustrated, satisfied, excited, polite, impolite, and sympathetic. If you submit more than 50 utterances, the service returns a warning for the overall content and analyzes only the first 50 utterances. If you submit a single utterance that contains more than 500 characters, the service returns an error for that utterance and does not analyze the utterance. The request fails if all utterances have more than 500 characters. Per the JSON specification, the default character encoding for JSON content is effectively always UTF-8.

Parameters:
  • utterances (list[Utterance]) – An array of Utterance objects that provides the input content that the service is to analyze.
  • accept_language (str) – The desired language of the response. For two-character arguments, regional variants are treated as their parent language; for example, en-US is interpreted as en.
Returns:

A dict containing the UtteranceAnalyses response.
Return type:

dict
class DocumentAnalysis(tones=None, tone_categories=None, warning=None)[source]

Bases: object

DocumentAnalysis.

Attr list[ToneScore] tones:
 (optional) `2017-09-21`: An array of ToneScore objects that provides the results of the analysis for each qualifying tone of the document. The array includes results for any tone whose score is at least 0.5. The array is empty if no tone has a score that meets this threshold. `2016-05-19`: Not returned.
Attr list[ToneCategory] tone_categories:
 (optional) `2017-09-21`: Not returned. `2016-05-19`: An array of ToneCategory objects that provides the results of the tone analysis for the full document of the input content. The service returns results only for the tones specified with the tones parameter of the request.
Attr str warning:
 (optional) `2017-09-21`: A warning message if the overall content exceeds 128 KB or contains more than 1000 sentences. The service analyzes only the first 1000 sentences for document-level analysis and the first 100 sentences for sentence-level analysis. `2016-05-19`: Not returned.
class SentenceAnalysis(sentence_id, text, tones=None, tone_categories=None, input_from=None, input_to=None)[source]

Bases: object

SentenceAnalysis.

Attr int sentence_id:
 The unique identifier of a sentence of the input content. The first sentence has ID 0, and the ID of each subsequent sentence is incremented by one.
Attr str text:The text of the input sentence.
Attr list[ToneScore] tones:
 (optional) `2017-09-21`: An array of ToneScore objects that provides the results of the analysis for each qualifying tone of the sentence. The array includes results for any tone whose score is at least 0.5. The array is empty if no tone has a score that meets this threshold. `2016-05-19`: Not returned.
Attr list[ToneCategory] tone_categories:
 (optional) `2017-09-21`: Not returned. `2016-05-19`: An array of ToneCategory objects that provides the results of the tone analysis for the sentence. The service returns results only for the tones specified with the tones parameter of the request.
Attr int input_from:
 (optional) `2017-09-21`: Not returned. `2016-05-19`: The offset of the first character of the sentence in the overall input content.
Attr int input_to:
 (optional) `2017-09-21`: Not returned. `2016-05-19`: The offset of the last character of the sentence in the overall input content.
class ToneAnalysis(document_tone, sentences_tone=None)[source]

Bases: object

ToneAnalysis.

Attr DocumentAnalysis document_tone:
 An object of type DocumentAnalysis that provides the results of the analysis for the full input document.
Attr list[SentenceAnalysis] sentences_tone:
 (optional) An array of SentenceAnalysis objects that provides the results of the analysis for the individual sentences of the input content. The service returns results only for the first 100 sentences of the input. The field is omitted if the sentences parameter of the request is set to false.
class ToneCategory(tones, category_id, category_name)[source]

Bases: object

ToneCategory.

Attr list[ToneScore] tones:
 An array of ToneScore objects that provides the results for the tones of the category.
Attr str category_id:
 The unique, non-localized identifier of the category for the results. The service can return results for the following category IDs: emotion_tone, language_tone, and social_tone.
Attr str category_name:
 The user-visible, localized name of the category.
class ToneChatScore(score, tone_id, tone_name)[source]

Bases: object

ToneChatScore.

Attr float score:
 The score for the tone in the range of 0.5 to 1. A score greater than 0.75 indicates a high likelihood that the tone is perceived in the utterance.
Attr str tone_id:
 The unique, non-localized identifier of the tone for the results. The service can return results for the following tone IDs: sad, frustrated, satisfied, excited, polite, impolite, and sympathetic. The service returns results only for tones whose scores meet a minimum threshold of 0.5.
Attr str tone_name:
 The user-visible, localized name of the tone.
class ToneInput(text)[source]

Bases: object

ToneInput.

Attr str text:The input content that the service is to analyze.
class ToneScore(score, tone_id, tone_name)[source]

Bases: object

ToneScore.

Attr float score:
 The score for the tone. * `2017-09-21`: The score that is returned lies in the range of 0.5 to 1. A score greater than 0.75 indicates a high likelihood that the tone is perceived in the content. * `2016-05-19`: The score that is returned lies in the range of 0 to 1. A score less than 0.5 indicates that the tone is unlikely to be perceived in the content; a score greater than 0.75 indicates a high likelihood that the tone is perceived.
Attr str tone_id:
 The unique, non-localized identifier of the tone. * `2017-09-21`: The service can return results for the following tone IDs: anger, fear, joy, and sadness (emotional tones); analytical, confident, and tentative (language tones). The service returns results only for tones whose scores meet a minimum threshold of 0.5. * `2016-05-19`: The service can return results for the following tone IDs of the different categories: for the emotion category: anger, disgust, fear, joy, and sadness; for the language category: analytical, confident, and tentative; for the social category: openness_big5, conscientiousness_big5, extraversion_big5, agreeableness_big5, and emotional_range_big5. The service returns scores for all tones of a category, regardless of their values.
Attr str tone_name:
 The user-visible, localized name of the tone.
class Utterance(text, user=None)[source]

Bases: object

Utterance.

Attr str text:An utterance contributed by a user in the conversation that is to be analyzed. The utterance can contain multiple sentences.
Attr str user:(optional) A string that identifies the user who contributed the utterance specified by the text parameter.
class UtteranceAnalyses(utterances_tone, warning=None)[source]

Bases: object

UtteranceAnalyses.

Attr list[UtteranceAnalysis] utterances_tone:
 An array of UtteranceAnalysis objects that provides the results for each utterance of the input.
Attr str warning:
 (optional) `2017-09-21`: A warning message if the content contains more than 50 utterances. The service analyzes only the first 50 utterances. `2016-05-19`: Not returned.
class UtteranceAnalysis(utterance_id, utterance_text, tones, error=None)[source]

Bases: object

UtteranceAnalysis.

Attr str utterance_id:
 The unique identifier of the utterance. The first utterance has ID 0, and the ID of each subsequent utterance is incremented by one.
Attr str utterance_text:
 The text of the utterance.
Attr list[ToneChatScore] tones:
 An array of ToneChatScore objects that provides results for the most prevalent tones of the utterance. The array includes results for any tone whose score is at least 0.5. The array is empty if no tone has a score that meets this threshold.
Attr str error:(optional) `2017-09-21`: An error message if the utterance contains more than 500 characters. The service does not analyze the utterance. `2016-05-19`: Not returned.