watson-developer-cloud
Advanced tools
Node client library to use the Watson Developer Cloud services, a collection of REST APIs and SDKs that use cognitive computing to solve complex problems.
Several breaking changes were introduced with the v1.0.0 release:
v1 is now v1-betav1 is now v1-betav1 is now v1-betav2 is now v2-experimentalv1 is now v1-experimentalv1 is now v1-betacreateRecognizeStream() method replacing the existing live streaming methods with a simpler Read/Write stream.
The older methods are still available in v1.0 but each log a deprecation warning (unless {silent: true} is passed in) and will be removed from a future release.
The affected methods are:
recognizeLive()observeResult()getRecognizeStatus()convert() method; it no longer offers batch conversion or cloud storage of files.$ npm install watson-developer-cloud --save
The examples below assume that you already have service credentials. If not, you will have to create a service in Bluemix.
If you are running your application in Bluemix, you don't need to specify the
credentials; the library will get them for you by looking at the VCAP_SERVICES environment variable.
You will need the username and password (api_key for AlchemyAPI) credentials for each service. Service credentials are different from your Bluemix account username and password.
To get your service credentials, follow these steps:
Log in to Bluemix at https://bluemix.net.
Create an instance of the service:
my-service-name. Leave the default values for the other options.Copy your credentials:
username and password(api_key for AlchemyAPI).If you are having difficulties using the APIs or have a question about the IBM Watson Services, please ask a question on dW Answers or Stack Overflow.
The examples folder has basic and advanced examples.
The Watson Developer Cloud offers a variety of services for building cognitive apps.
Alchemy Language offers 12 API functions as part of its text analysis service, each of which uses sophisticated natural language processing techniques to analyze your content and add high-level semantic information.
Use the Sentiment Analysis endpoint to identify positive/negative sentiment within a sample text document.
var watson = require('watson-developer-cloud');
var alchemy_language = watson.alchemy_language({
api_key: '<api_key>'
});
var params = {
text: 'IBM Watson won the Jeopardy television show hosted by Alex Trebek'
};
alchemy_language.sentiment(params, function (err, response) {
if (err)
console.log('error:', err);
else
console.log(JSON.stringify(response, null, 2));
});
Alchemy Vision uses deep learning innovations to understand a picture's content and context. It sees complex visual scenes in their entirety —without needing any textual clues— leveraging a holistic approach to understanding the multiple objects and surroundings.
Example: Extract keywords from an image.
var watson = require('watson-developer-cloud');
var fs = require('fs');
var alchemy_vision = watson.alchemy_vision({
api_key: '<api_key>'
});
var params = {
image: fs.createReadStream('src/test/resources/obama.jpg')
};
alchemy_vision.getImageKeywords(params, function (err, keywords) {
if (err)
console.log('error:', err);
else
console.log(JSON.stringify(keywords, null, 2));
});
Alchemy Data News indexes 250k to 300k English language news and blog articles every day with historical search available for the past 60 days. Example: Get the volume data from the last 7 days using 12hs of time slice.
var watson = require('watson-developer-cloud');
var alchemy_data_news = watson.alchemy_data_news({
api_key: '<api_key>'
});
var params = {
start: 'now-1d',
end: 'now'
};
alchemy_data_news.getNews(params, function (err, news) {
if (err)
console.log('error:', err);
else
console.log(JSON.stringify(news, null, 2));
});
The Authorization service can generates tokens, this are useful when it's too cumbersome to provide a username/password pair.
Tokens are valid for 1 hour and need to be send using the X-Watson-Authorization-Token header.
var watson = require('watson-developer-cloud');
var authorization = watson.authorization({
username: '<username>',
password: '<password>',
version: 'v1'
});
var params = {
// URL of the resource you wish to access
url: 'https://stream.watsonplatform.net/text-to-speech/api'
};
authorization.getToken(params, function (err, token) {
if (!token) {
console.log('error:', err);
} else {
// Use your token here
}
});
The Watson Concept Expansion Service will be withdrawn. The Watson Concept Expansion Service tile will be removed from the Bluemix catalog on Sunday, March 6, 2016, after which you cannot provision new instances of this service. However, existing provisioned instances will continue to be usable until March 30, 2016.
Use the Concept Insights service to identify words in the text that correspond to concepts in a Wikipedia graph.
var watson = require('watson-developer-cloud');
var concept_insights = watson.concept_insights({
username: '<username>',
password: '<password>',
version: 'v2'
});
var params = {
graph: '/graphs/wikipedia/en-20120601',
text: 'IBM Watson won the Jeopardy television show hosted by Alex Trebek'
};
// Retrieve the concepts for input text
concept_insights.graphs.annotateText(params, function(err, res) {
if (err)
console.log(err);
else {
console.log(JSON.stringify(res, null, 2));
}
});
Use the Dialog service to list all the dialogs you have.
var watson = require('watson-developer-cloud');
var dialog = watson.dialog({
username: '<username>',
password: '<password>',
version: 'v1'
});
dialog.getDialogs({}, function (err, dialogs) {
if (err)
console.log('error:', err);
else
console.log(JSON.stringify(dialogs, null, 2));
});
var watson = require('watson-developer-cloud');
var fs = require('fs');
var document_conversion = watson.document_conversion({
username: '<username>',
password: '<password>',
version: 'v1',
version_date: '2015-12-01'
});
// convert a single document
document_conversion.convert({
// (JSON) ANSWER_UNITS, NORMALIZED_HTML, or NORMALIZED_TEXT
file: fs.createReadStream('sample-docx.docx'),
conversion_target: document_conversion.conversion_target.ANSWER_UNITS,
// Add custom configuration properties or omit for defaults
word: {
heading: {
fonts: [
{ level: 1, min_size: 24 },
{ level: 2, min_size: 16, max_size: 24 }
]
}
}
}, function (err, response) {
if (err) {
console.error(err);
} else {
console.log(JSON.stringify(response, null, 2));
}
});
See the Document Conversion integration example about how to integrate the Document Conversion service with the Retrieve and Rank service.
Translate text from one language to another or idenfity a language using the Language Translation service.
var watson = require('watson-developer-cloud');
var language_translation = watson.language_translation({
username: '<username>',
password: '<password>',
version: 'v2'
});
language_translation.translate({
text: 'A sentence must have a verb', source : 'en', target: 'es' },
function (err, translation) {
if (err)
console.log('error:', err);
else
console.log(JSON.stringify(translation, null, 2));
});
language_translation.identify({
text: 'The language translation service takes text input and identifies the language used.' },
function (err, language) {
if (err)
console.log('error:', err);
else
console.log(JSON.stringify(language, null, 2));
});
Use Natural Language Classifier service to create a classifier instance by providing a set of representative strings and a set of one or more correct classes for each as training. Then use the trained classifier to classify your new question for best matching answers or to retrieve next actions for your application.
var watson = require('watson-developer-cloud');
var natural_language_classifier = watson.natural_language_classifier({
url: 'https://gateway.watsonplatform.net/natural-language-classifier/api',
username: '<username>',
password: '<password>',
version: 'v1'
});
natural_language_classifier.classify({
text: 'Is it sunny?',
classifier_id: '<classifier-id>' },
function(err, response) {
if (err)
console.log('error:', err);
else
console.log(JSON.stringify(response, null, 2));
});
See this example to learn how to create a classifier.
Analyze text in english and get a personality profile by using the Personality Insights service.
var watson = require('watson-developer-cloud');
var personality_insights = watson.personality_insights({
username: '<username>',
password: '<password>',
version: 'v2'
});
personality_insights.profile({
text: 'Enter more than 100 unique words here...',
language: 'en' },
function (err, response) {
if (err)
console.log('error:', err);
else
console.log(JSON.stringify(response, null, 2));
});
Note: Don't forget to update the text variable!
Analyze an English news article and get the relationships between sentence components (nouns, verbs, subjects, objects, etc.) by using the Relationship Extraction service.
var watson = require('watson-developer-cloud');
var relationship_extraction = watson.relationship_extraction({
username: '<username>',
password: '<password>',
version: 'v1-beta'
});
relationship_extraction.extract({
text: 'IBM Watson developer cloud',
dataset: 'ie-en-news' },
function (err, response) {
if (err)
console.log('error:', err);
else
console.log(JSON.stringify(response, null, 2));
});
Use the Retrieve and Rank service to enhance search results with machine learning.
var retrieve = watson.retrieve_and_rank({
username: 'INSERT YOUR USERNAME FOR THE SERVICE HERE',
password: 'INSERT YOUR PASSWORD FOR THE SERVICE HERE',
version: 'v1',
url: 'https://gateway.watsonplatform.net/retrieve-and-rank/api'
});
var solrClient = retrieve.createSolrClient({
cluster_id: 'INSERT YOUR CLUSTER ID HERE',
collection_name: 'example_collection'
});
// add a document
var doc = { id : 1234, title_t : 'Hello', text_field_s: 'some text' };
solrClient.add(doc, function(err) {
if(err) {
console.log('Error indexing document: ' + err);
} else {
console.log('Indexed a document.');
solrClient.commit(function(err) {
if(err) {
console.log('Error committing change: ' + err);
} else {
console.log('Successfully commited changes.');
}
});
}
});
// search all documents
var query = solrClient.createQuery();
query.q({ '*' : '*' });
solrClient.search(query, function(err, searchResponse) {
if(err) {
console.log('Error searching for documents: ' + err);
} else {
console.log('Found ' + searchResponse.response.numFound + ' document(s).');
console.log('First document: ' + JSON.stringify(searchResponse.response.docs[0], null, 2));
}
});
Use the Speech to Text service to recognize the text from a .wav file.
var watson = require('watson-developer-cloud');
var fs = require('fs');
var speech_to_text = watson.speech_to_text({
username: '<username>',
password: '<password>',
version: 'v1'
});
var params = {
// From file
audio: fs.createReadStream('./resources/speech.wav'),
content_type: 'audio/l16; rate=44100'
};
speech_to_text.recognize(params, function(err, res) {
if (err)
console.log(err);
else
console.log(JSON.stringify(res, null, 2));
});
// or streaming
fs.createReadStream('./resources/speech.wav')
.pipe(speech_to_text.createRecognizeStream({ content_type: 'audio/l16; rate=44100' })
.pipe(fs.createWriteStream('./transcription.txt'));
Use the Text to Speech service to synthesize text into a .wav file.
var watson = require('watson-developer-cloud');
var fs = require('fs');
var text_to_speech = watson.text_to_speech({
username: '<username>',
password: '<password>',
version: 'v1'
});
var params = {
text: 'Hello from IBM Watson',
voice: 'en-US_AllisonVoice', // Optional voice
accept: 'audio/wav'
};
// Pipe the synthesized text to a file
text_to_speech.synthesize(params).pipe(fs.createWriteStream('output.wav'));
Use the Tone Analyzer service to analyze the emotion, writing and social tones of a text.
var watson = require('watson-developer-cloud');
var tone_analyzer = watson.tone_analyzer({
username: '<username>',
password: '<password>',
version: 'v3-beta',
version_date: '2016-02-11'
});
tone_analyzer.tone({ text: 'Greetings from Watson Developer Cloud!' },
function(err, tone) {
if (err)
console.log(err);
else
console.log(JSON.stringify(tone, null, 2));
});
Use the Tradeoff Analytics service to find the best phone that minimizes price and weight and maximizes screen size.
var watson = require('watson-developer-cloud');
var tradeoff_analytics = watson.tradeoff_analytics({
username: '<username>',
password: '<password>',
version: 'v1'
});
// From file
var params = require('./resources/problem.json');
tradeoff_analytics.dilemmas(params, function(err, res) {
if (err)
console.log(err);
else
console.log(JSON.stringify(res, null, 2));
});
Use the Visual Insights to get insight into the themes present in a collection of images based on their visual appearance/content.
var watson = require('watson-developer-cloud');
var fs = require('fs');
var visual_insights = watson.visual_insights({
username: '<username>',
password: '<password>',
version: 'v1-experimental'
});
var params = {
images_file: fs.createReadStream('./resources/images.zip')
};
visual_insights.summary(params, function(err, res) {
if (err)
console.log(err);
else
console.log(JSON.stringify(res, null, 2));
});
Use the Visual Recognition service to recognize the following picture.
var watson = require('watson-developer-cloud');
var fs = require('fs');
var visual_recognition = watson.visual_recognition({
username: '<username>',
password: '<password>',
version: 'v2-beta',
version_date: '2015-12-02'
});
var params = {
images_file: fs.createReadStream('./resources/car.png')
};
visual_recognition.classify(params, function(err, res) {
if (err)
console.log(err);
else
console.log(JSON.stringify(res, null, 2));
});
By default, the library tries to use the Bluemix VCAP_SERVICES environment
variable to get the credentials for a given service. You can avoid this by
using:
use_vcap_services.
var watson = require('watson-developer-cloud');
var concept_expansion = watson.concept_expansion({
version: 'v1-beta',
use_vcap_services: false
});
This example fails because you did not provide a username and password and the library will not look into Bluemix for these values.
By default, the library tries to use Basic Auth and will ask for api_key or username and password and send an Authorization: Basic XXXXXXX. You can avoid this by using:
use_unauthenticated.
var watson = require('watson-developer-cloud');
var dialog = watson.dialog({
version: 'v1',
use_unauthenticated: true
});
This library relies on the request npm module writted by
request to call the Watson Services. To debug the apps, add
'request' to the NODE_DEBUG environment variable:
$ NODE_DEBUG='request' node app.js
where app.js is your Node.js file.
Running all the tests:
$ npm test
Running a specific test:
$ mocha -g '<test name>'
Find more open source projects on the IBM Github Page.
This library is licensed under Apache 2.0. Full license text is available in COPYING.
See CONTRIBUTING.
FAQs
Client library to use the IBM Watson Services
The npm package watson-developer-cloud receives a total of 2,940 weekly downloads. As such, watson-developer-cloud popularity was classified as popular.
We found that watson-developer-cloud demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 4 open source maintainers collaborating on the project.
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