Java code wrappers to quickly get started with the various Watson Developer Cloud services - A collection of REST APIs and SDKs that use cognitive computing to solve complex problems.
- Watson Developer Cloud
- Questions
- Installation
- Usage
- Getting the Service Credentials
- Alchemy Services
- IBM Watson Services
- Concept Expansion
- Concept Insights
- Dialog
- Document Conversion
- Language Identification
- Language Translation
- Machine Translation
- Message Resonance
- Natural Language Classifier
- Personality Insights
- Question and Answer
- Relationship Extraction
- Speech to Text
- Text to Speech
- Tone Analyzer
- Tradeoff Analytics
- Visual Insights
- Visual Recognition
- Android
- Build + Test
- Eclipse and Intellij
- Open Source @ IBM
- License
- Contributing
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.
Download the jar, and add it to your project.
Now, you are ready to see some examples.
<dependency>
<groupId>com.ibm.watson.developer_cloud</groupId>
<artifactId>java-wrapper</artifactId>
<version>1.1.0</version>
</dependency>'com.ibm.watson.developer_cloud:java-wrapper:1.1.0'The examples below assumes that you already have service credentials. If you don't have service credentials, you will have to create and bind the service in Bluemix.
If you are running your application in Bluemix, you don't need to specify the
credentials; the wrapper will get them for you by looking at the VCAP_SERVICES
environment variable.
The credentials for the services are stored in the VCAP_SERVICES environment variable. To get them, you need to first create and bind the service to your application.
You will need the username and password credentials for each service these are not your Bluemix credentials, and are found in the VCAP_SERVICES variable on Bluemix, and they are different for each service.
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.
AlchemyLanguage service = new AlchemyLanguage();
service.setApiKey("<api_key>");
Map<String,Object> params = new HashMap<String, Object>();
params.put(AlchemyLanguage.TEXT, "IBM Watson won the Jeopardy television show hosted by Alex Trebek");
DocumentSentiment sentiment = service.getSentiment(params);
System.out.println(sentiment);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 understand the objects, faces, and words in an image.
Example: Extract keywords from an image.
AlchemyVision service = new AlchemyVision();
service.setApiKey("<api_key>");
Map<String,Object> params = new HashMap<String, Object>();
params.put(AlchemyVision.IMAGE, new File("src/test/resources/obama.jpg"));
ImageKeywords keywords = service.getImageKeywords(params);
System.out.println(keywords);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.
AlchemyDataNews service = new AlchemyDataNews();
service.setApiKey("<api_key>");
VolumeResult result = service.getVolume("now-7d", "now", "12h");
System.out.println(result);The Watson Developer Cloud offers a variety of services for building cognitive applications.
Map euphemisms or colloquial terms to more commonly understood phrases using the Concept Expansion service. Example: Create a job, wait for it to finish, and then retrieve results.
import com.ibm.watson.developer_cloud.concept_expansion.v1.ConceptExpansion;
import com.ibm.watson.developer_cloud.concept_expansion.v1.model.ConceptExpansionDataset;
import com.ibm.watson.developer_cloud.concept_expansion.v1.model.Job;
ConceptExpansion service = new ConceptExpansion();
service.setUsernameAndPassword("<username>", "<password>");
String[] seeds = new String[]{"motrin","tylenol","aspirin"};
String label = "medicine";
service.setDataset(ConceptExpansionDataset.MT_SAMPLES);
Job job = service.createJob(label, seeds);
while (service.getJobStatus(job) == Job.Status.AWAITING_WORK
|| service.getJobStatus(job) == Job.Status.IN_FLIGHT) {
try {
Thread.sleep(4000);
} catch (InterruptedException e) {
e.printStackTrace();
}
}
System.out.println(service.getJobResult(job));Use the Concept Insights service to identify words in the text that correspond to concepts in a Wikipedia graph.
import com.ibm.watson.developer_cloud.concept_insights.v2.ConceptInsights;
import com.ibm.watson.developer_cloud.concept_insights.v2.model.Annotations;
ConceptInsights service = new ConceptInsights();
service.setUsernameAndPassword("<username>", "<password>");
Map<String,Object> params = new HashMap<String, Object>();
params.put(ConceptInsights.ACCOUNT_ID, "wikipedia");
params.put(ConceptInsights.GRAPH, "en-20120601");
params.put(ConceptInsights.TEXT, "IBM Watson won the Jeopardy television show hosted by Alex Trebek");
Annotations annotations = service.annotateText(params);
System.out.println(annotations);Returns the dialog list using the Dialog service.
import com.ibm.watson.developer_cloud.dialog.v1.DialogService;
import com.ibm.watson.developer_cloud.dialog.v1.model.Dialog;
DialogService service = new DialogService();
service.setUsernameAndPassword("<username>", "<password>");
List<Dialog> dialogs = service.getDialogs();
System.out.println(dialogs);The Document Conversion service allows to convert pdf, word, and html documents into formats useful to other Watson Cognitive services. Target formats include normalized html, plain text, and sets of potential answers for Watson question answering. You can convert documents synchronously one at a time, or asynchronously in batches
Returns the document list using the Document Conversion service.
import com.ibm.watson.developer_cloud.document_conversion.v1.DocumentConversion;
import com.ibm.watson.developer_cloud.document_conversion.v1.model.DocumentCollection;
import java.util.HashMap;
import java.util.Map;
DocumentConversion service = new DocumentConversion();
service.setUsernameAndPassword("<username>", "<password>");
Map<String, Object> docListParams = new HashMap<String, Object>();
docListParams.put(DocumentConversion.LIMIT, 10);
DocumentCollection documentCollection = service.getDocumentCollection(docListParams);
System.out.println(documentCollection);Example: Identify a language using the Language Identification service.
import com.ibm.watson.developer_cloud.language_identification.v1.LanguageIdentification;
import com.ibm.watson.developer_cloud.language_identification.v1.model.IdentifiedLanguage;
LanguageIdentification service = new LanguageIdentification();
service.setUsernameAndPassword("<username>", "<password>");
IdentifiedLanguage lang = service.identify("The language identification service takes text input and identifies the language used.");
System.out.println(lang);Select a domain, then identify or select the language of text, and then translate the text from one supported language to another.
Example: Translate 'hello' from English to Spanish using the Language Translation service.
import com.ibm.watson.developer_cloud.language_translation.v2.LanguageTranslation;
import com.ibm.watson.developer_cloud.language_translation.v2.model.TranslationResult;
LanguageTranslation service = new LanguageTranslation();
service.setUsernameAndPassword("<username>", "<password>");
TranslationResult translationResult = service.translate("hello", "en", "es");
System.out.println(translationResult);Example: Translate text from one language to another using the Machine Translation service.
import com.ibm.watson.developer_cloud.machine_translation.v1.MachineTranslation;
import com.ibm.watson.developer_cloud.machine_translation.v1.model.Language;
MachineTranslation service = new MachineTranslation();
service.setUsernameAndPassword("<username>", "<password>");
String response = service.translate("The IBM Watson team is awesome", Language.ENGLISH, Language.SPANISH);
System.out.println(response);Send a word and Watson responds with the resonance scoring for the word, allowing you to enhance the effectiveness of your language for the intended audience.
Example: Get resonance information for individual words in a sentence from the Message Resonance service.
import com.ibm.watson.developer_cloud.message_resonance.v1.MessageResonance;
import com.ibm.watson.developer_cloud.message_resonance.v1.model.MessageResonanceDataset;
import com.ibm.watson.developer_cloud.message_resonance.v1.model.Message;
MessageResonance service = new MessageResonance();
service.setUsernameAndPassword("<username>", "<password>");
service.setDataset(MessageResonanceDataset.BIG_DATA);
Message message = service.getResonance("IBM Watson Developer Cloud");
System.out.println(message);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.
import com.ibm.watson.developer_cloud.natural_language_classifier.v1.NaturalLanguageClassifier;
import com.ibm.watson.developer_cloud.natural_language_classifier.v1.model.Classification;
NaturalLanguageClassifier service = new NaturalLanguageClassifier();
service.setUsernameAndPassword("<username>", "<password>");
Classification classification = service.classify("<classifier-id>", "Is it sunny?");
System.out.println(classification);Note: You will need to create and train a classifier in order to be able to classify phrases.
Use linguistic analytics to infer personality and social characteristics, including Big Five, Needs, and Values, from text.
Example: Analyze text and get a personality profile using the Personality Insights service.
import com.ibm.watson.developer_cloud.personality_insights.v2.PersonalityInsights;
import com.ibm.watson.developer_cloud.personality_insights.v2.model.Profile;
PersonalityInsights service = new PersonalityInsights();
service.setUsernameAndPassword("<username>", "<password>");
// Demo content from Moby Dick by Hermann Melville (Chapter 1)
String text = "Call me Ishmael. Some years ago-never mind how long precisely-having "
+ "little or no money in my purse, and nothing particular to interest me on shore, "
+ "I thought I would sail about a little and see the watery part of the world. "
+ "It is a way I have of driving off the spleen and regulating the circulation. "
+ "Whenever I find myself growing grim about the mouth; whenever it is a damp, "
+ "drizzly November in my soul; whenever I find myself involuntarily pausing before "
+ "coffin warehouses, and bringing up the rear of every funeral I meet; and especially "
+ "whenever my hypos get such an upper hand of me, that it requires a strong moral "
+ "principle to prevent me from deliberately stepping into the street, and methodically "
+ "knocking people's hats off-then, I account it high time to get to sea as soon as I can. "
+ "This is my substitute for pistol and ball. With a philosophical flourish Cato throws himself "
+ "upon his sword; I quietly take to the ship. There is nothing surprising in this. "
+ "If they but knew it, almost all men in their degree, some time or other, cherish "
+ "very nearly the same feelings towards the ocean with me. There now is your insular "
+ "city of the Manhattoes, belted round by wharves as Indian isles by coral reefs-commerce surrounds "
+ "it with her surf. Right and left, the streets take you waterward.";
Profile profile = service.getProfile(text);
System.out.println(profile);Node: Don't forget to update the text variable! Also, if you experience
authentication errors, remember that the Personality Insights service is not
a free service.
Ask a healthcare-related question of the Question and Answer service.
import com.ibm.watson.developer_cloud.question_and_answer.v1.QuestionAndAnswer;
import com.ibm.watson.developer_cloud.question_and_answer.v1.model.Pipeline;
import com.ibm.watson.developer_cloud.question_and_answer.v1.model.QuestionAndAnswerDataset;
QuestionAndAnswer service = new QuestionAndAnswer();
service.setUsernameAndPassword("<username>", "<password>");
service.setDataset(QuestionAndAnswerDataset.HEALTHCARE);
WatsonAnswer watsonAnswers = service.ask("What is HIV?");
System.out.println(watsonAnswers);Analyze an English news article and get the relationships between sentence components (nouns, verbs, subjects, objects, etc.) by using the Relationship Extraction service.
import com.ibm.watson.developer_cloud.relationship_extraction.v1.RelationshipExtraction;
import com.ibm.watson.developer_cloud.relationship_extraction.v1.model.RelationshipExtractionDataset;
RelationshipExtraction service = new RelationshipExtraction();
service.setUsernameAndPassword("<username>", "<password>");
service.setDataset(RelationshipExtractionDataset.ENGLISH_NEWS);
String response = service.extract("IBM Watson Developer Cloud");
System.out.println(response);Use the Speech to Text service to recognize the text from a .wav file.
import com.ibm.watson.developer_cloud.speech_to_text.v1.SpeechToText;
import com.ibm.watson.developer_cloud.speech_to_text.v1.model.SpeechResults;
import java.io.File;
SpeechToText service = new SpeechToText();
service.setUsernameAndPassword("<username>", "<password>");
File audio = new File("src/test/resources/sample1.wav");
SpeechResults transcript = service.recognize(audio, "audio/l16; rate=44100");
System.out.println(transcript);Speech to Text supports WebSocket, the url is:
wss://stream.watsonplatform.net/speech-to-text/api/v1/recognize
We recommend you use this java client.
Use the Text to Speech service to get the available voices to synthesize.
import com.ibm.watson.developer_cloud.text_to_speech.v1.TextToSpeech;
import com.ibm.watson.developer_cloud.text_to_speech.v1.model.Voice;
TextToSpeech service = new TextToSpeech();
service.setUsernameAndPassword("<username>", "<password>");
List<Voice> voices = service.getVoices();
System.out.println(voices);Use the [Tone Analyzer][tone_analyzer] service to get the tone of your email.
import com.ibm.watson.developer_cloud.tone_analyzer.v1.ToneAnalyzer;
import com.ibm.watson.developer_cloud.tone_analyzer.v1.model.Scorecard;
import com.ibm.watson.developer_cloud.tone_analyzer.v1.model.SynonymResult;
import com.ibm.watson.developer_cloud.tone_analyzer.v1.model.Tone;
ToneAnalyzer service = new ToneAnalyzer();
service.setUsernameAndPassword("<username>", "<password>");
String text = "I know the times are difficult! Our sales have been "
+ "disappointing for the past three quarters for our data analytics "
+ "product suite. We have a competitive data analytics product "
+ "suite in the industry. But we need to do our job selling it! "
+ "We need to acknowledge and fix our sales challenges.";
// Call the service and get the tone
Tone tone = service.getTone(text, Scorecard.EMAIL);
System.out.println(tone);Use the Tradeoff Analytics service to find the best phone that minimizes price and weight and maximizes screen size.
import com.ibm.watson.developer_cloud.tradeoff_analytics.v1.TradeoffAnalytics;
import com.ibm.watson.developer_cloud.tradeoff_analytics.v1.model.Dilemma;
import com.ibm.watson.developer_cloud.tradeoff_analytics.v1.model.Problem;
TradeoffAnalytics service = new TradeoffAnalytics();
service.setUsernameAndPassword("<username>", "<password>");
Problem problem = new Problem("phone");
// Define the objectives
List<Column> columns = new ArrayList<Column>();
problem.setColumns(columns);
columns.add(new Column("price", "Price", "NUMERIC", true, "MIN"));
columns.add(new Column("ram", "Ram", "NUMERIC", false, "MAX"));
columns.add(new Column("screen", "Screen", "NUMERIC", true, "MAX"));
// Define the options to choose
List<Option> options = new ArrayList<Option>();
problem.setOptions(options);
HashMap<String, String> galaxySpecs = new HashMap<String, String>();
galaxySpecs.put("price", "300");
galaxySpecs.put("ram", "45");
galaxySpecs.put("screen", "5");
options.add(new Option("1", "Galaxy S4", galaxySpecs, ""));
HashMap<String, String> iphoneSpecs = new HashMap<String, String>();
iphoneSpecs.put("price", "400");
iphoneSpecs.put("ram", "40");
iphoneSpecs.put("screen", "4");
options.add(new Option("2", "iPhone 5", iphoneSpecs, ""));
HashMap<String, String> optimusSpecs = new HashMap<String, String>();
optimusSpecs.put("price", "300");
optimusSpecs.put("ram", "300");
optimusSpecs.put("screen", "5");
options.add(new Option("3", "LG Optimus G", optimusSpecs, ""));
// Call the service and get the resolution
Dilemma dilemma = service.dilemmas(problem);
System.out.println(dilemma);Use the Visual Insights to get insight into the themes present in a collection of images based on their visual appearance/content.
import com.ibm.watson.developer_cloud.visual_insights.v1.VisualInsights;
import com.ibm.watson.developer_cloud.visual_insights.v1.model.Classifiers;
import java.io.File;
VisualInsights service = new VisualInsights();
service.setUsernameAndPassword("<username>", "<password>");
File images = new File("src/test/resources/images.zip");
Summary summary = service.getSummary(images);
System.out.println(summary);Use the Visual Recognition service to recognize the following picture.
import com.ibm.watson.developer_cloud.visual_recognition.v1.VisualRecognition;
import com.ibm.watson.developer_cloud.visual_recognition.v1.model.RecognizedImage;
import com.ibm.watson.developer_cloud.visual_recognition.v1.model.LabelSet;
import java.io.File;
VisualRecognition service = new VisualRecognition();
service.setUsernameAndPassword("<username>", "<password>");
File image = new File("src/test/resources/car.png");
LabelSet labelSet = new LabelSet();
labelSet.withLabelGroup("Auto Racing").withLabelGroup("Sports");
RecognizedImage recognizedImage = service.recognize(image, labelSet);
System.out.println(recognizedImage);The wrapper works well on Android. It depends on Apache HttpClient (including the HttpMime module) and json-java. Android SDK already comes with these two libraries so you don't need to include them when using the wrapper there.
To build and test the project you can use Gradle (version 1.x): or Apache Maven.
Gradle:
$ cd java-wrapper
$ gradle jar # build jar file (build/libs/watson-developer-cloud-1.0.1.jar)
$ gradle test # run testsor Maven:
$ cd java-wrapper
$ mvn installIf you want to work on the code in an IDE instead of a text editor you can easily create project files with gradle:
$ gradle idea # Intellij IDEA
$ gradle eclipse # Eclipseor maven:
$ mvn idea:idea # Intellij IDEA
$ mvn eclipse:eclipse # EclipseFind more open source projects on the IBM Github Page
This library is licensed under Apache 2.0. Full license text is available in LICENSE.
See CONTRIBUTING.md.