Merge remote-tracking branch 'watson-developer-cloud/develop'

Author: lpatino10

.bumpversion.cfg

@@ -0,0 +1,20 @@
+[bumpversion]
+current_version = 4.0.0
+
+[bumpversion:file:README.md]
+[bumpversion:file:alchemy/README.md]
+[bumpversion:file:conversation/README.md]
+[bumpversion:file:discovery/README.md]
+[bumpversion:file:document-conversion/README.md]
+[bumpversion:file:language-translator/README.md]
+[bumpversion:file:natural-language-classifier/README.md]
+[bumpversion:file:natural-language-understanding/README.md]
+[bumpversion:file:personality-insights/README.md]
+[bumpversion:file:retrieve-and-rank/README.md]
+[bumpversion:file:speech-to-text/README.md]
+[bumpversion:file:text-to-speech/README.md]
+[bumpversion:file:tone-analyzer/README.md]
+[bumpversion:file:tradeoff-analytics/README.md]
+[bumpversion:file:visual-recognition/README.md]
+search = {current_version}
+replace = {new_version}

.utility/push-javadoc-to-gh-pages.sh

@@ -4,7 +4,7 @@ if [ "$TRAVIS_PULL_REQUEST" == "false" ] && [ "$TRAVIS_BRANCH" ]; then
 
   git config --global user.email "[email protected]"
   git config --global user.name "Watson Github Bot"
-  git clone --quiet --branch=gh-pages https://${GITHUB_TOKEN_DOCS}@github.com/watson-developer-cloud/java-sdk gh-pages > /dev/null
+  git clone --quiet --branch=gh-pages https://${GITHUB_TOKEN_DOCS}@github.com/watson-developer-cloud/java-sdk.git gh-pages > /dev/null
 
   pushd gh-pages
     # on tagged builds, $TRAVIS_BRANCH is the tag (e.g. v1.2.3), otherwise it's the branch name (e.g. master)

RELEASE.md

@@ -17,9 +17,26 @@ If you are not familiar with Sonatype and/or the maven release process please re
 
 ### Release steps
 
-  1. Update `README.md` to include the new version number
+  1. Update all READMEs to include the new version number
+
+     This can be done using [bumpversion]. If necessary, it can be installed with the following command:
+
+     ```bash
+     pip install bumpversion
+     ```
+
+     To then update all version numbers, simply run:
+
+     ```bash
+     bumpversion major|minor|patch
+     ```
+
   1. Perform a release deployment to OSSRH (Staging) with:
 
-    `gradle release`
+     ```bash
+     `gradle release`
+     ```
+
+     You will have to answer prompts for versions and tags. That will tag and commit a new version into your repository automatically.
 
-    You will have to answer prompts for versions and tags. That will tag and commit a new version into your repository automatically.
+[bumpversion]: https://pypi.python.org/pypi/bumpversion

natural-language-understanding/src/main/java/com/ibm/watson/developer_cloud/natural_language_understanding/v1/model/DocumentSentimentResults.java

@@ -20,6 +20,7 @@
 public class DocumentSentimentResults extends GenericModel {
 
   private Double score;
+  private String label;
 
   /**
    * Gets the score.
@@ -40,4 +41,24 @@ public Double getScore() {
   public void setScore(final Double score) {
     this.score = score;
   }
+
+  /**
+   * Gets the label.
+   *
+   * Sentiment label
+   *
+   * @return the label
+   */
+  public String getLabel() {
+    return label;
+  }
+
+  /**
+   * Sets the label.
+   *
+   * @param label the new label
+   */
+  public void setLabel(String label) {
+    this.label = label;
+  }
 }

natural-language-understanding/src/test/java/com/ibm/watson/developer_cloud/natural_language_understanding/v1/NaturalLanguageUnderstandingTest.java

@@ -257,7 +257,9 @@ public void testModelOptions1() throws InterruptedException {
     // DocumentSentimentResults
     DocumentSentimentResults documentSentimentResults = new DocumentSentimentResults();
     documentSentimentResults.setScore(10.10);
+    documentSentimentResults.setLabel("neutral");
     assertEquals(documentSentimentResults.getScore(), 10.10, 0);
+    assertEquals(documentSentimentResults.getLabel(), "neutral");
 
     // EmotionOptions
     EmotionOptions emotionOptions = new EmotionOptions.Builder().document(true).targets(null).build();

speech-to-text/src/main/java/com/ibm/watson/developer_cloud/speech_to_text/v1/SpeechToText.java

@@ -69,6 +69,7 @@ public class SpeechToText extends WatsonService {
   private static final String CALLBACK_URL = "callback_url";
   private static final String CONTINUOUS = "continuous";
   private static final String CUSTOMIZATION_ID = "customization_id";
+  private static final String CUSTOMIZATION_WEIGHT = "customization_weight";
   private static final String EVENTS = "events";
   private static final String INACTIVITY_TIMEOUT = "inactivity_timeout";
   private static final String KEYWORDS = "keywords";
@@ -232,6 +233,10 @@ private void buildRecognizeRequest(RequestBuilder requestBuilder, RecognizeOptio
     if (options.customizationId() != null) {
       requestBuilder.query(CUSTOMIZATION_ID, options.customizationId());
     }
+
+    if (options.customizationWeight() != null) {
+      requestBuilder.query(CUSTOMIZATION_WEIGHT, options.customizationWeight());
+    }
   }
 
   /**
@@ -815,6 +820,10 @@ public WebSocket recognizeUsingWebSocket(final InputStream audio, final Recogniz
       urlBuilder.addQueryParameter(CUSTOMIZATION_ID, options.customizationId());
     }
 
+    if (options.customizationWeight() != null) {
+      urlBuilder.addQueryParameter(CUSTOMIZATION_WEIGHT, String.valueOf(options.customizationWeight()));
+    }
+
     String url = urlBuilder.toString().replace("https://", "wss://");
     Builder builder = new Request.Builder().url(url);
 

speech-to-text/src/main/java/com/ibm/watson/developer_cloud/speech_to_text/v1/model/RecognizeOptions.java

@@ -48,6 +48,7 @@ public static class Builder {
     private Boolean smartFormatting;
     private String customizationId;
     private Boolean speakerLabels;
+    private Double customizationWeight;
 
     private Builder(RecognizeOptions options) {
       contentType = options.contentType;
@@ -66,6 +67,7 @@ private Builder(RecognizeOptions options) {
       smartFormatting = options.smartFormatting;
       customizationId = options.customizationId;
       speakerLabels = options.speakerLabels;
+      customizationWeight = options.customizationWeight;
     }
 
     /**
@@ -135,6 +137,21 @@ public Builder speakerLabels(Boolean speakerLabels) {
       return this;
     }
 
+    /**
+     * If a custom model is specified, this parameter tells the service how much weight to give
+     * to words from the custom language model compared to those from the base model.
+     * Specify a value between 0.0 and 1.0 (inclusive). If value is null or omitted, the customization
+     * weight from the model is used. If no customization weight is specified on the model, the default
+     * value of the service will be used.
+     *
+     * @param customizationWeight Labels or "diarization"
+     * @return the recognize options
+     */
+    public Builder customizationWeight(Double customizationWeight) {
+      this.customizationWeight = customizationWeight;
+      return this;
+    }
+
     /**
      * If true, filters profanity from all output except for keyword results by replacing inappropriate words with a
      * series of asterisks. Set the parameter to false to return results with no censoring. Applies to US English
@@ -330,6 +347,9 @@ public Builder wordConfidence(Boolean wordConfidence) {
   @SerializedName("speaker_labels")
   private Boolean speakerLabels;
 
+  @SerializedName("customization_weight")
+  private Double customizationWeight;
+
   private RecognizeOptions(Builder builder) {
     contentType = builder.contentType;
     continuous = builder.continuous;
@@ -347,6 +367,7 @@ private RecognizeOptions(Builder builder) {
     smartFormatting = builder.smartFormatting;
     customizationId = builder.customizationId;
     speakerLabels = builder.speakerLabels;
+    customizationWeight = builder.customizationWeight;
   }
 
   /**
@@ -394,6 +415,15 @@ public Boolean speakerLabels() {
     return speakerLabels;
   }
 
+  /**
+   * Gets the customizationWeight.
+   *
+   * @return the customizationWeight
+   */
+  public Double customizationWeight() {
+    return customizationWeight;
+  }
+
   /**
    * Gets the continuous.
    *

speech-to-text/src/test/java/com/ibm/watson/developer_cloud/speech_to_text/v1/SpeechToTextTest.java

@@ -358,6 +358,29 @@ public void testRecognizeWithCustomization() throws FileNotFoundException, Inter
     assertEquals(recognition, GSON.toJsonTree(result));
   }
 
+    /**
+   * Test recognize with customization weight.
+   *
+   * @throws FileNotFoundException the file not found exception
+   * @throws InterruptedException the interrupted exception
+   */
+  @Test
+  public void testRecognizeWithCustomizationWeight() throws FileNotFoundException, InterruptedException {
+    String id = "foo";
+    String recString =
+        getStringFromInputStream(new FileInputStream("src/test/resources/speech_to_text/recognition.json"));
+    JsonObject recognition = new JsonParser().parse(recString).getAsJsonObject();
+
+    server.enqueue(new MockResponse().addHeader(CONTENT_TYPE, HttpMediaType.APPLICATION_JSON).setBody(recString));
+
+    RecognizeOptions options = new RecognizeOptions.Builder().customizationId(id).customizationWeight(0.5).build();
+    SpeechResults result = service.recognize(SAMPLE_WAV, options).execute();
+    final RecordedRequest request = server.takeRequest();
+
+    assertEquals(PATH_RECOGNIZE + "?customization_id=" + id + "&customization_weight=0.5", request.getPath());
+    assertEquals(recognition, GSON.toJsonTree(result));
+  }
+
   /**
    * Test recognize -missing audio file, generate IllegalArgumentException.
    *

tone-analyzer/src/main/java/com/ibm/watson/developer_cloud/tone_analyzer/v3/ToneAnalyzer.java

@@ -21,25 +21,23 @@
 import com.ibm.watson.developer_cloud.tone_analyzer.v3.model.ToneOptions;
 import com.ibm.watson.developer_cloud.tone_analyzer.v3.model.UtteranceAnalyses;
 import com.ibm.watson.developer_cloud.util.GsonSingleton;
-import com.ibm.watson.developer_cloud.util.RequestUtils;
 import com.ibm.watson.developer_cloud.util.ResponseConverterUtils;
 import com.ibm.watson.developer_cloud.util.Validator;
 
 /**
  * ### Service Overview
- * The IBM Watson Tone Analyzer service uses linguistic analysis to detect emotional, social, 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.
+ * 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 a maximum of 128 KB of content in JSON, plain text, or HTML
- * format.
+ * 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 a maximum of
- * 128 KB of content in JSON format.
+ * 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
@@ -98,17 +96,7 @@ public ToneAnalyzer(String versionDate, String username, String password) {
   /**
    * Analyze general purpose tone.
    *
-   * Uses the general purpose endpoint to analyze the tone of your input content. The service can analyze the input for
-   * several tones: emotion, language, and social. It derives various characteristics for each tone that it analyzes.
-   * The method always analyzes the tone of the full document; by default, it also analyzes the tone of each individual
-   * sentence of the input. You can submit a maximum of 128 KB of content in JSON, plain text, or HTML format.   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.   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.
+   * 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.   **Note:** The `tones` query parameter is no longer supported. The service continues to accept the parameter for backward-compatibility, but the parameter no longer affects the response.
    *
    * @param toneOptions the {@link ToneOptions} containing the options for the call
    * @return the {@link ToneAnalysis} with the response
@@ -118,8 +106,11 @@ public ServiceCall<ToneAnalysis> tone(ToneOptions toneOptions) {
     RequestBuilder builder = RequestBuilder.post("/v3/tone");
     builder.query(VERSION, versionDate);
     builder.header("content-type", toneOptions.contentType());
-    if (toneOptions.tones() != null) {
-    builder.query("tones", RequestUtils.join(toneOptions.tones(), ","));
+    if (toneOptions.contentLanguage() != null) {
+      builder.header("Content-Language", toneOptions.contentLanguage());
+    }
+    if (toneOptions.acceptLanguage() != null) {
+      builder.header("Accept-Language", toneOptions.acceptLanguage());
     }
     if (toneOptions.sentences() != null) {
     builder.query("sentences", String.valueOf(toneOptions.sentences()));
@@ -135,11 +126,7 @@ public ServiceCall<ToneAnalysis> tone(ToneOptions toneOptions) {
   /**
    * Analyze customer engagement tone.
    *
-   * Uses 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. You can submit a maximum of 128 KB of
-   * JSON input. Per the JSON specification, the default character encoding for JSON content is effectively always
-   * UTF-8.
+   * 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.
    *
    * @param toneChatOptions the {@link ToneChatOptions} containing the options for the call
    * @return the {@link UtteranceAnalyses} with the response
@@ -148,6 +135,9 @@ public ServiceCall<UtteranceAnalyses> toneChat(ToneChatOptions toneChatOptions)
     Validator.notNull(toneChatOptions, "toneChatOptions cannot be null");
     RequestBuilder builder = RequestBuilder.post("/v3/tone_chat");
     builder.query(VERSION, versionDate);
+    if (toneChatOptions.acceptLanguage() != null) {
+      builder.header("Accept-Language", toneChatOptions.acceptLanguage());
+    }
     final JsonObject contentJson = new JsonObject();
     contentJson.add("utterances", GsonSingleton.getGson().toJsonTree(toneChatOptions.utterances()));
     builder.bodyJson(contentJson);

tone-analyzer/src/main/java/com/ibm/watson/developer_cloud/tone_analyzer/v3/model/DocumentAnalysis.java

@@ -14,35 +14,53 @@
 
 import java.util.List;
 
-import com.google.gson.annotations.SerializedName;
 import com.ibm.watson.developer_cloud.service.model.GenericModel;
 
 /**
  * DocumentAnalysis.
  */
 public class DocumentAnalysis extends GenericModel {
 
-  @SerializedName("tone_categories")
-  private List<ToneCategory> toneCategories;
+  private List<ToneScore> tones;
+  private String warning;
 
   /**
-   * Gets the toneCategories.
+   * Gets the tones.
    *
-   * 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.
+   * 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.
    *
-   * @return the toneCategories
+   * @return the tones
    */
-  public List<ToneCategory> getToneCategories() {
-    return toneCategories;
+  public List<ToneScore> getTones() {
+    return tones;
   }
 
   /**
-   * Sets the toneCategories.
+   * Gets the warning.
    *
-   * @param toneCategories the new toneCategories
+   * 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.
+   *
+   * @return the warning
+   */
+  public String getWarning() {
+    return warning;
+  }
+
+  /**
+   * Sets the tones.
+   *
+   * @param tones the new tones
+   */
+  public void setTones(final List<ToneScore> tones) {
+    this.tones = tones;
+  }
+
+  /**
+   * Sets the warning.
+   *
+   * @param warning the new warning
    */
-  public void setToneCategories(final List<ToneCategory> toneCategories) {
-    this.toneCategories = toneCategories;
+  public void setWarning(final String warning) {
+    this.warning = warning;
   }
 }