Text analytics sentiment

sdk/textanalytics/azure-ai-textanalytics/src/main/java/com/azure/ai/textanalytics/TextAnalyticsAsyncClient.java

@@ -944,13 +944,16 @@ private TextSentimentResult convertToTextSentimentResult(final DocumentSentiment
             return null;
         }
         //TODO (shawn): calculate max length
-        documentSentimentText.setLength("MAX_LENGTH").setOffset(0).setTextSentimentClass(documentSentimentClass);
+        documentSentimentText.setTextSentimentClass(documentSentimentClass);
         setTextSentimentScore(documentSentiment.getDocumentScores(), documentSentimentClass, documentSentimentText);
 
         // Sentence text sentiment
         final List<TextSentiment> sentenceSentimentTexts =
             convertToSentenceSentiments(documentSentiment.getSentences());
 
+        documentSentimentText.setLength(sentenceSentimentTexts.stream().mapToInt(TextSentiment::getLength).sum());
+        documentSentimentText.setOffset(0);
+
         return new TextSentimentResult(documentSentiment.getId(), documentSentiment.getStatistics(), null,
             documentSentimentText, sentenceSentimentTexts);
     }
@@ -959,8 +962,8 @@ private List<TextSentiment> convertToSentenceSentiments(final List<SentenceSenti
         final List<TextSentiment> sentenceSentimentCollection = new ArrayList<>();
         sentenceSentiments.stream().forEach(sentenceSentiment -> {
             final TextSentiment singleSentenceSentiment = new TextSentiment();
-            singleSentenceSentiment.setLength(Integer.toString(sentenceSentiment.getLength()));
-            singleSentenceSentiment.setLength(Integer.toString(sentenceSentiment.getOffset()));
+            singleSentenceSentiment.setLength(sentenceSentiment.getLength());
+            singleSentenceSentiment.setOffset(sentenceSentiment.getOffset());
             final TextSentimentClass sentimentClass = convertToTextSentimentClass(sentenceSentiment.getSentiment());
             setTextSentimentScore(sentenceSentiment.getSentenceScores(), sentimentClass, singleSentenceSentiment);
             singleSentenceSentiment.setTextSentimentClass(sentimentClass);

sdk/textanalytics/azure-ai-textanalytics/src/main/java/com/azure/ai/textanalytics/models/TextSentiment.java

@@ -19,18 +19,18 @@ public class TextSentiment {
     private double positiveScore;
 
     // sentence
-    private String length;
+    private int length;
 
     private int offset;
 
     // sentiment string
     private TextSentimentClass textSentimentClass;
 
-    public String getLength() {
+    public int getLength() {
         return length;
     }
 
-    public TextSentiment setLength(String length) {
+    public TextSentiment setLength(int length) {
         this.length = length;
         return this;
     }

sdk/textanalytics/azure-ai-textanalytics/src/main/java/com/azure/ai/textanalytics/models/TextSentimentResult.java

@@ -16,17 +16,36 @@ public final class TextSentimentResult extends DocumentResult {
     private final TextSentiment documentSentiment;
     private final List<TextSentiment> sentenceSentiments;
 
+    /**
+     * TextSentimentResult model constructor
+     *
+     * @param id document id
+     * @param textDocumentStatistics text document statistics
+     * @param error the document error
+     * @param documentSentiment the document sentiment
+     * @param sentenceSentiments a list of sentence sentiments
+     */
     public TextSentimentResult(String id, TextDocumentStatistics textDocumentStatistics, Error error,
         TextSentiment documentSentiment, List<TextSentiment> sentenceSentiments) {
         super(id, textDocumentStatistics, error);
         this.documentSentiment = documentSentiment;
         this.sentenceSentiments = sentenceSentiments;
     }
 
+    /**
+     * Get the document sentiment.
+     *
+     * @return the document sentiment
+     */
     public TextSentiment getDocumentSentiment() {
         return documentSentiment;
     }
 
+    /**
+     * Get a list of sentence sentiments.
+     *
+     * @return a list of sentence sentiments
+     */
     public List<TextSentiment> getSentenceSentiments() {
         return sentenceSentiments;
     }

sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/batch/AnalyzeSentimentBatchDocuments.java

@@ -11,6 +11,7 @@
 import com.azure.ai.textanalytics.models.TextDocumentInput;
 import com.azure.ai.textanalytics.models.TextSentiment;
 import com.azure.ai.textanalytics.models.TextSentimentResult;
+import com.azure.core.util.Configuration;
 import com.azure.core.util.Context;
 
 import java.util.Arrays;
@@ -21,14 +22,16 @@ public class AnalyzeSentimentBatchDocuments {
     public static void main(String[] args) {
         // Instantiate a client that will be used to call the service.
         TextAnalyticsClient client = new TextAnalyticsClientBuilder()
-            .subscriptionKey("subscription-key")
-            .endpoint("https://servicename.cognitiveservices.azure.com/")
+//            .subscriptionKey("subscription-key")
+//            .endpoint("https://servicename.cognitiveservices.azure.com/")
+            .subscriptionKey(Configuration.getGlobalConfiguration().get("AZURE_TEXT_ANALYTICS_SUBSCRIPTION_KEY"))
+            .endpoint(Configuration.getGlobalConfiguration().get("AZURE_TEXT_ANALYTICS_ENDPOINT"))
             .buildClient();
 
         // The texts that need be analysed.
         List<TextDocumentInput> inputs = Arrays.asList(
-            new TextDocumentInput("1", "The hotel was dark and unclean.", "en"),
-            new TextDocumentInput("2", "The restaurant had amazing gnocchi.", "en")
+            new TextDocumentInput("1", "The hotel was dark and unclean. The restaurant had amazing gnocchi.", "en"),
+            new TextDocumentInput("2", "The restaurant had amazing gnocchi. The hotel was dark and unclean.", "en")
         );
 
         final TextAnalyticsRequestOptions requestOptions = new TextAnalyticsRequestOptions().setShowStatistics(true);
@@ -60,8 +63,8 @@ public static void main(String[] args) {
                     sentenceSentiment.getNeutralScore(),
                     sentenceSentiment.getNegativeScore(),
                     sentenceSentiment.getLength(),
-                    sentenceSentiment.getOffset());
-            }
-        }
+                    sentenceSentiment.getOffset()));
+
+        });
     }
 }

sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics/batch/DetectLanguageBatchDocuments.java

@@ -57,9 +57,9 @@ public static void main(String[] args) {
                 System.out.printf("Other detected Languages: %s, ISO 6391 Name: %s, Score: %s.%n",
                     detectedLanguage.getName(),
                     detectedLanguage.getIso6391Name(),
-                    detectedLanguage.getScore());
-            }
-        }
+                    detectedLanguage.getScore()));
+
+        });
     }
 
 }

sdk/textanalytics/azure-ai-textanalytics/src/test/java/com/azure/ai/textanalytics/TextAnalyticsAsyncClientTest.java

@@ -10,6 +10,8 @@
 import com.azure.ai.textanalytics.models.LinkedEntityResult;
 import com.azure.ai.textanalytics.models.NamedEntity;
 import com.azure.ai.textanalytics.models.NamedEntityResult;
+import com.azure.ai.textanalytics.models.TextSentiment;
+import com.azure.ai.textanalytics.models.TextSentimentClass;
 import com.azure.core.exception.HttpResponseException;
 import com.azure.core.util.Context;
 import org.junit.jupiter.api.Test;
@@ -352,5 +354,57 @@ public void recognizePiiEntitiesForListLanguageHint() {
         });
     }
 
+
     // Key Phrases
+
+
+
+    // Sentiment
+    @Test
+    public void analyseSentimentForTextInput() {
+
+        final TextSentiment expectedDocumentSentiment = new TextSentiment()
+            .setTextSentimentClass(TextSentimentClass.MIXED).setLength(66).setOffset(0);
+        final List<TextSentiment> expectedSentiments = Arrays.asList(
+           new TextSentiment().setTextSentimentClass(TextSentimentClass.NEGATIVE).setLength(31).setOffset(0),
+           new TextSentiment().setTextSentimentClass(TextSentimentClass.POSITIVE).setLength(35).setOffset(32)
+        );
+
+        StepVerifier.create(client.analyzeSentiment("The hotel was dark and unclean. The restaurant had amazing gnocchi."))
+            .assertNext(response -> {
+                validateAnalysedSentiment(expectedDocumentSentiment, response.getDocumentSentiment());
+                validateAnalysedSentenceSentiment(expectedSentiments, response.getSentenceSentiments());
+            })
+            .verifyComplete();
+    }
+
+    @Test
+    public void analyseSentimentForEmptyText() {
+
+    }
+
+    @Test
+    public void analyseSentimentForFaultyText() {
+
+    }
+
+    @Test
+    public void analyseSentimentForBatchInput() {
+
+    }
+
+    @Test
+    public void analyseSentimentForBatchInputShowStatistics() {
+
+    }
+
+    @Test
+    public void analyseSentimentForBatchStringInput() {
+
+    }
+
+    @Test
+    public void analyseSentimentForListLanguageHint() {
+
+    }
 }

sdk/textanalytics/azure-ai-textanalytics/src/test/java/com/azure/ai/textanalytics/TextAnalyticsClientTest.java

@@ -313,4 +313,40 @@ public void recognizeKeyPhrasesForBatchStringInput() {
     public void recognizeKeyPhrasesForListLanguageHint() {
 
     }
+
+    // Sentiment
+    @Test
+    public void analyseSentimentForTextInput() {
+
+    }
+
+    @Test
+    public void analyseSentimentForEmptyText() {
+
+    }
+
+    @Test
+    public void analyseSentimentForFaultyText() {
+
+    }
+
+    @Test
+    public void analyseSentimentForBatchInput() {
+
+    }
+
+    @Test
+    public void analyseSentimentForBatchInputShowStatistics() {
+
+    }
+
+    @Test
+    public void analyseSentimentForBatchStringInput() {
+
+    }
+
+    @Test
+    public void analyseSentimentForListLanguageHint() {
+
+    }
 }