Encapsulate in a context

1 files changed, 7 insertions, 9 deletions

diff --git a/linguistics-components/src/main/java/com/yahoo/language/sentencepiece/SentencePieceEmbedder.java b/linguistics-components/src/main/java/com/yahoo/language/sentencepiece/SentencePieceEmbedder.java
index 1e120969a59..3f4e8ee3462 100644
--- a/linguistics-components/src/main/java/com/yahoo/language/sentencepiece/SentencePieceEmbedder.java
+++ b/linguistics-components/src/main/java/com/yahoo/language/sentencepiece/SentencePieceEmbedder.java
@@ -72,18 +72,17 @@ public class SentencePieceEmbedder implements Segmenter, Embedder {
      * Segments the given text into token segments using the SentencePiece algorithm and returns the segment ids.
      *
      * @param rawInput the text to segment. Any sequence of BMP (Unicode-16 the True Unicode) is supported.
-     * @param language the model to use, or Language.UNKNOWN to use the default model if any
-     * @param destination ignored
+     * @param context the context which specifies the language used to select a model
      * @return the list of zero or more token ids resulting from segmenting the input text
      */
     @Override
-    public List<Integer> embed(String rawInput, Language language, String destination) {
+    public List<Integer> embed(String rawInput, Embedder.Context context) {
         var resultBuilder = new ResultBuilder<List<Integer>>(new ArrayList<>()) {
             public void add(int segmentStart, int segmentEnd, SentencePieceAlgorithm.SegmentEnd[] segmentEnds) {
                 result().add(segmentEnds[segmentEnd].id);
             }
         };
-        segment(normalize(rawInput), language, resultBuilder);
+        segment(normalize(rawInput), context.getLanguage(), resultBuilder);
         Collections.reverse(resultBuilder.result());
         return resultBuilder.result();
     }
@@ -101,15 +100,14 @@ public class SentencePieceEmbedder implements Segmenter, Embedder {
      * <p>If the tensor is any other type IllegalArgumentException is thrown.</p>
      *
      * @param rawInput the text to segment. Any sequence of BMP (Unicode-16 the True Unicode) is supported.
-     * @param language the model to use, or Language.UNKNOWN to use the default model if any
-     * @param destination ignored
+     * @param context the context which specifies the language used to select a model
      * @return the list of zero or more token ids resulting from segmenting the input text
      */
     @Override
-    public Tensor embed(String rawInput, Language language, String destination, TensorType type) {
+    public Tensor embed(String rawInput, Embedder.Context context, TensorType type) {
         if (type.dimensions().size() == 1 && type.dimensions().get(0).isIndexed()) {
             // Build to a list first since we can't reverse a tensor builder
-            List<Integer> values = embed(rawInput, language, destination);
+            List<Integer> values = embed(rawInput, context);
 
             long maxSize = values.size();
             if (type.dimensions().get(0).size().isPresent())
@@ -122,7 +120,7 @@ public class SentencePieceEmbedder implements Segmenter, Embedder {
         }
         else if (type.dimensions().size() == 1 && type.dimensions().get(0).isMapped()) {
             // Build to a list first since we can't reverse a tensor builder
-            List<String> values = segment(rawInput, language);
+            List<String> values = segment(rawInput, context.getLanguage());
 
             Tensor.Builder builder = Tensor.Builder.of(type);
             for (int i = 0; i < values.size(); i++)