renaming around to make it clearer

solr/modules/llm/src/java/org/apache/solr/llm/embedding/SolrEmbeddingModel.java

@@ -36,19 +36,19 @@ public class SolrEmbeddingModel implements Accountable {
 
   private final String name;
   private final Map<String, Object> params;
-  private final EmbeddingModel embedder;
+  private final EmbeddingModel textToVector;
   private final Integer hashCode;
 
   public static SolrEmbeddingModel getInstance(
       String className, String name, Map<String, Object> params) throws EmbeddingModelException {
     try {
       /*
-       * The idea herea is to build a {@link dev.langchain4j.model.embedding.EmbeddingModel} using inversion
+       * The idea here is to build a {@link dev.langchain4j.model.embedding.EmbeddingModel} using inversion
        * of control.
        * Each model has its own list of parameters we don't know beforehand, but each {@link dev.langchain4j.model.embedding.EmbeddingModel} class
        * has its own builder that uses setters with the same name of the parameter in input.
        * */
-      EmbeddingModel embedder;
+      EmbeddingModel textToVector;
       Class<?> modelClass = Class.forName(className);
       var builder = modelClass.getMethod("builder").invoke(null);
       if (params != null) {
@@ -94,22 +94,22 @@ public static SolrEmbeddingModel getInstance(
           }
         }
       }
-      embedder = (EmbeddingModel) builder.getClass().getMethod("build").invoke(builder);
-      return new SolrEmbeddingModel(name, embedder, params);
+      textToVector = (EmbeddingModel) builder.getClass().getMethod("build").invoke(builder);
+      return new SolrEmbeddingModel(name, textToVector, params);
     } catch (final Exception e) {
       throw new EmbeddingModelException("Model loading failed for " + className, e);
     }
   }
 
-  public SolrEmbeddingModel(String name, EmbeddingModel embedder, Map<String, Object> params) {
+  public SolrEmbeddingModel(String name, EmbeddingModel textToVector, Map<String, Object> params) {
     this.name = name;
-    this.embedder = embedder;
+    this.textToVector = textToVector;
     this.params = params;
     this.hashCode = calculateHashCode();
   }
 
   public float[] vectorise(String text) {
-    Embedding vector = embedder.embed(text).content();
+    Embedding vector = textToVector.embed(text).content();
     return vector.vector();
   }
 
@@ -122,7 +122,7 @@ public String toString() {
   public long ramBytesUsed() {
     return BASE_RAM_BYTES
         + RamUsageEstimator.sizeOfObject(name)
-        + RamUsageEstimator.sizeOfObject(embedder);
+        + RamUsageEstimator.sizeOfObject(textToVector);
   }
 
   @Override
@@ -134,7 +134,7 @@ private int calculateHashCode() {
     final int prime = 31;
     int result = 1;
     result = (prime * result) + Objects.hashCode(name);
-    result = (prime * result) + Objects.hashCode(embedder);
+    result = (prime * result) + Objects.hashCode(textToVector);
     return result;
   }
 
@@ -143,15 +143,15 @@ public boolean equals(Object obj) {
     if (this == obj) return true;
     if (!(obj instanceof SolrEmbeddingModel)) return false;
     final SolrEmbeddingModel other = (SolrEmbeddingModel) obj;
-    return Objects.equals(embedder, other.embedder) && Objects.equals(name, other.name);
+    return Objects.equals(textToVector, other.textToVector) && Objects.equals(name, other.name);
   }
 
   public String getName() {
     return name;
   }
 
-  public String getEmbedderClassName() {
-    return embedder.getClass().getName();
+  public String getEmbeddingModelClassName() {
+    return textToVector.getClass().getName();
   }
 
   public Map<String, Object> getParams() {

solr/modules/llm/src/java/org/apache/solr/llm/search/TextEmbedderQParserPlugin.java → solr/modules/llm/src/java/org/apache/solr/llm/search/TextToVectorQParserPlugin.java

@@ -39,19 +39,19 @@
 import org.apache.solr.search.neural.KnnQParser;
 
 /**
- * A neural query parser that embed the query and then run K-nearest neighbors search on Dense
- * Vector fields. See Wiki page
+ * A neural query parser that encode the query to a vector and then run K-nearest neighbors search
+ * on Dense Vector fields. See Wiki page
  * https://solr.apache.org/guide/solr/latest/query-guide/dense-vector-search.html
  */
-public class TextEmbedderQParserPlugin extends QParserPlugin
+public class TextToVectorQParserPlugin extends QParserPlugin
     implements ResourceLoaderAware, ManagedResourceObserver {
   public static final String EMBEDDING_MODEL_PARAM = "model";
   private ManagedEmbeddingModelStore modelStore = null;
 
   @Override
   public QParser createParser(
       String qstr, SolrParams localParams, SolrParams params, SolrQueryRequest req) {
-    return new TextEmbedderQParser(qstr, localParams, params, req);
+    return new TextToVectorQParser(qstr, localParams, params, req);
   }
 
   @Override
@@ -67,26 +67,25 @@ public void onManagedResourceInitialized(NamedList<?> args, ManagedResource res)
       modelStore = (ManagedEmbeddingModelStore) res;
     }
     if (modelStore != null) {
-      // now we can safely load the models
       modelStore.loadStoredModels();
     }
   }
 
-  public class TextEmbedderQParser extends KnnQParser {
+  public class TextToVectorQParser extends KnnQParser {
 
-    public TextEmbedderQParser(
-        String qstr, SolrParams localParams, SolrParams params, SolrQueryRequest req) {
-      super(qstr, localParams, params, req);
+    public TextToVectorQParser(
+        String queryString, SolrParams localParams, SolrParams params, SolrQueryRequest req) {
+      super(queryString, localParams, params, req);
     }
 
     @Override
     public Query parse() throws SyntaxError {
-      checkParam(qstr, "Query string is empty, nothing to embed");
+      checkParam(qstr, "Query string is empty, nothing to vectorise");
       final String embeddingModelName = localParams.get(EMBEDDING_MODEL_PARAM);
       checkParam(embeddingModelName, "The 'model' parameter is missing");
-      SolrEmbeddingModel embedder = modelStore.getModel(embeddingModelName);
+      SolrEmbeddingModel textToVector = modelStore.getModel(embeddingModelName);
 
-      if (embedder != null) {
+      if (textToVector != null) {
         final SchemaField schemaField = req.getCore().getLatestSchema().getField(getFieldName());
         final DenseVectorField denseVectorType = getCheckedFieldType(schemaField);
         int fieldDimensions = denseVectorType.getDimension();
@@ -96,7 +95,7 @@ public Query parse() throws SyntaxError {
         switch (vectorEncoding) {
           case FLOAT32:
             {
-              float[] vectorToSearch = embedder.vectorise(qstr);
+              float[] vectorToSearch = textToVector.vectorise(qstr);
               checkVectorDimension(vectorToSearch.length, fieldDimensions);
               return new KnnFloatVectorQuery(
                   schemaField.getName(), vectorToSearch, topK, getFilterQuery());

solr/modules/llm/src/java/org/apache/solr/llm/store/rest/ManagedEmbeddingModelStore.java

@@ -197,7 +197,7 @@ public static SolrEmbeddingModel fromEmbeddingModelMap(Map<String, Object> embed
   private static LinkedHashMap<String, Object> toEmbeddingModelMap(SolrEmbeddingModel model) {
     final LinkedHashMap<String, Object> modelMap = new LinkedHashMap<>(5, 1.0f);
     modelMap.put(NAME_KEY, model.getName());
-    modelMap.put(CLASS_KEY, model.getEmbedderClassName());
+    modelMap.put(CLASS_KEY, model.getEmbeddingModelClassName());
     modelMap.put(PARAMS_KEY, model.getParams());
     return modelMap;
   }

solr/modules/llm/src/test-files/solr/collection1/conf/solrconfig-llm.xml

@@ -22,8 +22,8 @@
  </requestDispatcher>
 
  <!-- Query parser used to run neural queries-->
- <queryParser name="text_embedder"
-  class="org.apache.solr.llm.search.TextEmbedderQParserPlugin" />
+ <queryParser name="text_to_vector"
+  class="org.apache.solr.llm.search.TextToVectorQParserPlugin" />
 
  <query>
   <filterCache class="solr.CaffeineCache" size="4096"

solr/modules/llm/src/test/org/apache/solr/llm/search/TextEmbedderQParserTest.java → solr/modules/llm/src/test/org/apache/solr/llm/search/TextToVectorQParserTest.java

@@ -22,7 +22,7 @@
 import org.junit.BeforeClass;
 import org.junit.Test;
 
-public class TextEmbedderQParserTest extends TestLlmBase {
+public class TextToVectorQParserTest extends TestLlmBase {
   @BeforeClass
   public static void init() throws Exception {
     setupTest("solrconfig-llm.xml", "schema.xml", true, false);
@@ -31,7 +31,7 @@ public static void init() throws Exception {
 
   @Test
   public void notExistentModel_shouldThrowException() throws Exception {
-    final String solrQuery = "{!text_embedder model=not-exist f=vector topK=5}hello world";
+    final String solrQuery = "{!text_to_vector model=not-exist f=vector topK=5}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.add("fl", "id");
@@ -44,7 +44,7 @@ public void notExistentModel_shouldThrowException() throws Exception {
 
   @Test
   public void missingModelParam_shouldThrowException() throws Exception {
-    final String solrQuery = "{!text_embedder f=vector topK=5}hello world";
+    final String solrQuery = "{!text_to_vector f=vector topK=5}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.add("fl", "id");
@@ -57,7 +57,7 @@ public void missingModelParam_shouldThrowException() throws Exception {
 
   @Test
   public void incorrectVectorFieldType_shouldThrowException() throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 f=id topK=5}hello world";
+    final String solrQuery = "{!text_to_vector model=dummy-1 f=id topK=5}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.add("fl", "id");
@@ -70,7 +70,7 @@ public void incorrectVectorFieldType_shouldThrowException() throws Exception {
 
   @Test
   public void undefinedVectorField_shouldThrowException() throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 f=notExistent topK=5}hello world";
+    final String solrQuery = "{!text_to_vector model=dummy-1 f=notExistent topK=5}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.add("fl", "id");
@@ -83,7 +83,7 @@ public void undefinedVectorField_shouldThrowException() throws Exception {
 
   @Test
   public void missingVectorFieldParam_shouldThrowException() throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 topK=5}hello world";
+    final String solrQuery = "{!text_to_vector model=dummy-1 topK=5}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.add("fl", "id");
@@ -97,7 +97,7 @@ public void missingVectorFieldParam_shouldThrowException() throws Exception {
   @Test
   public void vectorByteEncodingField_shouldRaiseException() throws Exception {
     final String solrQuery =
-        "{!text_embedder model=dummy-1 f=vector_byte_encoding topK=5}hello world";
+        "{!text_to_vector model=dummy-1 f=vector_byte_encoding topK=5}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.add("fl", "id");
@@ -110,20 +110,21 @@ public void vectorByteEncodingField_shouldRaiseException() throws Exception {
 
   @Test
   public void missingQueryToEmbed_shouldThrowException() throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 f=vector topK=5}";
+    final String solrQuery = "{!text_to_vector model=dummy-1 f=vector topK=5}";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.add("fl", "id");
 
     assertJQ(
         "/query" + query.toQueryString(),
-        "/error/msg=='Query string is empty, nothing to embed'",
+        "/error/msg=='Query string is empty, nothing to vectorise'",
         "/error/code==400");
   }
 
   @Test
   public void incorrectVectorToSearchDimension_shouldThrowException() throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 f=2048_float_vector topK=5}hello world";
+    final String solrQuery =
+        "{!text_to_vector model=dummy-1 f=2048_float_vector topK=5}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.add("fl", "id");
@@ -136,7 +137,7 @@ public void incorrectVectorToSearchDimension_shouldThrowException() throws Excep
 
   @Test
   public void topK_shouldEmbedAndReturnOnlyTopKResults() throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 f=vector topK=5}hello world";
+    final String solrQuery = "{!text_to_vector model=dummy-1 f=vector topK=5}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.add("fl", "id");
@@ -153,7 +154,7 @@ public void topK_shouldEmbedAndReturnOnlyTopKResults() throws Exception {
 
   @Test
   public void vectorFieldParam_shouldSearchOnThatField() throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 f=vector2 topK=5}hello world";
+    final String solrQuery = "{!text_to_vector model=dummy-1 f=vector2 topK=5}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.add("fl", "id");
@@ -168,7 +169,7 @@ public void vectorFieldParam_shouldSearchOnThatField() throws Exception {
 
   @Test
   public void embeddedQuery_shouldRankBySimilarityFunction() throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 f=vector topK=10}hello world";
+    final String solrQuery = "{!text_to_vector model=dummy-1 f=vector topK=10}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.add("fl", "id");
@@ -191,7 +192,7 @@ public void embeddedQuery_shouldRankBySimilarityFunction() throws Exception {
   @Test
   public void embeddedQueryUsedInFilter_shouldFilterResultsBeforeTheQueryExecution()
       throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 f=vector topK=4}hello world";
+    final String solrQuery = "{!text_to_vector model=dummy-1 f=vector topK=4}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery("id:(3 4 9 2)");
     query.setFilterQueries(solrQuery);
@@ -207,7 +208,7 @@ public void embeddedQueryUsedInFilter_shouldFilterResultsBeforeTheQueryExecution
   @Test
   public void embeddedQueryUsedInFilters_shouldFilterResultsBeforeTheQueryExecution()
       throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 f=vector topK=4}hello world";
+    final String solrQuery = "{!text_to_vector model=dummy-1 f=vector topK=4}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery("id:(3 4 9 2)");
     query.setFilterQueries(solrQuery, "id:(4 20 9)");
@@ -222,7 +223,7 @@ public void embeddedQueryUsedInFilters_shouldFilterResultsBeforeTheQueryExecutio
   public void embeddedQueryUsedInFiltersWithPreFilter_shouldFilterResultsBeforeTheQueryExecution()
       throws Exception {
     final String solrQuery =
-        "{!text_embedder model=dummy-1 f=vector topK=4 preFilter='id:(1 4 7 8 9)'}hello world";
+        "{!text_to_vector model=dummy-1 f=vector topK=4 preFilter='id:(1 4 7 8 9)'}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery("id:(3 4 9 2)");
     query.setFilterQueries(solrQuery, "id:(4 20 9)");
@@ -240,8 +241,8 @@ public void embeddedQueryUsedInFiltersWithPreFilter_shouldFilterResultsBeforeThe
   public void embeddedQueryUsedInFilters_rejectIncludeExclude() throws Exception {
     for (String fq :
         Arrays.asList(
-            "{!text_embedder model=dummy-1 f=vector topK=5 includeTags=xxx}hello world",
-            "{!text_embedder model=dummy-1 f=vector topK=5 excludeTags=xxx}hello world")) {
+            "{!text_to_vector model=dummy-1 f=vector topK=5 includeTags=xxx}hello world",
+            "{!text_to_vector model=dummy-1 f=vector topK=5 excludeTags=xxx}hello world")) {
       final SolrQuery query = new SolrQuery();
       query.setQuery("*:*");
       query.setFilterQueries(fq);
@@ -257,7 +258,7 @@ public void embeddedQueryUsedInFilters_rejectIncludeExclude() throws Exception {
   @Test
   public void embeddedQueryAsSubQuery() throws Exception {
     final String solrQuery =
-        "*:* AND {!text_embedder model=dummy-1 f=vector topK=5 v='hello world'}";
+        "*:* AND {!text_to_vector model=dummy-1 f=vector topK=5 v='hello world'}";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.setFilterQueries("id:(2 4 7 9 8 20 3)");
@@ -276,7 +277,7 @@ public void embeddedQueryAsSubQuery() throws Exception {
   @Test
   public void embeddedQueryAsSubQuery_withPreFilter() throws Exception {
     final String solrQuery =
-        "*:* AND {!text_embedder model=dummy-1 f=vector topK=5 preFilter='id:(2 4 7 9 8 20 3)' v='hello world'}";
+        "*:* AND {!text_to_vector model=dummy-1 f=vector topK=5 preFilter='id:(2 4 7 9 8 20 3)' v='hello world'}";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.add("fl", "id");
@@ -297,8 +298,8 @@ public void embeddedQueryAsSubQuery_withPreFilter() throws Exception {
   public void embeddedQueryAsSubQuery_rejectIncludeExclude() throws Exception {
     for (String q :
         Arrays.asList(
-            "{!text_embedder model=dummy-1 f=vector topK=5 includeTags=xxx}hello world",
-            "{!text_embedder model=dummy-1 f=vector topK=5 excludeTags=xxx}hello world")) {
+            "{!text_to_vector model=dummy-1 f=vector topK=5 includeTags=xxx}hello world",
+            "{!text_to_vector model=dummy-1 f=vector topK=5 excludeTags=xxx}hello world")) {
       final SolrQuery query = new SolrQuery();
       query.setQuery("*:* OR " + q);
       query.add("fl", "id");
@@ -312,7 +313,7 @@ public void embeddedQueryAsSubQuery_rejectIncludeExclude() throws Exception {
 
   @Test
   public void embeddedQueryWithCostlyFq_shouldPerformKnnSearchWithPostFilter() throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 f=vector topK=10}hello world";
+    final String solrQuery = "{!text_to_vector model=dummy-1 f=vector topK=10}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.setFilterQueries("{!frange cache=false l=0.99}$q");
@@ -331,7 +332,7 @@ public void embeddedQueryWithCostlyFq_shouldPerformKnnSearchWithPostFilter() thr
   @Test
   public void embeddedQueryWithFilterQueries_shouldPerformKnnSearchWithPreFiltersAndPostFilters()
       throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 f=vector topK=4}hello world";
+    final String solrQuery = "{!text_to_vector model=dummy-1 f=vector topK=4}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.setFilterQueries("id:(3 4 9 2)", "{!frange cache=false l=0.99}$q");
@@ -347,7 +348,7 @@ public void embeddedQueryWithFilterQueries_shouldPerformKnnSearchWithPreFiltersA
   @Test
   public void embeddedQueryWithNegativeFilterQuery_shouldPerformKnnSearchInPreFilteredResults()
       throws Exception {
-    final String solrQuery = "{!text_embedder model=dummy-1 f=vector topK=4}hello world";
+    final String solrQuery = "{!text_to_vector model=dummy-1 f=vector topK=4}hello world";
     final SolrQuery query = new SolrQuery();
     query.setQuery(solrQuery);
     query.setFilterQueries("-id:4");
@@ -370,7 +371,7 @@ public void embeddedQueryWithNegativeFilterQuery_shouldPerformKnnSearchInPreFilt
   public void embeddedQueryAsRerank_shouldAddSimilarityFunctionScore() throws Exception {
     final SolrQuery query = new SolrQuery();
     query.set("rq", "{!rerank reRankQuery=$rqq reRankDocs=4 reRankWeight=1}");
-    query.set("rqq", "{!text_embedder model=dummy-1 f=vector topK=4}hello world");
+    query.set("rqq", "{!text_to_vector model=dummy-1 f=vector topK=4}hello world");
     query.setQuery("id:(3 4 9 2)");
     query.add("fl", "id");