Increase default chunks to 100 and add comments

datastaxdevs · Jun 23, 2024 · 5af665b · 5af665b
1 parent 624fcbb
commit 5af665b
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Showing 2 changed files with 21 additions and 2 deletions.
diff --git a/...-astradb/src/main/java/dev/langchain4j/store/embedding/astradb/AstraDBEmbeddingStore.java b/...-astradb/src/main/java/dev/langchain4j/store/embedding/astradb/AstraDBEmbeddingStore.java
@@ -84,7 +84,7 @@ public AstraDBEmbeddingStore(@NonNull Collection<Document> client) {
      *      concurrent threads
      */
     public AstraDBEmbeddingStore(@NonNull Collection<Document> client, int itemsPerChunk, int concurrentThreads) {
-        if (itemsPerChunk>20 || itemsPerChunk<1) {
+        if (itemsPerChunk>100 || itemsPerChunk<1) {
             throw new IllegalArgumentException("'itemsPerChunk' should be in between 1 and 20");
         }
         if (concurrentThreads<1) {

diff --git a/...db/src/main/java/dev/langchain4j/store/embedding/astradb/EmbeddingSearchRequestAstra.java b/...db/src/main/java/dev/langchain4j/store/embedding/astradb/EmbeddingSearchRequestAstra.java
@@ -4,11 +4,30 @@
 import dev.langchain4j.store.embedding.EmbeddingSearchRequest;
 import dev.langchain4j.store.embedding.filter.Filter;
 
-
+/**
+ * This abstract class represents a search request for embeddings in AstraDB
+ * A user can provide a field 'vectorize' that will be converted as a embedding on the spot and use for search or insertion
+ */
 public class EmbeddingSearchRequestAstra extends EmbeddingSearchRequest {
 
+    /**
+     * The field to vectorize
+     */
     private final String vectorize;
 
+    /**
+     * Constructor leveraging default search request but with the vectorize options.
+     * @param queryEmbedding
+     *      vector or left empty to use the vectorize field
+     * @param vectorize
+     *      field to vectorize
+     * @param maxResults
+     *      maximum number of results to return
+     * @param minScore
+     *     minimum score to return
+     * @param filter
+     *      filter to apply
+     */
     public EmbeddingSearchRequestAstra(Embedding queryEmbedding, String vectorize, Integer maxResults, Double minScore, Filter filter) {
         super(queryEmbedding != null ? queryEmbedding : Embedding.from(new float[0]), maxResults, minScore, filter);
         this.vectorize = vectorize;