DOC-7228 Update the Lettuce recommendation-engine and feature-store demos to 7.9.0

content/develop/use-cases/feature-store/java-lettuce/FeatureStore.java

@@ -39,7 +39,7 @@
  * <p>{@code HEXPIRE} and {@code HTTL} require Redis 7.4 or later.
  * Lettuce exposes them as {@code hexpire} / {@code httl} on
  * {@code RedisAsyncCommands} from 6.4 onwards; the demo pins
- * 7.5.2.RELEASE.</p>
+ * 7.9.0.RELEASE.</p>
  *
  * <h2>Lettuce vs. Jedis</h2>
  *

content/develop/use-cases/feature-store/java-lettuce/_index.md

@@ -273,7 +273,7 @@ for debugging and as a freshness signal in the model itself.
 
 > **HEXPIRE requires Redis 7.4 or later.** `HEXPIRE` and the field-level TTL
 > commands were added in Redis 7.4. Lettuce 6.4 was the first release with
-> the bindings; the demo's `pom.xml` pins 7.5.2.RELEASE.
+> the bindings; the demo's `pom.xml` pins 7.9.0.RELEASE.
 
 ### Inference reads with HMGET
 
@@ -448,7 +448,7 @@ Endpoints:
   demo relies on per-field TTL for the mixed-staleness story.
 * **Java 17 or later.** The demo uses switch expressions with arrow labels
   (`case "..." -> ...`), records, and text blocks.
-* **Lettuce 6.4 or later.** The demo's `pom.xml` pins 7.5.2.RELEASE.
+* **Lettuce 6.4 or later.** The demo's `pom.xml` pins 7.9.0.RELEASE.
   Field-level TTL bindings (`hexpire`, `httl`, `hpersist`) ship from
   Lettuce 6.4.
 

content/develop/use-cases/feature-store/java-lettuce/pom.xml

@@ -30,11 +30,11 @@
 
   <dependencies>
     <!-- Redis client. Lettuce 6.4+ ships per-field TTL bindings
-         (hexpire / httl / hpersist); the demo pins 7.5.2.RELEASE. -->
+         (hexpire / httl / hpersist); the demo pins 7.9.0.RELEASE. -->
     <dependency>
       <groupId>io.lettuce</groupId>
       <artifactId>lettuce-core</artifactId>
-      <version>7.5.2.RELEASE</version>
+      <version>7.9.0.RELEASE</version>
     </dependency>
   </dependencies>
 

content/develop/use-cases/recommendation-engine/java-lettuce/Recommender.java

@@ -19,6 +19,7 @@
 import io.lettuce.core.output.NestedMultiOutput;
 import io.lettuce.core.protocol.CommandArgs;
 import io.lettuce.core.protocol.ProtocolKeyword;
+import io.lettuce.core.search.FieldValue;
 import io.lettuce.core.search.SearchReply;
 import io.lettuce.core.search.arguments.CreateArgs;
 import io.lettuce.core.search.arguments.FieldArgs;
@@ -161,27 +162,27 @@ public String userKey(String userId) {
      * {@code FT.SEARCH} can pre-filter and then KNN-rank in one pass.</p>
      */
     public void createIndex() {
-        List<FieldArgs<String>> schema = Arrays.asList(
-                TextFieldArgs.<String>builder().name("name").weight(1L).build(),
+        List<FieldArgs> schema = Arrays.asList(
+                TextFieldArgs.builder().name("name").weight(1L).build(),
                 // Lettuce's TextField weight is a long: 1 == default weight,
                 // we accept the loss of the 0.5 fractional weight on
                 // description because Lettuce 7 does not expose a double
                 // weight builder.
-                TextFieldArgs.<String>builder().name("description").build(),
-                TagFieldArgs.<String>builder().name("category").build(),
-                TagFieldArgs.<String>builder().name("brand").build(),
-                TagFieldArgs.<String>builder().name("in_stock").build(),
-                NumericFieldArgs.<String>builder().name("price").sortable().build(),
-                NumericFieldArgs.<String>builder().name("rating").sortable().build(),
-                VectorFieldArgs.<String>builder()
+                TextFieldArgs.builder().name("description").build(),
+                TagFieldArgs.builder().name("category").build(),
+                TagFieldArgs.builder().name("brand").build(),
+                TagFieldArgs.builder().name("in_stock").build(),
+                NumericFieldArgs.builder().name("price").sortable().build(),
+                NumericFieldArgs.builder().name("rating").sortable().build(),
+                VectorFieldArgs.builder()
                         .name("embedding")
                         .hnsw()
                         .type(VectorFieldArgs.VectorType.FLOAT32)
                         .dimensions(vectorDim)
                         .distanceMetric(VectorFieldArgs.DistanceMetric.COSINE)
                         .build());
 
-        CreateArgs<String, String> createArgs = CreateArgs.<String, String>builder()
+        CreateArgs createArgs = CreateArgs.builder()
                 .on(CreateArgs.TargetType.HASH)
                 .withPrefix(keyPrefix)
                 .build();
@@ -205,15 +206,23 @@ public void dropIndex(boolean deleteDocuments) {
         try {
             connection.sync().ftDropindex(indexName, deleteDocuments);
         } catch (RedisCommandExecutionException exc) {
-            String msg = String.valueOf(exc.getMessage()).toLowerCase();
-            // Different Redis Search versions phrase the missing-index
-            // error differently; tolerate either.
-            if (!msg.contains("no such index") && !msg.contains("unknown index name")) {
+            if (!isMissingIndex(exc)) {
                 throw exc;
             }
         }
     }
 
+    /**
+     * Different Redis Search versions phrase the missing-index error
+     * differently ("Unknown index name", "no such index", and, from
+     * Redis 8.10, "SEARCH_INDEX_NOT_FOUND Index not found").
+     */
+    private static boolean isMissingIndex(RedisCommandExecutionException exc) {
+        String msg = String.valueOf(exc.getMessage()).toLowerCase();
+        return msg.contains("no such index") || msg.contains("unknown index name")
+                || msg.contains("index not found");
+    }
+
     // ------------------------------------------------------------------
     // Catalogue ingest
     // ------------------------------------------------------------------
@@ -325,7 +334,7 @@ public List<Candidate> candidateRetrieve(float[] queryVec, RetrieveOptions opts)
         // parameter goes through as raw bytes and the returned hash
         // field values come back as byte[] (we UTF-8-decode the text
         // fields ourselves below).
-        SearchArgs<String, byte[]> args = SearchArgs.<String, byte[]>builder()
+        SearchArgs<String> args = SearchArgs.<String>builder()
                 .param("vec", floatsToBytes(effective))
                 .returnField("name")
                 .returnField("description")
@@ -335,39 +344,37 @@ public List<Candidate> candidateRetrieve(float[] queryVec, RetrieveOptions opts)
                 .returnField("rating")
                 .returnField("in_stock")
                 .returnField("vector_score")
-                .sortBy(SortByArgs.<String>builder().attribute("vector_score").build())
+                .sortBy(SortByArgs.builder().attribute("vector_score").build())
                 .limit(0, k)
                 .dialect(QueryDialects.DIALECT2)
                 .build();
 
-        // ftSearch's V (value type) is byte[] on the binary connection,
-        // so the query expression has to be supplied as UTF-8 bytes too.
-        SearchReply<String, byte[]> reply = binConnection.sync()
-                .ftSearch(indexName, utf8(queryStr), args);
-        List<SearchReply.SearchResult<String, byte[]>> results =
+        SearchReply<String> reply = binConnection.sync()
+                .ftSearch(indexName, queryStr, args);
+        List<SearchReply.SearchResult<String>> results =
                 reply == null ? Collections.emptyList() : reply.getResults();
         List<Candidate> out = new ArrayList<>(results.size());
-        for (SearchReply.SearchResult<String, byte[]> doc : results) {
+        for (SearchReply.SearchResult<String> doc : results) {
             out.add(decodeCandidate(doc));
         }
         return out;
     }
 
-    private Candidate decodeCandidate(SearchReply.SearchResult<String, byte[]> doc) {
+    private Candidate decodeCandidate(SearchReply.SearchResult<String> doc) {
         String rawKey = doc.getId();
         String bareId = rawKey.startsWith(keyPrefix)
                 ? rawKey.substring(keyPrefix.length()) : rawKey;
-        Map<String, byte[]> fields = doc.getFields();
-        double dist = parseDouble(fromUtf8(fields.get("vector_score")), 0.0);
-        double price = parseDouble(fromUtf8(fields.get("price")), 0.0);
-        double rating = parseDouble(fromUtf8(fields.get("rating")), 0.0);
-        boolean inStock = "true".equals(fromUtf8(fields.get("in_stock")));
+        Map<String, FieldValue> fields = doc.getFields();
+        double dist = parseDouble(text(fields, "vector_score"), 0.0);
+        double price = parseDouble(text(fields, "price"), 0.0);
+        double rating = parseDouble(text(fields, "rating"), 0.0);
+        boolean inStock = "true".equals(text(fields, "in_stock"));
         Candidate c = new Candidate();
         c.id = bareId;
-        c.name = fromUtf8(fields.get("name"));
-        c.description = fromUtf8(fields.get("description"));
-        c.category = fromUtf8(fields.get("category"));
-        c.brand = fromUtf8(fields.get("brand"));
+        c.name = stringOrEmpty(text(fields, "name"));
+        c.description = stringOrEmpty(text(fields, "description"));
+        c.category = stringOrEmpty(text(fields, "category"));
+        c.brand = stringOrEmpty(text(fields, "brand"));
         c.price = price;
         c.rating = rating;
         c.inStock = inStock;
@@ -695,8 +702,7 @@ public IndexStats indexInfo() {
             Object vecMb = info.get("vector_index_sz_mb");
             stats.vectorIndexSizeMb = vecMb == null ? 0.0 : parseDouble(vecMb.toString(), 0.0);
         } catch (RedisCommandExecutionException exc) {
-            String msg = String.valueOf(exc.getMessage()).toLowerCase();
-            if (!msg.contains("no such index") && !msg.contains("unknown index name")) {
+            if (!isMissingIndex(exc)) {
                 throw exc;
             }
         }
@@ -709,32 +715,32 @@ public IndexStats indexInfo() {
      */
     public List<ProductSummary> listProducts(int limit) {
         if (limit <= 0) limit = 100;
-        SearchArgs<String, String> args = SearchArgs.<String, String>builder()
+        SearchArgs<String> args = SearchArgs.<String>builder()
                 .returnField("name")
                 .returnField("category")
                 .returnField("brand")
                 .returnField("price")
                 .returnField("rating")
                 .returnField("in_stock")
-                .sortBy(SortByArgs.<String>builder().attribute("price").build())
+                .sortBy(SortByArgs.builder().attribute("price").build())
                 .limit(0, limit)
                 .dialect(QueryDialects.DIALECT2)
                 .build();
-        SearchReply<String, String> reply = connection.sync().ftSearch(indexName, "*", args);
-        List<SearchReply.SearchResult<String, String>> results =
+        SearchReply<String> reply = connection.sync().ftSearch(indexName, "*", args);
+        List<SearchReply.SearchResult<String>> results =
                 reply == null ? Collections.emptyList() : reply.getResults();
         List<ProductSummary> out = new ArrayList<>(results.size());
-        for (SearchReply.SearchResult<String, String> doc : results) {
+        for (SearchReply.SearchResult<String> doc : results) {
             ProductSummary p = new ProductSummary();
             String rawKey = doc.getId();
             p.id = rawKey.startsWith(keyPrefix) ? rawKey.substring(keyPrefix.length()) : rawKey;
-            Map<String, String> fields = doc.getFields();
-            p.name = stringOrEmpty(fields.get("name"));
-            p.category = stringOrEmpty(fields.get("category"));
-            p.brand = stringOrEmpty(fields.get("brand"));
-            p.price = parseDouble(fields.get("price"), 0.0);
-            p.rating = parseDouble(fields.get("rating"), 0.0);
-            p.inStock = "true".equals(fields.get("in_stock"));
+            Map<String, FieldValue> fields = doc.getFields();
+            p.name = stringOrEmpty(text(fields, "name"));
+            p.category = stringOrEmpty(text(fields, "category"));
+            p.brand = stringOrEmpty(text(fields, "brand"));
+            p.price = parseDouble(text(fields, "price"), 0.0);
+            p.rating = parseDouble(text(fields, "rating"), 0.0);
+            p.inStock = "true".equals(text(fields, "in_stock"));
             out.add(p);
         }
         return out;
@@ -851,6 +857,12 @@ private static String stringOrEmpty(Object value) {
         return value == null ? "" : value.toString();
     }
 
+    /** The field's value as a string, or null if the document doesn't have it. */
+    private static String text(Map<String, FieldValue> fields, String key) {
+        FieldValue value = fields.get(key);
+        return value == null ? null : value.asString();
+    }
+
     private static byte[] utf8(String value) {
         return value == null ? new byte[0] : value.getBytes(StandardCharsets.UTF_8);
     }

content/develop/use-cases/recommendation-engine/java-lettuce/_index.md

@@ -178,23 +178,22 @@ FT.SEARCH recommend:idx
 
 When there's no filter, the pre-filter clause is just `(*)`. `vector_score` is the cosine *distance* (0 means identical, 2 means opposite), so the result is sorted ascending and the top row is the closest candidate to the query.
 
-The Lettuce equivalent uses the typed `ftSearch` method on the binary-codec connection's `RediSearchCommands`. The query expression is passed as the value type (`byte[]` on the binary connection, so UTF-8-encoded) and the binary `$vec` parameter goes through `SearchArgs.Builder.param(...)`:
+The Lettuce equivalent uses the typed `ftSearch` method on the binary-codec connection's `RediSearchCommands`. The query expression is an ordinary `String`, and the binary `$vec` parameter goes through `SearchArgs.Builder.param(...)`:
 
 ```java
 String knn = filterClause + "=>[KNN " + k + " @embedding $vec AS vector_score]";
-SearchArgs<String, byte[]> args = SearchArgs.<String, byte[]>builder()
+SearchArgs<String> args = SearchArgs.<String>builder()
         .param("vec", Recommender.floatsToBytes(queryVec))
         .returnField("name").returnField("description")
         .returnField("category").returnField("brand")
         .returnField("price").returnField("rating")
         .returnField("in_stock").returnField("vector_score")
-        .sortBy(SortByArgs.<String>builder().attribute("vector_score").build())
+        .sortBy(SortByArgs.builder().attribute("vector_score").build())
         .limit(0, k)
         .dialect(QueryDialects.DIALECT2)
         .build();
-SearchReply<String, byte[]> reply = binConn.sync()
-        .ftSearch("recommend:idx",
-                knn.getBytes(StandardCharsets.UTF_8), args);
+SearchReply<String> reply = binConn.sync()
+        .ftSearch("recommend:idx", knn, args);
 ```
 
 ## Lettuce specifics: binary fields and pipelining

content/develop/use-cases/recommendation-engine/java-lettuce/pom.xml

@@ -33,7 +33,7 @@
     <dependency>
       <groupId>io.lettuce</groupId>
       <artifactId>lettuce-core</artifactId>
-      <version>7.5.2.RELEASE</version>
+      <version>7.9.0.RELEASE</version>
     </dependency>
 
     <!-- DJL: pure-Java inference orchestration -->