From 10f70a11f9d5fbcc7bb754799be340d2366cdc64 Mon Sep 17 00:00:00 2001
From: Marvin Lindner <marvin.lindner@sap.com>
Date: Fri, 22 May 2026 20:14:18 +0200
Subject: [PATCH] fix: filter recommendations to unfilled fields only (#22)

The Fiori recommendation handler used to emit a SAP_Recommendations entry
for every column in the prediction response, regardless of whether the
user had already filled that column. This worked locally because the
mock client only returns predictions for cells marked [PREDICT], but it
broke in CI where the real RPT model returns predictions for every
target column. Filter the response to columns that were null in the
input row so behaviour is consistent across both clients.

Adds a regression unit test that simulates the RPT-style response shape.
---
 .../FioriRecommendationHandler.java           |  4 +-
 .../FioriRecommendationHandlerTest.java       | 50 +++++++++++++++++++
 2 files changed, 53 insertions(+), 1 deletion(-)

diff --git a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/FioriRecommendationHandler.java b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/FioriRecommendationHandler.java
index f6ae25c..46aef51 100644
--- a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/FioriRecommendationHandler.java
+++ b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/FioriRecommendationHandler.java
@@ -215,8 +215,10 @@ public void afterRead(CdsReadEventContext context, List<CdsData> dataList) {
       return;
     }
 
+    List<String> missingPredictionElementNames =
+        predictionElementNames.stream().filter(c -> row.get(c) == null).toList();
     Map<String, Object> recommendations =
-        buildRecommendations(db, predictions.get(0), predictionElementNames, context, rowType);
+        buildRecommendations(db, predictions.get(0), missingPredictionElementNames, context, rowType);
     row.put("SAP_Recommendations", recommendations);
   }
 
diff --git a/cds-feature-recommendations/src/test/java/com/sap/cds/feature/recommendation/FioriRecommendationHandlerTest.java b/cds-feature-recommendations/src/test/java/com/sap/cds/feature/recommendation/FioriRecommendationHandlerTest.java
index cdb4158..7e46d4b 100644
--- a/cds-feature-recommendations/src/test/java/com/sap/cds/feature/recommendation/FioriRecommendationHandlerTest.java
+++ b/cds-feature-recommendations/src/test/java/com/sap/cds/feature/recommendation/FioriRecommendationHandlerTest.java
@@ -271,6 +271,31 @@ void composedKeys_usesSyntheticKeyColumn() {
         });
   }
 
+  @Test
+  @SuppressWarnings({"unchecked", "rawtypes"})
+  void rptStyleClient_filledColumns_areExcludedFromRecommendations() {
+    runIn(
+        () -> {
+          Map<String, Object> row = new HashMap<>();
+          row.put("ID", "a009c640-434a-4542-ac68-51b400c880ec");
+          row.put("IsActiveEntity", false);
+          row.put("genre_ID", 12);
+          row.put("currency_code", null);
+          CdsReadEventContext ctx = readContext("test.Books", List.of(row));
+          when(db.run(any(CqnSelect.class)))
+              .thenReturn(
+                  twoContextRows(),
+                  ResultBuilder.selectedRows(List.of()).result(),
+                  ResultBuilder.selectedRows(List.of()).result());
+          predictionClient = rptStyleClient();
+          cut.afterRead(ctx, dataList(row));
+          assertThat(row).containsKey("SAP_Recommendations");
+          Map<String, Object> recs = (Map<String, Object>) row.get("SAP_Recommendations");
+          assertThat(recs).doesNotContainKey("genre_ID");
+          assertThat((List<?>) recs.get("currency_code")).hasSize(1);
+        });
+  }
+
   // ── helpers ────────────────────────────────────────────────────────────────
 
   private CdsReadEventContext readContext(String entityName, List<Map<String, Object>> resultRows) {
@@ -317,6 +342,31 @@ private static Result twoContextRows() {
         .result();
   }
 
+  private static RecommendationClient rptStyleClient() {
+    Random random = new Random(42);
+    return (rows, predictionColumns, indexColumn) -> {
+      List<CdsData> predictions = new ArrayList<>();
+      for (CdsData row : rows) {
+        if (predictionColumns.stream().noneMatch(col -> "[PREDICT]".equals(row.get(col)))) {
+          continue;
+        }
+        Map<String, Object> prediction = new HashMap<>();
+        for (String col : predictionColumns) {
+          List<Object> available =
+              rows.stream()
+                  .filter(r -> r.get(col) != null && !"[PREDICT]".equals(r.get(col)))
+                  .map(r -> r.get(col))
+                  .toList();
+          Object val = available.isEmpty() ? null : available.get(random.nextInt(available.size()));
+          prediction.put(col, List.of(Map.of("prediction", val)));
+        }
+        prediction.put(indexColumn, row.get(indexColumn));
+        predictions.add(CdsData.create(prediction));
+      }
+      return predictions;
+    };
+  }
+
   private static RecommendationClient randomPickClient() {
     Random random = new Random(42);
     return (rows, predictionColumns, indexColumn) -> {