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 36e9634..1498d0f 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 @@ -6,7 +6,6 @@ import com.github.benmanes.caffeine.cache.Cache; import com.github.benmanes.caffeine.cache.Caffeine; import com.sap.cds.CdsData; -import com.sap.cds.feature.aicore.api.AICoreService; import com.sap.cds.feature.recommendation.api.RecommendationClient; import com.sap.cds.feature.recommendation.api.RecommendationClientResolver; import com.sap.cds.reflect.CdsStructuredType; @@ -29,9 +28,10 @@ class FioriRecommendationHandler implements EventHandler { private static final Logger logger = LoggerFactory.getLogger(FioriRecommendationHandler.class); private static final int DEFAULT_CONTEXT_ROW_LIMIT = 2000; + private static final String SAP_RECOMMENDATIONS = "SAP_Recommendations"; - private final AICoreService aiCoreService; - private final RecommendationClientResolver clientResolver; + private final RecommendationClientResolver> clientResolver; + private final PersistenceService db; private final RecommendationResultParser resultParser = new RecommendationResultParser(); // Avoids re-evaluating the CDS model on every read to check whether an entity has prediction // columns. Keys are ":" because if an entity needs a prediction can be @@ -40,9 +40,9 @@ class FioriRecommendationHandler implements EventHandler { Caffeine.newBuilder().maximumSize(10_000).build(); FioriRecommendationHandler( - AICoreService aiCoreService, RecommendationClientResolver clientResolver) { - this.aiCoreService = aiCoreService; + RecommendationClientResolver> clientResolver, PersistenceService db) { this.clientResolver = clientResolver; + this.db = db; } void invalidateTenant(String tenantId) { @@ -77,10 +77,13 @@ public void afterRead(CdsReadEventContext context, List dataList) { return; } - if (!Boolean.FALSE.equals(row.get(Drafts.IS_ACTIVE_ENTITY))) { + if (row.containsKey(Drafts.IS_ACTIVE_ENTITY) + && !Boolean.FALSE.equals(row.get(Drafts.IS_ACTIVE_ENTITY))) { return; } + // rowType reflects the projected shape (columns actually selected); target is the full entity. + // Fall back to target when rowType is absent, e.g. when the result carries no type metadata. CdsStructuredType rowType = context.getResult().rowType(); if (rowType == null) { rowType = target; @@ -100,18 +103,13 @@ public void afterRead(CdsReadEventContext context, List dataList) { return; } - if (builder.contextColumns().isEmpty()) { - logger.debug("No suitable context columns found, skipping predictions."); + if (builder.keyNames().isEmpty()) { + logger.debug("Entity has no key elements, skipping predictions."); return; } - PersistenceService db = - context - .getServiceCatalog() - .getService(PersistenceService.class, PersistenceService.DEFAULT_NAME); - List contextRows = new ArrayList<>(db.run(builder.buildContextQuery()).list()); - if (contextRows.size() < 2) { - logger.debug("Not enough context rows (minimum 2), skipping predictions."); + if (builder.contextColumns().isEmpty()) { + logger.trace("No suitable context columns found, skipping predictions."); return; } @@ -121,11 +119,19 @@ public void afterRead(CdsReadEventContext context, List dataList) { return; } - List allRows = builder.assembleRows(contextRows, predictRow, row); + // Result.list() returns List; the ArrayList copy also converts it to List. + List contextRows = new ArrayList<>(db.run(builder.buildContextQuery()).list()); + if (contextRows.size() < 2) { + logger.debug("Not enough context rows (minimum 2), skipping predictions."); + return; + } + + List missingPredictionElementNames = + builder.predictionElementNames().stream().filter(c -> row.get(c) == null).toList(); - RecommendationClient client = clientResolver.resolve(aiCoreService); + RecommendationClient client = clientResolver.resolve(builder.keyNames()); List predictions = - client.predict(allRows, builder.predictionElementNames(), builder.indexColumn()); + client.predict(predictRow, contextRows, missingPredictionElementNames); if (predictions.isEmpty()) { logger.warn("No predictions returned from AI client."); @@ -136,11 +142,9 @@ public void afterRead(CdsReadEventContext context, List dataList) { return; } - List missingPredictionElementNames = - builder.predictionElementNames().stream().filter(c -> row.get(c) == null).toList(); Map recommendations = resultParser.buildRecommendations( db, predictions.get(0), missingPredictionElementNames, context, rowType); - row.put("SAP_Recommendations", recommendations); + row.put(SAP_RECOMMENDATIONS, recommendations); } } diff --git a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/MockRecommendationClient.java b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/MockRecommendationClient.java index 27498bb..c2c9157 100644 --- a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/MockRecommendationClient.java +++ b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/MockRecommendationClient.java @@ -5,45 +5,48 @@ import com.sap.cds.CdsData; import com.sap.cds.feature.recommendation.api.RecommendationClient; -import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Map; import java.util.Random; +// Mock implementation used when no AI Core binding is present. For each prediction column that +// is null in the predict row, it picks a random non-null value from the same column across the +// context rows and returns it as the prediction. Columns already filled are left unchanged. class MockRecommendationClient implements RecommendationClient { + // We use random here so you can see a difference in the UI. The actual value returned here is not + // relevant for tests. private final Random random = new Random(); + private final List keyNames; + + MockRecommendationClient(List keyNames) { + this.keyNames = keyNames; + } @Override public List predict( - List rows, List predictionColumns, String indexColumn) { - List predictions = new ArrayList<>(); - for (CdsData row : rows) { - Map prediction = new HashMap<>(); - boolean addPrediction = false; - for (String col : predictionColumns) { - if ("[PREDICT]".equals(row.get(col))) { - addPrediction = true; - List availableValues = - rows.stream() - .filter(r -> r.get(col) != null && !"[PREDICT]".equals(r.get(col))) - .map(r -> r.get(col)) - .toList(); - Object contextValue = - availableValues.isEmpty() - ? null - : availableValues.get(random.nextInt(availableValues.size())); - Map predictionEntry = new HashMap<>(); - predictionEntry.put("prediction", contextValue); - prediction.put(col, List.of(predictionEntry)); - } - } - if (addPrediction) { - prediction.put(indexColumn, row.get(indexColumn)); - predictions.add(CdsData.create(prediction)); + CdsData predictionRow, List contextRows, List predictionColumns) { + String indexColumn = RptIndexColumns.resolveIndexColumn(keyNames, predictionRow); + Map prediction = new HashMap<>(); + for (String col : predictionColumns) { + if (predictionRow.get(col) == null) { + List availableValues = + contextRows.stream().filter(r -> r.get(col) != null).map(r -> r.get(col)).toList(); + Object contextValue = + availableValues.isEmpty() + ? null + : availableValues.get(random.nextInt(availableValues.size())); + Map predictionEntry = new HashMap<>(); + // Replace the empty entry in col with a randomly picked value of entries in the + // contextRows. + predictionEntry.put("prediction", contextValue); + prediction.put(col, List.of(predictionEntry)); } } - return predictions; + if (!keyNames.isEmpty()) { + prediction.put(indexColumn, predictionRow.get(keyNames.get(0))); + } + return List.of(CdsData.create(prediction)); } } diff --git a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/RecommendationConfiguration.java b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/RecommendationConfiguration.java index afde35c..529c7cf 100644 --- a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/RecommendationConfiguration.java +++ b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/RecommendationConfiguration.java @@ -9,10 +9,12 @@ import com.sap.cds.feature.recommendation.api.RptInferenceClient; import com.sap.cds.feature.recommendation.api.RptModelSpec; import com.sap.cds.services.ServiceCatalog; +import com.sap.cds.services.persistence.PersistenceService; import com.sap.cds.services.runtime.CdsRuntime; import com.sap.cds.services.runtime.CdsRuntimeConfiguration; import com.sap.cds.services.runtime.CdsRuntimeConfigurer; import com.sap.cds.services.utils.environment.ServiceBindingUtils; +import java.util.List; import org.slf4j.Logger; import org.slf4j.LoggerFactory; @@ -33,13 +35,25 @@ public void eventHandlers(CdsRuntimeConfigurer configurer) { return; } + PersistenceService db = + serviceCatalog.getService(PersistenceService.class, PersistenceService.DEFAULT_NAME); + + if (db == null) { + logger.info( + "No PersistenceService found, skipping Fiori recommendation handler registration."); + return; + } + boolean hasBind = hasAICoreBinding(runtime); - RecommendationClientResolver resolver = + // The real resolver is a lambda resolved at prediction time. That's necessary because + // resource group and deployment ID are tenant-specific and are only available at + // prediction time from the request context. AICoreService is captured in the closure. + RecommendationClientResolver> clientResolver = hasBind - ? RecommendationConfiguration::resolveRptClient - : service -> new MockRecommendationClient(); + ? keyNames -> resolveRptClient(aiCoreService, keyNames) + : keyNames -> new MockRecommendationClient(keyNames); - FioriRecommendationHandler handler = new FioriRecommendationHandler(aiCoreService, resolver); + FioriRecommendationHandler handler = new FioriRecommendationHandler(clientResolver, db); configurer.eventHandler(handler); configurer.eventHandler(new RecommendationModelChangedHandler(handler)); } @@ -53,9 +67,10 @@ private static boolean hasAICoreBinding(CdsRuntime runtime) { .isPresent(); } - private static RecommendationClient resolveRptClient(AICoreService service) { + private static RecommendationClient resolveRptClient( + AICoreService service, List keyNames) { String resourceGroup = service.resourceGroup(); String deploymentId = service.deploymentId(resourceGroup, RptModelSpec.rpt1()); - return new RptInferenceClient(service.inferenceClient(resourceGroup, deploymentId)); + return new RptInferenceClient(service.inferenceClient(resourceGroup, deploymentId), keyNames); } } diff --git a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/RecommendationContextBuilder.java b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/RecommendationContextBuilder.java index a158123..049d6e5 100644 --- a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/RecommendationContextBuilder.java +++ b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/RecommendationContextBuilder.java @@ -14,23 +14,26 @@ import com.sap.cds.reflect.CdsSimpleType; import com.sap.cds.reflect.CdsStructuredType; import com.sap.cds.services.draft.Drafts; -import java.util.ArrayList; import java.util.EnumSet; import java.util.HashMap; +import java.util.HashSet; import java.util.List; import java.util.Map; import java.util.Set; /** * Builds the context data needed for prediction: determines which elements to predict, which - * columns provide context, builds the context query, and prepares rows for the AI model. + * columns provide context and builds the context query. This class is cds-model aware, but does not + * know about which client will be used for the predictions. */ class RecommendationContextBuilder { private static final String VALUE_LIST_ANNOTATION = "@Common.ValueList"; private static final String VALUE_LIST_WITH_FIXED_VALUES_ANNOTATION = "@Common.ValueListWithFixedValues"; - private static final String SYNTHETIC_KEY_COLUMN = "SAP_RECOMMENDATIONS_ID"; + private static final String ODATA_VALUE_LIST_ANNOTATION = "@cds.odata.valuelist"; + private static final String COMPUTED_ANNOTATION = "@Core.Computed"; + private static final String READONLY_ANNOTATION = "@readonly"; private static final Set SUPPORTED_CONTEXT_TYPES = EnumSet.of( CdsBaseType.STRING, @@ -64,8 +67,6 @@ class RecommendationContextBuilder { private final List predictionElementNames; private final List contextColumns; private final List keyNames; - private final boolean syntheticKeyNeeded; - private final String indexColumn; RecommendationContextBuilder(CdsStructuredType target, CdsStructuredType rowType, int limit) { this.target = target; @@ -74,10 +75,6 @@ class RecommendationContextBuilder { this.predictionElementNames = computePredictionElements(); this.contextColumns = computeContextColumns(); this.keyNames = target.keyElements().map(CdsElement::getName).toList(); - this.syntheticKeyNeeded = - keyNames.size() > 1 || (keyNames.size() == 1 && !"ID".equals(keyNames.get(0))); - this.indexColumn = - syntheticKeyNeeded ? SYNTHETIC_KEY_COLUMN : keyNames.stream().findFirst().orElse("ID"); } List predictionElementNames() { @@ -88,30 +85,27 @@ List contextColumns() { return contextColumns; } - String indexColumn() { - return indexColumn; - } - - boolean syntheticKeyNeeded() { - return syntheticKeyNeeded; + List keyNames() { + return keyNames; } CqnSelect buildContextQuery() { - List selectColumns = new ArrayList<>(contextColumns); - for (String key : keyNames) { - if (!selectColumns.contains(key)) { - selectColumns.add(key); - } - } + Set selectColumns = new HashSet<>(contextColumns); + selectColumns.addAll(keyNames); + var select = Select.from(target.getQualifiedName()) .columns(selectColumns.toArray(String[]::new)) .where( predictionElementNames.stream() + // the row for which we want to do predictions is automatically + // excluded by this isNotNull check .map(col -> CQL.get(col).isNotNull()) .collect(CQL.withAnd())) .limit(contextRowLimit); target + // ensure there is some stable ordering of the contextRows, if possible order by + // "most recently changed" so the model gets the most up-to-date data .concreteNonAssociationElements() .filter(byAnnotation("cds.on.update")) .map(CdsElement::getName) @@ -121,49 +115,22 @@ CqnSelect buildContextQuery() { return select; } + // Builds the predict row from only the allowed columns (same set used in buildContextQuery), + // so draft, computed, and readonly fields are excluded by construction rather than explicit + // removal. CdsData buildPredictRow(CdsData row) { if (predictionElementNames.stream().noneMatch(c -> row.get(c) == null)) { return null; } - Map predictRow = new HashMap<>(row); - Drafts.ELEMENTS.forEach(predictRow::remove); - for (String col : predictionElementNames) { - predictRow.putIfAbsent(col, "[PREDICT]"); - } + Set allowed = new HashSet<>(contextColumns); + allowed.addAll(keyNames); + Map predictRow = + allowed.stream() + .filter(row::containsKey) + .collect(HashMap::new, (m, col) -> m.put(col, row.get(col)), HashMap::putAll); return CdsData.create(predictRow); } - private String computeSyntheticKey(Map row) { - StringBuilder sb = new StringBuilder(); - for (int i = 0; i < keyNames.size(); i++) { - if (i > 0) { - sb.append('\0'); - } - sb.append(keyNames.get(i)); - sb.append('\0'); - Object value = row.get(keyNames.get(i)); - if (value != null) { - sb.append(value); - } - } - return sb.toString(); - } - - List assembleRows(List contextRows, CdsData predictRow, CdsData currentRow) { - List allRows = new ArrayList<>(); - if (syntheticKeyNeeded) { - for (CdsData contextRow : contextRows) { - contextRow.put(SYNTHETIC_KEY_COLUMN, computeSyntheticKey(contextRow)); - allRows.add(contextRow); - } - predictRow.put(SYNTHETIC_KEY_COLUMN, computeSyntheticKey(currentRow)); - } else { - allRows.addAll(contextRows); - } - allRows.add(predictRow); - return allRows; - } - private List computePredictionElements() { return rowType .elements() @@ -171,6 +138,7 @@ private List computePredictionElements() { byAnnotation(VALUE_LIST_ANNOTATION) .or(byAnnotation(VALUE_LIST_WITH_FIXED_VALUES_ANNOTATION))) .filter(e -> !e.getType().isAssociation()) + .filter(e -> !Boolean.FALSE.equals(e.getAnnotationValue(ODATA_VALUE_LIST_ANNOTATION, null))) .map(CdsElement::getName) .toList(); } @@ -178,10 +146,13 @@ private List computePredictionElements() { private List computeContextColumns() { return rowType .concreteNonAssociationElements() - .filter(e -> e.getType().isSimple()) .filter( - e -> SUPPORTED_CONTEXT_TYPES.contains(e.getType().as(CdsSimpleType.class).getType())) + e -> + e.getType() instanceof CdsSimpleType st + && SUPPORTED_CONTEXT_TYPES.contains(st.getType())) .filter(e -> !Drafts.ELEMENTS.contains(e.getName())) + .filter(byAnnotation(COMPUTED_ANNOTATION).negate()) + .filter(byAnnotation(READONLY_ANNOTATION).negate()) .map(CdsElement::getName) .toList(); } diff --git a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/RptIndexColumns.java b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/RptIndexColumns.java new file mode 100644 index 0000000..26bc7a4 --- /dev/null +++ b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/RptIndexColumns.java @@ -0,0 +1,25 @@ +/* + * © 2026 SAP SE or an SAP affiliate company and cds-ai contributors. + */ +package com.sap.cds.feature.recommendation; + +import com.sap.cds.CdsData; +import java.util.List; + +public class RptIndexColumns { + + // RPT-1 requires a single string index column to identify rows in the request/response. + // When the entity has a composite or non-string key, a synthetic string column is used instead. + public static final String SYNTHETIC_INDEX_COLUMN = "SAP_RECOMMENDATIONS_ID"; + + // Returns the column name to use as the RPT-1 index column. Uses the single key directly if + // it holds a String value; falls back to the synthetic column for composite or non-string keys. + public static String resolveIndexColumn(List keyNames, CdsData sampleRow) { + if (keyNames.size() == 1 && sampleRow.get(keyNames.get(0)) instanceof String) { + return keyNames.get(0); + } + return SYNTHETIC_INDEX_COLUMN; + } + + private RptIndexColumns() {} +} diff --git a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/api/RecommendationClient.java b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/api/RecommendationClient.java index 8694745..4558ec8 100644 --- a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/api/RecommendationClient.java +++ b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/api/RecommendationClient.java @@ -8,5 +8,25 @@ public interface RecommendationClient { - List predict(List rows, List predictionColumns, String indexColumn); + /** + * Predicts values for the missing columns of a single entity row. + * + *

Currently limited to a single prediction row. Multiple prediction rows may be supported in + * the future via a separate overload, but are ruled out at two points for now: + * + *

    + *
  1. {@code FioriRecommendationHandler} bails out when the read returns more than one entity, + * so predictions only fire on single-entity reads. + *
  2. {@code FioriRecommendationHandler} also rejects responses with more than one prediction + * back from the model, treating it as an unexpected state. + *
+ * + * @param predictionRow the single entity row to predict values for; prediction columns contain + * null for missing values that the model should fill + * @param contextRows historical rows from the same entity used as training context + * @param predictionColumns names of the columns the model should predict + * @return the predicted values as a list of result rows + */ + List predict( + CdsData predictionRow, List contextRows, List predictionColumns); } diff --git a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/api/RecommendationClientResolver.java b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/api/RecommendationClientResolver.java index ecc6837..82b2eca 100644 --- a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/api/RecommendationClientResolver.java +++ b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/api/RecommendationClientResolver.java @@ -3,10 +3,12 @@ */ package com.sap.cds.feature.recommendation.api; -import com.sap.cds.feature.aicore.api.AICoreService; - +// A single-method interface so callers can supply a custom client via lambda. +// @FunctionalInterface enforces this and causes a compile error if a second method is ever added. +// The type parameter T allows the resolver to receive any context the client might need (e.g. key +// names). @FunctionalInterface -public interface RecommendationClientResolver { +public interface RecommendationClientResolver { - RecommendationClient resolve(AICoreService aiCoreService); + RecommendationClient resolve(T context); } diff --git a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/api/RptInferenceClient.java b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/api/RptInferenceClient.java index c6e4c3a..c8058e6 100644 --- a/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/api/RptInferenceClient.java +++ b/cds-feature-recommendations/src/main/java/com/sap/cds/feature/recommendation/api/RptInferenceClient.java @@ -12,16 +12,16 @@ import com.sap.ai.sdk.foundationmodels.rpt.generated.model.RowsInnerValue; import com.sap.ai.sdk.foundationmodels.rpt.generated.model.TargetColumnConfig; import com.sap.cds.CdsData; -import com.sap.cds.services.draft.Drafts; +import com.sap.cds.feature.recommendation.RptIndexColumns; import com.sap.cloud.sdk.services.openapi.apache.apiclient.ApiClient; import com.sap.cloud.sdk.services.openapi.apache.core.OpenApiRequestException; import io.github.resilience4j.core.IntervalFunction; import io.github.resilience4j.retry.Retry; import io.github.resilience4j.retry.RetryConfig; +import java.util.ArrayList; import java.util.HashMap; import java.util.List; import java.util.Map; -import java.util.Set; import org.slf4j.Logger; import org.slf4j.LoggerFactory; @@ -36,38 +36,45 @@ * AICoreService service = ...; * String rg = service.resourceGroup(); * String deploymentId = service.deploymentId(rg, RptModelSpec.rpt1()); - * RptInferenceClient client = new RptInferenceClient(service.inferenceClient(rg, deploymentId)); - * List predictions = client.predict(rows, List.of("targetColumn"), "ID"); + * RptInferenceClient client = new RptInferenceClient(service.inferenceClient(rg, deploymentId), keyNames); + * List predictions = client.predict(predictionRow, contextRows, List.of("targetColumn")); * } */ public class RptInferenceClient implements RecommendationClient { private static final Logger logger = LoggerFactory.getLogger(RptInferenceClient.class); - private static final Set MANAGED_FIELDS = - Set.of("createdBy", "modifiedBy", "createdAt", "modifiedAt"); + // RPT-1 specific: the placeholder value that marks a column as a prediction target in the request + public static final String PREDICT = "[PREDICT]"; private static final Retry INFERENCE_RETRY = buildInferenceRetry(); - private final DefaultApi api; + private final DefaultApi rpt; + private final List keyNames; - public RptInferenceClient(ApiClient apiClient) { - this.api = + public RptInferenceClient(ApiClient apiClient, List keyNames) { + this.rpt = new DefaultApi(apiClient.withObjectMapper(JacksonConfiguration.getDefaultObjectMapper())); + this.keyNames = keyNames; } @Override public List predict( - List rows, List predictionColumns, String indexColumn) { - PredictRequestPayload request = buildRequest(rows, predictionColumns, indexColumn); + CdsData predictionRow, List contextRows, List predictionColumns) { + String indexColumn = RptIndexColumns.resolveIndexColumn(keyNames, predictionRow); + CdsData preparedPredictRow = preparePredictRow(predictionRow, predictionColumns); + List allRows = new ArrayList<>(contextRows); + allRows.add(preparedPredictRow); + + PredictRequestPayload request = buildRequest(allRows, predictionColumns, indexColumn, keyNames); logger.debug( - "Sending prediction request for {} rows, {} target columns", - rows.size(), + "Sending prediction request for one row with {} context rows, {} target columns", + contextRows.size(), predictionColumns.size()); return Retry.decorateSupplier( INFERENCE_RETRY, () -> { - var response = api.predict(request); + var response = rpt.predict(request); logger.debug("Prediction response id: {}", response.getId()); List> raw = JacksonConfiguration.getDefaultObjectMapper() @@ -77,35 +84,58 @@ public List predict( .get(); } + // '\0' is used as separator because it cannot appear in database string values + // (VARCHAR/NVARCHAR), so concatenation of any composite key values is guaranteed collision-free. + static String computeSyntheticKey(Map row, List keyNames) { + StringBuilder sb = new StringBuilder(); + for (int i = 0; i < keyNames.size(); i++) { + if (i > 0) sb.append('\0'); + sb.append(keyNames.get(i)).append('\0'); + Object value = row.get(keyNames.get(i)); + if (value != null) sb.append(value); + } + return sb.toString(); + } + + // Returns a copy of the predictRow with a prediction placeholder replacing empty values + // in the predictionColumns - these will get filled by the predict method. + private static CdsData preparePredictRow(CdsData predictRow, List predictionColumns) { + Map preparedPredictRowMap = new HashMap<>(predictRow); + for (String col : predictionColumns) { + preparedPredictRowMap.putIfAbsent(col, PREDICT); + } + return CdsData.create(preparedPredictRowMap); + } + private static PredictRequestPayload buildRequest( - List rows, List predictionColumns, String indexColumn) { + List rows, + List predictionColumns, + String indexColumn, + List keyNames) { var targetColumns = predictionColumns.stream() .map( col -> TargetColumnConfig.create() .name(col) - .predictionPlaceholder(PredictionPlaceholder.create("[PREDICT]")) + .predictionPlaceholder(PredictionPlaceholder.create(PREDICT)) .taskType(TargetColumnConfig.TaskTypeEnum.CLASSIFICATION)) .toList(); + // RPT-1 requires exactly one string-typed index column per row to identify predictions. + // When the entity key is composite or non-string, then the index column is + // RptIndexColumns.SYNTHETIC_INDEX_COLUMN and we need to compute the sytheticKey for all rows + // before sending them to RPT-1. + boolean syntheticKeyNeeded = RptIndexColumns.SYNTHETIC_INDEX_COLUMN.equals(indexColumn); var sdkRows = rows.stream() .map( row -> { - Map sdkRow = new HashMap<>(); - row.forEach( - (k, v) -> { - if (v != null - && !Drafts.ELEMENTS.contains(k) - && !MANAGED_FIELDS.contains(k)) { - sdkRow.put(k, RowsInnerValue.create(v.toString())); - } - }); - for (String target : predictionColumns) { - if (!row.containsKey(target) || row.get(target) == null) { - sdkRow.put(target, RowsInnerValue.create("[PREDICT]")); - } + Map sdkRow = toSdkRow(row); + if (syntheticKeyNeeded) { + sdkRow.put( + RptIndexColumns.SYNTHETIC_INDEX_COLUMN, + RowsInnerValue.create(computeSyntheticKey(row, keyNames))); } return sdkRow; }) @@ -117,6 +147,18 @@ private static PredictRequestPayload buildRequest( .indexColumn(indexColumn); } + // Converts a CdsData row to the RPT SDK row format, i.e., into Map + private static Map toSdkRow(CdsData row) { + Map sdkRow = new HashMap<>(); + row.forEach( + (k, v) -> { + if (v != null) { + sdkRow.put(k, RowsInnerValue.create(v.toString())); + } + }); + return sdkRow; + } + private static Retry buildInferenceRetry() { RetryConfig config = RetryConfig.custom() 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 c7f1a22..c21c823 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 @@ -13,7 +13,6 @@ import com.sap.cds.CdsData; import com.sap.cds.Result; import com.sap.cds.ResultBuilder; -import com.sap.cds.feature.aicore.api.AICoreService; import com.sap.cds.feature.recommendation.api.RecommendationClient; import com.sap.cds.ql.cqn.CqnSelect; import com.sap.cds.services.Service; @@ -33,9 +32,7 @@ import org.junit.jupiter.api.BeforeEach; import org.junit.jupiter.api.Test; import org.junit.jupiter.api.extension.ExtendWith; -import org.mockito.Answers; import org.mockito.ArgumentCaptor; -import org.mockito.Mock; import org.mockito.junit.jupiter.MockitoExtension; @ExtendWith(MockitoExtension.class) @@ -44,9 +41,6 @@ class FioriRecommendationHandlerTest { private static CdsRuntime runtime; private static PersistenceService db; - @Mock(answer = Answers.CALLS_REAL_METHODS) - private AICoreService aiCoreService; - private FioriRecommendationHandler cut; private RecommendationClient predictionClient; @@ -67,7 +61,7 @@ void setup() { reset(db); when(db.getName()).thenReturn(PersistenceService.DEFAULT_NAME); predictionClient = randomPickClient(); - cut = new FioriRecommendationHandler(aiCoreService, (service) -> predictionClient); + cut = new FioriRecommendationHandler(keyNames -> predictionClient, db); } // ── tests ────────────────────────────────────────────────────────────────── @@ -152,7 +146,7 @@ void emptyPredictions_returnsEarlyWithoutRecommendations() { Map row = draftRow("genre_ID", null); CdsReadEventContext ctx = readContext("test.Books", List.of(row)); when(db.run(any(CqnSelect.class))).thenReturn(twoContextRows()); - predictionClient = (rows, cols, idx) -> List.of(); + predictionClient = (predictionRow, contextRows, cols) -> List.of(); cut.afterRead(ctx, dataList(row)); assertThat(row).doesNotContainKey("SAP_Recommendations"); }); @@ -166,7 +160,7 @@ void multiplePredictions_returnsEarlyWithoutRecommendations() { CdsReadEventContext ctx = readContext("test.Books", List.of(row)); when(db.run(any(CqnSelect.class))).thenReturn(twoContextRows()); predictionClient = - (rows, cols, idx) -> + (predictionRow, contextRows, cols) -> List.of( CdsData.create(Map.of("ID", "id-1")), CdsData.create(Map.of("ID", "id-2"))); cut.afterRead(ctx, dataList(row)); @@ -203,6 +197,55 @@ void draftRow_withGenreAndCurrency_addsSapRecommendations() { }); } + @Test + void contextQuery_excludesPredictionRowByRequiringNonNullPredictionColumns() { + runIn( + () -> { + Map row = draftRow("genre_ID", null); + CdsReadEventContext ctx = readContext("test.Books", List.of(row)); + ArgumentCaptor selectCaptor = ArgumentCaptor.forClass(CqnSelect.class); + when(db.run(selectCaptor.capture())).thenReturn(twoContextRows()); + cut.afterRead(ctx, dataList(row)); + // The WHERE clause requires all prediction columns to be non-null, so the current row + // (which has genre_ID = null) is automatically excluded from the context. + String selectSql = selectCaptor.getAllValues().get(0).toString(); + assertThat(selectSql).contains("\"is not\",\"null\""); + assertThat(selectSql).contains("genre_ID"); + }); + } + + @Test + void cdsoDataValueListFalse_fieldIsExcludedFromPredictions() { + runIn( + () -> { + Map row = new HashMap<>(); + row.put("ID", "a009c640-434a-4542-ac68-51b400c880ec"); + row.put("IsActiveEntity", false); + row.put("genre_ID", null); + row.put("suppressed_ID", null); + CdsReadEventContext ctx = readContext("test.BooksWithDisabledValueList", List.of(row)); + when(db.run(any(CqnSelect.class))) + .thenReturn( + ResultBuilder.selectedRows( + new ArrayList<>( + List.of( + new HashMap<>( + Map.of("ID", "x1", "genre_ID", 1, "suppressed_ID", 10)), + new HashMap<>( + Map.of("ID", "x2", "genre_ID", 2, "suppressed_ID", 20))))) + .result(), + ResultBuilder.selectedRows(List.of()).result()); + cut.afterRead(ctx, dataList(row)); + // genre_ID has @Common.ValueListWithFixedValues → predicted + // suppressed_ID has @cds.odata.valuelist: false → excluded + assertThat(row).containsKey("SAP_Recommendations"); + @SuppressWarnings("unchecked") + Map recs = (Map) row.get("SAP_Recommendations"); + assertThat(recs).containsKey("genre_ID"); + assertThat(recs).doesNotContainKey("suppressed_ID"); + }); + } + @Test void blobAndVectorFields_areExcludedFromContextSelect() { runIn( @@ -393,55 +436,33 @@ private static Result twoContextRows() { private static RecommendationClient rptStyleClient() { Random random = new Random(42); - return (rows, predictionColumns, indexColumn) -> { - List predictions = new ArrayList<>(); - for (CdsData row : rows) { - if (predictionColumns.stream().noneMatch(col -> "[PREDICT]".equals(row.get(col)))) { - continue; - } - Map prediction = new HashMap<>(); - for (String col : predictionColumns) { - List 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 (predictionRow, contextRows, predictionColumns) -> { + Map prediction = new HashMap<>(); + for (String col : predictionColumns) { + List available = + contextRows.stream().filter(r -> r.get(col) != null).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))); } - return predictions; + prediction.put("ID", predictionRow.get("ID")); + return List.of(CdsData.create(prediction)); }; } private static RecommendationClient randomPickClient() { Random random = new Random(42); - return (rows, predictionColumns, indexColumn) -> { - List predictions = new ArrayList<>(); - for (CdsData row : rows) { - Map prediction = new HashMap<>(); - boolean addPrediction = false; - for (String col : predictionColumns) { - if ("[PREDICT]".equals(row.get(col))) { - addPrediction = true; - List 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))); - } - } - if (addPrediction) { - prediction.put(indexColumn, row.get(indexColumn)); - predictions.add(CdsData.create(prediction)); + return (predictionRow, contextRows, predictionColumns) -> { + Map prediction = new HashMap<>(); + for (String col : predictionColumns) { + if (predictionRow.get(col) == null) { + List available = + contextRows.stream().filter(r -> r.get(col) != null).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))); } } - return predictions; + prediction.put("ID", predictionRow.get("ID")); + return List.of(CdsData.create(prediction)); }; } } diff --git a/cds-feature-recommendations/src/test/java/com/sap/cds/feature/recommendation/RecommendationConfigurationTest.java b/cds-feature-recommendations/src/test/java/com/sap/cds/feature/recommendation/RecommendationConfigurationTest.java index 69b5062..8b3ebce 100644 --- a/cds-feature-recommendations/src/test/java/com/sap/cds/feature/recommendation/RecommendationConfigurationTest.java +++ b/cds-feature-recommendations/src/test/java/com/sap/cds/feature/recommendation/RecommendationConfigurationTest.java @@ -8,6 +8,7 @@ import com.sap.cds.feature.aicore.api.AICoreService; import com.sap.cds.services.ServiceCatalog; import com.sap.cds.services.environment.CdsEnvironment; +import com.sap.cds.services.persistence.PersistenceService; import com.sap.cds.services.runtime.CdsRuntime; import com.sap.cds.services.runtime.CdsRuntimeConfigurer; import java.util.stream.Stream; @@ -24,6 +25,7 @@ class RecommendationConfigurationTest { @Mock private ServiceCatalog serviceCatalog; @Mock private CdsEnvironment environment; @Mock private AICoreService aiCoreService; + @Mock private PersistenceService persistenceService; @Test void aiCoreServiceFound_registersHandler() { @@ -33,6 +35,8 @@ void aiCoreServiceFound_registersHandler() { when(environment.getServiceBindings()).thenReturn(Stream.empty()); when(serviceCatalog.getService(AICoreService.class, AICoreService.DEFAULT_NAME)) .thenReturn(aiCoreService); + when(serviceCatalog.getService(PersistenceService.class, PersistenceService.DEFAULT_NAME)) + .thenReturn(persistenceService); new RecommendationConfiguration().eventHandlers(configurer); diff --git a/cds-feature-recommendations/src/test/java/com/sap/cds/feature/recommendation/api/RptInferenceClientTest.java b/cds-feature-recommendations/src/test/java/com/sap/cds/feature/recommendation/api/RptInferenceClientTest.java new file mode 100644 index 0000000..8abce82 --- /dev/null +++ b/cds-feature-recommendations/src/test/java/com/sap/cds/feature/recommendation/api/RptInferenceClientTest.java @@ -0,0 +1,48 @@ +/* + * © 2026 SAP SE or an SAP affiliate company and cds-ai contributors. + */ +package com.sap.cds.feature.recommendation.api; + +import static org.assertj.core.api.Assertions.assertThat; + +import java.util.List; +import java.util.Map; +import org.junit.jupiter.api.Test; + +class RptInferenceClientTest { + + @Test + void computeSyntheticKey_singleKey() { + String key = RptInferenceClient.computeSyntheticKey(Map.of("ID", "abc"), List.of("ID")); + assertThat(key).isEqualTo("ID" + '\0' + "abc"); + } + + @Test + void computeSyntheticKey_compositeKey() { + String key = + RptInferenceClient.computeSyntheticKey( + Map.of("order_ID", 1, "item_no", 10), List.of("order_ID", "item_no")); + assertThat(key).isEqualTo("order_ID" + '\0' + "1" + '\0' + "item_no" + '\0' + "10"); + } + + @Test + void computeSyntheticKey_noCollision_betweenDifferentCompositions() { + // "1" + "0" must not produce the same key as "10" + "" + String key1 = + RptInferenceClient.computeSyntheticKey( + Map.of("order_ID", "1", "item_no", "0"), List.of("order_ID", "item_no")); + String key2 = + RptInferenceClient.computeSyntheticKey( + Map.of("order_ID", "10", "item_no", ""), List.of("order_ID", "item_no")); + assertThat(key1).isNotEqualTo(key2); + } + + @Test + void computeSyntheticKey_nullValue_doesNotCrash() { + Map row = new java.util.HashMap<>(); + row.put("order_ID", 1); + row.put("item_no", null); + String key = RptInferenceClient.computeSyntheticKey(row, List.of("order_ID", "item_no")); + assertThat(key).isEqualTo("order_ID" + '\0' + "1" + '\0' + "item_no" + '\0'); + } +} diff --git a/cds-feature-recommendations/src/test/resources/model/recommendations-test.cds b/cds-feature-recommendations/src/test/resources/model/recommendations-test.cds index bfcd611..5c30916 100644 --- a/cds-feature-recommendations/src/test/resources/model/recommendations-test.cds +++ b/cds-feature-recommendations/src/test/resources/model/recommendations-test.cds @@ -1,5 +1,7 @@ namespace test; +// genre_ID and currency_code are declared as plain scalars here because this is a test model. +// In a real CDS model these would be generated foreign key columns from annotated associations. @odata.draft.enabled entity Books { key ID : UUID; @@ -46,6 +48,16 @@ entity PlainEntity { title : String; } +@odata.draft.enabled +entity BooksWithDisabledValueList { + key ID : UUID; + @Common.ValueListWithFixedValues + genre_ID : Integer; + @Common.ValueListWithFixedValues + @cds.odata.valuelist: false + suppressed_ID : Integer; +} + service TestService { entity Books as projection on test.Books; entity Genres as projection on test.Genres; @@ -53,4 +65,5 @@ service TestService { entity OrderItems as projection on test.OrderItems; entity IsbnBooks as projection on test.IsbnBooks; entity PlainEntity as projection on test.PlainEntity; + entity BooksWithDisabledValueList as projection on test.BooksWithDisabledValueList; } diff --git a/samples/bookshop/srv/src/main/java/customer/bookshop/handlers/AICoreShowcaseHandler.java b/samples/bookshop/srv/src/main/java/customer/bookshop/handlers/AICoreShowcaseHandler.java index ebaa19f..5ebfdf3 100644 --- a/samples/bookshop/srv/src/main/java/customer/bookshop/handlers/AICoreShowcaseHandler.java +++ b/samples/bookshop/srv/src/main/java/customer/bookshop/handlers/AICoreShowcaseHandler.java @@ -112,45 +112,39 @@ public void onCreateConfiguration(EventContext context) { public void onPredictCategory(EventContext context) { List> products = (List>) context.get("products"); - List rows = new ArrayList<>(); - rows.add( - CdsData.create( - Map.of("ID", "ctx-1", "name", "Laptop", "price", "999.99", "category", "Electronics"))); - rows.add( - CdsData.create( - Map.of("ID", "ctx-2", "name", "Mouse", "price", "29.99", "category", "Electronics"))); - rows.add( - CdsData.create( - Map.of("ID", "ctx-3", "name", "Shirt", "price", "49.99", "category", "Clothing"))); - rows.add( - CdsData.create( - Map.of("ID", "ctx-4", "name", "Novel", "price", "14.99", "category", "Books"))); - rows.add( - CdsData.create( - Map.of("ID", "ctx-5", "name", "Blender", "price", "89.99", "category", "Appliances"))); - - for (Map product : products) { - Map row = new HashMap<>(product); - row.put("category", "[PREDICT]"); - rows.add(CdsData.create(row)); - } + List contextRows = + List.of( + CdsData.create( + Map.of("ID", "ctx-1", "name", "Laptop", "price", "999.99", "category", "Electronics")), + CdsData.create( + Map.of("ID", "ctx-2", "name", "Mouse", "price", "29.99", "category", "Electronics")), + CdsData.create( + Map.of("ID", "ctx-3", "name", "Shirt", "price", "49.99", "category", "Clothing")), + CdsData.create( + Map.of("ID", "ctx-4", "name", "Novel", "price", "14.99", "category", "Books")), + CdsData.create( + Map.of( + "ID", "ctx-5", "name", "Blender", "price", "89.99", "category", "Appliances"))); AICoreService service = getAICoreService(); String rg = service.resourceGroup(); String deploymentId = service.deploymentId(rg, RptModelSpec.rpt1()); RptInferenceClient client = - new RptInferenceClient(service.inferenceClient(rg, deploymentId)); - List predictions = client.predict(rows, List.of("category"), "ID"); + new RptInferenceClient(service.inferenceClient(rg, deploymentId), List.of("ID")); List> results = new ArrayList<>(); - for (CdsData prediction : predictions) { - String id = (String) prediction.get("ID"); - Object categoryObj = prediction.get("category"); - String category = - categoryObj instanceof List list && !list.isEmpty() - ? extractPrediction(list) - : String.valueOf(categoryObj); - results.add(Map.of("ID", id, "category", category)); + for (Map product : products) { + CdsData predictionRow = CdsData.create(new HashMap<>(product)); + List predictions = client.predict(predictionRow, contextRows, List.of("category")); + for (CdsData prediction : predictions) { + String id = (String) prediction.get("ID"); + Object categoryObj = prediction.get("category"); + String category = + categoryObj instanceof List list && !list.isEmpty() + ? extractPrediction(list) + : String.valueOf(categoryObj); + results.add(Map.of("ID", id, "category", category)); + } } context.put("result", results);