TED Notice Lot documents embedding
This commit is contained in:
parent
902456001e
commit
4bc503ed29
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@ -7,10 +7,10 @@ Included changes:
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- Score normalization and result fusion
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- Generic /search endpoint
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- Lexical index maintenance service and startup backfill runner
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- DOC lexical search migration (V9)
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- DOC lexical search migration (V14)
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- Modified DOC representation write path to refresh search vectors
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Important note:
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- Full-text search requires V9__doc_search_slice1_support.sql to be applied.
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- Full-text search requires V14__doc_search_slice1_support.sql to be applied.
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- The lexical index service is guarded and will no-op if the search columns are not yet present.
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- Because Flyway is currently disabled in application.yml, apply the migration manually or enable Flyway before using the new search endpoint.
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@ -1,11 +1,16 @@
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package at.procon.dip.domain.document.repository;
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import at.procon.dip.domain.document.RepresentationType;
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import at.procon.dip.domain.document.DocumentType;
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import at.procon.dip.domain.document.EmbeddingStatus;
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import at.procon.dip.domain.document.entity.DocumentTextRepresentation;
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import java.util.List;
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import java.util.Optional;
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import java.util.UUID;
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import org.springframework.data.domain.Pageable;
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import org.springframework.data.jpa.repository.JpaRepository;
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import org.springframework.data.jpa.repository.Query;
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import org.springframework.data.repository.query.Param;
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public interface DocumentTextRepresentationRepository extends JpaRepository<DocumentTextRepresentation, UUID> {
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@ -20,4 +25,33 @@ public interface DocumentTextRepresentationRepository extends JpaRepository<Docu
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long countByRepresentationType(RepresentationType representationType);
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Optional<DocumentTextRepresentation> findFirstByDocument_IdAndPrimaryRepresentationTrue(UUID documentId);
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@Query("""
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SELECT r
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FROM DocumentTextRepresentation r
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JOIN r.document d
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WHERE (:documentType IS NULL OR d.documentType = :documentType)
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AND (:representationType IS NULL OR r.representationType = :representationType)
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AND (:builderKey IS NULL OR r.builderKey = :builderKey)
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AND (:primaryOnly = false OR r.primaryRepresentation = true)
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AND r.textBody IS NOT NULL
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AND r.textBody <> ''
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AND (:includeCompleted = true OR NOT EXISTS (
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SELECT e.id
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FROM DocumentEmbedding e
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WHERE e.representation.id = r.id
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AND e.model.modelKey = :modelKey
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AND e.embeddingStatus = :completedStatus
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))
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ORDER BY r.createdAt ASC, r.id ASC
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""")
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List<DocumentTextRepresentation> findEmbeddingCandidatesByDocumentType(
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@Param("documentType") DocumentType documentType,
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@Param("representationType") RepresentationType representationType,
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@Param("builderKey") String builderKey,
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@Param("primaryOnly") boolean primaryOnly,
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@Param("modelKey") String modelKey,
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@Param("completedStatus") EmbeddingStatus completedStatus,
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@Param("includeCompleted") boolean includeCompleted,
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Pageable pageable);
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}
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@ -1,17 +1,23 @@
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package at.procon.dip.domain.ted.config;
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import jakarta.validation.constraints.Min;
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import jakarta.validation.constraints.Positive;
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import lombok.Data;
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import org.springframework.boot.context.properties.ConfigurationProperties;
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import org.springframework.context.annotation.Configuration;
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import org.springframework.validation.annotation.Validated;
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@Configuration
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@ConfigurationProperties(prefix = "dip.ted.projection")
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@Validated
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@Data
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public class TedProjectionProperties {
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private boolean enabled = true;
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private boolean startupBackfillEnabled = false;
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@Positive
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/**
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* Maximum number of legacy TED documents to backfill on startup. 0 means no limit.
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*/
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@Min(0)
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private int startupBackfillLimit = 250;
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@Positive
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private int structuredSearchHybridCandidateLimit = 5000;
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@ -29,7 +35,10 @@ public class TedProjectionProperties {
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* Optional startup/backfill path for notices that were imported before lot documents existed.
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*/
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private boolean startupBackfillEnabled = false;
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@Positive
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/**
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* Maximum number of projections to backfill on startup. 0 means no limit.
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*/
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@Min(0)
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private int startupBackfillLimit = 1000;
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/**
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* Queue embeddings whenever the lot semantic text representation is created or changed.
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@ -37,7 +37,7 @@ import org.springframework.util.StringUtils;
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@Slf4j
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public class TedLotDocumentMaterializationService {
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public static final String BUILDER_KEY = "ted-lot-structured-text";
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public static final String BUILDER_KEY = "ted-lot-clustering-text-v1";
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private final TedProjectionProperties properties;
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private final TedNoticeLotRepository lotRepository;
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@ -174,22 +174,20 @@ public class TedLotDocumentMaterializationService {
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private String buildSemanticText(TedNoticeProjection projection, TedNoticeLot lot) {
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StringBuilder sb = new StringBuilder(1024);
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append(sb, "Document type", "TED procurement lot");
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append(sb, "Lot title", lot.getTitle());
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append(sb, "Lot description", lot.getDescription());
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append(sb, "Project title", projection.getProjectTitle());
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append(sb, "Entity type", "Procurement lot");
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append(sb, "Procurement scope", joinedLines(lot.getTitle(), lot.getDescription()));
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append(sb, "Procurement category", joined(firstNonEmpty(lot.getCpvCodes(), projection.getCpvCodes())));
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append(sb, "Relevant domain", projection.getBuyerActivityType());
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append(sb, "Contract type", projection.getContractNature() == null ? null : projection.getContractNature().name());
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append(sb, "Geographic context", joined(firstNonEmpty(lot.getNutsCodes(), projection.getNutsCodes()), projection.getBuyerCountryCode()));
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if (!StringUtils.hasText(lot.getDescription())) {
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append(sb, "Project description", projection.getProjectDescription());
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append(sb, "Parent notice context", joinedLines(projection.getProjectTitle(), projection.getProjectDescription()));
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} else if (properties.getLotDocuments().isIncludeProjectDescription()) {
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append(sb, "Project context", projection.getProjectDescription());
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append(sb, "Parent notice context", joinedLines(projection.getProjectTitle(), projection.getProjectDescription()));
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} else {
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append(sb, "Parent notice context", projection.getProjectTitle());
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}
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append(sb, "Contract nature", projection.getContractNature() == null ? null : projection.getContractNature().name());
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append(sb, "Buyer activity", projection.getBuyerActivityType());
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append(sb, "Buyer country", projection.getBuyerCountryCode());
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append(sb, "CPV codes", joined(firstNonEmpty(lot.getCpvCodes(), projection.getCpvCodes())));
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append(sb, "NUTS codes", joined(firstNonEmpty(lot.getNutsCodes(), projection.getNutsCodes())));
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return sb.toString().trim();
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}
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@ -239,6 +237,23 @@ public class TedLotDocumentMaterializationService {
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.collect(Collectors.joining(", "));
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}
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private String joined(String[] values, String fallback) {
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String joined = joined(values);
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if (StringUtils.hasText(joined)) {
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return joined;
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}
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return fallback;
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}
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private String joinedLines(String... values) {
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String joined = Arrays.stream(values)
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.filter(StringUtils::hasText)
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.map(String::trim)
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.distinct()
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.collect(Collectors.joining("\n"));
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return StringUtils.hasText(joined) ? joined : null;
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}
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private String sanitizeKey(String value) {
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return value == null ? "unknown" : value.trim().replaceAll("\\s+", "_");
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}
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@ -24,6 +24,8 @@ import org.springframework.stereotype.Component;
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@Slf4j
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public class TedProjectionStartupRunner implements ApplicationRunner {
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private static final int STARTUP_BACKFILL_BATCH_SIZE = 1000;
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private final TedProjectionProperties properties;
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private final ProcurementDocumentRepository procurementDocumentRepository;
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private final TedNoticeProjectionRepository projectionRepository;
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@ -47,13 +49,22 @@ public class TedProjectionStartupRunner implements ApplicationRunner {
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private void backfillNoticeProjections() {
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int limit = properties.getStartupBackfillLimit();
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log.info("Phase 3 startup backfill enabled - ensuring TED projections for up to {} documents", limit);
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var page = procurementDocumentRepository.findAll(
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PageRequest.of(0, limit, Sort.by(Sort.Direction.ASC, "createdAt")));
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log.info("Phase 3 startup backfill enabled - ensuring TED projections for {} documents", describeLimit(limit));
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int synced = 0;
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int processed = 0;
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int pageNumber = 0;
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Sort sort = Sort.by(Sort.Direction.ASC, "createdAt");
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while (limit <= 0 || processed < limit) {
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int pageSize = pageSizeFor(limit, processed);
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var page = procurementDocumentRepository.findAll(PageRequest.of(pageNumber++, pageSize, sort));
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if (page.isEmpty()) {
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break;
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}
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for (var legacyDocument : page.getContent()) {
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processed++;
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if (projectionRepository.existsByLegacyProcurementDocumentId(legacyDocument.getId())) {
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continue;
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}
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@ -61,21 +72,51 @@ public class TedProjectionStartupRunner implements ApplicationRunner {
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synced++;
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}
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if (!page.hasNext()) {
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break;
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}
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}
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log.info("Phase 3 startup backfill completed - synced {} TED projections", synced);
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}
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private void backfillLotDocuments() {
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int limit = properties.getLotDocuments().getStartupBackfillLimit();
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log.info("TED lot document startup backfill enabled - materializing lots for up to {} projections", limit);
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var page = projectionRepository.findAll(
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PageRequest.of(0, limit, Sort.by(Sort.Direction.ASC, "createdAt")));
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log.info("TED lot document startup backfill enabled - materializing lots for {} projections", describeLimit(limit));
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int lotDocuments = 0;
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int processed = 0;
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int pageNumber = 0;
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Sort sort = Sort.by(Sort.Direction.ASC, "createdAt");
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while (limit <= 0 || processed < limit) {
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int pageSize = pageSizeFor(limit, processed);
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var page = projectionRepository.findAll(PageRequest.of(pageNumber++, pageSize, sort));
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if (page.isEmpty()) {
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break;
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}
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for (var projection : page.getContent()) {
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processed++;
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lotDocuments += lotDocumentMaterializationService.materializeProjectionLots(projection.getId());
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}
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if (!page.hasNext()) {
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break;
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}
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}
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log.info("TED lot document startup backfill completed - materialized/updated {} lot documents", lotDocuments);
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}
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private int pageSizeFor(int limit, int processed) {
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if (limit <= 0) {
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return STARTUP_BACKFILL_BATCH_SIZE;
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}
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return Math.min(STARTUP_BACKFILL_BATCH_SIZE, limit - processed);
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}
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private String describeLimit(int limit) {
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return limit > 0 ? "up to " + limit : "all available";
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}
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}
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@ -1,6 +1,8 @@
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package at.procon.dip.embedding.config;
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import at.procon.dip.domain.document.DistanceMetric;
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import at.procon.dip.domain.document.DocumentType;
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import at.procon.dip.domain.document.RepresentationType;
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import at.procon.dip.embedding.model.EmbeddingPrefixMode;
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import java.time.Duration;
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import java.util.LinkedHashMap;
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@ -21,6 +23,7 @@ public class EmbeddingProperties {
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private Map<String, ModelProperties> models = new LinkedHashMap<>();
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private IndexingProperties indexing = new IndexingProperties();
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private JobsProperties jobs = new JobsProperties();
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private StartupProperties startup = new StartupProperties();
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@Data
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public static class ProviderProperties {
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@ -79,4 +82,18 @@ public class EmbeddingProperties {
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private Duration maxRetryDelay = Duration.ofHours(6);
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private long schedulerDelayMs = 5000;
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}
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@Data
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public static class StartupProperties {
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private boolean enqueueMissingEnabled = false;
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private boolean processReadyEnabled = false;
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private DocumentType documentType;
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private RepresentationType representationType;
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private String builderKey;
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private boolean primaryOnly = false;
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private String modelKey;
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private boolean force = false;
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private int batchSize = 1000;
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private long maxRepresentationsPerRun = 0;
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}
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}
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@ -0,0 +1,17 @@
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package at.procon.dip.embedding.service;
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import at.procon.dip.domain.document.DocumentType;
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import at.procon.dip.domain.document.RepresentationType;
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public record ScopedEmbeddingEnqueueResult(
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DocumentType documentType,
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RepresentationType representationType,
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String builderKey,
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boolean primaryOnly,
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String modelKey,
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boolean force,
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int requestedLimit,
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int matchedRepresentations,
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int jobsQueuedOrAlreadyActive
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) {
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}
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@ -0,0 +1,91 @@
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package at.procon.dip.embedding.service;
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import at.procon.dip.domain.document.DocumentType;
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import at.procon.dip.domain.document.EmbeddingStatus;
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import at.procon.dip.domain.document.RepresentationType;
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import at.procon.dip.domain.document.entity.DocumentTextRepresentation;
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import at.procon.dip.domain.document.repository.DocumentTextRepresentationRepository;
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import at.procon.dip.embedding.job.service.EmbeddingJobService;
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import at.procon.dip.embedding.model.EmbeddingJobType;
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import at.procon.dip.embedding.registry.EmbeddingModelRegistry;
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import java.util.List;
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import lombok.RequiredArgsConstructor;
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import org.springframework.data.domain.PageRequest;
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import org.springframework.stereotype.Service;
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import org.springframework.transaction.annotation.Transactional;
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import org.springframework.util.StringUtils;
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@Service
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@RequiredArgsConstructor
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public class ScopedEmbeddingEnqueueService {
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private static final int MAX_LIMIT = 10_000;
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private final DocumentTextRepresentationRepository representationRepository;
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private final EmbeddingJobService jobService;
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private final EmbeddingModelRegistry modelRegistry;
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@Transactional
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public ScopedEmbeddingEnqueueResult enqueueByDocumentType(DocumentType documentType,
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RepresentationType representationType,
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String builderKey,
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boolean primaryOnly,
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String modelKey,
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boolean force,
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int limit) {
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return enqueueByDocumentType(documentType, representationType, builderKey, primaryOnly, modelKey, force, 0, limit);
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}
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@Transactional
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public ScopedEmbeddingEnqueueResult enqueueByDocumentType(DocumentType documentType,
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RepresentationType representationType,
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String builderKey,
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boolean primaryOnly,
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String modelKey,
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boolean force,
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int pageNumber,
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int limit) {
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String effectiveModelKey = StringUtils.hasText(modelKey)
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? modelKey
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: modelRegistry.getRequiredDefaultDocumentModelKey();
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modelRegistry.getRequired(effectiveModelKey);
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int effectiveLimit = Math.max(1, Math.min(limit, MAX_LIMIT));
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int effectivePageNumber = Math.max(0, pageNumber);
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String normalizedBuilderKey = StringUtils.hasText(builderKey) ? builderKey.trim() : null;
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List<DocumentTextRepresentation> representations = representationRepository.findEmbeddingCandidatesByDocumentType(
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documentType,
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representationType,
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normalizedBuilderKey,
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primaryOnly,
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effectiveModelKey,
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EmbeddingStatus.COMPLETED,
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force,
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PageRequest.of(effectivePageNumber, effectiveLimit)
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);
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int jobs = 0;
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for (DocumentTextRepresentation representation : representations) {
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jobService.enqueueForRepresentation(
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representation.getDocument().getId(),
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representation.getId(),
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effectiveModelKey,
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EmbeddingJobType.DOCUMENT_EMBED
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);
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jobs++;
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}
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return new ScopedEmbeddingEnqueueResult(
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documentType,
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representationType,
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normalizedBuilderKey,
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primaryOnly,
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effectiveModelKey,
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force,
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effectiveLimit,
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representations.size(),
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jobs
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);
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}
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}
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@ -0,0 +1,92 @@
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package at.procon.dip.embedding.startup;
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import at.procon.dip.embedding.config.EmbeddingProperties;
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import at.procon.dip.embedding.service.RepresentationEmbeddingOrchestrator;
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import at.procon.dip.embedding.service.ScopedEmbeddingEnqueueResult;
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import at.procon.dip.embedding.service.ScopedEmbeddingEnqueueService;
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import at.procon.dip.runtime.condition.ConditionalOnRuntimeMode;
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import at.procon.dip.runtime.config.RuntimeMode;
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import lombok.RequiredArgsConstructor;
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import lombok.extern.slf4j.Slf4j;
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import org.springframework.boot.ApplicationArguments;
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import org.springframework.boot.ApplicationRunner;
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import org.springframework.core.Ordered;
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import org.springframework.core.annotation.Order;
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import org.springframework.stereotype.Component;
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@Component
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@ConditionalOnRuntimeMode(RuntimeMode.NEW)
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@RequiredArgsConstructor
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@Order(Ordered.LOWEST_PRECEDENCE)
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@Slf4j
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public class EmbeddingStartupRunner implements ApplicationRunner {
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private final EmbeddingProperties properties;
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private final ScopedEmbeddingEnqueueService enqueueService;
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private final RepresentationEmbeddingOrchestrator orchestrator;
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@Override
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public void run(ApplicationArguments args) {
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EmbeddingProperties.StartupProperties startup = properties.getStartup();
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if (!properties.isEnabled() || startup == null) {
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return;
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}
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if (startup.isEnqueueMissingEnabled()) {
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enqueueMissing(startup);
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}
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if (startup.isProcessReadyEnabled()) {
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processReadyJobs();
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}
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}
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private void enqueueMissing(EmbeddingProperties.StartupProperties startup) {
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int batchSize = Math.max(1, startup.getBatchSize());
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long max = startup.getMaxRepresentationsPerRun();
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long remaining = max > 0 ? max : Long.MAX_VALUE;
|
||||
int pageNumber = 0;
|
||||
long matched = 0;
|
||||
long queued = 0;
|
||||
|
||||
log.info("Startup embedding enqueue enabled (documentType={}, representationType={}, builderKey={}, primaryOnly={}, force={}, modelKey={}, maxRepresentationsPerRun={})",
|
||||
startup.getDocumentType(), startup.getRepresentationType(), startup.getBuilderKey(), startup.isPrimaryOnly(),
|
||||
startup.isForce(), startup.getModelKey(), max > 0 ? max : "unbounded");
|
||||
|
||||
while (remaining > 0) {
|
||||
int requested = (int) Math.min(batchSize, remaining);
|
||||
ScopedEmbeddingEnqueueResult result = enqueueService.enqueueByDocumentType(
|
||||
startup.getDocumentType(),
|
||||
startup.getRepresentationType(),
|
||||
startup.getBuilderKey(),
|
||||
startup.isPrimaryOnly(),
|
||||
startup.getModelKey(),
|
||||
startup.isForce(),
|
||||
pageNumber,
|
||||
requested
|
||||
);
|
||||
|
||||
matched += result.matchedRepresentations();
|
||||
queued += result.jobsQueuedOrAlreadyActive();
|
||||
remaining -= result.matchedRepresentations();
|
||||
|
||||
if (result.matchedRepresentations() < requested) {
|
||||
break;
|
||||
}
|
||||
pageNumber++;
|
||||
}
|
||||
|
||||
log.info("Startup embedding enqueue completed - matched {} representation(s), queued/already-active {} job(s)",
|
||||
matched, queued);
|
||||
}
|
||||
|
||||
private void processReadyJobs() {
|
||||
if (!properties.getJobs().isEnabled()) {
|
||||
log.warn("Startup embedding processing was requested but dip.embedding.jobs.enabled=false; queued jobs will not be processed by the NEW embedding job subsystem");
|
||||
return;
|
||||
}
|
||||
|
||||
int processed = orchestrator.processNextReadyBatch();
|
||||
log.info("Startup embedding processing completed - processed {} ready job(s)", processed);
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,66 @@
|
|||
package at.procon.dip.embedding.web;
|
||||
|
||||
import at.procon.dip.domain.document.DocumentType;
|
||||
import at.procon.dip.domain.document.RepresentationType;
|
||||
import at.procon.dip.embedding.service.ScopedEmbeddingEnqueueResult;
|
||||
import at.procon.dip.embedding.service.ScopedEmbeddingEnqueueService;
|
||||
import at.procon.dip.runtime.condition.ConditionalOnRuntimeMode;
|
||||
import at.procon.dip.runtime.config.RuntimeMode;
|
||||
import io.swagger.v3.oas.annotations.Operation;
|
||||
import io.swagger.v3.oas.annotations.tags.Tag;
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import org.springframework.http.HttpStatus;
|
||||
import org.springframework.web.bind.annotation.PostMapping;
|
||||
import org.springframework.web.bind.annotation.RequestMapping;
|
||||
import org.springframework.web.bind.annotation.RequestParam;
|
||||
import org.springframework.web.bind.annotation.RestController;
|
||||
import org.springframework.web.server.ResponseStatusException;
|
||||
|
||||
@RestController
|
||||
@ConditionalOnRuntimeMode(RuntimeMode.NEW)
|
||||
@RequestMapping("/v1/dip/admin/embeddings")
|
||||
@RequiredArgsConstructor
|
||||
@Tag(name = "Embedding Admin", description = "Administrative operations for NEW-runtime representation embeddings")
|
||||
public class EmbeddingAdminController {
|
||||
|
||||
private final ScopedEmbeddingEnqueueService enqueueService;
|
||||
|
||||
@PostMapping("/enqueue-by-document-type")
|
||||
@Operation(
|
||||
summary = "Queue embeddings by document type",
|
||||
description = "Queues embedding jobs only for DOC text representations belonging to the requested document type."
|
||||
)
|
||||
public ScopedEmbeddingEnqueueResult enqueueByDocumentType(
|
||||
@RequestParam String documentType,
|
||||
@RequestParam(required = false) String representationType,
|
||||
@RequestParam(required = false) String builderKey,
|
||||
@RequestParam(required = false, defaultValue = "false") boolean primaryOnly,
|
||||
@RequestParam(required = false) String modelKey,
|
||||
@RequestParam(required = false, defaultValue = "false") boolean force,
|
||||
@RequestParam(required = false, defaultValue = "1000") int limit) {
|
||||
return enqueueService.enqueueByDocumentType(
|
||||
parseEnum(DocumentType.class, documentType, "documentType"),
|
||||
parseEnum(RepresentationType.class, representationType, "representationType"),
|
||||
builderKey,
|
||||
primaryOnly,
|
||||
modelKey,
|
||||
force,
|
||||
limit
|
||||
);
|
||||
}
|
||||
|
||||
private <E extends Enum<E>> E parseEnum(Class<E> enumType, String value, String parameterName) {
|
||||
if (value == null || value.isBlank()) {
|
||||
return null;
|
||||
}
|
||||
String normalized = value.trim().replace('-', '_').toUpperCase(java.util.Locale.ROOT);
|
||||
try {
|
||||
return Enum.valueOf(enumType, normalized);
|
||||
} catch (IllegalArgumentException ex) {
|
||||
throw new ResponseStatusException(
|
||||
HttpStatus.BAD_REQUEST,
|
||||
"Invalid " + parameterName + ": " + value
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -119,7 +119,7 @@ ted:
|
|||
# Mail account username (email address)
|
||||
username: archiv@procon.co.at
|
||||
# Mail account password
|
||||
password: ${MAIL_PASSWORD:worasigg}
|
||||
password: ${MAIL_PASSWORD:}
|
||||
# Use SSL/TLS connection
|
||||
ssl: true
|
||||
# Mail folder to read from
|
||||
|
|
|
|||
|
|
@ -43,10 +43,29 @@ dip:
|
|||
enabled: true
|
||||
jobs:
|
||||
enabled: false
|
||||
parallel-batch-count: 1
|
||||
parallel-batch-count: 2
|
||||
process-in-batches: true
|
||||
batch-size: 16
|
||||
execution-batch-size: 16
|
||||
batch-size: 48
|
||||
execution-batch-size: 48
|
||||
startup:
|
||||
# Enqueue missing DOC representation embeddings on NEW-runtime startup.
|
||||
enqueue-missing-enabled: true
|
||||
# Also process ready embedding jobs during startup. Requires dip.embedding.jobs.enabled=true.
|
||||
process-ready-enabled: true
|
||||
# Leave empty to enqueue missing embeddings for all document types, or set e.g. TED_NOTICE_LOT.
|
||||
document-type: TED_NOTICE_LOT
|
||||
# Optional representation filter, e.g. SEMANTIC_TEXT.
|
||||
representation-type:
|
||||
# Optional builder filter, e.g. ted-lot-clustering-text-v1.
|
||||
builder-key:
|
||||
primary-only: false
|
||||
# Leave empty to use dip.embedding.default-document-model.
|
||||
model-key:
|
||||
# False skips representations that already have a COMPLETED embedding for the model.
|
||||
force: false
|
||||
batch-size: 1000
|
||||
# 0 means enqueue all matching not-vectorized representations.
|
||||
max-representations-per-run: 0
|
||||
|
||||
default-document-model: e5-default
|
||||
default-query-model: e5-default
|
||||
|
|
@ -258,7 +277,7 @@ dip:
|
|||
# Mailbox username
|
||||
username: archiv@procon.co.at
|
||||
# Mailbox password
|
||||
password: ${MAIL_PASSWORD:worasigg}
|
||||
password: ${MAIL_PASSWORD}
|
||||
# Folder/mailbox name
|
||||
folder-name: INBOX
|
||||
# Optional stable provider account key; falls back to username
|
||||
|
|
@ -350,6 +369,17 @@ dip:
|
|||
startup-backfill-limit: 250
|
||||
structured-search-hybrid-candidate-limit: 5000
|
||||
structured-search-facet-bucket-limit: 12
|
||||
lot-documents:
|
||||
# Materialize one canonical DOC document of type TED_NOTICE_LOT per TED lot.
|
||||
enabled: true
|
||||
# Optional startup/backfill path for notices that were imported before lot documents existed.
|
||||
startup-backfill-enabled: true
|
||||
# Maximum number of legacy TED lot documents to backfill during startup (0 = all)
|
||||
startup-backfill-limit: 0
|
||||
# Queue embeddings whenever the lot semantic text representation is created or changed.
|
||||
queue-embeddings-on-change: true
|
||||
# Include parent notice project description even when the lot already has its own description.
|
||||
include-parent-description: false
|
||||
|
||||
migration:
|
||||
legacy-audit:
|
||||
|
|
|
|||
|
|
@ -14,12 +14,11 @@ spring:
|
|||
name: document-intelligence-platform
|
||||
|
||||
datasource:
|
||||
#url: jdbc:postgresql://localhost:5432/RELM
|
||||
#username: ${DB_USERNAME:postgres}
|
||||
#password: ${DB_PASSWORD:P54!pcd#Wi}
|
||||
url: jdbc:postgresql://94.130.218.54:32333/RELM
|
||||
username: ${DB_USERNAME:postgres}
|
||||
password: ${DB_PASSWORD:PDmXRx0Rbk9OFOn9qO5Gm/mPCfqW8zwbZ+/YIU1lySc=}
|
||||
url: jdbc:postgresql://localhost:5432/RELM
|
||||
#url: jdbc:postgresql://94.130.218.54:32333/RELM
|
||||
username: ${DB_USERNAME}
|
||||
password: ${DB_PASSWORD}
|
||||
|
||||
driver-class-name: org.postgresql.Driver
|
||||
hikari:
|
||||
maximum-pool-size: 5
|
||||
|
|
@ -27,7 +26,7 @@ spring:
|
|||
connection-timeout: 30000
|
||||
idle-timeout: 300000
|
||||
max-lifetime: 900000
|
||||
leak-detection-threshold: 120000 # 2 minutes - increased to avoid false positives with batch processing
|
||||
leak-detection-threshold: 300000 # 5 minutes - increased to avoid false positives with batch processing
|
||||
|
||||
jpa:
|
||||
hibernate:
|
||||
|
|
|
|||
|
|
@ -0,0 +1,7 @@
|
|||
-- Adds an index for the TED lot clustering-oriented semantic representation builder.
|
||||
-- The original ted-lot-structured-text index is left in place for databases that
|
||||
-- already materialized or queried the earlier representation shape.
|
||||
|
||||
CREATE INDEX IF NOT EXISTS idx_doc_text_repr_ted_lot_clustering_builder
|
||||
ON DOC.doc_text_representation(builder_key)
|
||||
WHERE builder_key = 'ted-lot-clustering-text-v1';
|
||||
Loading…
Reference in New Issue