feat(kg): add tsvector FTS, entity deduplication, and embedding fixes

- Replace ILIKE search with PostgreSQL tsvector/GIN full-text search
  for KG entities (migration 000031)
- Add entity deduplication system with dual-threshold strategy:
  auto-merge at 0.98+ similarity with Jaro-Winkler name match,
  flag 0.90-0.98 as candidates for manual review
- Add ScanDuplicates for bulk on-demand duplicate detection
- Add MergeEntities with advisory lock and tenant-scoped relation
  re-pointing (delete-then-update to avoid ON CONFLICT on UPDATE)
- Wire dedup inline after KG extraction pipeline
- Fix BackfillKGEmbeddings: was failing silently due to
  context.Background() missing tenant_id; now runs cross-tenant
- Fix BackfillKGEmbeddings: break on error → continue with failed
  ID tracking and max consecutive error cap
- Add EmbedEntity helper; UpsertEntity now generates embeddings
  in background goroutine
- Add HTTP endpoints: POST /kg/dedup/scan, GET /kg/dedup,
  POST /kg/merge, POST /kg/dedup/dismiss
- Add web UI: Dedup dialog with Scan All button, side-by-side
  entity comparison, merge/dismiss actions
- Add Jaro-Winkler similarity algorithm with 34 unit tests
- Update IngestExtraction to return upserted entity IDs
- Bump RequiredSchemaVersion to 31

internal/store/pg/knowledge_graph_embedding.go

@@ -2,7 +2,6 @@ package pg
 
 import (
 	"context"
-	"fmt"
 	"log/slog"
 
 	"github.com/google/uuid"
@@ -10,27 +9,29 @@ import (
 
 // BackfillKGEmbeddings generates embeddings for all KG entities that don't have one yet.
 // Processes in batches of 50. Returns total number of entities updated.
+// On batch-level embedding failure, skips the batch and continues (up to 3 consecutive failures).
 func (s *PGKnowledgeGraphStore) BackfillKGEmbeddings(ctx context.Context) (int, error) {
 	if s.embProvider == nil {
 		return 0, nil
 	}
 
 	const batchSize = 50
+	const maxConsecutiveErrors = 3
 	total := 0
+	consecutiveErrors := 0
 
-	// $1=batchSize (LIMIT), tenant at $2 if not cross-tenant
-	tc, tcArgs, _, tcErr := scopeClause(ctx, 2)
-	if tcErr != nil {
-		return 0, tcErr
-	}
-	batchQ := fmt.Sprintf(`SELECT id, name, description FROM kg_entities
-		 WHERE embedding IS NULL%s
+	// Backfill is a cross-tenant admin operation — no tenant scoping.
+	// context.Background() is typically passed here (no tenant in context).
+	batchQ := `SELECT id, name, description FROM kg_entities
+		 WHERE embedding IS NULL
 		 ORDER BY created_at DESC
-		 LIMIT $1`, tc)
-	batchBaseArgs := tcArgs // tenant uuid(s) prepended after $1
+		 LIMIT $1`
+
+	// Track failed entity IDs to avoid re-fetching them
+	failedIDs := make(map[uuid.UUID]bool)
 
 	for {
-		queryArgs := append([]any{batchSize}, batchBaseArgs...)
+		queryArgs := []any{batchSize}
 		rows, err := s.db.QueryContext(ctx, batchQ, queryArgs...)
 		if err != nil {
 			return total, err
@@ -47,6 +48,9 @@ func (s *PGKnowledgeGraphStore) BackfillKGEmbeddings(ctx context.Context) (int,
 			if err := rows.Scan(&id, &name, &desc); err != nil {
 				continue
 			}
+			if failedIDs[id] {
+				continue // skip previously failed entities
+			}
 			pending = append(pending, entityRow{id: id, text: name + " " + desc})
 		}
 		rows.Close()
@@ -63,9 +67,19 @@ func (s *PGKnowledgeGraphStore) BackfillKGEmbeddings(ctx context.Context) (int,
 		}
 		embeddings, err := s.embProvider.Embed(ctx, texts)
 		if err != nil {
-			slog.Warn("kg entity embedding batch failed", "error", err)
-			break
+			slog.Warn("kg entity embedding batch failed, skipping batch", "error", err, "batch_size", len(pending))
+			// Mark these entities as failed so we don't re-fetch them
+			for _, p := range pending {
+				failedIDs[p.id] = true
+			}
+			consecutiveErrors++
+			if consecutiveErrors >= maxConsecutiveErrors {
+				slog.Warn("kg backfill: too many consecutive errors, stopping", "errors", consecutiveErrors)
+				break
+			}
+			continue
 		}
+		consecutiveErrors = 0 // reset on success
 
 		for i, emb := range embeddings {
 			if len(emb) == 0 {
@@ -92,3 +106,23 @@ func (s *PGKnowledgeGraphStore) BackfillKGEmbeddings(ctx context.Context) (int,
 	}
 	return total, nil
 }
+
+// EmbedEntity generates and stores an embedding for a single entity.
+// Called by UpsertEntity to ensure entities created via HTTP API also get embeddings.
+func (s *PGKnowledgeGraphStore) EmbedEntity(ctx context.Context, entityID, name, description string) {
+	if s.embProvider == nil {
+		return
+	}
+	text := name + " " + description
+	embeddings, err := s.embProvider.Embed(ctx, []string{text})
+	if err != nil || len(embeddings) == 0 || len(embeddings[0]) == 0 {
+		return // best-effort, don't fail the upsert
+	}
+	vecStr := vectorToString(embeddings[0])
+	if _, err := s.db.ExecContext(ctx,
+		`UPDATE kg_entities SET embedding = $1::vector WHERE id = $2`,
+		vecStr, mustParseUUID(entityID),
+	); err != nil {
+		slog.Warn("kg entity embedding failed", "entity_id", entityID, "error", err)
+	}
+}