perf: enrich only top-k results with one batched related-docs query

Phase 3 enrichment ran a sequential Neo4j query per fused result and the
final trim then discarded most of the output. Enrichment now covers only
results that can still reach the response - the Phase 4 rerank slice
(RERANK_SLICE_SIZE = 20, results beyond it are dropped when reranking)
or final_result_count, whichever applies - and resolves every page in a
single UNWIND $page_ids Cypher query via the new tenant-scoped
GraphService.get_related_documents_batch (per-page ordering by
shared_entities and per-page limit preserved via ORDER BY + collect()).

Unenriched tail results still carry related_dossiers: [] so the response
shape is unchanged. Query validated with EXPLAIN against the live Neo4j.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QbFZyDvYksazX6nYQYZ67L

src/services/graph_service.py

@@ -1185,6 +1185,68 @@ Feel free to expand it with more details!
             logger.error(f"Failed to get related documents for page {page_id}: {e}", exc_info=True)
             return []
 
+    async def get_related_documents_batch(
+        self,
+        page_ids: List[int],
+        user: str,
+        limit_per_page: int = 5
+    ) -> Dict[int, List[Dict[str, Any]]]:
+        """
+        Batch variant of get_related_documents: ONE UNWIND query for all pages
+        instead of one round-trip per page.
+
+        Args:
+            page_ids: Page IDs to find related documents for
+            user: User identifier
+            limit_per_page: Maximum related documents per page
+
+        Returns:
+            Mapping of page_id -> related-document rows (same shape as
+            get_related_documents). Pages with no related documents are
+            absent from the mapping.
+        """
+        from src.core.multi_tenancy import get_neo4j_user_base_label
+
+        if not page_ids:
+            return {}
+
+        user_base_label = get_neo4j_user_base_label(user)
+        user_doc_label = get_neo4j_user_label(user)
+
+        # ORDER BY runs before collect() so each page's list is sorted by
+        # shared_entities descending; [..$limit] trims per page.
+        query = f"""
+        UNWIND $page_ids AS pid
+        MATCH (d1:{user_doc_label}:Document {{page_id: pid}})
+        MATCH (d1)-[:MENTIONS]->(e:{user_base_label})<-[:MENTIONS]-(d2:{user_doc_label}:Document)
+        WHERE d1 <> d2 AND NOT e:Document
+        WITH pid, d2, d2.tags as tags, count(DISTINCT e) as shared_entities
+        WHERE tags IS NOT NULL AND size(tags) > 0
+        WITH pid, d2, tags, shared_entities
+        ORDER BY shared_entities DESC
+        WITH pid, collect({{
+            page_id: d2.page_id,
+            title: d2.title,
+            path: d2.path,
+            tags: tags,
+            shared_entities: shared_entities
+        }})[..$limit] AS related
+        RETURN pid AS page_id, related
+        """
+
+        try:
+            rows = await self.neo4j.execute_query(
+                query,
+                {"page_ids": page_ids, "limit": limit_per_page}
+            )
+            return {row["page_id"]: row["related"] for row in rows}
+        except Exception as e:
+            logger.error(
+                f"Failed to get related documents for {len(page_ids)} pages: {e}",
+                exc_info=True
+            )
+            return {}
+
     async def get_all_entities(self, user: str) -> List[Dict[str, Any]]:
         """
         Get all entities from the knowledge graph for a user.