feat(B-VEC): pgvector HNSW Optimierung — ef_construction=128, m=16, ef_search=40

B-VEC: Migration 0118 — HNSW-Indizes mit optimierten Parametern (ef_construction=128, m=16)
- 5 Tabellen: contacts, mails, files, calendar_entries, tags
- config.py: hnsw_ef_construction, hnsw_m, hnsw_ef_search, vector_index_type Settings
- base_provider.py + search_engine.py: SET LOCAL hnsw.ef_search vor Vector-Queries

B-VEC-IVF: IVFFlat als Alternative dokumentiert (vector_index_type Setting)
B-VEC-BATCH: Batch-Embedding verifiziert (generate_embeddings_batch nutzt llm_embed())
B-VEC-TEST: Performance-Tests auf Coolify-Instanz verschoben (benötigt 10k+ Datensätze)

app/plugins/builtins/unified_search/base_provider.py

@@ -13,6 +13,8 @@ from typing import Any
 from sqlalchemy import text
 from sqlalchemy.ext.asyncio import AsyncSession
 
+from app.config import settings
+
 logger = logging.getLogger(__name__)
 
 
@@ -53,6 +55,8 @@ class BaseSearchProvider:
         is_system_admin: bool = False,
     ) -> list[dict[str, Any]]:
         """Semantic vector search with visibility filter."""
+        # Set HNSW ef_search parameter for this transaction
+        await db.execute(text(f"SET LOCAL hnsw.ef_search = {settings.hnsw_ef_search}"))
         if is_system_admin or not user_id:
             return await self._search_vector_filtered(db, embedding, tenant_id, limit, None)
 

app/plugins/builtins/unified_search/search_engine.py

@@ -9,6 +9,7 @@ from typing import Any
 from sqlalchemy import text
 from sqlalchemy.ext.asyncio import AsyncSession
 
+from app.config import settings
 from app.plugins.builtins.unified_search.embedding import generate_embedding
 from app.plugins.builtins.unified_search.provider_registry import get_search_registry
 
@@ -164,6 +165,9 @@ async def find_similar_all_types(
 
     source_embedding_str = str(row["embedding"])
 
+    # Set HNSW ef_search parameter for this transaction
+    await db.execute(text(f"SET LOCAL hnsw.ef_search = {settings.hnsw_ef_search}"))
+
     registry = get_search_registry()
     similar: dict[str, list[dict[str, Any]]] = {}