feat(02-01): add two-layer memory system — Redis sliding window + pgvector long-term

- ConversationEmbedding ORM model with Vector(384) column (pgvector)
- memory_short_key, escalation_status_key, pending_tool_confirm_key in redis_keys.py
- orchestrator/memory/short_term.py: RPUSH/LTRIM sliding window (get_recent_messages, append_message)
- orchestrator/memory/long_term.py: pgvector HNSW cosine search (retrieve_relevant, store_embedding)
- Migration 002: conversation_embeddings table, HNSW index, RLS with FORCE, SELECT/INSERT only
- 10 unit tests (fakeredis), 6 integration tests (pgvector) — all passing
- Auto-fix [Rule 3]: postgres image updated to pgvector/pgvector:pg16 (extension required)

docker-compose.yml

@@ -11,7 +11,7 @@ volumes:
 
 services:
   postgres:
-    image: postgres:16-alpine
+    image: pgvector/pgvector:pg16
     container_name: konstruct-postgres
     environment:
       POSTGRES_DB: konstruct