Fix pgvector integration: VECTOR(512) for voyage-3-lite, register_vector on connect

- voyage-3-lite returns 512 dims (not 1024) — migrated column + schema
- register_vector now called once at connection time, not per-query
- Removes per-function register_vector calls that caused type cast conflicts

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Knowledgebase/schema.sql

@@ -2,6 +2,7 @@
 -- PostgreSQL, bez pgvector (embeddingy jako double precision[])
 -- pg_trgm pro fuzzy matching (volitelné)
 
+CREATE EXTENSION IF NOT EXISTS vector;
 CREATE EXTENSION IF NOT EXISTS pg_trgm;
 
 -- ─── Conversation sessions ────────────────────────────────────────────────────
@@ -56,7 +57,7 @@ CREATE TABLE IF NOT EXISTS kb_memories (
     -- search
     tags        TEXT[]          DEFAULT '{}',
     importance  FLOAT           DEFAULT 0.5,   -- 0..1
-    embedding   double precision[],  -- Voyage AI voyage-3-lite (1024-dim), Python-side similarity
+    embedding   vector(512),         -- Voyage AI voyage-3-lite (512-dim)
     fts         TSVECTOR,
 
     -- lifecycle
@@ -94,4 +95,5 @@ CREATE INDEX IF NOT EXISTS kb_memories_project_idx   ON kb_memories(project);
 CREATE INDEX IF NOT EXISTS kb_memories_importance_idx ON kb_memories(importance DESC);
 CREATE INDEX IF NOT EXISTS kb_memories_created_idx   ON kb_memories(created_at DESC);
 CREATE INDEX IF NOT EXISTS kb_memories_session_idx   ON kb_memories(session_id);
--- Note: embedding je double precision[] — similarity se počítá Python-side po FTS pre-filtru
+-- Vector index (aktivovat po ~1k řádcích pro lepší recall)
+-- CREATE INDEX kb_memories_vec_idx ON kb_memories USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);