Add rulebook RAG pipeline and LLM-driven game setup wizard

RAG: switch Postgres to pgvector, chunk and embed the three D&D
rulebooks locally via sentence-transformers, and retrieve relevant
excerpts per DM turn (query = latest player message) to ground the
system prompt. Retrieval runs off the event loop and is capped by a
relevance threshold and a max character budget so it can't blow up
context size or cost.

Game setup wizard: creating a game now opens a short chat where the
DM asks about genre, length, and the player's experience level, then
proposes a name and description via a tool call. The player can edit
both before creating the game. Stateless endpoint — the frontend
carries the conversation, no DB needed since the game doesn't exist
yet.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

backend/app/api/ws_game.py

@@ -120,7 +120,7 @@ async def game_websocket(websocket: WebSocket, game_id: uuid.UUID, ticket: str)
                     )
 
                     try:
-                        dm_message = await run_dm_turn(session, game_id)
+                        dm_message = await run_dm_turn(session, game_id, latest_player_message=content)
                     except Exception:  # noqa: BLE001
                         logger.exception("DM turn failed for game %s", game_id)
                         await websocket.send_json({"type": "error", "detail": "dm_turn_failed"})