perf(kb-planner): route internal planner calls to dedicated small/fast LLM

Adds an optional planner LLM role wired through KnowledgePriorityMiddleware
so KB query rewriting, date extraction, and recency classification run on a
cheap model (e.g. gpt-4o-mini, Haiku, Azure nano) instead of the user's
chat LLM. Operators opt in by setting is_planner: true on exactly one
global config; without it, behavior is unchanged.

surfsense_backend/app/agents/new_chat/chat_deepagent.py

@@ -102,6 +102,7 @@ from app.agents.new_chat.tools.registry import (
 )
 from app.db import ChatVisibility
 from app.services.connector_service import ConnectorService
+from app.services.llm_service import get_planner_llm
 from app.utils.perf import get_perf_logger
 
 _perf_log = get_perf_logger()
@@ -1077,6 +1078,7 @@ def _build_compiled_agent_blocking(
         else None,
         KnowledgePriorityMiddleware(
             llm=llm,
+            planner_llm=get_planner_llm(),
             search_space_id=search_space_id,
             filesystem_mode=filesystem_mode,
             available_connectors=available_connectors,