feat: unified model registry with role-based routing

Introduces model_registry.py as the single source of truth for all LLM
backend configuration. Replaces scattered backend settings across user_settings,
config distill_backend_*, and the UI toggle.

model_registry.py:
- Per-user home/{user}/model_registry.json with version, hosts, models, roles
- Models have: type (local_openai|claude_cli|gemini_cli|gemini_api), label,
  model_name, host_id, context_k (tokens), tags (capability labels)
- Roles map to priority chains: primary, backup_1..backup_4
- Built-in IDs (claude_cli, gemini_cli, gemini_api) always resolvable
- Auto-migrates existing local_llm.json on first access
- CRUD: save_host, remove_host, save_model, remove_model, set_role
- get_model_for_role(): registry → .env default → hardcoded fallback

config.py:
- role_chat/orchestrator/distill/coder/research .env defaults
- defined_roles: comma-separated standard role list (extensible)
- get_defined_roles() and get_role_default() helper methods

llm_client.complete():
- New role= parameter (default "chat") for registry-based routing
- model= still accepted for explicit UI toggle override
- _claude() and _local() accept model_cfg dict instead of raw string
- _local() uses pre-resolved config from registry

memory_distiller.py:
- distill_mid/long now use role="distill" (no more distill_backend_* .env vars needed)

cron_runner.py:
- brief jobs use role="chat"

routers/chat.py + auth.py:
- Use model_registry instead of user_settings for local model info

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

cortex/cron_runner.py

@@ -181,6 +181,7 @@ async def run_job(job: dict) -> None:
             response_text, backend = await complete(
                 system_prompt=system_prompt,
                 messages=[{"role": "user", "content": payload}],
+                role="chat",
             )
             await notify(username, response_text, channel=channel)
             logger.info("cron [brief] sent via %s: %s", backend, label)