feat: local LLM multi-model, session search, cron proactive types, notifications, docs overhaul

Local LLM:
- user_settings.py: per-user hosts/models config (local_llm.json)
- routers/local_llm.py + static/local_llm.html: dedicated settings page
- llm_client.py: local OpenAI-compatible backend via httpx
- config.py: LOCAL_API_URL/KEY/MODEL + per-backend timeouts
- Active model shown near backend toggle (amber hint text)

Memory distillation:
- memory_distiller.py: DISTILL_BACKEND_MID/LONG .env overrides
- scheduler.py + notification.py: notify NC Talk after mid/long distill
- notification.py: outbound channel abstraction (NC Talk, extensible)

Session search:
- routers/files.py: GET /sessions/search?q= with excerpts grouped by date
- static/index.html + app.js: search UI in file sidebar with highlight
- _esc() helper to prevent XSS in search results

Proactive cron:
- cron_runner.py: new job types — message (send directly) and brief (LLM + send)
- Both support optional per-job channel override

Channels:
- routers/nextcloud_talk.py: consolidated using notification._send_nct_message()
- routers/auth.py: local backend status in /auth/status
- routers/chat.py: /backend returns {primary, fallback, local_model} object

UI / UX:
- Copy button for user messages (matching assistant)
- Autocomplete disabled on sensitive form fields
- settings.html: local model section replaced with link to /settings/local

Docs overhaul:
- MASTER.md hub + ARCH__SYSTEM/BACKENDS/PERSONA/CHANNELS/FUTURE.md
- ARCH__Intelligence_Layer.md replaced with redirect table
- CORTEX.md trimmed to vision only; README updated
- OPEN_WEBUI_API.md added to docs/

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

cortex/scheduler.py

@@ -30,24 +30,28 @@ async def _run_short() -> None:
 
 async def _run_mid() -> None:
     from memory_distiller import distill_mid
+    from notification import notify
     try:
         result = await distill_mid()
         if "error" in result:
             logger.warning("auto distill mid skipped: %s", result["error"])
         else:
             logger.info("auto distill mid: %d chars via %s", result["chars_written"], result["backend"])
+            await notify(result["username"], f"📝 Weekly memory digest complete ({result['chars_written']} chars via {result['backend']}).")
     except Exception as e:
         logger.error("auto distill mid failed: %s", e)
 
 
 async def _run_long() -> None:
     from memory_distiller import distill_long
+    from notification import notify
     try:
         result = await distill_long()
         if "error" in result:
             logger.warning("auto distill long skipped: %s", result["error"])
         else:
             logger.info("auto distill long: %d chars via %s", result["chars_written"], result["backend"])
+            await notify(result["username"], f"🧠 Monthly long-term memory integration complete ({result['chars_written']} chars via {result['backend']}). Worth a quick review.")
     except Exception as e:
         logger.error("auto distill long failed: %s", e)