fix(preference): propagate health statuses to personal suffixed IDs

fix(preference): ensure personal providers are authorized and marked healthy in effective view

feat(preference): support personal account addition via automatic suffixing on collision

fix(preference): treat DB as Source of Truth for provider list to enable removal

feat: decouple global AI configuration and update frontend with admin toggle

feat: Decouple Global Configuration from User Preferences

feat: add missing integration tests and fix multiple bugs discovered during testing

Windows stabilization and Hub API health fixes: Automated TLS provisioning, singleton enforcement, gRPC limit increases, and PreferenceService crash fix

fix: restore swarm control and windows node connectivity ...

- Resolved LLM provider identification issue in PreferenceService by implementing strict prefix matching and model version parsing.
- Enforced strict tenant-level LLM resolution by removing all system-wide hardcoded fallbacks to 'gemini'.
- Fixed Windows node persistence by updating SchtasksManager to explicitly set the working directory for background agent tasks.
- Hardened bootstrap_windows.ps1 with explicit watchdog and dependency verification to ensure reliable file sync on Windows.
- Added self-correcting path logic to install_service.py to resolve agent_node package imports.

feat(mesh): autonomous windows provisioning and lifecycle management ...

- Implemented secure self-purge mechanism for agent nodes (purge.py).
- Refactored bootstrap_windows.ps1 for headless/non-interactive installation.
- Added POST /nodes/purge endpoint to Hub for token-based self-deregistration.
- Enhanced Nodes UI with 'Purge & Deregister' option and platform-aware command dispatch.
- Modularized backend services (Mesh, NodeRegistry, Session, Tool, RAG) to centralize business logic.
- Stabilized Windows PTY serialization and terminal output dispatch.
- Added integration tests for node purge flows.

Fix Windows PyWinPTY terminal boundary string drops via bat spool execution and full Windows deployment support

Refactor configuration flow (Day 0 vs Day 1 separation) and add startup scripts ...

- Stop AI provider settings from syncing back to config.yaml (stored in DB only now).
- Parameterize frontend port in docker-compose.
- Add start_server.sh and stop_server.sh scripts.
- Update .gitignore to exclude scratch files.

feat: periodic background health check for system LLM providers

Refactor AI Config and Fix Login failure: Migrated services to a structured api directory, updated backend schemas for multiple TTS/STT providers, and improved settings/chat UI coverage.

Refactor backend code to improve modularity and extensibility