Fix recall race, ContextVar leaks, dead code, and recall duplication ...

- run_recall: wrap busy check + create_run in session_lock to prevent
  race between scheduler and websocket handler
- run_recall: save ContextVar tokens and reset in finally to avoid
  leaking user context into subsequent background tasks
- websocket.py: reset user ContextVars in finally after run completes
- orchestrator.py: remove dead set_notify / _notify abstraction
- orchestrator.py: extract _finalize_recall to deduplicate success /
  MaxIterationsReached / Exception finalization blocks

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

Unify in-memory session state in AgentSessionOrchestrator ...

Replace scattered _runs + _busy_sessions + _session_sockets with a
single _sessions: dict[str, SessionState] on the orchestrator.

- SessionState dataclass holds run, busy_event, and websockets
- _session_sockets module-level global removed from websocket.py;
  socket tracking moved into orchestrator (add/remove_websocket)
- Event bus subscriber _on_recall_update moved into orchestrator
- Per-session asyncio.Lock added to protect concurrent-run guard
- _cleanup() auto-removes empty SessionState entries

Tests updated to reference _sessions instead of legacy _runs.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

Extract WebSocket business logic into AgentSessionOrchestrator ...

- Create navi/core/orchestrator.py with AgentSessionOrchestrator and SessionRun
- Orchestrator owns _runs, _busy_sessions, Agent creation, run_agent(), run_recall()
- Transport-agnostic: accepts notify callback from WebSocket handler
- WebSocket handler (websocket.py) now only does serialization/deserialization
- _fire_recall delegates to orchestrator.run_recall() instead of inline logic
- recall_scheduler_loop now accepts orchestrator parameter
- AppContainer gains .orchestrator field, created in create_container()
- deps.py: add get_orchestrator()
- Update integration tests for scheduler_loop and websocket unit tests

All 392 tests pass.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

Initial implementation of the agent system core ...

- FastAPI server with REST API and WebSocket streaming
- Modular LLM backend abstraction (Ollama implemented, OpenAI stub)
- Tool system: web_search (ddgs), filesystem, http_request, code_exec, terminal
- Agent profiles: smart_home, server_admin, secretary
- Tool-calling loop with concurrent tool execution
- In-memory session store with SessionStore ABC for future persistence
- Registry pattern for tools, profiles, and backends
- Orchestrator stub as foundation for multi-agent scenarios