44e8d05e2cb74015cb2040fecb1361ae36c2e5b4
- agent/task_registry.py: file-based JSONL event registry (cross-process) - agent/task_worker.py: autonomous LLM loop with weather/time/memory/web tools - agent/dispatch_mcp.py: MCP tool exposing dispatch_task to the main agent - agent/agent.py: registers dispatch toolset, polls task events → room data - web: slide-out task panel (FAB button + badge), live step streaming via data channel topic 'tasks', status dots (running/completed/failed) - Dockerfile: copies new task_*.py and dispatch_mcp.py files The dispatch MCP runs in its own process; events flow through /tmp/tasks/events.jsonl which the main agent tails every second and forwards to the browser. Tasks run up to 10 LLM iterations with tool calls.
Description
Real-time voice assistant: LiveKit + Azure Speech + local Gemma LLM
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