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* Archive agents on worktree archive; clean up schedules on archive Worktree archive used to hard-delete every agent inside it (storage removed, agent_deleted emitted), losing history along with the worktree. It now archives those agents instead, so they remain in storage with an archivedAt timestamp and stay visible in the archived list. Schedules targeting an archived agent were left as dead records that the schedule service rejected at run time. AgentManager now fires an onAgentArchived callback from every archive path (live, stored snapshot, cascade-to-children), and bootstrap wires it to ScheduleService.deleteForAgent so those schedules are cleaned up automatically. * Push agent_state when archiving stored-only agents; tolerate schedule delete errors Greptile review on PR #1206 flagged two issues: 1. archiveSnapshot persisted archivedAt to storage but did not emit an agent_state event for stored-only agents. Connected clients would keep showing them as active until a full reload. Mirror the dispatch logic from markRecordArchived: notifyAgentState for live agents, dispatchArchivedStoredAgent for off-memory non-internal agents. 2. ScheduleService.deleteForAgent used Promise.all, which short-circuits on the first store error and abandons the rest. Switch to Promise.allSettled, count fulfilled deletions, and log rejections. * Tighten agent-manager archive tests after /audit-tests review - Split "fires onAgentArchived for live, stored, and cascaded archives" into two single-behavior tests with independent fixtures, so the assertion array isn't reset mid-test. - Strict equality on the cascade hook assertion (no more arrayContaining). - "archiveSnapshot dispatches archived state" now captures the full agent state event, asserts a dispatch happened, asserts the dispatched agent id, and asserts the lifecycle is closed.
Voice Assistant
A voice-controlled terminal assistant that runs as a single local service.
Quick Start
# Install dependencies
npm install
# Copy environment variables
cp .env.example .env
# Edit .env and add your API keys (OpenAI, Deepgram)
# Run development servers
npm run dev
# Open browser to http://localhost:5173
Architecture
- Express Server (port 3000) - Serves API and built UI in production
- Vite Dev Server (port 5173) - Hot-reload React UI in development
- WebSocket (
/ws) - Real-time bidirectional communication - Agent - STT → LLM → TTS pipeline with terminal control
- Daemon - tmux-based terminal management (in-process)
Development
# Run both servers (recommended)
npm run dev
# Or run separately:
npm run dev:server # Express on port 3000
npm run dev:ui # Vite on port 5173
# Type checking
npm run typecheck
# Build for production
npm run build
# Start production server
npm start
Project Status
✅ Completed (Phases 1-2):
- Package setup and configuration
- Express server with WebSocket
- React UI with Vite
- WebSocket client with ping/pong testing
⏳ In Progress (Phase 3):
- Terminal control (tmux integration)
📋 Planned (Phases 4-9):
- LLM integration (OpenAI GPT-4)
- Agent orchestrator
- Speech-to-Text (Deepgram)
- Text-to-Speech (OpenAI)
- Audio streaming
- UI polish
See IMPLEMENTATION_PLAN.md for complete details.
Environment Variables
OPENAI_API_KEY=your-openai-key-here # GPT-4 and TTS
DEEPGRAM_API_KEY=your-deepgram-key-here # Streaming STT
STT_MODEL=whisper-1 # Optional: override to gpt-4o-transcribe, etc.
STT_CONFIDENCE_THRESHOLD=-3.0 # Optional: reject low-confidence clips
STT_DEBUG_AUDIO_DIR=.stt-debug # Optional: persist raw dictation audio for debugging
PASEO_HOME=~/.paseo # Runtime state directory (agents/, etc.)
PASEO_LISTEN=127.0.0.1:6767 # Listen address (host:port or /path/to/socket)
PASEO_HOME defaults to ~/.paseo and isolates runtime artifacts like agents/. PASEO_LISTEN controls the daemon listen address. For blue/green testing you can run a parallel server without touching production state:
PASEO_HOME=~/.paseo-blue PASEO_LISTEN=127.0.0.1:7777 npm run dev
Tech Stack
- Server: Express, TypeScript, ws (WebSocket)
- Client: React 18, Vite, TypeScript
- Terminal: tmux (via child_process)
- AI: OpenAI (LLM + TTS), Deepgram (STT)
Testing
Currently manual testing via:
- Start servers:
npm run dev - Open http://localhost:5173
- Test WebSocket connection (green status indicator)
- Click "Send Ping" button to test communication
More testing guidance as features are implemented.
License
MIT