e4408a63e6
- Conversation sidebar with create/delete/history - Chat area with streaming LLM responses (z-ai-web-dev-sdk) - Voice input via Web Speech API with recording indicator - Browser TTS auto-speak for assistant responses - Settings panel (voice, TTS, sidebar toggle) - Prisma schema: Conversation + Message models - API routes: /api/chat/stream, /api/conversations, /api/messages - Zustand store for state management - Web Speech API type declarations
1.2 KiB
1.2 KiB
Echo Voice Assistant — Work Log
Task ID: 1 Agent: Main Orchestrator Task: Build complete Echo voice assistant project
Work Log:
- Created project directory structure: /echo-assistant/{models/,audio_output/}
- Implemented stt.py (195 lines) — WakeWordListener with openWakeWord + Transcriber with Vosk
- Implemented brain.py (159 lines) — Async OpenRouter client with streaming, JSON command parsing, Qwen3 thinking tag cleanup
- Implemented tts.py (181 lines) — Qwen3-TTS wrapper with lazy model loading, voice selection, instruction control, pygame playback
- Implemented actions.py (275 lines) — 10 registered local actions: open_app, set_timer, get_time, get_date, get_weather, create_reminder, control_volume, search_web, calculate, shutdown
- Implemented main.py (283 lines) — Async orchestrator with Phase 5 parallel processing (TTS starts on first sentence from LLM stream)
- Created requirements.txt with all dependencies
- Created .env.example with configuration template
Stage Summary:
- Total: 1,093 lines of Python across 5 modules
- Project is ready for environment setup (Python 3.12+, CUDA GPU, Vosk model download, OpenRouter API key)
- Phase 5 parallel streaming is implemented in main.py._stream_and_speak()