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
22 lines
1.2 KiB
Markdown
22 lines
1.2 KiB
Markdown
# Echo Voice Assistant — Work Log
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---
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Task ID: 1
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Agent: Main Orchestrator
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Task: Build complete Echo voice assistant project
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Work Log:
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- Created project directory structure: /echo-assistant/{models/,audio_output/}
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- Implemented stt.py (195 lines) — WakeWordListener with openWakeWord + Transcriber with Vosk
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- Implemented brain.py (159 lines) — Async OpenRouter client with streaming, JSON command parsing, Qwen3 thinking tag cleanup
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- Implemented tts.py (181 lines) — Qwen3-TTS wrapper with lazy model loading, voice selection, instruction control, pygame playback
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- 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
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- Implemented main.py (283 lines) — Async orchestrator with Phase 5 parallel processing (TTS starts on first sentence from LLM stream)
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- Created requirements.txt with all dependencies
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- Created .env.example with configuration template
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Stage Summary:
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- Total: 1,093 lines of Python across 5 modules
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- Project is ready for environment setup (Python 3.12+, CUDA GPU, Vosk model download, OpenRouter API key)
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- Phase 5 parallel streaming is implemented in main.py._stream_and_speak()
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