6a0bae2a0b
## Voice Pipeline (P3) - Replace openWakeWord daemon with Wyoming Satellite approach - Add Wyoming Satellite service on port 10700 for HA voice pipeline - Update setup.sh with cross-platform sed compatibility (macOS/Linux) - Add version field to Kokoro TTS voice info - Update launchd service loader to use Wyoming Satellite ## Home Assistant Integration (P4) - Add custom conversation agent component (openclaw_conversation) - Fix: Use IntentResponse instead of plain strings (HA API requirement) - Support both HTTP API and CLI fallback modes - Config flow for easy HA UI setup - Add OpenClaw bridge scripts (Python + Bash) - Add ha-ctl utility for HA entity control - Fix: Use context manager for token file reading - Add HA configuration examples and documentation ## Infrastructure - Add mem0 backup automation (launchd + script) - Add n8n workflow templates (morning briefing, notification router) - Add VS Code workspace configuration - Reorganize model files into categorized folders: - lmstudio-community/ - mlx-community/ - bartowski/ - mradermacher/ ## Documentation - Update PROJECT_PLAN.md with Wyoming Satellite architecture - Update TODO.md with completed Wyoming integration tasks - Add OPENCLAW_INTEGRATION.md for HA setup guide ## Testing - Verified Wyoming services running (STT:10300, TTS:10301, Satellite:10700) - Verified OpenClaw CLI accessibility - Confirmed cross-platform compatibility fixes
37 lines
928 B
Python
37 lines
928 B
Python
import os
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from mem0 import Memory
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config = {
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"vector_store": {
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"provider": "chroma",
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"config": {
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"collection_name": "homeai_memory",
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"path": os.path.expanduser("~/.openclaw/memory/chroma/"),
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}
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},
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"llm": {
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"provider": "ollama",
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"config": {
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"model": "qwen2.5:7b",
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"ollama_base_url": "http://localhost:11434",
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}
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},
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"embedder": {
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"provider": "ollama",
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"config": {
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"model": "nomic-embed-text",
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"ollama_base_url": "http://localhost:11434",
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}
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}
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}
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m = Memory.from_config(config)
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# Test storing a memory
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result = m.add("The user's favorite color is blue.", user_id="aodhan")
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print(f"Store result: {result}")
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# Test searching for the memory
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search_results = m.search("What is the user's favorite color?", user_id="aodhan")
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print(f"Search results: {search_results}")
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