Compaction: - GemmaLLM.chat() truncates ChatContext to last 30 items (~15 turns) before sending to LLM, preventing context window overflow on long conversations. Preserves system prompt and removes orphaned tool calls. Skills: - agent/skills_mcp.py: MCP server with skill_save, skill_recall, skill_list, skill_update tools backed by .md files in /skills - skills/ dir bind-mounted into container, git-trackable - System prompt instructs Hope to save repeatable procedures as skills and recall them before performing tasks she's done before - Distinct from memory (facts) — skills are learned *procedures*
30 lines
1.1 KiB
YAML
30 lines
1.1 KiB
YAML
services:
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voice:
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build: .
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container_name: voice
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network_mode: host
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environment:
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LIVEKIT_URL: "http://localhost:7880"
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LIVEKIT_API_KEY: "${LIVEKIT_API_KEY:-devkey}"
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LIVEKIT_API_SECRET: "${LIVEKIT_API_SECRET:-devsecret}"
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AZURE_SPEECH_KEY: "${AZURE_SPEECH_KEY:?Set AZURE_SPEECH_KEY in .env}"
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AZURE_SPEECH_REGION: "${AZURE_SPEECH_REGION:-eastus}"
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AZURE_TTS_VOICE: "${AZURE_TTS_VOICE:-en-US-AvaNeural}"
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GEMMA_BASE_URL: "${GEMMA_BASE_URL:-http://192.168.86.2:8023/v1}"
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GEMMA_MODEL: "${GEMMA_MODEL:-gemma-4-e4b}"
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GEMMA_API_KEY: "${GEMMA_API_KEY:-not-needed}"
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WEB_MCP_ENABLED: "${WEB_MCP_ENABLED:-true}"
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FIRECRAWL_BASE: "${FIRECRAWL_BASE:-http://192.168.86.2:3002}"
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volumes:
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- ./livekit.yaml:/etc/livekit.yaml:ro
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- ./certs:/etc/voice/certs
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- ./memory:/memory
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- ./skills:/skills
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healthcheck:
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test: ["CMD-SHELL", "curl -sk https://localhost:8090/ -o /dev/null && curl -s http://localhost:7880/ -o /dev/null"]
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interval: 15s
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timeout: 5s
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retries: 3
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start_period: 20s
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restart: unless-stopped
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