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feat: Hybrid RAG knowledge base, sentence-aware chunking, MeshMonitor HTTP sync
Knowledge Base: - Hybrid FTS5 + vector search using sqlite-vec and bge-small-en-v1.5 - Reciprocal Rank Fusion for result merging - Domain-aware query construction handles typos - Configurable weights for keyword vs semantic matching Message Chunking: - Sentence-aware splitting respects message boundaries - Continuation prompts for long responses - Natural follow-up detection (yes, ok, continue, more, etc.) - Per-user continuation state management MeshMonitor Integration: - HTTP API trigger sync (replaces file-based triggers.json) - Dynamic refresh interval - Trigger injection into LLM prompt Other: - Updated system prompt for better response length control - Simplified responder to handle message lists - Updated README with new features and architecture diagram - Cleaned up config.example.yaml Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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# MeshAI Configuration
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# LLM-powered Meshtastic assistant
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#
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# Copy this to config.yaml and customize as needed
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# For Docker: mount as /data/config.yaml
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# === BOT IDENTITY ===
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bot:
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name: ai # Bot's display name
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owner: "" # Owner's callsign (optional)
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respond_to_dms: true # Respond to direct messages
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filter_bbs_protocols: true # Ignore advBBS sync/notification messages
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# === MESHTASTIC CONNECTION ===
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connection:
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type: tcp # serial | tcp
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serial_port: /dev/ttyUSB0 # For serial connection
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tcp_host: localhost # For TCP connection (meshtasticd)
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tcp_port: 4403
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# === RESPONSE BEHAVIOR ===
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response:
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delay_min: 2.2 # Min delay before responding (seconds)
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delay_max: 3.0 # Max delay before responding
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max_length: 150 # Max chars per message chunk
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max_messages: 2 # Max message chunks per response
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# === CONVERSATION HISTORY ===
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history:
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database: /data/conversations.db
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max_messages_per_user: 50 # Messages to keep per user
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conversation_timeout: 86400 # Conversation expiry (seconds, 86400=24h)
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auto_cleanup: true # Auto-delete old conversations
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cleanup_interval_hours: 24 # How often to run cleanup
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max_age_days: 30 # Delete conversations older than this
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# === MEMORY OPTIMIZATION ===
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memory:
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enabled: true # Enable rolling summary memory
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window_size: 4 # Recent message pairs to keep in full
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summarize_threshold: 8 # Messages before re-summarizing
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# === MESH CONTEXT ===
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context:
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enabled: true # Observe channel traffic for LLM context
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observe_channels: [] # Channel indices to observe (empty = all)
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ignore_nodes: [] # Node IDs to exclude from observation
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max_age: 2592000 # Max age in seconds (default 30 days)
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max_context_items: 20 # Max observations injected into LLM context
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# === LLM BACKEND ===
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llm:
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backend: openai # openai | anthropic | google
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api_key: "" # API key (or use LLM_API_KEY env var)
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base_url: https://api.openai.com/v1 # API base URL
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model: gpt-4o-mini # Model name
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timeout: 30 # Request timeout (seconds)
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system_prompt: >-
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You are a helpful assistant on a Meshtastic mesh network.
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Keep responses VERY brief - under 250 characters total.
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Be concise but friendly. No markdown formatting.
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google_grounding: false # Enable Google Search grounding (Gemini only, $35/1k queries)
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# === WEATHER ===
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weather:
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primary: openmeteo # openmeteo | wttr | llm
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fallback: llm # openmeteo | wttr | llm | none
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default_location: "" # Default location for !weather (optional)
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# === MESHMONITOR INTEGRATION ===
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meshmonitor:
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enabled: false
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triggers_file: /data/triggers.json
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inject_into_prompt: true
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# MeshAI Configuration
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# LLM-powered Meshtastic assistant
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#
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# Copy this to config.yaml and customize as needed
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# For Docker: mount as /data/config.yaml
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# === BOT IDENTITY ===
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bot:
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name: ai # Bot's display name
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owner: "" # Owner's callsign (optional)
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respond_to_dms: true # Respond to direct messages
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filter_bbs_protocols: true # Ignore advBBS sync/notification messages
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# === MESHTASTIC CONNECTION ===
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connection:
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type: tcp # serial | tcp
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serial_port: /dev/ttyUSB0 # For serial connection
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tcp_host: localhost # For TCP connection (meshtasticd)
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tcp_port: 4403
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# === RESPONSE BEHAVIOR ===
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response:
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delay_min: 2.2 # Min delay before responding (seconds)
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delay_max: 3.0 # Max delay before responding
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max_length: 200 # Max chars per message chunk
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max_messages: 3 # Max message chunks per response
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# === CONVERSATION HISTORY ===
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history:
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database: /data/conversations.db
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max_messages_per_user: 50 # Messages to keep per user
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conversation_timeout: 86400 # Conversation expiry (seconds, 86400=24h)
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auto_cleanup: true # Auto-delete old conversations
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cleanup_interval_hours: 24 # How often to run cleanup
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max_age_days: 30 # Delete conversations older than this
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# === MEMORY OPTIMIZATION ===
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memory:
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enabled: true # Enable rolling summary memory
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window_size: 4 # Recent message pairs to keep in full
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summarize_threshold: 8 # Messages before re-summarizing
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# === MESH CONTEXT ===
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context:
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enabled: true # Observe channel traffic for LLM context
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observe_channels: [] # Channel indices to observe (empty = all)
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ignore_nodes: [] # Node IDs to exclude from observation
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max_age: 2592000 # Max age in seconds (default 30 days)
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max_context_items: 20 # Max observations injected into LLM context
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# === LLM BACKEND ===
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llm:
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backend: openai # openai | anthropic | google
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api_key: "" # API key (or use LLM_API_KEY env var)
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base_url: https://api.openai.com/v1 # API base URL
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model: gpt-4o-mini # Model name
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timeout: 30 # Request timeout (seconds)
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system_prompt: >-
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You are a helpful assistant on a Meshtastic mesh network.
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Keep responses very brief - 1-2 short sentences, under 300 characters.
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Only give longer answers if the user explicitly asks for detail or explanation.
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Be concise but friendly. No markdown formatting.
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google_grounding: false # Enable Google Search grounding (Gemini only, $35/1k queries)
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# === WEATHER ===
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weather:
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primary: openmeteo # openmeteo | wttr | llm
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fallback: llm # openmeteo | wttr | llm | none
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default_location: "" # Default location for !weather (optional)
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# === MESHMONITOR INTEGRATION ===
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meshmonitor:
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enabled: false # Enable MeshMonitor trigger sync
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url: "" # MeshMonitor web UI URL (e.g. http://192.168.1.100:8080)
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inject_into_prompt: true # Include trigger list in LLM prompt
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refresh_interval: 300 # Seconds between trigger refreshes
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# === KNOWLEDGE BASE (RAG) ===
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knowledge:
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enabled: false # Enable knowledge base search
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db_path: "" # Path to knowledge SQLite database
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top_k: 5 # Number of chunks to retrieve per query
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fts_weight: 0.5 # Weight for FTS5 keyword matches (0-1)
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vector_weight: 0.5 # Weight for vector semantic matches (0-1)
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