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Add passive mesh context awareness — observe channel traffic, inject into LLM prompts

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New context.py module: ring buffer (50K hard cap, ~25MB ceiling) passively
records all channel broadcasts. Observations are formatted with relative
timestamps and injected into the system prompt when generating LLM responses.
Only public channel traffic is observed; DMs to the bot are excluded (already
in per-user history). Bot's own node ID is auto-added to ignore list.

Config: context.enabled, observe_channels, ignore_nodes, max_age, max_context_items
TUI: new Context settings submenu (menu item 7)
Hourly prune removes expired observations.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Ubuntu 2026-02-24 22:02:42 +00:00
commit 63a2caad37
7 changed files with 302 additions and 12 deletions
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config.example.yaml
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@ -40,6 +40,14 @@ memory:
window_size: 4 # Recent message pairs to keep in full
summarize_threshold: 8 # Messages before re-summarizing
# === MESH CONTEXT ===
context:
enabled: true # Observe channel traffic for LLM context
observe_channels: [] # Channel indices to observe (empty = all)
ignore_nodes: [] # Node IDs to exclude from observation
max_age: 2592000 # Max age in seconds (default 30 days)
max_context_items: 20 # Max observations injected into LLM context
# === LLM BACKEND ===
llm:
backend: openai # openai | anthropic | google