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mimo/build
...
mimo/creat
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d5099a18c6 | ||
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| fba972f8be | |||
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6
app.js
6
app.js
@@ -1,4 +1,4 @@
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import * as THREE from 'three';
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import ResonanceVisualizer from './nexus/components/resonance-visualizer.js';\nimport * as THREE from 'three';
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import { EffectComposer } from 'three/addons/postprocessing/EffectComposer.js';
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import { RenderPass } from 'three/addons/postprocessing/RenderPass.js';
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import { UnrealBloomPass } from 'three/addons/postprocessing/UnrealBloomPass.js';
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@@ -597,7 +597,7 @@ class PSELayer {
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let pseLayer;
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let metaLayer, neuroBridge, cbr, symbolicPlanner, knowledgeGraph, blackboard, symbolicEngine, calibrator;
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let resonanceViz, metaLayer, neuroBridge, cbr, symbolicPlanner, knowledgeGraph, blackboard, symbolicEngine, calibrator;
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let agentFSMs = {};
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function setupGOFAI() {
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@@ -666,7 +666,7 @@ async function init() {
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scene = new THREE.Scene();
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scene.fog = new THREE.FogExp2(0x050510, 0.012);
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setupGOFAI();
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setupGOFAI();\n resonanceViz = new ResonanceVisualizer(scene);
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camera = new THREE.PerspectiveCamera(65, window.innerWidth / window.innerHeight, 0.1, 1000);
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camera.position.copy(playerPos);
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@@ -586,8 +586,8 @@ def alert_on_failure(report: HealthReport, dry_run: bool = False) -> None:
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logger.info("Created alert issue #%d", result["number"])
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def run_once(args: argparse.Namespace) -> tuple[bool, HealthReport]:
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"""Run one health check cycle. Returns (healthy, report)."""
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def run_once(args: argparse.Namespace) -> bool:
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"""Run one health check cycle. Returns True if healthy."""
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report = run_health_checks(
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ws_host=args.ws_host,
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ws_port=args.ws_port,
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@@ -615,20 +615,7 @@ def run_once(args: argparse.Namespace) -> tuple[bool, HealthReport]:
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except Exception:
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pass # never crash the watchdog over its own heartbeat
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return report.overall_healthy, report
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def _emit_json(report: HealthReport) -> None:
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"""Print a HealthReport as JSON to stdout."""
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print(json.dumps({
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"healthy": report.overall_healthy,
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"timestamp": report.timestamp,
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"checks": [
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{"name": c.name, "healthy": c.healthy,
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"message": c.message, "details": c.details}
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for c in report.checks
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],
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}, indent=2))
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return report.overall_healthy
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def main():
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@@ -691,18 +678,30 @@ def main():
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signal.signal(signal.SIGINT, _handle_sigterm)
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while _running:
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_healthy, report = run_once(args)
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if args.output_json:
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_emit_json(report)
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run_once(args)
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for _ in range(args.interval):
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if not _running:
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break
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time.sleep(1)
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else:
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healthy, report = run_once(args)
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healthy = run_once(args)
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if args.output_json:
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_emit_json(report)
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report = run_health_checks(
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ws_host=args.ws_host,
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ws_port=args.ws_port,
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heartbeat_path=Path(args.heartbeat_path),
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stale_threshold=args.stale_threshold,
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)
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print(json.dumps({
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"healthy": report.overall_healthy,
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"timestamp": report.timestamp,
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"checks": [
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{"name": c.name, "healthy": c.healthy,
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"message": c.message, "details": c.details}
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for c in report.checks
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],
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}, indent=2))
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sys.exit(0 if healthy else 1)
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@@ -1,13 +1,18 @@
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class MemoryOptimizer {
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constructor(options = {}) {
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this.threshold = options.threshold || 0.8;
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this.decayRate = options.decayRate || 0.05;
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this.threshold = options.threshold || 0.3;
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this.decayRate = options.decayRate || 0.01;
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this.lastRun = Date.now();
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}
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optimize(memory) {
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console.log('Optimizing memory...');
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// Heuristic-based pruning
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return memory.filter(m => m.strength > this.threshold);
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optimize(memories) {
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const now = Date.now();
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const elapsed = (now - this.lastRun) / 1000;
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this.lastRun = now;
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return memories.map(m => {
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const decay = (m.importance || 1) * this.decayRate * elapsed;
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return { ...m, strength: Math.max(0, (m.strength || 1) - decay) };
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}).filter(m => m.strength > this.threshold || m.locked);
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}
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}
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export default MemoryOptimizer;
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14
nexus/mnemosyne/reasoner.py
Normal file
14
nexus/mnemosyne/reasoner.py
Normal file
@@ -0,0 +1,14 @@
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class Reasoner:
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def __init__(self, rules):
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self.rules = rules
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def evaluate(self, entries):
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return [r['action'] for r in self.rules if self._check(r['condition'], entries)]
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def _check(self, cond, entries):
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if cond.startswith('count'):
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# e.g. count(type=anomaly)>3
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p = cond.replace('count(', '').split(')')
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key, val = p[0].split('=')
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count = sum(1 for e in entries if e.get(key) == val)
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return eval(f"{count}{p[1]}")
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return False
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22
nexus/mnemosyne/resonance_linker.py
Normal file
22
nexus/mnemosyne/resonance_linker.py
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@@ -0,0 +1,22 @@
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"""Resonance Linker — Finds second-degree connections in the holographic graph."""
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class ResonanceLinker:
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def __init__(self, archive):
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self.archive = archive
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def find_resonance(self, entry_id, depth=2):
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"""Find entries that are connected via shared neighbors."""
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if entry_id not in self.archive._entries: return []
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entry = self.archive._entries[entry_id]
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neighbors = set(entry.links)
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resonance = {}
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for neighbor_id in neighbors:
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if neighbor_id in self.archive._entries:
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for second_neighbor in self.archive._entries[neighbor_id].links:
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if second_neighbor != entry_id and second_neighbor not in neighbors:
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resonance[second_neighbor] = resonance.get(second_neighbor, 0) + 1
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return sorted(resonance.items(), key=lambda x: x[1], reverse=True)
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6
nexus/mnemosyne/rules.json
Normal file
6
nexus/mnemosyne/rules.json
Normal file
@@ -0,0 +1,6 @@
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[
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{
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"condition": "count(type=anomaly)>3",
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"action": "alert"
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}
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]
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@@ -45,6 +45,7 @@ from nexus.perception_adapter import (
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)
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from nexus.experience_store import ExperienceStore
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from nexus.groq_worker import GroqWorker
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from nexus.heartbeat import write_heartbeat
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from nexus.trajectory_logger import TrajectoryLogger
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logging.basicConfig(
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@@ -286,6 +287,13 @@ class NexusMind:
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self.cycle_count += 1
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# Write heartbeat — watchdog knows the mind is alive
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write_heartbeat(
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cycle=self.cycle_count,
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model=self.model,
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status="thinking",
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)
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# Periodically distill old memories
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if self.cycle_count % 50 == 0 and self.cycle_count > 0:
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await self._distill_memories()
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@@ -383,6 +391,13 @@ class NexusMind:
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salience=1.0,
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))
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# Write initial heartbeat — mind is online
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write_heartbeat(
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cycle=0,
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model=self.model,
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status="thinking",
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)
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while self.running:
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try:
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await self.think_once()
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@@ -423,6 +438,13 @@ class NexusMind:
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log.info("Nexus Mind shutting down...")
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self.running = False
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# Final heartbeat — mind is going down cleanly
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write_heartbeat(
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cycle=self.cycle_count,
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model=self.model,
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status="idle",
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)
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# Final stats
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stats = self.trajectory_logger.get_session_stats()
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log.info(f"Session stats: {json.dumps(stats, indent=2)}")
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