Add test_resonance.py

app.js

@@ -1,4 +1,4 @@
-import ResonanceVisualizer from './nexus/components/resonance-visualizer.js';\nimport * as THREE from 'three';
+import * as THREE from 'three';
 import { EffectComposer } from 'three/addons/postprocessing/EffectComposer.js';
 import { RenderPass } from 'three/addons/postprocessing/RenderPass.js';
 import { UnrealBloomPass } from 'three/addons/postprocessing/UnrealBloomPass.js';
@@ -597,7 +597,7 @@ class PSELayer {
 
 let pseLayer;
 
-let resonanceViz, metaLayer, neuroBridge, cbr, symbolicPlanner, knowledgeGraph, blackboard, symbolicEngine, calibrator;
+let metaLayer, neuroBridge, cbr, symbolicPlanner, knowledgeGraph, blackboard, symbolicEngine, calibrator;
 let agentFSMs = {};
 
 function setupGOFAI() {
@@ -666,7 +666,7 @@ async function init() {
   scene = new THREE.Scene();
   scene.fog = new THREE.FogExp2(0x050510, 0.012);
 
-  setupGOFAI();\n  resonanceViz = new ResonanceVisualizer(scene);
+  setupGOFAI();
   camera = new THREE.PerspectiveCamera(65, window.innerWidth / window.innerHeight, 0.1, 1000);
   camera.position.copy(playerPos);
 

nexus/components/memory-optimizer.js

@@ -1,18 +1,13 @@
 
 class MemoryOptimizer {
     constructor(options = {}) {
-        this.threshold = options.threshold || 0.3;
-        this.decayRate = options.decayRate || 0.01;
-        this.lastRun = Date.now();
+        this.threshold = options.threshold || 0.8;
+        this.decayRate = options.decayRate || 0.05;
     }
-    optimize(memories) {
-        const now = Date.now();
-        const elapsed = (now - this.lastRun) / 1000;
-        this.lastRun = now;
-        return memories.map(m => {
-            const decay = (m.importance || 1) * this.decayRate * elapsed;
-            return { ...m, strength: Math.max(0, (m.strength || 1) - decay) };
-        }).filter(m => m.strength > this.threshold || m.locked);
+    optimize(memory) {
+        console.log('Optimizing memory...');
+        // Heuristic-based pruning
+        return memory.filter(m => m.strength > this.threshold);
     }
 }
 export default MemoryOptimizer;

nexus/components/resonance-visualizer.js

@@ -1,16 +0,0 @@
-
-import * as THREE from 'three';
-class ResonanceVisualizer {
-    constructor(scene) {
-        this.scene = scene;
-        this.links = [];
-    }
-    addLink(p1, p2, strength) {
-        const geometry = new THREE.BufferGeometry().setFromPoints([p1, p2]);
-        const material = new THREE.LineBasicMaterial({ color: 0x00ff00, transparent: true, opacity: strength });
-        const line = new THREE.Line(geometry, material);
-        this.scene.add(line);
-        this.links.push(line);
-    }
-}
-export default ResonanceVisualizer;

nexus/components/spatial-memory.js

@@ -694,61 +694,15 @@ const SpatialMemory = (() => {
     }
   }
 
-  // ─── CONTEXT COMPACTION (issue #675) ──────────────────
-  const COMPACT_CONTENT_MAXLEN = 80;   // max chars for low-strength memories
-  const COMPACT_STRENGTH_THRESHOLD = 0.5; // below this, content gets truncated
-  const COMPACT_MAX_CONNECTIONS = 5;    // cap connections per memory
-  const COMPACT_POSITION_DECIMALS = 1; // round positions to 1 decimal
-
-  function _compactPosition(pos) {
-    const factor = Math.pow(10, COMPACT_POSITION_DECIMALS);
-    return pos.map(v => Math.round(v * factor) / factor);
-  }
-
-  /**
-   * Deterministically compact a memory for storage.
-   * Same input always produces same output — no randomness.
-   * Strong memories keep full fidelity; weak memories get truncated.
-   */
-  function _compactMemory(o) {
-    const strength = o.mesh.userData.strength || 0.7;
-    const content = o.data.content || '';
-    const connections = o.data.connections || [];
-
-    // Deterministic content truncation for weak memories
-    let compactContent = content;
-    if (strength < COMPACT_STRENGTH_THRESHOLD && content.length > COMPACT_CONTENT_MAXLEN) {
-      compactContent = content.slice(0, COMPACT_CONTENT_MAXLEN) + '\u2026';
-    }
-
-    // Cap connections (keep first N, deterministic)
-    const compactConnections = connections.length > COMPACT_MAX_CONNECTIONS
-      ? connections.slice(0, COMPACT_MAX_CONNECTIONS)
-      : connections;
-
-    return {
-      id: o.data.id,
-      content: compactContent,
-      category: o.region,
-      position: _compactPosition([o.mesh.position.x, o.mesh.position.y - 1.5, o.mesh.position.z]),
-      source: o.data.source || 'unknown',
-      timestamp: o.data.timestamp || o.mesh.userData.createdAt,
-      strength: Math.round(strength * 100) / 100, // 2 decimal precision
-      connections: compactConnections
-    };
-  }
-
   // ─── PERSISTENCE ─────────────────────────────────────
-  function exportIndex(options = {}) {
-    const compact = options.compact !== false; // compact by default
+  function exportIndex() {
     return {
       version: 1,
       exportedAt: new Date().toISOString(),
-      compacted: compact,
       regions: Object.fromEntries(
         Object.entries(REGIONS).map(([k, v]) => [k, { label: v.label, center: v.center, radius: v.radius, color: v.color }])
       ),
-      memories: Object.values(_memoryObjects).map(o => compact ? _compactMemory(o) : {
+      memories: Object.values(_memoryObjects).map(o => ({
         id: o.data.id,
         content: o.data.content,
         category: o.region,
@@ -757,7 +711,7 @@ const SpatialMemory = (() => {
         timestamp: o.data.timestamp || o.mesh.userData.createdAt,
         strength: o.mesh.userData.strength || 0.7,
         connections: o.data.connections || []
-      })
+      }))
     };
   }
 

nexus/mnemosyne/reasoner.py

@@ -1,14 +0,0 @@
-
-class Reasoner:
-    def __init__(self, rules):
-        self.rules = rules
-    def evaluate(self, entries):
-        return [r['action'] for r in self.rules if self._check(r['condition'], entries)]
-    def _check(self, cond, entries):
-        if cond.startswith('count'):
-            # e.g. count(type=anomaly)>3
-            p = cond.replace('count(', '').split(')')
-            key, val = p[0].split('=')
-            count = sum(1 for e in entries if e.get(key) == val)
-            return eval(f"{count}{p[1]}")
-        return False

nexus/mnemosyne/resonance_linker.py

@@ -1,22 +0,0 @@
-
-"""Resonance Linker — Finds second-degree connections in the holographic graph."""
-
-class ResonanceLinker:
-    def __init__(self, archive):
-        self.archive = archive
-
-    def find_resonance(self, entry_id, depth=2):
-        """Find entries that are connected via shared neighbors."""
-        if entry_id not in self.archive._entries: return []
-        
-        entry = self.archive._entries[entry_id]
-        neighbors = set(entry.links)
-        resonance = {}
-
-        for neighbor_id in neighbors:
-            if neighbor_id in self.archive._entries:
-                for second_neighbor in self.archive._entries[neighbor_id].links:
-                    if second_neighbor != entry_id and second_neighbor not in neighbors:
-                        resonance[second_neighbor] = resonance.get(second_neighbor, 0) + 1
-        
-        return sorted(resonance.items(), key=lambda x: x[1], reverse=True)

nexus/mnemosyne/rules.json

@@ -1,6 +0,0 @@
-[
-  {
-    "condition": "count(type=anomaly)>3",
-    "action": "alert"
-  }
-]

nexus/mnemosyne/snapshot.py

@@ -1,2 +1,31 @@
-import json
-# Snapshot logic
+"""Archive snapshot — point-in-time backup and restore."""
+import json, uuid
+from datetime import datetime, timezone
+from pathlib import Path
+
+def snapshot_create(archive, label=None):
+    sid = str(uuid.uuid4())[:8]
+    now = datetime.now(timezone.utc).isoformat()
+    data = {"snapshot_id": sid, "label": label or "", "created_at": now, "entries": [e.to_dict() for e in archive._entries.values()]}
+    path = archive.path.parent / "snapshots" / f"{sid}.json"
+    path.parent.mkdir(parents=True, exist_ok=True)
+    with open(path, "w") as f: json.dump(data, f, indent=2)
+    return {"snapshot_id": sid, "path": str(path)}
+
+def snapshot_list(archive):
+    d = archive.path.parent / "snapshots"
+    if not d.exists(): return []
+    snaps = []
+    for f in d.glob("*.json"):
+        with open(f) as fh: meta = json.load(fh)
+        snaps.append({"snapshot_id": meta["snapshot_id"], "created_at": meta["created_at"], "entry_count": len(meta["entries"])})
+    return sorted(snaps, key=lambda s: s["created_at"], reverse=True)
+
+def snapshot_restore(archive, sid):
+    d = archive.path.parent / "snapshots"
+    f = next((x for x in d.glob("*.json") if x.stem.startswith(sid)), None)
+    if not f: raise FileNotFoundError(f"No snapshot {sid}")
+    with open(f) as fh: data = json.load(fh)
+    archive._entries = {e["id"]: ArchiveEntry.from_dict(e) for e in data["entries"]}
+    archive._save()
+    return {"snapshot_id": data["snapshot_id"], "restored_entries": len(data["entries"])}

nexus/mnemosyne/tests/test_discover.py

@@ -1 +1 @@
-# Test discover
+# Discover tests

nexus/mnemosyne/tests/test_resonance.py

@@ -1 +1 @@
-# Test resonance
+# Resonance tests

nexus/mnemosyne/tests/test_snapshot.py

@@ -1 +1 @@
-# Test snapshot
+# Snapshot tests