chore: recovery checkpoint - v3.0 API successfully recovered

CRITICAL CHECKPOINT - DO NOT PUSH TO GITHUB

Recovery Status:
- Successfully recovered brainy.ts from compiled JavaScript
- All core v3.0 API methods functional (add, get, update, delete, relate, find, etc.)
- Neural subsystem intact (562KB embedded patterns, NLP working)
- Augmentation pipeline operational (20+ augmentations)
- HNSW clustering system complete
- Triple Intelligence compiled (needs constructor fix)
- Test suite validates functionality

Changes preserved:
- 898 files with changes from last 3 days
- 144,475 insertions
- All augmentation improvements
- All test coverage enhancements
- Complete v3.0 feature set

This is a LOCAL checkpoint only - contains recovered work after corruption incident.
Created backup in .backups/brainy-full-20250910-151314.tar.gz

Branch: recovery-checkpoint-20250910-151433
Date: Wed Sep 10 03:18:04 PM PDT 2025

.recovery-workspace/dist-backup-20250910-141917/embeddings/worker-embedding.js

@@ -0,0 +1,73 @@
+/**
+ * Worker process for embeddings - Workaround for transformers.js memory leak
+ *
+ * This worker can be killed and restarted to release memory completely.
+ * Based on 2024 research: dispose() doesn't fully free memory in transformers.js
+ */
+import { TransformerEmbedding } from '../utils/embedding.js';
+import { parentPort } from 'worker_threads';
+import { getModelPrecision } from '../config/modelPrecisionManager.js';
+let model = null;
+let requestCount = 0;
+const MAX_REQUESTS = 100; // Restart worker after 100 requests to prevent memory leak
+async function initModel() {
+    if (!model) {
+        model = new TransformerEmbedding({
+            verbose: false,
+            precision: getModelPrecision(), // Use centrally managed precision
+            localFilesOnly: process.env.BRAINY_ALLOW_REMOTE_MODELS !== 'true'
+        });
+        await model.init();
+        console.log('🔧 Worker: Model initialized');
+    }
+}
+if (parentPort) {
+    parentPort.on('message', async (message) => {
+        try {
+            const { id, type, data } = message;
+            switch (type) {
+                case 'embed':
+                    await initModel();
+                    const embeddings = await model.embed(data);
+                    parentPort.postMessage({ id, success: true, result: embeddings });
+                    requestCount++;
+                    // Proactively restart worker to prevent memory leak
+                    if (requestCount >= MAX_REQUESTS) {
+                        console.log(`🔄 Worker: Restarting after ${requestCount} requests (memory leak prevention)`);
+                        process.exit(0); // Parent will restart us
+                    }
+                    break;
+                case 'dispose':
+                    // SingletonModelManager persists - just acknowledge
+                    console.log('ℹ️ Worker: Singleton model persists');
+                    parentPort.postMessage({ id, success: true });
+                    break;
+                case 'restart':
+                    // Force restart to clear memory
+                    console.log('🔄 Worker: Force restart requested');
+                    process.exit(0);
+                    break;
+                default:
+                    parentPort.postMessage({
+                        id,
+                        success: false,
+                        error: `Unknown message type: ${type}`
+                    });
+            }
+        }
+        catch (error) {
+            parentPort.postMessage({
+                id: message.id,
+                success: false,
+                error: error instanceof Error ? error.message : String(error)
+            });
+        }
+    });
+    console.log('🚀 Embedding worker started');
+    parentPort.postMessage({ type: 'ready' });
+}
+else {
+    console.error('❌ Worker: parentPort is null, cannot communicate with main thread');
+    process.exit(1);
+}
+//# sourceMappingURL=worker-embedding.js.map