mirror of
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Merge pull request #94 from ruvnet/feature/mcp-server
feat: RuVector v2.0 - Edge WASM, MCP Server, Intelligence Layer & Web Workers
This commit is contained in:
rUv
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commit
ffb2ee176f
6 changed files with 840 additions and 11 deletions
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@ -156,6 +156,64 @@ gossipNode.join_swarm(relayUrl); // Eventually consistent, Byzantine-tolerant
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---
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### Web Workers: Keep Your UI Responsive
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When you're running vector searches on thousands of vectors or encrypting large messages, you don't want your app to freeze. Web Workers solve this by running heavy operations in background threads while your UI stays smooth.
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**The problem without workers:**
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```javascript
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// This blocks your UI - buttons won't click, animations freeze
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const results = await vectorDB.search(query, k); // 100ms+ blocking
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```
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**The solution with WorkerPool:**
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```javascript
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import { WorkerPool } from '@ruvector/edge/worker-pool';
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// Create a pool of background workers (auto-detects CPU cores)
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const pool = new WorkerPool(
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new URL('@ruvector/edge/worker', import.meta.url),
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new URL('@ruvector/edge/ruvector_edge.js', import.meta.url),
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{ dimensions: 128, metric: 'cosine', useHnsw: true }
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);
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await pool.init(); // Workers load WASM in parallel
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// Now searches run in background - UI stays responsive!
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const results = await pool.search(queryVector, 10);
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// Insert 10,000 vectors? Workers split the work automatically
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const ids = await pool.insertBatch(largeDataset); // Parallel insertion
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// Search multiple queries at once
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const allResults = await pool.searchBatch(queries, 10); // Parallel search
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```
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**What the Worker Pool does for you:**
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| Feature | What It Means |
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|---------|---------------|
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| **Auto-scaling** | Creates workers based on your CPU cores (2-8 typically) |
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| **Load balancing** | Distributes work evenly across workers |
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| **Batch splitting** | Large datasets are chunked and processed in parallel |
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| **Timeout handling** | Stuck operations fail gracefully after 30 seconds |
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| **Error recovery** | One failing worker doesn't crash your whole app |
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**When to use workers:**
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| Scenario | Use Workers? | Why |
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|----------|--------------|-----|
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| 100+ vectors | Maybe | Small searches are fast enough inline |
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| 1,000+ vectors | Yes | Noticeable speedup from parallelism |
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| 10,000+ vectors | Definitely | 3-4x faster with worker pool |
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| Batch inserts | Yes | Don't block UI during data loading |
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| Real-time search | Yes | Keep typing responsive during search |
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| Mobile devices | Yes | Avoid UI jank on slower processors |
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**Simple rule:** If the operation takes more than 50ms, use a worker.
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---
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### Quick Start
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```bash
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@ -187,13 +245,15 @@ const best = matcher.find_best_agent("write a function");
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1. [Why Edge-First?](#why-edge-first)
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2. [Features](#features)
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3. [Tutorial: Build Your First Swarm](#tutorial-build-your-first-swarm)
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4. [P2P Transport Options](#p2p-transport-options)
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5. [Free Infrastructure](#free-infrastructure-zero-cost-at-any-scale)
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6. [Architecture](#architecture)
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7. [API Reference](#api-reference)
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8. [Performance](#performance)
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9. [Security](#security)
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3. [Consensus Modes](#consensus-modes-trusted-vs-open)
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4. [Web Workers](#web-workers-keep-your-ui-responsive)
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5. [Tutorial: Build Your First Swarm](#tutorial-build-your-first-swarm)
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6. [P2P Transport Options](#p2p-transport-options)
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7. [Free Infrastructure](#free-infrastructure-zero-cost-at-any-scale)
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8. [Architecture](#architecture)
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9. [API Reference](#api-reference)
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10. [Performance](#performance)
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11. [Security](#security)
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---
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@ -1097,6 +1157,23 @@ comp.decompress(data)
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comp.condition() // "excellent"|"good"|"poor"|"critical"
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```
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### WorkerPool (Web Workers)
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```javascript
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import { WorkerPool } from '@ruvector/edge/worker-pool';
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const pool = new WorkerPool(workerUrl, wasmUrl, options);
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await pool.init() // Start workers
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pool.insert(vector, id, metadata) // Insert single vector
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pool.insertBatch(entries) // Parallel batch insert
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pool.search(query, k, filter) // Search k nearest
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pool.searchBatch(queries, k) // Parallel multi-query
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pool.delete(id) // Remove vector
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pool.get(id) // Retrieve by ID
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pool.len() // Count vectors
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pool.getStats() // {poolSize, busyWorkers, ...}
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pool.terminate() // Stop all workers
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```
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---
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## Performance
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@ -50,6 +50,7 @@ This library gives you everything you need to build distributed AI systems: cryp
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| **Post-Quantum** | Hybrid signatures | Future-proof |
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| **Neural Networks** | Spiking + STDP | Bio-inspired learning |
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| **Compression** | Adaptive 4-32x | Network-aware |
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| **Web Workers** | Worker pool | Parallel ops, non-blocking UI |
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### What It Costs
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@ -84,6 +85,7 @@ RuVector provides a complete edge AI platform. This package (`@ruvector/edge`) i
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│ ✓ Post-Quantum Crypto ✓ RVLite Vector DB (260KB) │
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│ ✓ Spiking Neural Networks SQL + SPARQL + Cypher queries │
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│ ✓ Adaptive Compression IndexedDB persistence │
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│ ✓ Web Worker Pool │
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│ │
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│ Best for: ✓ SONA Neural Router (238KB) │
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│ • Lightweight P2P apps Self-learning with LoRA │
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@ -156,6 +158,57 @@ gossipNode.join_swarm(relayUrl); // Eventually consistent, Byzantine-tolerant
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---
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### Web Workers: Keep the UI Responsive
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Heavy operations (vector search, encryption, neural network inference) run in Web Workers to avoid blocking the main thread. The package includes a ready-to-use worker pool:
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```javascript
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import { WorkerPool } from '@ruvector/edge/worker-pool';
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// Create worker pool (auto-detects CPU cores)
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const pool = new WorkerPool(
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new URL('@ruvector/edge/worker', import.meta.url),
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new URL('@ruvector/edge/ruvector_edge_bg.wasm', import.meta.url),
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{
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poolSize: navigator.hardwareConcurrency,
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dimensions: 384,
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useHnsw: true
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}
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);
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await pool.init();
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// Operations run in parallel across workers
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await pool.insert(embedding, 'doc-1', { title: 'Hello' });
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await pool.insertBatch([
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{ vector: emb1, id: 'doc-2' },
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{ vector: emb2, id: 'doc-3' },
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{ vector: emb3, id: 'doc-4' }
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]);
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// Search distributed across workers
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const results = await pool.search(queryEmbedding, 10);
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// Batch search (each query on different worker)
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const batchResults = await pool.searchBatch([query1, query2, query3], 10);
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// Pool statistics
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console.log(pool.getStats());
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// { poolSize: 8, busyWorkers: 2, idleWorkers: 6, pendingRequests: 0 }
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// Clean up
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pool.terminate();
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```
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**Worker Pool Features:**
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- Round-robin task distribution with load balancing
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- Automatic batch splitting across workers
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- Promise-based API with 30s timeout
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- Zero-copy transfers via transferable objects
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- Works in browsers, Deno, and Cloudflare Workers
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---
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### Quick Start
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```bash
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@ -327,6 +327,28 @@
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</div>
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</div>
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<div class="section">
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<div class="section-title">Concurrency (Web Workers)</div>
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<div class="option-grid" id="worker-options">
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<div class="option" data-value="none">
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<div class="option-title">⚡ Main Thread</div>
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<div class="option-desc">Simple, no workers</div>
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</div>
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<div class="option selected" data-value="pool">
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<div class="option-title">🔄 Worker Pool</div>
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<div class="option-desc">Auto-scaling workers</div>
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</div>
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<div class="option" data-value="dedicated">
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<div class="option-title">🎯 Dedicated</div>
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<div class="option-desc">One worker per task</div>
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</div>
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<div class="option" data-value="shared">
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<div class="option-title">🤝 Shared Worker</div>
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<div class="option-desc">Cross-tab sharing</div>
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</div>
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</div>
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</div>
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<div class="section">
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<div class="section-title">Exotic Patterns</div>
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<div class="tag-list" id="exotic-tags">
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@ -346,8 +368,8 @@
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<div class="stat-label">Agents</div>
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</div>
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<div class="stat">
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<div class="stat-value" id="msg-latency">~100ms</div>
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<div class="stat-label">Latency</div>
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<div class="stat-value" id="worker-count">4</div>
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<div class="stat-label">Workers</div>
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</div>
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<div class="stat">
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<div class="stat-value">$0</div>
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@ -415,6 +437,7 @@
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usecase: 'ai-assistants',
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modules: ['edge'],
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features: ['identity', 'encryption'],
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workers: 'pool',
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exotic: []
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};
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@ -1431,6 +1454,210 @@ class SelfHealingSwarm {
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}`,
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emergent: `// Emergent Behavior - Agent evolution
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class EmergentSwarm {`,
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},
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// Worker patterns
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workers: {
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none: `// Main Thread Execution
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// All operations run on the main thread (simpler, but may block UI)
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// Best for: Small datasets (<1000 vectors), simple operations`,
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pool: `// Worker Pool - Auto-scaling background threads
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import { WorkerPool } from '@ruvector/edge/worker-pool';
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class SwarmWorkerPool {
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constructor(options = {}) {
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this.pool = null;
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this.options = {
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dimensions: options.dimensions || 128,
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metric: options.metric || 'cosine',
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useHnsw: options.useHnsw !== false,
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poolSize: options.poolSize || navigator.hardwareConcurrency || 4
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};
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}
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async init() {
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// Create worker pool - auto-detects CPU cores
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this.pool = new WorkerPool(
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new URL('@ruvector/edge/worker', import.meta.url),
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new URL('@ruvector/edge/ruvector_edge.js', import.meta.url),
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this.options
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);
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await this.pool.init();
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console.log(\`Worker pool ready: \${this.options.poolSize} workers\`);
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}
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// Non-blocking vector insert
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async insert(vector, id, metadata) {
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return this.pool.insert(vector, id, metadata);
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}
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// Parallel batch insert - splits across workers
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async insertBatch(entries) {
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return this.pool.insertBatch(entries);
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}
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// Background search - UI stays responsive
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async search(query, k = 10) {
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return this.pool.search(query, k);
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}
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// Parallel multi-query search
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async searchBatch(queries, k = 10) {
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return this.pool.searchBatch(queries, k);
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}
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// Get pool statistics
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getStats() {
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return this.pool.getStats();
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}
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// Clean up workers
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terminate() {
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this.pool.terminate();
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}
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}
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// Usage example
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const workerPool = new SwarmWorkerPool({ dimensions: 128 });
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await workerPool.init();
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// Insert 10,000 vectors in parallel (doesn't block UI)
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const vectors = Array(10000).fill(null).map((_, i) => ({
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vector: new Float32Array(128).fill(Math.random()),
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id: \`doc-\${i}\`,
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metadata: { index: i }
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}));
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await workerPool.insertBatch(vectors);
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// Search runs in background
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const results = await workerPool.search(queryVector, 10);`,
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dedicated: `// Dedicated Worker - One worker per task type
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class DedicatedWorkerManager {
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constructor() {
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this.workers = new Map();
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}
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// Create dedicated worker for a task type
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createWorker(taskType, workerScript) {
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const worker = new Worker(workerScript, { type: 'module' });
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this.workers.set(taskType, {
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worker,
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busy: false,
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pending: []
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});
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worker.onmessage = (e) => this.handleResponse(taskType, e.data);
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return worker;
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}
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// Send task to dedicated worker
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async execute(taskType, data) {
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const workerInfo = this.workers.get(taskType);
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if (!workerInfo) throw new Error(\`No worker for: \${taskType}\`);
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return new Promise((resolve, reject) => {
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workerInfo.pending.push({ resolve, reject });
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workerInfo.worker.postMessage(data);
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});
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}
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handleResponse(taskType, data) {
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const workerInfo = this.workers.get(taskType);
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const pending = workerInfo.pending.shift();
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if (data.error) pending.reject(new Error(data.error));
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else pending.resolve(data.result);
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}
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terminateAll() {
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for (const [_, info] of this.workers) {
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info.worker.terminate();
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}
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this.workers.clear();
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}
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}
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// Example: Separate workers for different operations
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const manager = new DedicatedWorkerManager();
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manager.createWorker('search', './search-worker.js');
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manager.createWorker('embed', './embed-worker.js');
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manager.createWorker('encrypt', './crypto-worker.js');`,
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shared: `// Shared Worker - Cross-tab coordination
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class SharedSwarmWorker {
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constructor(workerUrl) {
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this.worker = new SharedWorker(workerUrl, { type: 'module' });
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this.port = this.worker.port;
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this.requestId = 0;
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this.pending = new Map();
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this.port.onmessage = (e) => this.handleMessage(e.data);
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this.port.start();
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}
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handleMessage(data) {
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const pending = this.pending.get(data.requestId);
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if (pending) {
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this.pending.delete(data.requestId);
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if (data.error) pending.reject(new Error(data.error));
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else pending.resolve(data.result);
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}
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}
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async execute(type, data) {
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return new Promise((resolve, reject) => {
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const requestId = this.requestId++;
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this.pending.set(requestId, { resolve, reject });
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this.port.postMessage({ type, requestId, data });
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});
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}
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}
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// Benefits of Shared Workers:
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// 1. Single WASM instance shared across all tabs
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// 2. Consistent vector index across browser tabs
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// 3. Reduced memory usage (one index, not N copies)
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// 4. Cross-tab agent coordination
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// Example shared-worker.js:
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/*
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let vectorIndex = null;
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const connections = [];
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self.onconnect = (e) => {
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const port = e.ports[0];
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connections.push(port);
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port.onmessage = async (event) => {
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const { type, requestId, data } = event.data;
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if (type === 'init' && !vectorIndex) {
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const { init, WasmHnswIndex } = await import('./ruvector_edge.js');
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await init();
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vectorIndex = new WasmHnswIndex(128, 16, 200);
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}
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// All tabs share the same index
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if (type === 'insert') {
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vectorIndex.insert(data.id, new Float32Array(data.vector));
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}
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if (type === 'search') {
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const results = vectorIndex.search(new Float32Array(data.query), data.k);
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port.postMessage({ requestId, result: results });
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}
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};
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port.start();
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};
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*/`
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}
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};
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// Replace the last line of exotic.emergent to close the object properly
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templates.exotic.emergent = `// Emergent Behavior - Agent evolution
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class EmergentSwarm {
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constructor(populationSize = 20) {
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this.population = [];
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@ -1500,7 +1727,7 @@ class EmergentSwarm {
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let code = `// ${packageName} - Generated Swarm Configuration
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// Topology: ${state.topology} | Transport: ${state.transport} | Use Case: ${state.usecase}
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// Modules: ${state.modules.join(', ')} | Features: ${state.features.join(', ')}${state.exotic.length ? '\n// Exotic: ' + state.exotic.join(', ') : ''}
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// Modules: ${state.modules.join(', ')} | Workers: ${state.workers} | Features: ${state.features.join(', ')}${state.exotic.length ? '\n// Exotic: ' + state.exotic.join(', ') : ''}
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`;
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||||
// Generate imports based on selected modules
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||||
|
|
@ -1570,6 +1797,17 @@ ${templates.transports[state.transport]}
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|
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${templates.usecases[state.usecase]}`;
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|
||||
// Add worker pattern if not 'none'
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if (state.workers !== 'none') {
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code += `
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||||
|
||||
// ═══════════════════════════════════════════════════════════════
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// CONCURRENCY: ${state.workers.toUpperCase()} WORKERS
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||||
// ═══════════════════════════════════════════════════════════════
|
||||
|
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${templates.workers[state.workers]}`;
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||||
}
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||||
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||||
// Add module-specific sections
|
||||
if (state.modules.includes('graph')) {
|
||||
code += `
|
||||
|
|
@ -1894,6 +2132,21 @@ main().catch(console.error);`;
|
|||
});
|
||||
});
|
||||
|
||||
// Worker options
|
||||
document.querySelectorAll('#worker-options .option').forEach(el => {
|
||||
el.addEventListener('click', () => {
|
||||
document.querySelectorAll('#worker-options .option').forEach(e => e.classList.remove('selected'));
|
||||
el.classList.add('selected');
|
||||
state.workers = el.dataset.value;
|
||||
|
||||
// Update worker count display
|
||||
const workerCounts = { none: '0', pool: '4', dedicated: '3', shared: '1' };
|
||||
document.getElementById('worker-count').textContent = workerCounts[state.workers];
|
||||
|
||||
updateCode();
|
||||
});
|
||||
});
|
||||
|
||||
// Feature tags
|
||||
document.querySelectorAll('#feature-tags .tag').forEach(el => {
|
||||
el.addEventListener('click', () => {
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
{
|
||||
"name": "@ruvector/edge",
|
||||
"version": "0.1.8",
|
||||
"version": "0.1.9",
|
||||
"type": "module",
|
||||
"description": "Free edge-based AI swarms in the browser - P2P, crypto, vector search, neural networks. Install @ruvector/edge-full for graph DB, SQL, ONNX embeddings.",
|
||||
"main": "ruvector_edge.js",
|
||||
|
|
@ -40,6 +40,8 @@
|
|||
"ruvector_edge.js",
|
||||
"ruvector_edge.d.ts",
|
||||
"ruvector_edge_bg.wasm.d.ts",
|
||||
"worker.js",
|
||||
"worker-pool.js",
|
||||
"generator.html",
|
||||
"LICENSE"
|
||||
],
|
||||
|
|
@ -47,6 +49,12 @@
|
|||
".": {
|
||||
"import": "./ruvector_edge.js",
|
||||
"types": "./ruvector_edge.d.ts"
|
||||
},
|
||||
"./worker": {
|
||||
"import": "./worker.js"
|
||||
},
|
||||
"./worker-pool": {
|
||||
"import": "./worker-pool.js"
|
||||
}
|
||||
},
|
||||
"sideEffects": [
|
||||
|
|
|
|||
254
examples/edge/pkg/worker-pool.js
Normal file
254
examples/edge/pkg/worker-pool.js
Normal file
|
|
@ -0,0 +1,254 @@
|
|||
/**
|
||||
* Web Worker Pool Manager
|
||||
*
|
||||
* Manages a pool of workers for parallel vector operations.
|
||||
* Supports:
|
||||
* - Round-robin task distribution
|
||||
* - Load balancing
|
||||
* - Automatic worker initialization
|
||||
* - Promise-based API
|
||||
*/
|
||||
|
||||
export class WorkerPool {
|
||||
constructor(workerUrl, wasmUrl, options = {}) {
|
||||
this.workerUrl = workerUrl;
|
||||
this.wasmUrl = wasmUrl;
|
||||
this.poolSize = options.poolSize || navigator.hardwareConcurrency || 4;
|
||||
this.workers = [];
|
||||
this.nextWorker = 0;
|
||||
this.pendingRequests = new Map();
|
||||
this.requestId = 0;
|
||||
this.initialized = false;
|
||||
this.options = options;
|
||||
}
|
||||
|
||||
/**
|
||||
* Initialize the worker pool
|
||||
*/
|
||||
async init() {
|
||||
if (this.initialized) return;
|
||||
|
||||
console.log(`Initializing worker pool with ${this.poolSize} workers...`);
|
||||
|
||||
const initPromises = [];
|
||||
|
||||
for (let i = 0; i < this.poolSize; i++) {
|
||||
const worker = new Worker(this.workerUrl, { type: 'module' });
|
||||
|
||||
worker.onmessage = (e) => this.handleMessage(i, e);
|
||||
worker.onerror = (error) => this.handleError(i, error);
|
||||
|
||||
this.workers.push({
|
||||
worker,
|
||||
busy: false,
|
||||
id: i
|
||||
});
|
||||
|
||||
// Initialize worker with WASM
|
||||
const initPromise = this.sendToWorker(i, 'init', {
|
||||
wasmUrl: this.wasmUrl,
|
||||
dimensions: this.options.dimensions,
|
||||
metric: this.options.metric,
|
||||
useHnsw: this.options.useHnsw
|
||||
});
|
||||
|
||||
initPromises.push(initPromise);
|
||||
}
|
||||
|
||||
await Promise.all(initPromises);
|
||||
this.initialized = true;
|
||||
|
||||
console.log(`Worker pool initialized successfully`);
|
||||
}
|
||||
|
||||
/**
|
||||
* Handle message from worker
|
||||
*/
|
||||
handleMessage(workerId, event) {
|
||||
const { type, requestId, data, error } = event.data;
|
||||
|
||||
if (type === 'error') {
|
||||
const request = this.pendingRequests.get(requestId);
|
||||
if (request) {
|
||||
request.reject(new Error(error.message));
|
||||
this.pendingRequests.delete(requestId);
|
||||
}
|
||||
return;
|
||||
}
|
||||
|
||||
const request = this.pendingRequests.get(requestId);
|
||||
if (request) {
|
||||
this.workers[workerId].busy = false;
|
||||
request.resolve(data);
|
||||
this.pendingRequests.delete(requestId);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Handle worker error
|
||||
*/
|
||||
handleError(workerId, error) {
|
||||
console.error(`Worker ${workerId} error:`, error);
|
||||
|
||||
// Reject all pending requests for this worker
|
||||
for (const [requestId, request] of this.pendingRequests) {
|
||||
if (request.workerId === workerId) {
|
||||
request.reject(error);
|
||||
this.pendingRequests.delete(requestId);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get next available worker (round-robin)
|
||||
*/
|
||||
getNextWorker() {
|
||||
// Try to find an idle worker
|
||||
for (let i = 0; i < this.workers.length; i++) {
|
||||
const idx = (this.nextWorker + i) % this.workers.length;
|
||||
if (!this.workers[idx].busy) {
|
||||
this.nextWorker = (idx + 1) % this.workers.length;
|
||||
return idx;
|
||||
}
|
||||
}
|
||||
|
||||
// All busy, use round-robin
|
||||
const idx = this.nextWorker;
|
||||
this.nextWorker = (this.nextWorker + 1) % this.workers.length;
|
||||
return idx;
|
||||
}
|
||||
|
||||
/**
|
||||
* Send message to specific worker
|
||||
*/
|
||||
sendToWorker(workerId, type, data) {
|
||||
return new Promise((resolve, reject) => {
|
||||
const requestId = this.requestId++;
|
||||
|
||||
this.pendingRequests.set(requestId, {
|
||||
resolve,
|
||||
reject,
|
||||
workerId,
|
||||
timestamp: Date.now()
|
||||
});
|
||||
|
||||
this.workers[workerId].busy = true;
|
||||
this.workers[workerId].worker.postMessage({
|
||||
type,
|
||||
data: { ...data, requestId }
|
||||
});
|
||||
|
||||
// Timeout after 30 seconds
|
||||
setTimeout(() => {
|
||||
if (this.pendingRequests.has(requestId)) {
|
||||
this.pendingRequests.delete(requestId);
|
||||
reject(new Error('Request timeout'));
|
||||
}
|
||||
}, 30000);
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Execute operation on next available worker
|
||||
*/
|
||||
async execute(type, data) {
|
||||
if (!this.initialized) {
|
||||
await this.init();
|
||||
}
|
||||
|
||||
const workerId = this.getNextWorker();
|
||||
return this.sendToWorker(workerId, type, data);
|
||||
}
|
||||
|
||||
/**
|
||||
* Insert vector
|
||||
*/
|
||||
async insert(vector, id = null, metadata = null) {
|
||||
return this.execute('insert', { vector, id, metadata });
|
||||
}
|
||||
|
||||
/**
|
||||
* Insert batch of vectors
|
||||
*/
|
||||
async insertBatch(entries) {
|
||||
// Distribute batch across workers
|
||||
const chunkSize = Math.ceil(entries.length / this.poolSize);
|
||||
const chunks = [];
|
||||
|
||||
for (let i = 0; i < entries.length; i += chunkSize) {
|
||||
chunks.push(entries.slice(i, i + chunkSize));
|
||||
}
|
||||
|
||||
const promises = chunks.map((chunk, i) =>
|
||||
this.sendToWorker(i % this.poolSize, 'insertBatch', { entries: chunk })
|
||||
);
|
||||
|
||||
const results = await Promise.all(promises);
|
||||
return results.flat();
|
||||
}
|
||||
|
||||
/**
|
||||
* Search for similar vectors
|
||||
*/
|
||||
async search(query, k = 10, filter = null) {
|
||||
return this.execute('search', { query, k, filter });
|
||||
}
|
||||
|
||||
/**
|
||||
* Parallel search across multiple queries
|
||||
*/
|
||||
async searchBatch(queries, k = 10, filter = null) {
|
||||
const promises = queries.map((query, i) =>
|
||||
this.sendToWorker(i % this.poolSize, 'search', { query, k, filter })
|
||||
);
|
||||
|
||||
return Promise.all(promises);
|
||||
}
|
||||
|
||||
/**
|
||||
* Delete vector
|
||||
*/
|
||||
async delete(id) {
|
||||
return this.execute('delete', { id });
|
||||
}
|
||||
|
||||
/**
|
||||
* Get vector by ID
|
||||
*/
|
||||
async get(id) {
|
||||
return this.execute('get', { id });
|
||||
}
|
||||
|
||||
/**
|
||||
* Get database length (from first worker)
|
||||
*/
|
||||
async len() {
|
||||
return this.sendToWorker(0, 'len', {});
|
||||
}
|
||||
|
||||
/**
|
||||
* Terminate all workers
|
||||
*/
|
||||
terminate() {
|
||||
for (const { worker } of this.workers) {
|
||||
worker.terminate();
|
||||
}
|
||||
this.workers = [];
|
||||
this.initialized = false;
|
||||
console.log('Worker pool terminated');
|
||||
}
|
||||
|
||||
/**
|
||||
* Get pool statistics
|
||||
*/
|
||||
getStats() {
|
||||
return {
|
||||
poolSize: this.poolSize,
|
||||
busyWorkers: this.workers.filter(w => w.busy).length,
|
||||
idleWorkers: this.workers.filter(w => !w.busy).length,
|
||||
pendingRequests: this.pendingRequests.size
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
export default WorkerPool;
|
||||
184
examples/edge/pkg/worker.js
Normal file
184
examples/edge/pkg/worker.js
Normal file
|
|
@ -0,0 +1,184 @@
|
|||
/**
|
||||
* Web Worker for parallel vector search operations
|
||||
*
|
||||
* This worker handles:
|
||||
* - Vector search operations in parallel
|
||||
* - Batch insert operations
|
||||
* - Zero-copy transfers via transferable objects
|
||||
*/
|
||||
|
||||
// Import the WASM module
|
||||
let wasmModule = null;
|
||||
let vectorDB = null;
|
||||
|
||||
/**
|
||||
* Initialize the worker with WASM module
|
||||
*/
|
||||
self.onmessage = async function(e) {
|
||||
const { type, data } = e.data;
|
||||
|
||||
try {
|
||||
switch (type) {
|
||||
case 'init':
|
||||
await initWorker(data);
|
||||
self.postMessage({ type: 'init', success: true });
|
||||
break;
|
||||
|
||||
case 'insert':
|
||||
await handleInsert(data);
|
||||
break;
|
||||
|
||||
case 'insertBatch':
|
||||
await handleInsertBatch(data);
|
||||
break;
|
||||
|
||||
case 'search':
|
||||
await handleSearch(data);
|
||||
break;
|
||||
|
||||
case 'delete':
|
||||
await handleDelete(data);
|
||||
break;
|
||||
|
||||
case 'get':
|
||||
await handleGet(data);
|
||||
break;
|
||||
|
||||
case 'len':
|
||||
const length = vectorDB.len();
|
||||
self.postMessage({ type: 'len', data: length });
|
||||
break;
|
||||
|
||||
default:
|
||||
throw new Error(`Unknown message type: ${type}`);
|
||||
}
|
||||
} catch (error) {
|
||||
self.postMessage({
|
||||
type: 'error',
|
||||
error: {
|
||||
message: error.message,
|
||||
stack: error.stack
|
||||
}
|
||||
});
|
||||
}
|
||||
};
|
||||
|
||||
/**
|
||||
* Initialize WASM module and VectorDB
|
||||
*/
|
||||
async function initWorker(config) {
|
||||
const { wasmUrl, dimensions, metric, useHnsw } = config;
|
||||
|
||||
// Import WASM module
|
||||
wasmModule = await import(wasmUrl);
|
||||
|
||||
// Initialize WASM
|
||||
await wasmModule.default();
|
||||
|
||||
// Create VectorDB instance
|
||||
vectorDB = new wasmModule.VectorDB(dimensions, metric, useHnsw);
|
||||
|
||||
console.log(`Worker initialized with dimensions=${dimensions}, metric=${metric}, SIMD=${wasmModule.detectSIMD()}`);
|
||||
}
|
||||
|
||||
/**
|
||||
* Handle single vector insert
|
||||
*/
|
||||
async function handleInsert(data) {
|
||||
const { vector, id, metadata, requestId } = data;
|
||||
|
||||
// Convert array to Float32Array if needed
|
||||
const vectorArray = new Float32Array(vector);
|
||||
|
||||
const resultId = vectorDB.insert(vectorArray, id, metadata);
|
||||
|
||||
self.postMessage({
|
||||
type: 'insert',
|
||||
requestId,
|
||||
data: resultId
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Handle batch insert
|
||||
*/
|
||||
async function handleInsertBatch(data) {
|
||||
const { entries, requestId } = data;
|
||||
|
||||
// Convert vectors to Float32Array
|
||||
const processedEntries = entries.map(entry => ({
|
||||
vector: new Float32Array(entry.vector),
|
||||
id: entry.id,
|
||||
metadata: entry.metadata
|
||||
}));
|
||||
|
||||
const ids = vectorDB.insertBatch(processedEntries);
|
||||
|
||||
self.postMessage({
|
||||
type: 'insertBatch',
|
||||
requestId,
|
||||
data: ids
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Handle vector search
|
||||
*/
|
||||
async function handleSearch(data) {
|
||||
const { query, k, filter, requestId } = data;
|
||||
|
||||
// Convert query to Float32Array
|
||||
const queryArray = new Float32Array(query);
|
||||
|
||||
const results = vectorDB.search(queryArray, k, filter);
|
||||
|
||||
// Convert results to plain objects
|
||||
const plainResults = results.map(result => ({
|
||||
id: result.id,
|
||||
score: result.score,
|
||||
vector: result.vector ? Array.from(result.vector) : null,
|
||||
metadata: result.metadata
|
||||
}));
|
||||
|
||||
self.postMessage({
|
||||
type: 'search',
|
||||
requestId,
|
||||
data: plainResults
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Handle delete operation
|
||||
*/
|
||||
async function handleDelete(data) {
|
||||
const { id, requestId } = data;
|
||||
|
||||
const deleted = vectorDB.delete(id);
|
||||
|
||||
self.postMessage({
|
||||
type: 'delete',
|
||||
requestId,
|
||||
data: deleted
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Handle get operation
|
||||
*/
|
||||
async function handleGet(data) {
|
||||
const { id, requestId } = data;
|
||||
|
||||
const entry = vectorDB.get(id);
|
||||
|
||||
const plainEntry = entry ? {
|
||||
id: entry.id,
|
||||
vector: Array.from(entry.vector),
|
||||
metadata: entry.metadata
|
||||
} : null;
|
||||
|
||||
self.postMessage({
|
||||
type: 'get',
|
||||
requestId,
|
||||
data: plainEntry
|
||||
});
|
||||
}
|
||||
Loading…
Add table
Add a link
Reference in a new issue