Merge commit 'd803bfe2b1fe7f5e219e50ac20d6801a0a58ac75' as 'vendor/ruvector'

2026-02-28 14:39:40 -05:00
parent 7885bf6278 d803bfe2b1
commit cd5943df23
7854 changed files with 3522914 additions and 0 deletions
--- a/vendor/ruvector/crates/ruvector-node/examples/advanced.mjs
+++ b/vendor/ruvector/crates/ruvector-node/examples/advanced.mjs
@@ -0,0 +1,145 @@
+#!/usr/bin/env node
+
+/**
+ * Advanced example demonstrating HNSW indexing and batch operations
+ */
+
+import { VectorDB } from '../index.js';
+
+// Generate random vector
+function randomVector(dim) {
+  return new Float32Array(dim).fill(0).map(() => Math.random());
+}
+
+async function main() {
+  console.log('🚀 Ruvector Advanced Example\n');
+
+  // Create database with HNSW indexing
+  const db = new VectorDB({
+    dimensions: 128,
+    distanceMetric: 'Cosine',
+    storagePath: './advanced-example.db',
+    hnswConfig: {
+      m: 32, // Number of connections per node
+      efConstruction: 200, // Construction quality
+      efSearch: 100, // Search quality
+      maxElements: 100000,
+    },
+    quantization: {
+      type: 'scalar', // 4x compression
+    },
+  });
+
+  console.log('✅ Created database with HNSW indexing');
+
+  // Batch insert
+  console.log('\n📝 Inserting 10,000 vectors in batches...');
+
+  const batchSize = 1000;
+  const totalVectors = 10000;
+  const startTime = Date.now();
+
+  for (let i = 0; i < totalVectors / batchSize; i++) {
+    const batch = Array.from({ length: batchSize }, (_, j) => ({
+      vector: randomVector(128),
+      metadata: {
+        batch: i,
+        index: i * batchSize + j,
+        category: ['A', 'B', 'C'][j % 3],
+      },
+    }));
+
+    await db.insertBatch(batch);
+
+    const progress = ((i + 1) / (totalVectors / batchSize)) * 100;
+    process.stdout.write(`\r  Progress: ${progress.toFixed(0)}%`);
+  }
+
+  const insertTime = Date.now() - startTime;
+  console.log(`\n  Inserted ${totalVectors} vectors in ${insertTime}ms`);
+  console.log(`  Throughput: ${((totalVectors / insertTime) * 1000).toFixed(0)} vectors/sec`);
+
+  // Verify database size
+  const count = await db.len();
+  console.log(`\n📊 Database contains ${count} vectors`);
+
+  // Benchmark search performance
+  console.log('\n🔍 Benchmarking search performance...');
+
+  const numQueries = 100;
+  const searchStart = Date.now();
+
+  for (let i = 0; i < numQueries; i++) {
+    const results = await db.search({
+      vector: randomVector(128),
+      k: 10,
+    });
+
+    if (i === 0) {
+      console.log(`\n  First query results:`);
+      results.slice(0, 3).forEach((r, idx) => {
+        console.log(`    ${idx + 1}. Score: ${r.score.toFixed(6)}, Category: ${r.metadata?.category}`);
+      });
+    }
+  }
+
+  const searchTime = Date.now() - searchStart;
+  const avgLatency = searchTime / numQueries;
+  const qps = (numQueries / searchTime) * 1000;
+
+  console.log(`\n  Completed ${numQueries} queries in ${searchTime}ms`);
+  console.log(`  Average latency: ${avgLatency.toFixed(2)}ms`);
+  console.log(`  QPS: ${qps.toFixed(0)} queries/sec`);
+
+  // Search with metadata filter
+  console.log('\n🎯 Searching with metadata filter...');
+
+  const filteredResults = await db.search({
+    vector: randomVector(128),
+    k: 20,
+    filter: { category: 'A' },
+  });
+
+  console.log(`  Found ${filteredResults.length} results in category 'A'`);
+  filteredResults.slice(0, 3).forEach((r, i) => {
+    console.log(`    ${i + 1}. Score: ${r.score.toFixed(6)}, Index: ${r.metadata?.index}`);
+  });
+
+  // Concurrent operations
+  console.log('\n⚡ Testing concurrent operations...');
+
+  const concurrentStart = Date.now();
+
+  const promises = [
+    // Concurrent searches
+    ...Array.from({ length: 50 }, () =>
+      db.search({
+        vector: randomVector(128),
+        k: 10,
+      })
+    ),
+    // Concurrent inserts
+    ...Array.from({ length: 50 }, (_, i) =>
+      db.insert({
+        vector: randomVector(128),
+        metadata: { concurrent: true, index: i },
+      })
+    ),
+  ];
+
+  await Promise.all(promises);
+
+  const concurrentTime = Date.now() - concurrentStart;
+  console.log(`  Completed 100 concurrent operations in ${concurrentTime}ms`);
+
+  // Final stats
+  const finalCount = await db.len();
+  console.log(`\n📊 Final database size: ${finalCount} vectors`);
+
+  console.log('\n✨ Advanced example complete!');
+}
+
+main().catch((err) => {
+  console.error('Error:', err);
+  process.exit(1);
+});