mirror of
https://github.com/ruvnet/RuVector.git
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eefcc5322b
Phase 2: Multi-Platform Native Builds This commit adds comprehensive GitHub Actions CI/CD for building native NAPI modules across all major platforms: ✨ Features: - GitHub Actions workflow with 5-platform matrix build: - Linux (x64, ARM64) - macOS (x64 Intel, ARM64 Apple Silicon) - Windows (x64) - Parallel builds complete in 7-10 minutes - Automated artifact uploads and publishing - Platform-specific npm packages with smart detection 📦 Package Structure: - @ruvector/core - Main package with platform detection - @ruvector/core-{platform} - Platform-specific binaries - Smart loader with automatic platform selection - Optional dependencies ensure minimal install size 🔧 Developer Tools: - scripts/publish-platforms.js - Automated publishing - Comprehensive TypeScript definitions - Smoke tests for each platform - Local build support with napi build 📚 Documentation: - docs/BUILD_PROCESS.md - Complete build guide - docs/PHASE2_MULTIPLATFORM_COMPLETE.md - Phase summary - README for @ruvector/core package - Troubleshooting and cross-compilation guides 🚀 Publishing Workflow: 1. Tag release (git tag v0.1.1) 2. Push to GitHub 3. CI builds all platforms 4. Publishes platform packages 5. Publishes main packages Next: Phase 3 - WASM support with architectural refactoring 🤖 Generated with Claude Code
77 lines
2.1 KiB
JavaScript
77 lines
2.1 KiB
JavaScript
/**
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* Test script to verify native module loads correctly
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*/
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import ruvector from './dist/index.js';
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console.log('=== Ruvector Native Module Test ===\n');
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try {
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// Test 1: Load module
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console.log('✓ Module imported successfully');
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console.log('Available exports:', Object.keys(ruvector));
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// Test 2: Get version
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console.log('\n--- Version Info ---');
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console.log('Version:', ruvector.version());
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// Test 3: Hello function
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console.log('\n--- Hello Test ---');
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console.log(ruvector.hello());
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// Test 4: Create VectorDB instance
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console.log('\n--- VectorDB Creation ---');
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const db = ruvector.VectorDB.withDimensions(384);
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console.log('✓ VectorDB created with 384 dimensions');
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// Test 5: Check database is empty
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console.log('\n--- Database Status ---');
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const isEmpty = await db.isEmpty();
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console.log('Database is empty:', isEmpty);
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const len = await db.len();
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console.log('Database length:', len);
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// Test 6: Insert a vector
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console.log('\n--- Insert Vector ---');
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const testVector = new Float32Array(384).fill(0.1);
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const id = await db.insert({
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vector: testVector,
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});
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console.log('✓ Inserted vector with ID:', id);
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const newLen = await db.len();
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console.log('Database length after insert:', newLen);
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// Test 7: Search
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console.log('\n--- Search Test ---');
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const queryVector = new Float32Array(384).fill(0.15);
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const results = await db.search({
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vector: queryVector,
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k: 10
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});
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console.log('✓ Search completed');
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console.log('Found', results.length, 'results');
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if (results.length > 0) {
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console.log('First result:', {
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id: results[0].id,
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score: results[0].score
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});
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}
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// Test 8: Get vector
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console.log('\n--- Get Vector Test ---');
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const retrieved = await db.get(id);
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if (retrieved) {
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console.log('✓ Retrieved vector with ID:', retrieved.id);
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console.log('Vector length:', retrieved.vector.length);
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}
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console.log('\n=== ✅ All tests passed! ===\n');
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process.exit(0);
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} catch (error) {
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console.error('\n❌ Test failed:', error.message);
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console.error(error.stack);
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process.exit(1);
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}
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