New features in this release:
- 13 new CLI hooks commands (AST, Diff, Coverage, Graph, Security, RAG)
- 16 new MCP tools for Claude Code integration
- Enhanced hooks init with v2.0 templates
- 9-phase pretrain with attention/GNN capabilities
- Comprehensive CLAUDE.md documentation generation
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
New features in this release:
- 13 new CLI hooks commands (AST, Diff, Coverage, Graph, Security, RAG)
- 16 new MCP tools for Claude Code integration
- Enhanced hooks init with v2.0 templates
- 9-phase pretrain with attention/GNN capabilities
- Comprehensive CLAUDE.md documentation generation
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Added SIMD badge and documentation
- Added ParallelEmbedder API reference and usage examples
- Updated performance benchmarks with parallel vs sequential comparison
- Added browser compatibility table
- Added changelog section
- Added batch processing use case example
- Updated build instructions with SIMD flags
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Added SIMD badge and documentation
- Added ParallelEmbedder API reference and usage examples
- Updated performance benchmarks with parallel vs sequential comparison
- Added browser compatibility table
- Added changelog section
- Added batch processing use case example
- Updated build instructions with SIMD flags
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- ParallelEmbedder class using Node.js worker_threads
- Distributes batches across multiple CPU cores
- Benchmark results: 3.6-3.8x speedup on batch processing
- Per-text latency drops from ~390ms to ~103ms with 4 workers
- Published v0.1.2 to npm and crates.io
Usage:
import { ParallelEmbedder } from 'ruvector-onnx-embeddings-wasm/parallel';
const embedder = new ParallelEmbedder({ numWorkers: 4 });
await embedder.init();
const embeddings = await embedder.embedBatch(texts);
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- ParallelEmbedder class using Node.js worker_threads
- Distributes batches across multiple CPU cores
- Benchmark results: 3.6-3.8x speedup on batch processing
- Per-text latency drops from ~390ms to ~103ms with 4 workers
- Published v0.1.2 to npm and crates.io
Usage:
import { ParallelEmbedder } from 'ruvector-onnx-embeddings-wasm/parallel';
const embedder = new ParallelEmbedder({ numWorkers: 4 });
await embedder.init();
const embeddings = await embedder.embedBatch(texts);
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Enable WASM SIMD128 instructions for vectorized operations
- Update simd_available() to properly detect SIMD at compile time
- SIMD build is 180KB smaller than non-SIMD (more compact instructions)
- Published v0.1.1 to both npm and crates.io
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Enable WASM SIMD128 instructions for vectorized operations
- Update simd_available() to properly detect SIMD at compile time
- SIMD build is 180KB smaller than non-SIMD (more compact instructions)
- Published v0.1.1 to both npm and crates.io
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Added npm and crates.io version badges
- WebAssembly and MIT license badges
- Quick start examples for Browser, Node.js, and Cloudflare Workers
- Complete API reference for WasmEmbedder, WasmEmbedderConfig
- Model comparison table with 6 HuggingFace models
- Performance benchmarks and use case examples
Published to npm as ruvector-onnx-embeddings-wasm@0.1.0
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Added npm and crates.io version badges
- WebAssembly and MIT license badges
- Quick start examples for Browser, Node.js, and Cloudflare Workers
- Complete API reference for WasmEmbedder, WasmEmbedderConfig
- Model comparison table with 6 HuggingFace models
- Performance benchmarks and use case examples
Published to npm as ruvector-onnx-embeddings-wasm@0.1.0
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Fixes PreToolUse:Read hook error by supporting --silent flag
for Read/Glob/Task hooks that should not produce output.
Published ruvector@0.1.54
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Fixes PreToolUse:Read hook error by supporting --silent flag
for Read/Glob/Task hooks that should not produce output.
Published ruvector@0.1.54
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- gnn-correlation-network.js: Added RollingStats class for O(1) incremental
updates and correlation caching with TTL to avoid redundant O(n²) calculations
- attention-regime-detection.js: Optimized matmul with cache-friendly i-k-j
loop order and added empty matrix guards
- quantum-portfolio-optimization.js: Added ComplexPool for object reuse to
reduce GC pressure, plus in-place operations (addInPlace, multiplyInPlace,
scaleInPlace) to avoid allocations in hot loops
- multi-agent-swarm.js: Added RingBuffer for O(1) bounded memory operations
and SignalPool for signal object reuse
- gnn-correlation-network.js: Added RollingStats class for O(1) incremental
updates and correlation caching with TTL to avoid redundant O(n²) calculations
- attention-regime-detection.js: Optimized matmul with cache-friendly i-k-j
loop order and added empty matrix guards
- quantum-portfolio-optimization.js: Added ComplexPool for object reuse to
reduce GC pressure, plus in-place operations (addInPlace, multiplyInPlace,
scaleInPlace) to avoid allocations in hot loops
- multi-agent-swarm.js: Added RingBuffer for O(1) bounded memory operations
and SignalPool for signal object reuse
New optional companion package using Tract for inference:
- Runs in browsers, Cloudflare Workers, Deno, edge environments
- Same API as native crate
- JavaScript bindings via wasm-bindgen
- Supports all pooling strategies (Mean, Cls, Max, etc.)
Uses Tract instead of ONNX Runtime for WASM compatibility.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
New optional companion package using Tract for inference:
- Runs in browsers, Cloudflare Workers, Deno, edge environments
- Same API as native crate
- JavaScript bindings via wasm-bindgen
- Supports all pooling strategies (Mean, Cls, Max, etc.)
Uses Tract instead of ONNX Runtime for WASM compatibility.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Changed invalid category "machine-learning" to "algorithms".
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Changed invalid category "machine-learning" to "algorithms".
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The download logic would immediately fail if model.onnx wasn't at the
repo root, never trying the onnx/ subfolder where most sentence-transformer
models store their ONNX files.
Now tries both locations:
1. Root: {repo}/model.onnx
2. Subfolder: {repo}/onnx/model.onnx
Also applies fallback logic to auxiliary files (tokenizer.json, config.json).
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
The download logic would immediately fail if model.onnx wasn't at the
repo root, never trying the onnx/ subfolder where most sentence-transformer
models store their ONNX files.
Now tries both locations:
1. Root: {repo}/model.onnx
2. Subfolder: {repo}/onnx/model.onnx
Also applies fallback logic to auxiliary files (tokenizer.json, config.json).
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Key fixes across exotic neural-trader examples:
- reinforcement-learning-agent.js: Fixed broken backpropagation that only
updated output layer. Now stores activations and flows gradients through
all hidden layers properly.
- quantum-portfolio-optimization.js: Fixed QAOA mixer Hamiltonian that was
incorrectly accumulating all qubit operations. Now applies Rx rotations
sequentially per-qubit with proper normalization.
- hyperbolic-embeddings.js: Fixed Math.acosh/atanh domain errors and
implemented proper Riemannian gradient descent using expMap in Poincaré
ball model.
- multi-agent-swarm.js: Added division-by-zero guards for linear regression,
z-score calculation, and iterator type fixes. Added memory bounds.
- gnn-correlation-network.js: Added guards for betweenness normalization
(n<3), density (n<2), and clustering/degree calculations (n=0).
- attention-regime-detection.js: Added empty array handling for softmax and
matrix validation for transpose operations.
- atomic-arbitrage.js: Added guard for flash loan spread calculation.
Key fixes across exotic neural-trader examples:
- reinforcement-learning-agent.js: Fixed broken backpropagation that only
updated output layer. Now stores activations and flows gradients through
all hidden layers properly.
- quantum-portfolio-optimization.js: Fixed QAOA mixer Hamiltonian that was
incorrectly accumulating all qubit operations. Now applies Rx rotations
sequentially per-qubit with proper normalization.
- hyperbolic-embeddings.js: Fixed Math.acosh/atanh domain errors and
implemented proper Riemannian gradient descent using expMap in Poincaré
ball model.
- multi-agent-swarm.js: Added division-by-zero guards for linear regression,
z-score calculation, and iterator type fixes. Added memory bounds.
- gnn-correlation-network.js: Added guards for betweenness normalization
(n<3), density (n<2), and clustering/degree calculations (n=0).
- attention-regime-detection.js: Added empty array handling for softmax and
matrix validation for transpose operations.
- atomic-arbitrage.js: Added guard for flash loan spread calculation.
- Added hooks feature summary near top of README.md
- Created comprehensive HOOKS.md documentation
- Links to detailed docs for pretrain, build-agents, verify, etc.
- Added hooks feature summary near top of README.md
- Created comprehensive HOOKS.md documentation
- Links to detailed docs for pretrain, build-agents, verify, etc.
- Intelligence now saves to .ruvector/intelligence.json in project dir
- Falls back to ~/.ruvector/ only if no project context found
- Prefers project-local when .ruvector/ or .claude/ exists
- Fixes verify showing 'will be created' after pretrain
- Intelligence now saves to .ruvector/intelligence.json in project dir
- Falls back to ~/.ruvector/ only if no project context found
- Prefers project-local when .ruvector/ or .claude/ exists
- Fixes verify showing 'will be created' after pretrain
