- Add Concurrency section with 4 worker modes:
- Main Thread (no workers, simple)
- Worker Pool (auto-scaling, recommended)
- Dedicated (one worker per task type)
- Shared Worker (cross-tab coordination)
- Add comprehensive worker templates with code examples
- Update stats to show worker count
- Include WorkerPool class with batch operations
- Add SharedWorker cross-tab example
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- Add comprehensive Web Workers section explaining UI responsiveness
- Include WorkerPool usage examples with practical code
- Add feature table explaining auto-scaling, load balancing, timeouts
- Add "when to use workers" guidance table
- Update Table of Contents with Consensus Modes and Web Workers
- Add WorkerPool to API Reference section
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- Add npm package section at top with install commands
- Link to pkg/README.md for JavaScript documentation
- Clarify Raft vs Gossip+CRDT consensus modes
- Add Web Worker pool to distributed systems features
- Update WASM badge to show 364KB size
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- Include worker.js and worker-pool.js in package
- Add exports for @ruvector/edge/worker and @ruvector/edge/worker-pool
- Document WorkerPool API with examples
- Features: round-robin distribution, batch splitting, load balancing
- Keeps UI responsive during heavy WASM operations
- Bump to v0.1.9
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Raft assumes stable membership and trusted nodes - not suitable for
wild browser swarms. Updated docs to:
- Position Raft for "trusted cohorts" (teams, enterprise, private relays)
- Add Gossip + CRDT for "open swarms" (public, high-churn, adversarial)
- Explain when to use each mode with code examples
- Update capability tables to reflect both consensus strategies
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- Update heading to "Free Self-Learning AI Swarms at the Edge"
- Emphasize self-optimizing agents that get smarter over time
- Mention LoRA fine-tuning, EWC++ continual learning, ReasoningBank
- Bump to v0.1.7
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- Add comprehensive platform diagram showing edge vs edge-full
- List all capabilities of edge-full modules
- Add optional/peer dependency on @ruvector/edge-full
- Show usage patterns for both packages together
- Bump to v0.1.6
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- 5-step tutorial: Identity, Crypto, Vector Search, Routing, Consensus
- P2P transport options: WebRTC, GUN.js, IPFS/libp2p, Nostr
- Full code examples for each transport integration
- Architecture diagrams showing edge-first design
- Transport comparison table with recommendations
- Complete API reference for all 9 WASM exports
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- Emphasize zero-cost edge-first architecture
- Add economics comparison (cloud vs edge)
- Document all WASM APIs with examples
- Add use cases and architecture diagram
- Compare with cloud alternatives (OpenAI, LangChain, AutoGPT)
- Include agentic-flow integration example
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- Built WASM bindings with wasm-pack for browser/Node.js usage
- Exports: WasmIdentity, WasmCrypto, WasmHnswIndex, WasmSemanticMatcher,
WasmRaftNode, WasmHybridKeyPair, WasmSpikingNetwork, WasmQuantizer,
WasmAdaptiveCompressor
- 364KB optimized WASM binary with full TypeScript types
- Published to npm as @ruvector/edge@0.1.0
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- 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
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- 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);
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- 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
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- 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
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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.
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Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Changed invalid category "machine-learning" to "algorithms".
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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).
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The Rust example files (learning_demo.rs, simd_distance_benchmark.rs)
were causing linker errors during pgrx tests because they use pgrx
functions without proper PostgreSQL library context.
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- Add setup.ps1: Auto-installs espup, espflash, and ESP32 toolchain
- Add build.ps1: Auto-detects toolchain paths, no hardcoded values
- Add flash.ps1: Auto-detects COM ports with interactive selection
- Add env.ps1: Sets up environment for current session
- Add monitor.ps1: Serial monitor with auto port detection
- Update CLI to use PowerShell scripts on Windows
- Improve COM port detection using System.IO.Ports
- Update README with improved Windows workflow
Fixes Windows-specific issues:
- No more hardcoded paths (C:\Users\ruv\...)
- Dynamic libclang and Python path resolution
- Auto-detection of ESP toolchain location
- Better error handling and user feedback
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- Run cargo fmt across all crates (468 files formatted)
- Add permissions for PR comments in benchmarks.yml
- Add continue-on-error for PR comment steps
- Remove Docker service from postgres-extension-ci (pgrx manages own postgres)
- Add permissions to postgres-extension-ci.yml
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- Add Option C: npx CLI quickstart section with all commands
- Add npm package link to Crate & Package Links table
- Add esp32-flash flashable project reference
- Update Related section with npm and esp32-flash links
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Replace static version badge with dynamic crates.io badge
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- Add value proposition section (why RuvLLM ESP32)
- Document all 10 major features with technical details
- Add supported hardware comparison table (ESP32 variants)
- Add npx quickstart as primary installation method
- Document all serial commands with examples
- Add complete feature guide with code samples
- Include memory/performance benchmarks
- Add project structure documentation
- Document feature flags and library API usage
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- INT8/INT4/Binary quantization for memory efficiency
- Multi-chip federation with pipeline/tensor parallelism (48x speedup)
- SNN-gated inference for 107x energy reduction (4.7mW vs 500mW)
- RuVector integration: Micro HNSW, semantic memory, RAG, anomaly detection
- WASM runtime support for hot-swappable plugins
- 10 application domains with 80+ use cases
- 96 passing tests, published to crates.io
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- Introduced a new WebAssembly binary file `rvlite_bg.wasm` for the rvlite project.
- Added TypeScript definitions in `rvlite_bg.wasm.d.ts` to expose various functions and memory management for the WebAssembly module.
- Add metadata field to JsVectorEntry (as JSON string)
- Add metadata and vector fields to JsSearchResult
- Add filter field to JsSearchQuery for filtered searches
- Update get() to return metadata
- Add VectorDBWrapper in ruvector for automatic JSON conversion
- Bump versions: @ruvector/core@0.1.28, ruvector@0.1.35
Fixes#71🤖 Generated with [Claude Code](https://claude.com/claude-code)
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