Changelog

July 27, 2026 · View on GitHub

All notable changes to RuVector will be documented in this file.

The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.

[ruvector npm 0.2.37] - 2026-07-27

Fixed

  • Restore the release CI's native backend installation so functional, learning, performance, and recall gates exercise HNSW instead of the in-memory fallback.
  • Preserve the Rust core's default HNSW behavior when JavaScript callers omit hnswConfig; the wrapper previously selected the exact FlatIndex path.
  • Normalize the package binary metadata and its integration assertion.
  • Remove the npm workspace's critical tar advisory with a patched override.
  • Correct the Shor factoring milestone table to distinguish a failed 35-factor experiment from the separate Schnorr/QAOA hybrid result.

[ruvector npm 0.2.36] - 2026-07-26

Fixed

  • Start the stdio MCP transport when launched through ruvector mcp start (#715).
  • Keep ONNX model-loader diagnostics on stderr so they cannot corrupt MCP JSON-RPC frames (#710).

Security

  • Update anyhow to 1.0.104 and memmap2 to 0.9.11, removing the corresponding RustSec soundness exceptions.
  • Update the MCP SDK to 1.29.x, clearing its shared-transport data-leak and ReDoS advisories, and remove the unused js-beautify dependency.

[hailo-backend] - 2026-05-03

Branch-only entry; not yet released to a versioned tag. 38 iters / 45 commits arc covering iter 133-171 to land NPU-accelerated embedding inference on Pi 5 + AI HAT+ end-to-end.

Added

  • NPU acceleration via Hailo-8 (ADR-176, iters 158-163). New modules hef_pipeline.rs, host_embeddings.rs, hef_embedder.rs in ruvector-hailo. HailoEmbedder auto-detects model.hef + safetensors trio and routes through the NPU; falls back to candle-on-CPU when HEF is absent.
  • First-known all-MiniLM-L6-v2 HEF for Hailo-8 — published as GitHub Release hailo-encoder-v0.1.0-iter156b (15.7 MB, sha256 cdbc89...). Compiled iter 156b after working around four distinct Hailo Dataflow Compiler v3.33 SDK bugs from user-space (KeyError, AccelerasValueError, ElementwiseAddDirectOp Keras serialize via acceleras Layer monkey-patch, RGB-align via single-input encoder form).
  • deploy/download-encoder-hef.sh — sha256-pinned downloader for the HEF artifact, matches the iter-134 download-cpu-fallback-model.sh pattern.
  • deploy/compile-encoder-hef.py — Python SDK driver for the HEF compile pipeline, replaces the iter-131 CLI invocations that hit the hailo CLI's -y auto-accept-recommendation bug.
  • deploy/export-minilm-encoder-onnx.py — torch.onnx.export helper that strips the BERT embedding lookup so the encoder block compiles cleanly on Hailo-8.
  • iter-167 ranking-aware startup self-test — worker now embeds three reference phrases at boot and checks sim(close) > sim(far); refuses to serve if the encoder is producing nonsense vectors.
  • Pi 4 / Pi 5-without-HAT deploy as a first-class target (ADR-177). cpu-fallback is fully hardware-agnostic across aarch64.
  • iter-147 cpu-fallback embedder pool — RUVECTOR_CPU_FALLBACK_POOL_SIZE=N runs N parallel BertModel instances behind try-lock dispatch. Measured 1.75× throughput on x86 release, 4× on Pi 5 expected.
  • iter-143 fingerprint integrity — compute_fingerprint now hashes the safetensors+tokenizer+config trio so cpu-fallback workers get integrity-checked by the cluster.
  • iter-141 cross-build with --with-worker — produces an aarch64 cpu-fallback worker binary in one command on x86.

Performance

Measured on cognitum-v0 (Pi 5 + AI HAT+) at concurrency=4 via cluster-bench:

PathThroughputp50 latencyΔ vs cpu-fallback
cpu-fallback (Pi 5)7.0 / sec572 ms—
NPU HEF (iter 163)67.3 / sec57 ms9.6×
cache hit (in-process)15.86 M / sec<1 µs226,000×

Saturation test (iter 170): 60s burst at C=100 — Pi never OOMs, worker RSS stable at 91 MB, tonic-level backpressure correctly drops excess requests with ResourceExhausted.

Documentation

  • ADR-167 updated: NPU is now production-default
  • ADR-173 updated: ruvllm-hailo upstream embedding seam is NPU-accelerated transparently
  • ADR-175 Option A status flipped to "production default"
  • ADR-176 new EPIC tracking the full integration arc
  • ADR-177 new — Pi 4 / no-HAT deploy
  • Cluster README now has an Operator QUICKSTART covering all three deploy paths

Internal

  • iter-153 acceleras Keras-registration monkey-patch — the breakthrough that unblocked the entire HEF compile pipeline. compile-encoder-hef.py walks every module under hailo_model_optimization.acceleras at import time and applies keras.saving.register_keras_serializable() to every keras.layers.Layer subclass it finds.

[2.0.5] - 2026-02-26

Fixed

  • ruvector-gnn: Replace assert!() with Result in MultiHeadAttention::new() and RuvectorLayer::new() — prevents fatal abort() in NAPI-RS/WASM bindings (#216)
  • ruvector-gnn: Fix pre-existing mmap.rs test compilation error (grad_offset returns Option<usize>)
  • install.sh: Remove stale hardcoded version pins (@0.1.2, @0.1.23), always fetch latest
  • install.sh: Fix operator precedence bug in CLI install guard (--npm-only now correctly skips CLI)
  • Docs: Fix stale capability counts in root README
  • Docs: Update guides to match current API surface and versions

Added

  • OpenFang Agent OS RVF example — 24 RVF capabilities demonstrated
  • OpenFang project research document
  • Missing capabilities added to advanced features guide

Security

  • SEC-001: Harden mmap pointer arithmetic with checked bounds
  • SEC-002: Cryptographic hash binding for proof attestations (prevents spoofing)

Changed

  • Workspace version bumped from 2.0.4 to 2.0.5
  • @ruvector/gnn bumped from 0.1.24 to 0.1.25 (all 7 platform packages)
  • All WASM/NAPI wrappers (ruvector-gnn-wasm, ruvector-gnn-node, ruvector-attention-unified-wasm) now propagate layer construction errors as catchable JS exceptions instead of process crashes

Published

  • ruvector-core@2.0.5 → crates.io
  • ruvector-gnn@2.0.5 → crates.io
  • @ruvector/gnn@0.1.25 → npm (linux-x64-gnu, linux-x64-musl, linux-arm64-gnu, linux-arm64-musl, darwin-x64, darwin-arm64, win32-x64-msvc)

[2.0.4] - 2026-02-25

Added

  • ADR-043: External Intelligence Providers for SONA learning — pluggable external AI intelligence integration
  • Intelligence module in @ruvector/ruvllm@2.5.0
  • Security Hardened RVF v3.0 — 30 verified capabilities, AIDefence + TEE hardened container (ADR-042)
  • Proof-gated graph transformer with 8 verified modules (#212)
  • Formal verification with lean-agentic dependent types (#206)
  • WASM cognitive stack — canonical min-cut, spectral coherence, container orchestration, cold-tier GNN training (#201)
  • rvDNA health biomarker analysis engine:
    • 20-SNP panel with streaming simulation
    • LPA cardiovascular SNPs from SOTA meta-analysis
    • CUSUM changepoint detection, gene-biomarker correlations
    • SNP weights calibrated from clinical meta-analyses
    • npm @ruvector/rvdna package with risk scoring and benchmarks
  • SPARQL parser backtrack fix and executor memory leak fix in ruvector-postgres@2.0.4

Security

  • Harden intelligence providers — type-safe enums, input validation, file size limits
  • Fix path traversal in MCP server vector_db_backup (CWE-22) (#211)
  • Harden MCP servers against command injection, CORS bypass, and prototype pollution (#213)

Fixed

  • Migrate attention/dag/tiny-dancer to workspace versioning
  • Fix all dependency version specs for crates.io publishing
  • Include prebuilt binaries in @ruvector/gnn platform packages (#195)
  • CI: Node.js upgraded to 20 in GNN build workflow
  • CI: Auto-publish on push to main for GNN packages
  • RVF NodeBackend string ID ↔ numeric label mapping

[0.3.0] - 2026-02-21

Major release introducing the RuVector Format (RVF) cognitive container, AGI runtime substrate, and a significant expansion of the platform from vector database to cognitive computing framework.

Added

RuVector Format (RVF) — Universal Cognitive Container

  • Complete RVF SDK with cognitive container specification (#166)
  • New crates: rvf-types, rvf-crypto, rvf-runtime, rvf-node, rvf-wasm, rvf-solver, rvf-solver-wasm, rvf-cli
  • WASM segment (WASM_SEG 0x10) for self-bootstrapping RVF files
  • Ed25519 asymmetric signing (RFC 8032) behind feature gate
  • Witness auto-append, CLI verification, prebuilt fallbacks
  • Integration into npx ruvector and rvlite (ADR-032)
  • Platform-specific scripts for Linux, Windows, Node, browser, Docker
  • Real Linux 6.8.12 kernel embedded in RVF for live-boot proof

AGI Cognitive Container (ADR-036)

  • authority_config and domain_profile TLV support
  • Authority guard, coherence monitor, benchmarks
  • Multi-dimensional IQ with cost/robustness/AGI contract
  • 5-level superintelligence pathway engine
  • KnowledgeCompiler Strategy Zero, StrategyRouter bandit, ablation protocol
  • Three-class memory, loop gating, RVF artifacts, rollback witnesses
  • Thompson Sampling two-signal model, speculative dual-path, constraint propagation

QR Cognitive Seed (ADR-034)

  • Pure-Rust QR code encoder for RVF seed bytes
  • In-browser RVF seed decoder PWA
  • Swift App Clip skeleton for iOS mobile FFI

Progressive Indexing Hardening (ADR-033)

  • QualityEnvelope, triple budget caps, selective scan, fuzz benchmark
  • ResultQuality extended to API boundary
  • Malicious manifest test and brute-force cap

Sublinear-Time Sparse Solver

  • Complete ruvector-solver crate with zero-overhead SpMV
  • Fused Neumann iteration kernel
  • WASM solver: self-learning AGI engine compiled to WASM
  • Min-cut gating experiment modules

Additional Systems

  • RvBot: Self-contained RVF bot with real Linux 6.6 kernel and initramfs boot
  • rvDNA Genomics: Complete SOTA genomic analysis pipeline, native 23andMe genotyping v0.2.0
  • Domain Expansion: Cross-domain AGI transfer learning engine with WASM bindings and meta-learning
  • OSPipe: RuVector-enhanced personal AI memory for Screenpipe (#163)
  • Quantum Simulation: ruqu-core, ruqu-algorithms, ruqu-wasm, Bell test CHSH inequality
  • Causal Atlas (ADR-040): Dashboard, solver, and desktop app
  • ruvector-postgres v0.3.0: 43 new SQL functions (ADR-044)

Fixed

  • HNSW index bugs, agent/SPARQL crashes (#152, #164, #167, #171)
  • LRU security fix (#148)
  • FPGA-transformer BackendSpec.as_ref and HNSW array indexing
  • Platform-specific errno on macOS/BSD (#174)
  • WASM path resolution in CJS→ESM interop
  • Docker Rust version bumped to 1.85 for edition2024

Changed

  • rvf-types, rvf-crypto, rvf-runtime bumped to 0.2.0
  • npm: ruvector@0.1.99, rvlite@0.2.4, rvf@0.1.3

[0.2.6] - 2025-12-09

Added

  • ruvector-postgres PostgreSQL extension with SIMD optimizations and 53 SQL function definitions
  • PostgreSQL 18 support with backward compatibility
  • @ruvector/postgres-cli with native installation support
  • W3C SPARQL 1.1 query language support in PostgreSQL extension
  • GNN v2 comprehensive implementation with cognitive substrate
  • iOS-optimized WASM recommendation engine
  • 9 cognitive substrate crates published as EXO-AI 2025
  • Neuromorphic HNSW v2.3 with SNN (Spiking Neural Network) integration
  • Ultra-low-latency meta-simulation engine example
  • 8 specialized Docker images with publishing infrastructure
  • RuVector Studio — complete web UI application
  • ruvector-attention functions exported from PostgreSQL extension

Fixed

  • Docker build and extension SQL for PG17
  • SPARQL build compilation — achieved 100% clean build
  • Docker Hub README and image references

Changed

  • npm packages reorganized from /src to /npm/packages

Breaking Changes

  • npm import paths changed due to /src → /npm/packages reorganization

[0.1.32] - 2026-01-17

Added

  • SONA Neural Architecture npm package (sona@0.1.5)
  • RuvLLM npm package with intelligence module
  • Graph Node bindings (@ruvector/graph-node@0.1.26)
  • npm package expansion and version consolidation

[0.1.19] - 2025-12-01

Fixed

  • GNN Node.js bindings: Use Float32Array for NAPI bindings to fix type conversion errors

[0.1.16] - 2025-11-27

Added

  • Persistent GNN layer caching — 250-500x performance improvement
  • Self-learning GNN strategy for accuracy improvement
  • GNN NAPI-RS bindings for all platforms

[0.1.0] - 2025-11-25

Initial release of RuVector — a high-performance vector database written in Rust.

Added

Core Vector Database

  • HNSW (Hierarchical Navigable Small World) graph indexing
  • SIMD-optimized distance metrics (Euclidean, Cosine, Dot Product, Manhattan)
  • Memory-mapped vector access via memmap2
  • Parallel index construction using rayon
  • Zero-copy serialization with rkyv
  • Scalar quantization (int8) for 4x memory compression

AgenticDB Compatibility Layer

  • Full 5-table schema: vectors_table, reflexion_episodes, skills_library, causal_edges, learning_sessions
  • Reflexion Memory API with semantic search over self-critique episodes
  • Skill Library with auto-consolidation and usage tracking
  • Causal Memory Graph with confidence scoring and hypergraph support
  • 9 RL algorithms (Q-Learning, SARSA, DQN, PPO, Actor-Critic, Policy Gradient, Decision Transformer, MCTS, Model-Based)
  • Product Quantization (PQ) with 8-16x memory compression at 90-95% recall
  • Filtered search (pre/post-filtering with complex expressions)
  • Hybrid search (vector similarity + BM25 keyword scoring)
  • MMR (Maximal Marginal Relevance) diversity-aware ranking
  • Conformal prediction with distribution-free confidence intervals

Multi-Platform Deployment

  • Node.js (NAPI-RS): Async API, TypeScript types, zero-copy Float32Array
  • WASM: Browser-compatible, Web Workers, IndexedDB persistence
  • CLI: JSON/CSV/NPY support, shell completions, benchmarking
  • Cross-platform builds: Linux (x64/arm64), macOS (x64/arm64), Windows (x64), WASM

Performance

  • 10-100x faster than Python/TypeScript implementations
  • Sub-millisecond latency (p50 < 0.8ms for 1M vectors)
  • 95%+ recall with HNSW (ef_search=100)
  • 4-32x memory compression with quantization
  • 200-300x distance calculation speedup with SIMD
  • Near-linear scaling to CPU core count

Dependencies

  • Core: redb, memmap2, hnsw_rs, simsimd, rayon, crossbeam
  • Serialization: rkyv, bincode, serde, serde_json
  • Node.js: napi, napi-derive
  • WASM: wasm-bindgen, wasm-bindgen-futures, js-sys, web-sys
  • Math: ndarray, rand, rand_distr
  • CLI: clap, indicatif, console

For questions or issues, visit: https://github.com/ruvnet/ruvector/issues