# Changelog

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

The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## [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](https://github.com/ruvnet/ruvector/issues/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](https://github.com/ruvnet/ruvector/pull/212))
- **Formal verification** with lean-agentic dependent types ([#206](https://github.com/ruvnet/ruvector/pull/206))
- **WASM cognitive stack** — canonical min-cut, spectral coherence, container orchestration, cold-tier GNN training ([#201](https://github.com/ruvnet/ruvector/pull/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](https://github.com/ruvnet/ruvector/pull/211))
- **Harden MCP servers** against command injection, CORS bypass, and prototype pollution ([#213](https://github.com/ruvnet/ruvector/pull/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](https://github.com/ruvnet/ruvector/issues/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](https://github.com/ruvnet/ruvector/pull/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](https://github.com/ruvnet/ruvector/pull/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](https://github.com/ruvnet/ruvector/issues/152), [#164](https://github.com/ruvnet/ruvector/issues/164), [#167](https://github.com/ruvnet/ruvector/issues/167), [#171](https://github.com/ruvnet/ruvector/issues/171))
- LRU security fix ([#148](https://github.com/ruvnet/ruvector/issues/148))
- FPGA-transformer `BackendSpec.as_ref` and HNSW array indexing
- Platform-specific errno on macOS/BSD ([#174](https://github.com/ruvnet/ruvector/issues/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)

#### Advanced Search
- 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

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