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