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License: - Replace MIT/Apache-2.0 with AGPL-3.0-only across all crates and npm packages - Replace LICENSE file with official GNU AGPL-3.0 text - Remove LICENSE-MIT and LICENSE-APACHE Code quality: - Fix all 44 clippy warnings (zero remaining) - Collapsible if statements, redundant closures, manual Option::map - Remove duplicate #[allow(dead_code)] attributes in deprecated tool modules - Add Default impl for CognitiveEngine - Replace manual sort_by with sort_by_key Documentation: - Update CHANGELOG with v1.2.0, v1.3.0, v1.5.0, v1.6.0 entries - Update README with v1.6.0 highlights and accurate stats (52K lines, 1100+ tests) - Add fastembed-rs/ to .gitignore - Add fastembed-rs to workspace exclude 1115 tests passing, zero warnings, RUSTFLAGS="-Dwarnings" clean.
182 lines
6.6 KiB
Markdown
182 lines
6.6 KiB
Markdown
# Changelog
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All notable changes to Vestige will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [1.6.0] - 2026-02-19
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### Changed
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- **F16 vector quantization** — USearch vectors stored as F16 instead of F32 (2x storage savings)
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- **Matryoshka 256-dim truncation** — embedding dimensions reduced from 768 to 256 (3x embedding storage savings)
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- **Convex Combination fusion** — replaced RRF with 0.3 keyword / 0.7 semantic weighted fusion for better score preservation
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- **Cross-encoder reranker** — added Jina Reranker v1 Turbo (fastembed TextRerank) for neural reranking (~20% retrieval quality improvement)
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- Combined: **6x vector storage reduction** with better retrieval quality
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- Cross-encoder loads in background — server starts instantly
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- Old 768-dim embeddings auto-migrated on load
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---
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## [1.5.0] - 2026-02-18
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### Added
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- **CognitiveEngine** — 28-module stateful engine with full neuroscience pipeline on every tool call
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- **`dream`** tool — memory consolidation via replay, discovers hidden connections and synthesizes insights
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- **`explore_connections`** tool — graph traversal with chain, associations, and bridges actions
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- **`predict`** tool — proactive retrieval based on context and activity patterns
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- **`restore`** tool — restore memories from JSON backup files
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- **Automatic consolidation** — FSRS-6 decay runs on a 6-hour timer + inline every 100 tool calls
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- ACT-R base-level activation with full access history
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- Episodic-to-semantic auto-merge during consolidation
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- Cross-memory reinforcement on access
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- Park et al. triple retrieval scoring
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- Personalized w20 optimization
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### Changed
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- All existing tools upgraded with cognitive pre/post processing pipelines
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- Tool count: 19 → 23
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---
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## [1.3.0] - 2026-02-12
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### Added
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- **`importance_score`** tool — 4-channel neuroscience scoring (novelty, arousal, reward, attention)
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- **`session_checkpoint`** tool — batch smart_ingest up to 20 items with Prediction Error Gating
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- **`find_duplicates`** tool — cosine similarity clustering with union-find for dedup
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- `vestige ingest` CLI command for memory ingestion via command line
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### Changed
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- Tool count: 16 → 19
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- Made `get_node_embedding` public in core API
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- Added `get_all_embeddings` for duplicate scanning
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---
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## [1.2.0] - 2026-02-12
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### Added
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- **Web dashboard** — Axum-based on port 3927 with memory browser, search, and system stats
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- **`memory_timeline`** tool — browse memories chronologically, grouped by day
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- **`memory_changelog`** tool — audit trail of memory state transitions
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- **`health_check`** tool — system health status with recommendations
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- **`consolidate`** tool — run FSRS-6 maintenance cycle
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- **`stats`** tool — full memory system statistics
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- **`backup`** tool — create SQLite database backups
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- **`export`** tool — export memories as JSON/JSONL with filters
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- **`gc`** tool — garbage collect low-retention memories
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- `backup_to()` and `get_recent_state_transitions()` storage APIs
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### Changed
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- Search now supports `detail_level` (brief/summary/full) to control token usage
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- Tool count: 8 → 16
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---
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## [1.1.3] - 2026-02-12
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### Changed
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- Upgraded to Rust edition 2024
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- Security hardening and dependency updates
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### Fixed
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- Dedup on ingest edge cases
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- Intel Mac CI builds
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- NPM package version alignment
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- Removed dead TypeScript package
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---
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## [1.1.2] - 2025-01-27
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### Fixed
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- Embedding model cache now uses platform-appropriate directories instead of polluting project folders
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- macOS: `~/Library/Caches/com.vestige.core/fastembed`
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- Linux: `~/.cache/vestige/fastembed`
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- Windows: `%LOCALAPPDATA%\vestige\cache\fastembed`
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- Can still override with `FASTEMBED_CACHE_PATH` environment variable
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---
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## [1.1.1] - 2025-01-27
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### Fixed
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- UTF-8 string slicing issues in keyword search and prospective memory
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- Silent error handling in MCP stdio protocol
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- Feature flag forwarding between crates
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- All GitHub issues resolved (#1, #3, #4)
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### Added
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- Pre-built binaries for Linux, Windows, and macOS (Intel & ARM)
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- GitHub Actions CI/CD for automated releases
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---
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## [1.1.0] - 2025-01-26
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### Changed
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- **Tool Consolidation**: 29 tools → 8 cognitive primitives
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- `recall`, `semantic_search`, `hybrid_search` → `search`
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- `get_knowledge`, `delete_knowledge`, `get_memory_state` → `memory`
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- `remember_pattern`, `remember_decision`, `get_codebase_context` → `codebase`
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- 5 intention tools → `intention`
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- Stats and maintenance moved from MCP to CLI (`vestige stats`, `vestige health`, etc.)
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### Added
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- CLI admin commands: `vestige stats`, `vestige health`, `vestige consolidate`, `vestige restore`
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- Feedback tools: `promote_memory`, `demote_memory`
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- 30+ FAQ entries with verified neuroscience claims
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- Storage modes documentation: Global, per-project, multi-Claude household
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- CLAUDE.md templates for proactive memory use
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- Version pinning via git tags
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### Deprecated
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- Old tool names (still work with warnings, removed in v2.0)
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---
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## [1.0.0] - 2025-01-25
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### Added
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- FSRS-6 spaced repetition algorithm with 21 parameters
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- Bjork & Bjork dual-strength memory model (storage + retrieval strength)
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- Local semantic embeddings with fastembed v5 (BGE-base-en-v1.5, 768 dimensions)
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- HNSW vector search with USearch (20x faster than FAISS)
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- Hybrid search combining BM25 keyword + semantic + RRF fusion
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- Two-stage retrieval with reranking (+15-20% precision)
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- MCP server for Claude Desktop integration
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- Tauri desktop application
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- Codebase memory module for AI code understanding
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- Neuroscience-inspired memory mechanisms:
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- Synaptic Tagging and Capture (retroactive importance)
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- Context-Dependent Memory (Tulving encoding specificity)
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- Spreading Activation Networks
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- Memory States (Active/Dormant/Silent/Unavailable)
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- Multi-channel Importance Signals (Novelty/Arousal/Reward/Attention)
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- Hippocampal Indexing (Teyler & Rudy 2007)
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- Prospective memory (intentions and reminders)
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- Sleep consolidation with 5-stage processing
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- Memory compression for long-term storage
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- Cross-project learning for universal patterns
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### Changed
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- Upgraded embedding model from all-MiniLM-L6-v2 (384d) to BGE-base-en-v1.5 (768d)
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- Upgraded fastembed from v4 to v5
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### Fixed
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- SQL injection protection in FTS5 queries
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- Infinite loop prevention in file watcher
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- SIGSEGV crash in vector index (reserve before add)
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- Memory safety with Mutex wrapper for embedding model
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---
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## [0.1.0] - 2025-01-24
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### Added
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- Initial release
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- Core memory storage with SQLite + FTS5
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- Basic FSRS scheduling
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- MCP protocol support
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- Desktop app skeleton
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