# Changelog
All notable changes to AgenticMemory will be documented in this file.
## [0.2.0] - 2026-02-18
### Added
- **Query Expansion: 9 new query types (queries 8-16)**
- BM25 text search with inverted index (fast path) and full-scan fallback (slow path)
- Hybrid search combining BM25 + vector similarity via Reciprocal Rank Fusion (RRF)
- Graph centrality: PageRank, degree centrality, and betweenness centrality (Brandes' algorithm)
- Shortest path: bidirectional BFS (unweighted) and Dijkstra's algorithm (weighted)
- Belief revision: counterfactual analysis with cascade propagation (read-only)
- Reasoning gap detection: unjustified decisions, single-source inferences, low-confidence foundations, unstable knowledge, stale evidence
- Analogical query: structural fingerprinting to find similar past reasoning patterns
- Consolidation: deduplication, contradiction linking, inference promotion (with dry-run mode)
- Drift detection: belief trajectory tracking with stability scoring
- **New index structures**
- TermIndex (tag 0x05): BM25 inverted index with posting lists
- DocLengths (tag 0x06): dense array of token counts per node
- Feature flags bitfield in header for forward/backward compatibility
- **9 new CLI commands**
- `amem text-search`, `amem hybrid-search`, `amem centrality`, `amem path`
- `amem revise`, `amem gaps`, `amem analogy`, `amem consolidate`, `amem drift`
- **Python SDK additions**
- 9 new Brain methods: search_text(), search(), centrality(), shortest_path(), revise(), gaps(), analogy(), consolidate(), drift()
- New result dataclasses in agentic_memory/results.py
- **Backward compatibility**
- v0.1 files readable by v0.2 code (new queries use slow path)
- v0.2 files skip unknown index tags gracefully for older readers
- Feature flags in previously reserved header field
### No new dependencies
All algorithms (PageRank, BFS, Dijkstra, BM25) implemented with `std::collections` only.
## [0.1.0] - 2025-02-18
### Added
- **Rust Core Engine**
- Binary graph format (.amem) with 6 cognitive event types and 7 edge types
- LZ4-compressed content blocks
- Memory-mapped I/O for zero-copy access
- 128-dimensional feature vectors with cosine similarity search
- Multi-level indexes (type, session, time, cluster)
- CLI tool (`amem`) with create, add, link, info, traverse, query, mcp-serve commands
- MCP (Model Context Protocol) server for IDE integration
- 96 tests passing
- **Python SDK** (`pip install agentic-brain`)
- `Brain` class wrapping the Rust CLI with full API
- `MemoryAgent` for LLM-powered agents with persistent memory
- Provider integrations: Anthropic Claude, OpenAI GPT, Ollama
- Automatic knowledge extraction from conversations
- Context injection for memory-aware responses
- 84 tests passing
- **Terminal Test Agent**
- Interactive agent with 6 validation protocols
- Basic recall, decision recall, correction persistence, long-range memory, cross-topic inference, stress testing
- 97 tests passing
- **Cross-Provider Validation**
- 21 tests validating memory portability across Claude, GPT, and Ollama
- Binary format identity verification across providers
- **One-Command Installer**
- Auto-detection of 11 AI tools (Claude Code, Cursor, Windsurf, Continue, Ollama, LM Studio, etc.)
- Automatic MCP configuration for supported tools
- Backup and restore for all modified configs
- 39 tests passing
- **Research Paper**
- 7-page publication-grade paper with 7 figures and 6 tables
- Full benchmark data and methodology
- **Documentation**
- Quickstart guide, core concepts, API reference, file format specification
- Integration guides for all supported tools and frameworks
- FAQ and benchmark documentation