518b8eca85
md-first memory extraction framework for AI agents. Markdown is the single source of truth; SQLite holds state and LanceDB provides the rebuildable vector + BM25 + scalar index. The codebase follows a single-direction DDD layering (entrypoints -> service -> memory -> infra, with component / core / config cross-cutting) enforced by import-linter. Engineering surface: - Coding conventions in .claude/rules/ (path-scoped) and workflows in .claude/skills/ (/commit, /new-branch, /pr). - GitHub Actions CI runs make lint + test + integration; pre-commit mirrors the gates locally (ruff, hygiene hooks, gitlint commit-msg). - Commit messages follow Conventional Commits, enforced by gitlint. - make lint also enforces datetime two-zone discipline and OpenAPI drift.
41 lines
1.6 KiB
Markdown
41 lines
1.6 KiB
Markdown
# Changelog
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All notable changes to **EverOS** are 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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## [Unreleased]
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_Unreleased changes on `dev` will be listed here._
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## [1.0.0] - 2026-06-03
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First public release of EverOS — a Markdown-first memory extraction framework
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for AI agents.
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### Added
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- **Markdown as source of truth** — all memory persists as plain `.md` files you
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can open, edit, grep, and version with Git.
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- **Lightweight three-piece storage** — Markdown (truth) + SQLite (state / queue
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/ audit) + LanceDB (vector + BM25 + scalar index). No external services
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required.
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- **Hybrid retrieval** — BM25, vector, and scalar filtering in a single LanceDB
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query.
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- **Cascade index sync** — editing a `.md` file triggers a file watcher →
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entry-level diff → sub-second LanceDB sync.
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- **Dual-track memory** — user-track (Episodes / Profiles) and agent-track
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(Cases / Skills).
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- **Multi-source extraction** — conversations, workflows, agent traces, and file
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knowledge.
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- **CLI + HTTP API** — the `everos` command-line tool and a FastAPI server,
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async-first throughout.
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- **Pluggable providers** — LLM / embedding / rerank via the OpenAI-compatible
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protocol (works with OpenAI, OpenRouter, vLLM, Ollama, …).
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- **Decoupled algorithms** — memory extraction algorithms live in the standalone
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`everalgo-*` libraries published on PyPI.
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[Unreleased]: https://github.com/EverMind-AI/EverOS/compare/v1.0.0...HEAD
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[1.0.0]: https://github.com/EverMind-AI/EverOS/releases/tag/v1.0.0
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