Files
EverOS/ACKNOWLEDGMENTS.md
Elliot Chen 518b8eca85 chore: initialize EverOS 1.0.0
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.
2026-06-06 07:33:17 +08:00

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3.8 KiB
Markdown

# Acknowledgments
[Home](README.md) > [Docs](docs/index.md) > Acknowledgments
Thanks to the following projects, communities, and individuals for their
inspiration and support.
---
## Inspiration & references
### [memsearch](https://github.com/zilliztech/memsearch)
Inspired our markdown-as-source-of-truth design and the SHA-256 +
file-watcher incremental sync model. memsearch is the closest project in
spirit to EverOS.
### [mem0](https://github.com/mem0ai/mem0)
Inspired the "one provider per file" flat adapter layout that EverOS uses
for `component/llm/` and `component/embedding/`.
### [Letta (MemGPT)](https://github.com/letta-ai/letta)
Inspired the multi-tier memory mapping (Core / Recall / Archival) that maps
naturally onto our MemCell / Episode / Archival pipeline.
### [MemOS](https://github.com/MemTensor/MemOS)
Provided a reference for memory taxonomy decisions (textual / parametric /
activation) and helped sharpen our scope choice to focus on textual memory.
### [Memos](https://github.com/usememos/memos)
A comprehensive open-source note-taking service whose plain-text-first
design philosophy reinforced our decision to keep markdown files as the
single source of truth.
### [Nemori](https://github.com/nemori-ai/nemori)
A self-organising long-term memory substrate for agentic LLM workflows that
provided valuable inspiration for our extraction pipeline.
---
## Open-source libraries
EverOS is built on top of excellent open-source libraries and frameworks:
### Core
- **[Python](https://www.python.org/)** — Programming language (3.12+)
- **[uv](https://github.com/astral-sh/uv)** — Fast Python package manager
- **[FastAPI](https://fastapi.tiangolo.com/)** — Modern async web framework (HTTP API)
- **[Pydantic](https://docs.pydantic.dev/)** — Data validation and settings
### Storage
- **[LanceDB](https://lancedb.com/)** — Embedded vector + BM25 + scalar database
- **[SQLite](https://sqlite.org/)** — Embedded relational database (state + audit log)
### Tooling
- **[Ruff](https://docs.astral.sh/ruff/)** — Lint + format
- **[import-linter](https://import-linter.readthedocs.io/)** — Layered architecture enforcement
- **[Hatchling](https://hatch.pypa.io/)** — Wheel build backend
- **[pytest](https://pytest.org/)** — Testing framework
- **[pre-commit](https://pre-commit.com/)** — Git hooks framework
### LLM & embedding providers
EverOS is provider-agnostic by design. Tested provider integrations include
OpenAI, Anthropic, Ollama, and SBERT. See [`component/llm/`](src/everos/component/llm/)
and [`component/embedding/`](src/everos/component/embedding/) for the
adapter layouts.
---
## Contributors
Thanks to all the developers who have contributed to this project.
See the full list of contributors on
[GitHub](https://github.com/EverMind-AI/EverOS/graphs/contributors).
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---
## Community
Thanks to our community for valuable feedback, bug reports, and feature
suggestions:
- **GitHub Issues & Discussions** — bug reports and feature requests
- **Discord** — [Join our Discord server](https://discord.gg/pfwwskxp)
- **X / Twitter** — [@EverMindAI](https://x.com/EverMindAI)
---
## Supporting organizations
- **Shanda Group** — for supporting the development of EverOS
---
## Special thanks
- To everyone who starred the repository
- To those who shared EverOS with others
- To researchers and developers using EverOS in their work
---
## Want to contribute?
Contributions are welcome! See the [Contributing Guide](CONTRIBUTING.md)
to get started.
---
## See also
- [Citation](CITATION.md)
- [Changelog](CHANGELOG.md)
- [Contributing Guide](CONTRIBUTING.md)