Files
mempalace/CONTRIBUTING.md
T
Igor Lins e Silva c35686c9e1 docs(install): recommend uv as the package manager
End-user installs now lead with `uv tool install mempalace`, with
`pip install mempalace` kept as a fallback. Dev/contributor docs lead
with `uv sync --extra dev` and `uv run` for tests/benchmarks/lint, with
the equivalent pip recipe kept inline. The shipped `/mempalace:init`
skill instructions (mempalace/instructions/init.md) try `uv tool install`
first when uv is on PATH, then fall back through the pip variants.

Adds a .python-version pin at 3.12 because the lockfile's
onnxruntime==1.24.3 only ships wheels for Python >=3.11; without the
pin, `uv sync` on a host where uv prefers 3.10 fails with no source
distribution available, which would make the documented command a
footgun. pyproject's `requires-python = ">=3.9"` is unchanged — pip
users on 3.9/3.10 are unaffected.

Files updated: README.md, CONTRIBUTING.md, CLAUDE.md, the gemini-cli
guide and example, the .claude-plugin / .codex-plugin READMEs, the
mempalace SKILL, the openclaw SKILL, tools/save.md, the three
benchmarks docs, and the corresponding website mirrors.
2026-05-08 01:38:00 -03:00

3.7 KiB

Contributing to MemPalace

Thanks for wanting to help. MemPalace is open source and we welcome contributions of all sizes — from typo fixes to new features.

Getting Started

# Fork the repo on GitHub first, then clone your fork
git clone https://github.com/<your-username>/mempalace.git
cd mempalace
git remote add upstream https://github.com/MemPalace/mempalace.git

# Recommended: uv (https://docs.astral.sh/uv/) handles the venv for you
uv sync --extra dev

# Or with pip in your own venv:
# pip install -e ".[dev]"

Running Tests

uv run pytest tests/ -v

All tests must pass before submitting a PR. Tests should run without API keys or network access.

Running Benchmarks

# Quick test (20 questions, ~30 seconds)
uv run python benchmarks/longmemeval_bench.py /path/to/longmemeval_s_cleaned.json --limit 20

# Full benchmark (500 questions, ~5 minutes)
uv run python benchmarks/longmemeval_bench.py /path/to/longmemeval_s_cleaned.json

See benchmarks/README.md for data download instructions and reproduction guide.

Project Structure

mempalace/          ← core package (see mempalace/README.md for module guide)
benchmarks/         ← reproducible benchmark runners
hooks/              ← Claude Code auto-save hooks
examples/           ← usage examples
tests/              ← test suite
assets/             ← logo + brand

PR Guidelines

  1. Fork the repo and create a feature branch: git checkout -b feat/my-thing
  2. Write your code
  3. Add or update tests if applicable
  4. Run uv run pytest tests/ -v — everything must pass
  5. Commit with a clear message following conventional commits:
    • feat: add Notion export format
    • fix: handle empty transcript files
    • docs: update MCP tool descriptions
    • bench: add LoCoMo turn-level metrics
  6. Push to your fork and open a PR against develop

Code Style

  • Formatting: Ruff with 100-char line limit (configured in pyproject.toml)
  • Naming: snake_case for functions/variables, PascalCase for classes
  • Docstrings: on all modules and public functions
  • Type hints: where they improve readability
  • Dependencies: minimize. ChromaDB + PyYAML only. Don't add new deps without discussion.

Good First Issues

Check the Issues tab. Great starting points:

  • New chat formats: Add import support for Cursor, Copilot, or other AI tool exports
  • Room detection: Improve pattern matching in room_detector_local.py
  • Tests: Increase coverage — especially for knowledge_graph.py and palace_graph.py
  • Entity detection: Better name disambiguation in entity_detector.py
  • Docs: Improve examples, add tutorials

Architecture Decisions

If you're planning a significant change, open an issue first to discuss the approach. Key principles:

  • Verbatim first: Never summarize user content. Store exact words.
  • Local first: Everything runs on the user's machine. No cloud dependencies.
  • Zero API by default: Core features must work without any API key.
  • Palace structure is scoping, not magic: Wings, halls, and rooms act as metadata filters in the underlying vector store. They keep retrieval predictable when a palace holds many unrelated projects or people. Respect the hierarchy — but don't present it as a novel retrieval mechanism.

Community

  • Discord: Join us
  • Issues: Bug reports and feature requests welcome
  • Discussions: For questions and ideas

License

MIT — your contributions will be released under the same license.