pyproject.toml

[build-system]
requires = ["setuptools>=68.0"]
build-backend = "setuptools.build_meta"

[project]
name = "mnemosyne-engine"
version = "1.0.4"
description = "LLM Context Compression and Retrieval Engine — zero dependencies, sub-100ms queries, 40-70% token reduction"
readme = "README.md"
requires-python = ">=3.11"
license = "AGPL-3.0-or-later"
authors = [{name = "Cast Rock Innovation L.L.C."}]
keywords = ["llm", "context", "compression", "retrieval", "token", "mnemosyne", "code-search", "bm25", "tfidf"]
classifiers = [
    "Development Status :: 5 - Production/Stable",
    "Intended Audience :: Developers",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.11",
    "Programming Language :: Python :: 3.12",
    "Programming Language :: Python :: 3.13",
    "Topic :: Software Development :: Libraries",
    "Topic :: Text Processing :: Indexing",
    "Typing :: Typed",
]

[project.urls]
Homepage = "https://castnettechnology.com"
Repository = "https://github.com/castnettech/mnemosyne"
Documentation = "https://github.com/castnettech/mnemosyne#readme"
Issues = "https://github.com/castnettech/mnemosyne/issues"

[project.scripts]
mnemosyne = "mnemosyne.cli:main"

[project.optional-dependencies]
dense = ["onnxruntime>=1.17"]
dev = ["pytest>=8.3"]

[tool.setuptools.packages.find]
include = ["mnemosyne*"]

[tool.pytest.ini_options]
testpaths = ["mnemosyne/tests"]
markers = [
    "benchmark: Httpx regression benchmark (requires network for first run)",
]