pyproject.toml

[project]
name = "memorylayer-server"
version = "0.0.6"
description = "MemoryLayer.ai - API-first memory infrastructure for LLM-powered agents (open source core)"
readme = "README.md"
requires-python = ">=3.12"
license = { text = "Apache 2.0" }
authors = [
    { name = "Scitrera", email = "open-source-team@scitrera.com" }
]
keywords = ["ai", "memory", "agents", "llm", "vector-search", "rag"]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Developers",
    "License :: OSI Approved :: Apache Software License",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.12",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
]

dependencies = [
    "scitrera-app-framework>=0.0.69",
    "scitrera-rt-data>=0.0.7",
    "scitrera-ext-cachetools>=0.0.1",
    "fastapi>=0.128.7",
    "uvicorn[standard]>=0.30.0",
    "pydantic>=2.12.5",
    "pydantic-settings>=2.12.0",
    "sqlalchemy[asyncio]>=2.0.46",
    "aiosqlite>=0.22.1",
    "sqlite-vec>=0.1.7a2", # NOTE: prerelease version required for proper arm64 support without custom rerelease
    "numpy>2.0.0",
    "httpx>=0.28.1",
    "python-multipart>=0.0.22",
    "click>=8.3.1",
]

[project.optional-dependencies]
# OpenAI API embeddings and LLM (bring your own key)
openai = [
    "openai>=2.18.0",
    "tiktoken>=0.12.0",
]

# Anthropic Claude LLM provider
anthropic = [
    "anthropic>=0.79.0",
]

# Google GenAI (Gemini) LLM provider
google = [
    "google-genai>=1.62.0",
]

# Local embedding providers (sentence-transformers)
local = [
    "sentence-transformers>=5.2.2",
]

# Context environment sandbox executor
context = [
    "smolagents>=1.0,<2.0",
]

# All embedding providers
embeddings = [
    "memorylayer-server[openai,local,google]",
]

# Development dependencies
dev = [
    "pytest>=9.0.2",
    "pytest-asyncio>=1.3.0",
    "pytest-cov>=7.0.0",
    "respx>=0.22.0",
    "ruff>=0.15.0",
    "mypy>=1.19.1",
]

# LLM providers (bring your own key)
llm = [
    "memorylayer-server[openai,anthropic,google]",
]

# Full installation with all features (excludes dev tools)
all = [
    "memorylayer-server[embeddings,llm,context]",
]

[project.scripts]
memorylayer = "memorylayer_server.cli:cli"

[project.urls]
Homepage = "https://memorylayer.ai"
Documentation = "https://docs.memorylayer.ai"
Repository = "https://github.com/scitrera/memorylayer"
Issues = "https://github.com/scitrera/memorylayer/issues"

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[tool.hatch.build.targets.wheel]
packages = ["src/memorylayer_server"]

[tool.hatch.build.targets.sdist]
include = ["src/memorylayer_server"]

[tool.ruff]
line-length = 140
target-version = "py312"

[tool.ruff.lint]
select = ["E", "F", "I", "N", "W", "UP"]
ignore = [
    "E402",   # module-level imports not at top — lazy imports used to avoid circular deps
    "E501",   # line too long — handled by formatter, some long strings intentional
    "UP042",  # str+Enum inheritance — StrEnum requires Python 3.11+ migration
    "UP031",  # printf-style formatting — used intentionally in logging
    "F841",   # unused variables — some intentional in batch/pipeline patterns
    "F821",   # undefined name — forward references and dynamic imports
    "N806",   # variable in function should be lowercase — established naming conventions
]

[tool.pytest.ini_options]
asyncio_mode = "auto"
testpaths = ["tests"]
markers = [
    "slow: marks tests as slow (deselect with '-m \"not slow\"')",
    "integration: marks tests as integration tests (deselect with '-m \"not integration\"')",
    "llm: marks tests requiring a live LLM provider (deselect with '-m \"not llm\"')",
    "llm_quality: marks LLM output quality tests (deselect with '-m \"not llm_quality\"')",
]

[tool.mypy]
python_version = "3.12"
strict = false
warn_return_any = true
warn_unused_configs = true