[project]
name = "llm-verify"
version = "0.1.0"
description = "Detect fake AI APIs — LLM fingerprinting toolkit to verify model identity and catch AI model fraud"
readme = "README.md"
requires-python = ">=3.12"
license = { text = "MIT" }

dependencies = [
    "fastapi>=0.115.0",
    "uvicorn[standard]>=0.32.0",
    "pydantic>=2.10.0",
    "pydantic-settings>=2.7.0",
    "httpx>=0.28.0",
    "sqlalchemy[asyncio]>=2.0.36",
    "aiosqlite>=0.20.0",
    "alembic>=1.14.0",
    "structlog>=24.4.0",
    "python-dotenv>=1.0.0",
]

[project.optional-dependencies]
dev = [
    "pytest>=8.3.0",
    "pytest-asyncio>=0.24.0",
    "pytest-cov>=6.0.0",
    "httpx",  # for TestClient
    "ruff>=0.8.0",
    "mypy>=1.13.0",
]

[project.scripts]
benchmarker = "src.cli:main"

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

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

[tool.ruff]
target-version = "py312"
line-length = 100

[tool.ruff.lint]
select = [
    "E",    # pycodestyle errors
    "W",    # pycodestyle warnings
    "F",    # pyflakes
    "I",    # isort
    "N",    # pep8-naming
    "UP",   # pyupgrade
    "B",    # flake8-bugbear
    "SIM",  # flake8-simplify
    "TCH",  # flake8-type-checking
    "RUF",  # ruff-specific rules
]
ignore = ["E501"]  # line length handled by formatter

[tool.ruff.lint.isort]
known-first-party = ["src"]

[tool.pytest.ini_options]
testpaths = ["tests"]
asyncio_mode = "auto"
pythonpath = ["."]

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