pyproject.toml

[build-system]
requires = ["setuptools>=61.0"]
build-backend = "setuptools.build_meta"

[project]
name = "proactive-cache"
version = "0.1.0"
description = "Make any HuggingFace transformer O(n) with proactive KV cache eviction"
readme = "README.md"
license = { file = "LICENSE" }
authors = [{ name = "S Khavin", email = "skhavin.res@gmail.com" }]
keywords = ["llm", "kv-cache", "inference", "transformers", "efficiency", "attention"]
classifiers = [
    "Development Status :: 3 - Alpha",
    "Intended Audience :: Science/Research",
    "License :: OSI Approved :: GNU Affero General Public License v3 (AGPLv3)",
    "Programming Language :: Python :: 3",
    "Programming Language :: Python :: 3.9",
    "Programming Language :: Python :: 3.10",
    "Programming Language :: Python :: 3.11",
    "Topic :: Scientific/Engineering :: Artificial Intelligence",
]
requires-python = ">=3.9"
dependencies = [
    "torch>=2.1.0",
    "transformers>=4.38.0",
    "numpy>=1.24.0",
    "scikit-learn>=1.3.0",
    "tqdm>=4.65.0",
    "datasets>=2.14.0",
]

[project.optional-dependencies]
dev = ["pytest>=7.0", "pytest-cov", "ruff"]
kvpress = ["kvpress"]
gradio = ["gradio>=4.0", "spaces"]

[project.urls]
Homepage = "https://github.com/skhavin/proactive-cache"
Repository = "https://github.com/skhavin/proactive-cache"
"Bug Tracker" = "https://github.com/skhavin/proactive-cache/issues"
Paper = "https://github.com/skhavin/supertransformers"

[tool.setuptools.packages.find]
where = ["."]
include = ["proactive_cache*"]

[tool.ruff]
line-length = 100
target-version = "py39"

[tool.pytest.ini_options]
testpaths = ["tests"]