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# Copyright (c) 2023 Microsoft
# Licensed under The MIT License [see LICENSE for details]
from setuptools import find_packages, setup
# PEP0440 compatible formatted version, see:
# https://www.python.org/dev/peps/pep-0440/
#
# release markers:
# X.Y
# X.Y.Z # For bugfix releases
#
# pre-release markers:
# X.YaN # Alpha release
# X.YbN # Beta release
# X.YrcN # Release Candidate
# X.Y # Final release
# version.py defines the VERSION and VERSION_SHORT variables.
# We use exec here so we don't import allennlp whilst setting up.
VERSION = {} # type: ignore
with open("llmlingua/version.py", "r") as version_file:
exec(version_file.read(), VERSION)
INSTALL_REQUIRES = [
"transformers>=4.26.0",
"accelerate",
"torch",
"tiktoken",
"nltk",
"numpy",
]
QUANLITY_REQUIRES = [
"black==21.4b0",
"flake8>=3.8.3",
"isort>=5.5.4",
"pre-commit",
"pytest",
"pytest-xdist",
]
DEV_REQUIRES = INSTALL_REQUIRES + QUANLITY_REQUIRES
setup(
name="llmlingua",
version=VERSION["VERSION"],
author="The LLMLingua team",
author_email="hjiang@microsoft.com",
description="To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.",
long_description=open("README.md", encoding="utf8").read(),
long_description_content_type="text/markdown",
keywords="Prompt Compression, LLMs, Inference Acceleration, Black-box LLMs, Efficient LLMs",
license="MIT License",
url="https://github.com/microsoft/LLMLingua",
classifiers=[
"Intended Audience :: Science/Research",
"Development Status :: 3 - Alpha",
"Programming Language :: Python :: 3",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
],
package_dir={"": "."},
packages=find_packages("."),
extras_require={
"dev": DEV_REQUIRES,
"quality": QUANLITY_REQUIRES,
},
install_requires=INSTALL_REQUIRES,
include_package_data=True,
python_requires=">=3.8.0",
zip_safe=False,
)
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