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setup.py
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77 lines (74 loc) · 2.43 KB
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"""Setup script for WebMainBench."""
from setuptools import setup, find_packages
with open("README.md", "r", encoding="utf-8") as fh:
long_description = fh.read()
setup(
name="webmainbench",
version="0.1.0",
author="WebMainBench Team",
author_email="chupei@pjlab.org.cn",
description="A comprehensive benchmark for web main content extraction",
long_description=long_description,
long_description_content_type="text/markdown",
url="https://github.com/opendatalab/WebMainBench",
packages=find_packages(),
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: Apache Software License",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Software Development :: Libraries :: Python Modules",
"Topic :: Text Processing :: Markup :: HTML",
],
python_requires=">=3.8",
install_requires=[
"lxml>=5.3.0",
"jsonlines>=3.1.0",
"requests>=2.28.0",
"beautifulsoup4>=4.12.0",
"numpy>=1.21.0,<2.0.0", # Avoid NumPy 2.x compatibility issues
"rapidfuzz>=3.0.0", # For text edit distance calculation
"apted>=1.0.3", # For tree edit distance calculation (TEDS)
"jieba>=0.42.0", # For Chinese word segmentation
"rouge>=1.0.0", # For ROUGE metrics
],
extras_require={
"all": [
"nltk>=3.8",
"rouge-score>=0.1.2",
"unstructured>=0.10.0",
],
"llm": [
"torch==2.6.0",
"transformers==4.52.4",
"vllm==0.8.5.post1",
"llm_web_kit>=3.0.0",
],
"nlp": [
"nltk>=3.8",
"rouge-score>=0.1.2",
],
"unstructured": [
"unstructured>=0.10.0",
],
"dev": [
"pytest>=7.0",
"pytest-cov>=4.0",
"black>=22.0",
"isort>=5.0",
"flake8>=5.0",
],
},
entry_points={
"console_scripts": [
"webmainbench=webmainbench.cli:main",
],
},
)