2019-11-27 14:02:23 +01:00
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from io import open
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from setuptools import find_packages, setup
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with open("requirements.txt") as f:
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parsed_requirements = f.read().splitlines()
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# remove blank lines and comments
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parsed_requirements = [
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x.strip()
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for x in parsed_requirements
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if ((x.strip()[0] != "#") and (len(x.strip()) > 3))
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]
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setup(
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2019-11-27 16:17:45 +01:00
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name="farm-haystack",
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2019-11-27 14:02:23 +01:00
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version="0.1.0",
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author="Malte Pietsch, Timo Moeller, Branden Chan, Tanay Soni",
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author_email="malte.pietsch@deepset.ai",
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description="Neural Question Answering at Scale. Use modern transformer based models like BERT to find answers in large document collections",
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long_description=open("readme.rst", "r", encoding="utf-8").read(),
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long_description_content_type="text/x-rst",
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keywords="QA Question-Answering Reader Retriever BERT roberta albert squad mrc transfer-learning language-model transformer",
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license="Apache",
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url="https://github.com/deepset-ai/haystack",
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download_url="https://github.com/deepset-ai/haystack/archive/0.1.0.tar.gz",
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packages=find_packages(exclude=["*.tests", "*.tests.*", "tests.*", "tests"]),
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install_requires=parsed_requirements,
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python_requires=">=3.6.0",
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tests_require=["pytest"],
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classifiers=[
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"Intended Audience :: Science/Research",
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"License :: OSI Approved :: Apache Software License",
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"Programming Language :: Python :: 3",
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"Topic :: Scientific/Engineering :: Artificial Intelligence",
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],
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)
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