Design the base interface of vector store, and apply it to the Chroma Vector Store (wrapped around llama_index's implementation). Provide the pipelines to populate and retrieve from vector store.
61 lines
1.5 KiB
Python
61 lines
1.5 KiB
Python
import codecs
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import re
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from pathlib import Path
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import setuptools
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def read(file_path: str) -> str:
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return codecs.open(file_path, "r").read()
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def get_version() -> str:
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version_file = read(str(Path("kotaemon", "__init__.py")))
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match = re.search(r"^__version__ = ['\"]([^'\"]*)['\"]", version_file, re.M)
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if match:
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return match.group(1)
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raise RuntimeError("Cannot find verison string")
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setuptools.setup(
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name="kotaemon",
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version=get_version(),
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author="john",
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author_email="john@cinnamon.com",
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description="Kotaemon core library for AI development",
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long_description=read("README.md"),
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long_description_content_type="text/markdown",
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url="https://github.com/Cinnamon/kotaemon/",
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packages=setuptools.find_packages(exclude=("tests", "tests.*")),
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install_requires=[
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"farm-haystack==1.19.0",
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"langchain",
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"theflow",
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"llama-index",
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"llama-hub",
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"nltk",
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],
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extras_require={
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"dev": [
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"ipython",
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"pytest",
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"pre-commit",
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"black",
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"flake8",
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"sphinx",
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"coverage",
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# optional dependency needed for test
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"openai",
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"chromadb",
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],
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},
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entry_points={"console_scripts": ["kh=kotaemon.cli:main"]},
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python_requires=">=3",
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classifiers=[
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"Programming Language :: Python :: 3",
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"License :: OSI Approved :: MIT License",
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"Operating System :: OS Independent",
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],
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include_package_data=True,
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)
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