/
setup.py
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setup.py
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# pylint: disable = C0111
from setuptools import find_packages, setup
with open("README.md", "r", encoding="utf-8") as f:
# Remove GitHub dark mode images
DESCRIPTION = "".join([line for line in f if "gh-dark-mode-only" not in line])
# Required dependencies
install = ["faiss-cpu>=1.7.1.post2", "torch>=1.12.1", "transformers>=4.28.0"]
# Required dependencies that are also transformers dependencies
install += ["huggingface-hub>=0.9.0", "numpy>=1.18.4", "pyyaml>=5.3", "regex>=2022.8.17"]
# Optional dependencies
extras = {}
# Development dependencies - not included in "all" install
extras["dev"] = [
"black",
"coverage",
"coveralls",
"httpx",
"mkdocs-material",
"mkdocs-redirects",
"mkdocstrings[python]",
"pre-commit",
"pylint",
]
extras["ann"] = [
"annoy>=1.16.3",
"hnswlib>=0.5.0",
"pgvector>=0.2.5",
"sqlalchemy>=2.0.20",
]
extras["api"] = [
"aiohttp>=3.8.1",
"fastapi>=0.94.0",
"msgpack>=1.0.7",
"pillow>=7.1.2",
"python-multipart>=0.0.7",
"uvicorn>=0.12.1",
]
extras["cloud"] = ["apache-libcloud>=3.3.1"]
extras["console"] = ["rich>=12.0.1"]
extras["database"] = ["duckdb>=0.7.1", "pillow>=7.1.2", "sqlalchemy>=2.0.20"]
extras["graph"] = ["grand-cypher>=0.6.0", "grand-graph>=0.5.0", "networkx>=2.6.3", "python-louvain>=0.16", "sqlalchemy>=2.0.20"]
extras["model"] = ["onnx>=1.11.0", "onnxruntime>=1.11.0"]
extras["pipeline-audio"] = ["onnx>=1.11.0", "onnxruntime>=1.11.0", "soundfile>=0.10.3.post1", "scipy>=1.4.1", "ttstokenizer>=1.0.0"]
extras["pipeline-data"] = ["beautifulsoup4>=4.9.3", "nltk>=3.5", "pandas>=1.1.0", "tika>=1.24"]
extras["pipeline-image"] = ["imagehash>=4.2.1", "pillow>=7.1.2", "timm>=0.4.12"]
extras["pipeline-llm"] = ["litellm>=1.37.16", "llama-cpp-python>=0.2.75"]
extras["pipeline-text"] = ["fasttext>=0.9.2", "sentencepiece>=0.1.91"]
extras["pipeline-train"] = [
"accelerate>=0.26.0",
"bitsandbytes>=0.42.0",
"onnx>=1.11.0",
"onnxmltools>=1.9.1",
"onnxruntime>=1.11.0",
"peft>=0.8.1",
"skl2onnx>=1.9.1",
]
extras["pipeline"] = (
extras["pipeline-audio"]
+ extras["pipeline-data"]
+ extras["pipeline-image"]
+ extras["pipeline-llm"]
+ extras["pipeline-text"]
+ extras["pipeline-train"]
)
extras["scoring"] = ["sqlalchemy>=2.0.20"]
extras["vectors"] = [
"fasttext>=0.9.2",
"pymagnitude-lite>=0.1.43",
"scikit-learn>=0.23.1",
"sentence-transformers>=2.2.0",
]
extras["workflow"] = [
"apache-libcloud>=3.3.1",
"croniter>=1.2.0",
"openpyxl>=3.0.9",
"pandas>=1.1.0",
"pillow>=7.1.2",
"requests>=2.26.0",
"xmltodict>=0.12.0",
]
# Backwards-compatible combination of ann and vectors extra
extras["similarity"] = extras["ann"] + extras["vectors"]
extras["all"] = (
extras["api"]
+ extras["cloud"]
+ extras["console"]
+ extras["database"]
+ extras["graph"]
+ extras["model"]
+ extras["pipeline"]
+ extras["scoring"]
+ extras["similarity"]
+ extras["workflow"]
)
setup(
name="txtai",
version="7.2.0",
author="NeuML",
description="All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows",
long_description=DESCRIPTION,
long_description_content_type="text/markdown",
url="https://github.com/neuml/txtai",
project_urls={
"Documentation": "https://github.com/neuml/txtai",
"Issue Tracker": "https://github.com/neuml/txtai/issues",
"Source Code": "https://github.com/neuml/txtai",
},
license="Apache 2.0: http://www.apache.org/licenses/LICENSE-2.0",
packages=find_packages(where="src/python"),
package_dir={"": "src/python"},
keywords="search embedding machine-learning nlp",
python_requires=">=3.8",
install_requires=install,
extras_require=extras,
classifiers=[
"License :: OSI Approved :: Apache Software License",
"Operating System :: OS Independent",
"Programming Language :: Python :: 3",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Software Development",
"Topic :: Text Processing :: Indexing",
"Topic :: Utilities",
],
)