mirror of https://github.com/microsoft/autogen.git
132 lines
4.0 KiB
Python
132 lines
4.0 KiB
Python
import os
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import platform
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import setuptools
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here = os.path.abspath(os.path.dirname(__file__))
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with open("README.md", "r", encoding="UTF-8") as fh:
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long_description = fh.read()
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# Get the code version
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version = {}
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with open(os.path.join(here, "autogen/version.py")) as fp:
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exec(fp.read(), version)
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__version__ = version["__version__"]
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current_os = platform.system()
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install_requires = [
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"openai>=1.3",
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"diskcache",
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"termcolor",
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"flaml",
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# numpy is installed by flaml, but we want to pin the version to below 2.x (see https://github.com/microsoft/autogen/issues/1960)
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"numpy>=1.17.0,<2",
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"python-dotenv",
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"tiktoken",
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# Disallowing 2.6.0 can be removed when this is fixed https://github.com/pydantic/pydantic/issues/8705
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"pydantic>=1.10,<3,!=2.6.0", # could be both V1 and V2
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"docker",
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"packaging",
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]
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jupyter_executor = [
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"jupyter-kernel-gateway",
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"websocket-client",
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"requests",
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"jupyter-client>=8.6.0",
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"ipykernel>=6.29.0",
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]
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retrieve_chat = [
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"protobuf==4.25.3",
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"chromadb",
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"sentence_transformers",
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"pypdf",
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"ipython",
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"beautifulsoup4",
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"markdownify",
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]
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retrieve_chat_pgvector = [*retrieve_chat, "pgvector>=0.2.5"]
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if current_os in ["Windows", "Darwin"]:
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retrieve_chat_pgvector.extend(["psycopg[binary]>=3.1.18"])
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elif current_os == "Linux":
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retrieve_chat_pgvector.extend(["psycopg>=3.1.18"])
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extra_require = {
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"test": [
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"ipykernel",
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"nbconvert",
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"nbformat",
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"pre-commit",
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"pytest-cov>=5",
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"pytest-asyncio",
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"pytest>=6.1.1,<8",
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"pandas",
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],
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"blendsearch": ["flaml[blendsearch]"],
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"mathchat": ["sympy", "pydantic==1.10.9", "wolframalpha"],
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"retrievechat": retrieve_chat,
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"retrievechat-pgvector": retrieve_chat_pgvector,
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"retrievechat-mongodb": [*retrieve_chat, "pymongo>=4.0.0"],
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"retrievechat-qdrant": [*retrieve_chat, "qdrant_client", "fastembed>=0.3.1"],
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"retrievechat-couchbase": [*retrieve_chat, "couchbase>=4.3.0"],
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"autobuild": ["chromadb", "sentence-transformers", "huggingface-hub", "pysqlite3"],
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"teachable": ["chromadb"],
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"lmm": ["replicate", "pillow"],
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"graph": ["networkx", "matplotlib"],
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"gemini": ["google-generativeai>=0.5,<1", "google-cloud-aiplatform", "google-auth", "pillow", "pydantic"],
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"together": ["together>=1.2"],
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"websurfer": [
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"beautifulsoup4",
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"markdownify",
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"pathvalidate",
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# for mdconvert
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"puremagic", # File identification
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"pdfminer.six", # Pdf
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"mammoth", # Docx
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"python-pptx", # Ppts
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"pandas", # Xlsx
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"openpyxl",
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"youtube_transcript_api==0.6.0", # Transcription
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],
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"redis": ["redis"],
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"cosmosdb": ["azure-cosmos>=4.2.0"],
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"websockets": ["websockets>=12.0,<13"],
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"jupyter-executor": jupyter_executor,
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"types": ["mypy==1.9.0", "pytest>=6.1.1,<8"] + jupyter_executor,
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"long-context": ["llmlingua<0.3"],
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"anthropic": ["anthropic>=0.23.1"],
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"cerebras": ["cerebras_cloud_sdk>=1.0.0"],
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"mistral": ["mistralai>=1.0.1"],
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"groq": ["groq>=0.9.0"],
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"cohere": ["cohere>=5.5.8"],
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"ollama": ["ollama>=0.3.3", "fix_busted_json>=0.0.18"],
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"bedrock": ["boto3>=1.34.149"],
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"kubernetes": ["kubernetes>=27.2.0"],
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}
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setuptools.setup(
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name="autogen-agentchat",
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version=__version__,
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author="AutoGen",
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author_email="autogen@microsoft.com",
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description="Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework",
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long_description=long_description,
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long_description_content_type="text/markdown",
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url="https://github.com/microsoft/autogen",
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packages=setuptools.find_packages(include=["autogen*"], exclude=["test"]),
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install_requires=install_requires,
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extras_require=extra_require,
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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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python_requires=">=3.8,<3.13",
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)
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