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d22b6b2006
* Initial commit. * Disable LLM response caching. * Add teachability option to setup.py * Modify test to use OAI_CONFIG_LIST as suggested in the docs. * Expand unit test. * Complete unit test. * Add filter_dict * details * AnalysisAgent * details * More documentation and debug output. * Support retrieval of any number of relevant memos, including zero. * More robust analysis separator. * cleanup * teach_config * refactoring * For robustness, allow more flexibility on memo storage and retrieval. * de-dupe the retrieved memos. * Simplify AnalysisAgent. The unit tests now pass with gpt-3.5 * comments * Add a verbosity level to control analyzer messages. * refactoring * comments * Persist memory on disk. * cleanup * Use markdown to format retrieved memos. * Use markdown in TextAnalyzerAgent * Add another verbosity level. * clean up logging * notebook * minor edits * cleanup * linter fixes * Skip tests that fail to import openai * Address reviewer feedback. * lint * refactoring * Improve wording * Improve code coverage. * lint * Use llm_config to control caching. * lowercase notebook name * Sort out the parameters passed through to ConversableAgent, and supply full docstrings for the others. * lint * Allow TextAnalyzerAgent to be given a different llm_config than TeachableAgent. * documentation * Modifications to run openai workflow. * Test on just python 3.10. Replace agent with agent teachable_agent as recommended. * Test on python 3.9 instead of 3.10. * Remove space from name -> teachableagent --------- Co-authored-by: Li Jiang <bnujli@gmail.com> Co-authored-by: Chi Wang <wang.chi@microsoft.com>
69 lines
1.8 KiB
Python
69 lines
1.8 KiB
Python
import setuptools
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import os
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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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install_requires = [
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"openai",
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"diskcache",
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"termcolor",
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"flaml",
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"python-dotenv",
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]
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setuptools.setup(
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name="pyautogen",
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version=__version__,
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author="AutoGen",
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author_email="auto-gen@outlook.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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# package_data={
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# "autogen.default": ["*/*.json"],
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# },
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# include_package_data=True,
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install_requires=install_requires,
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extras_require={
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"test": [
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"chromadb",
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"lancedb",
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"coverage>=5.3",
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"datasets",
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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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"pydantic==1.10.9",
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"pytest-asyncio",
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"pytest>=6.1.1",
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"sympy",
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"tiktoken",
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"wolframalpha",
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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": ["chromadb", "tiktoken", "sentence_transformers", "pypdf"],
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"teachable": ["chromadb"],
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},
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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",
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)
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