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update contact information on the repo and release package #3383

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Aug 20, 2024
Merged

update contact information on the repo and release package #3383

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702c609
update contact information on the repo and release package
ekzhu Aug 19, 2024
501b547
update contact
ekzhu Aug 19, 2024
433319f
update
ekzhu Aug 19, 2024
7e61912
fix format
ekzhu Aug 19, 2024
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5 changes: 0 additions & 5 deletions README.md
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AutoGen is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks. AutoGen aims to streamline the development and research of agentic AI, much like PyTorch does for Deep Learning. It offers features such as agents capable of interacting with each other, facilitates the use of various large language models (LLMs) and tool use support, autonomous and human-in-the-loop workflows, and multi-agent conversation patterns.

**Open Source Statement**: The project welcomes contributions from developers and organizations worldwide. Our goal is to foster a collaborative and inclusive community where diverse perspectives and expertise can drive innovation and enhance the project's capabilities. Whether you are an individual contributor or represent an organization, we invite you to join us in shaping the future of this project. Together, we can build something truly remarkable.
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The project is currently maintained by a [dynamic group of volunteers](https://butternut-swordtail-8a5.notion.site/410675be605442d3ada9a42eb4dfef30?v=fa5d0a79fd3d4c0f9c112951b2831cbb&pvs=4) from several different organizations. Contact project administrators Chi Wang and Qingyun Wu via [email protected] if you are interested in becoming a maintainer.
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![AutoGen Overview](https://github.com/microsoft/autogen/blob/main/website/static/img/autogen_agentchat.png)

- AutoGen enables building next-gen LLM applications based on [multi-agent conversations](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat) with minimal effort. It simplifies the orchestration, automation, and optimization of a complex LLM workflow. It maximizes the performance of LLM models and overcomes their weaknesses.
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2 changes: 1 addition & 1 deletion samples/tools/autogenbench/pyproject.toml
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Expand Up @@ -5,7 +5,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "autogenbench"
authors = [
{ name="Autogen Team", email="auto-gen@outlook.com" },
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{ name="Autogen Team", email="[email protected].com" },
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]
description = "AutoGen Testbed Tools"
readme = "README.md"
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2 changes: 1 addition & 1 deletion setup.py
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name="pyautogen",
version=__version__,
author="AutoGen",
author_email="auto-gen@outlook.com",
author_email="[email protected].com",
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description="Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework",
long_description=long_description,
long_description_content_type="text/markdown",
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3 changes: 0 additions & 3 deletions website/docs/contributor-guide/contributing.md
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Expand Up @@ -33,6 +33,3 @@ To see what we are working on and what we plan to work on, please check our

There is currently no formal reviewer solicitation process. Current reviewers identify reviewers from active contributors. If you are willing to become a reviewer, you are welcome to let us know on discord.

## Contact Maintainers

The project is currently maintained by a [dynamic group of volunteers](https://butternut-swordtail-8a5.notion.site/410675be605442d3ada9a42eb4dfef30?v=fa5d0a79fd3d4c0f9c112951b2831cbb&pvs=4) from several different organizations. Contact project administrators Chi Wang and Qingyun Wu via [email protected] if you are interested in becoming a maintainer.
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