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https://github.com/alipay/agentUniverse

agentUniverse is a LLM multi-agent framework that allows developers to easily build multi-agent applications. Furthermore, through the community, they can exchange and share practices of patterns across different domains.
https://github.com/alipay/agentUniverse

List: agentUniverse

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agentUniverse is a LLM multi-agent framework that allows developers to easily build multi-agent applications. Furthermore, through the community, they can exchange and share practices of patterns across different domains.

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README

        

# agentUniverse
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Language version: [English](./README.md) | [中文](./README_zh.md) | [日本語](./README_jp.md)

![](https://img.shields.io/badge/framework-agentUniverse-pink)
![](https://img.shields.io/badge/python-3.10%2B-blue?logo=Python)
[![](https://img.shields.io/badge/%20license-Apache--2.0-yellow)](LICENSE)
[![Static Badge](https://img.shields.io/badge/pypi-v0.0.9-blue?logo=pypi)](https://pypi.org/project/agentUniverse/)

![](docs/guidebook/_picture/logo_bar.jpg)
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## Overview
agentUniverse is a framework for developing applications powered by multi-agent base on large language model. It provides all the essential components for building a single agent, and a multi-agent collaboration mechanism which serves as a pattern factory that allowing developers to buid and customize multi-agent collaboration patterns. With this framework, developers can easily construct multi-agent applications, and share the pattern practices from different technical and business fields.

The framework will come with serveral pre-install multi-agent collaboration patterns which have been proven effective in real business scenarios, and will continue to be enriched in the future. Patterns that are currently about to be released include:

- PEER pattern:
This pattern utilizes four distinct agent roles: Plan, Execute, Express, and Review, to achieve a multi-step breakdown and sequential execution of a complex task. It also performs autonomous iteration based on evaluative feedback which enhancing performance in reasoning and analytical tasks.

- DOE pattern:
This pattern consists of three agents: Data-fining agent, which is designed to solve data-intensive and high-computational-precision task; Opinion-inject agent, which combines the data results from first agent and the expert opinions which are pre-collected and structured; the third agent, Express agent generates the final result base on given document type and language style.

More patterns are coming soon...

![](docs/guidebook/_picture/agent_universe_framework_resize.jpg)

## agentUniverseSample Project
[agentUniverse Sample Project](sample_standard_app/README.md)

## Quick Installation
Using pip:
```shell
pip install agentUniverse
```

## Quick Start
We will show you how to:
* Prepare the environment and application project
* Build a simple agent
* Use pattern components to complete multi-agent collaboration
* Test and optimize the performance of the agent
* Quickly serve the agent
For details, please read [Quick Start](docs/guidebook/en/1_3_Quick_Start.md).

## Use Cases
[Legal Consultation Agent](./docs/guidebook/en/7_1_1_Legal_Consultation_Case.md)

[Python Code Generation and Execution Agent](./docs/guidebook/en/7_1_1_Python_Auto_Runner.md)

[Discussion Group Based on Multi-Turn Multi-Agent Mode](./docs/guidebook/en/6_2_1_Discussion_Group.md)

## Guidebook
For more detailed information, please refer to the [Guidebook](docs/guidebook/en/0_index.md).

## API Reference
[readthedocs](https://agentuniverse.readthedocs.io/en/latest/)

## More Ways to Contact Us
* github: https://github.com/alipay/agentUniverse
* gitee: https://gitee.com/agentUniverse/agentUniverse
* gitcode: https://gitcode.com/agentUniverse
* Stack Overflow: https://stackoverflowteams.com/c/agentuniverse/questions
* Discord: https://discord.gg/VfhEvJzQ
* WeChat Official Account: agentUniverse智多星
* DingTalk Group:
![](./docs/guidebook/_picture/dingtalk_util20250429.png)