Merge pull request #129 from alipay/dev

Dev

CHANGELOG.md

@@ -24,6 +24,35 @@ Note - Additional remarks regarding the version.
 ***************************************************
 
 # Version Update History
+## [0.0.11] - 2024-07-11
+### Added
+- DataAgent Autonomous Data Agent MVP Version Released
+  - Minimum Viable Product version, DataAgent aims to empower your agent with the capability of self-assessment and evolution through intelligent agent abilities. For detailed information, please refer to the user documentation.
+- Added intermediate information streaming output capabilities in PEER and ReAct modes
+
+### Note
+- Latest PEER research findings released
+  - This paper provides a detailed introduction to the mechanisms and principles of the PEER multi-agent framework. Experimental validation proves the advancement of the PEER model. For detailed information, please refer to the user documentation.
+- Added use cases
+  - Andrew Ng's Reflexive Workflow Translation Agent Replication
+- Some code optimizations and documentation updates.
+
+## [0.0.10] - 2024-06-28
+### Added
+- Added standard integration for the DeepSeek model in the LLM module.
+- Added a new OpenAI general protocol wrapper class, OpenAIStyleLLM.
+  - Models using the OpenAI protocol can be configured directly.
+- Added a new LangChain tool wrapper class, LangChainTool, with several example tools for search and execution.
+  - LangChain tools can be configured directly.
+- Added Agent information collection capability in the monitor module.
+
+### Note
+- Added use cases.
+  - Supplemented documentation with a financial event analysis case study using PEER collaborative mode.
+- Added several new documents for LLM components, tool components, and the Monitor module.
+- Updated the new README.
+- Some code optimizations and documentation updates.
+
 ## [0.0.9] - 2024-06-14
 ### Added
 - Added standard integration for Claude and Ollama LLM components

CHANGELOG_zh.md

@@ -24,6 +24,35 @@ Note - 对于版本的额外说明。
 ***************************************************
 
 # 版本更新记录
+## [0.0.11] - 2024-07-11
+### Added
+- DataAgent数据自治智能体MVP版本发布
+  - Minimum Viable Product版本，DataAgent旨在使用智能体能力让您的Agent拥有自我评价与演进的能力，详细内容请查阅用户文档。
+- 增加PEER、ReAct模式中间信息流式输出能力
+
+### Note
+- PEER最新研究成果发布
+  - 该文献详细介绍了介绍了PEER多智能体框架的机制原理，同时在实验部分通过验证证明了PEER模式的先进性，详细内容请查阅用户文档。
+- 新增使用案例
+  - 吴恩达反思工作流翻译智能体复刻
+- 部分代码优化与文档更新
+
+## [0.0.10] - 2024-06-28
+### Added
+- LLM组件新增DeepSeek模型标准接入
+- 新增OpenAI通用协议包装类OpenAIStyleLLM
+  - openai协议类模型接入可直接配置
+- 新增LangChain工具包装类LangChainTool，新增搜索类、执行类示例工具若干
+  - LangChain工具接入可直接配置
+- monitor模块新增Agent纬度信息采集能力
+
+### Note
+- 新增使用案例
+  - PEER协同模式的金融事件分析案例文档补充
+- 新增若干LLM组件、工具组件、Monitor模块文档
+- 新版README更新
+- 部分代码优化与文档更新
+
 ## [0.0.9] - 2024-06-14
 ### Added
 - LLM组件新增claude、ollama标准接入

README.md

@@ -5,62 +5,125 @@ Language version: [English](./README.md) | [中文](./README_zh.md) | [日本語
 ![](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/)
+[![Static Badge](https://img.shields.io/badge/pypi-v0.0.11-blue?logo=pypi)](https://pypi.org/project/agentUniverse/)
 
 ![](docs/guidebook/_picture/logo_bar.jpg)
 ****************************************
 
-## 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.
+## What is agentUniverse?
 
-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:
+**agentUniverse is a multi-agent framework based on large language models.** agentUniverse provides you with the flexible and easily extensible capability to build single agents. At its core, agentUniverse features a rich set of multi-agent collaboration mode components (which can be viewed as a Collaboration Mode Factory, or Pattern Factory). These components allow agents to maximize their effectiveness by specializing in different domains to solve problems. agentUniverse also focuses on the integration of domain expertise, helping you seamlessly incorporate domain knowledge into the work of your agents.🎉🎉🎉
 
-- 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. 
+**🌈🌈🌈agentUniverse helps developers and enterprises to easily build powerful collaborative agents that perform at an expert level in their respective domains.**
 
+![](docs/guidebook/_picture/agent_universe_framework_resize.jpg)
 
-- 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...
+We encourage you to practice and share different domain Patterns within the community. The framework comes pre-loaded with several multi-agent collaboration mode components that have been validated in real-world industries and will continue to expand in the future. The components that will be available soon include:
 
-![](docs/guidebook/_picture/agent_universe_framework_resize.jpg)
+* PEER Mode Component: This pattern uses agents with different responsibilities—Plan, Execute, Express, and Review—to break down complex problems into manageable steps, execute the steps in sequence, and iteratively improve based on feedback, enhancing the performance of reasoning and analysis tasks. Typical use cases: Event interpretation, industry analysis.
+* DOE Mode Component: This pattern employs three agents—Data-fining, Opinion-inject, and Express—to improve the effectiveness of tasks that are data-intensive, require high computational precision, and incorporate expert opinions. Typical use cases: Financial report generation.
 
-## agentUniverseSample Project
-[agentUniverse Sample Project](sample_standard_app/README.md)
+More patterns are coming soon...
 
-## Quick Installation
+****************************************
+## Table of Contents
+* [Quick Start](#Quick-Start)
+* [Cases and Example Projects](#Cases-and-Example-Projects)
+* [More](#More)
+  * [Why Use agentUniverse](#Why-Use-agentUniverse)
+  * [Core Features](#Core-Features)
+  * [User Guide](#User-Guide)
+  * [API Reference](#API-Reference)
+  * [Support](#Support)
+  * [Citation](#Citation)
+  * [Acknowledgements](#Acknowledgements)
+****************************************
+## Quick Start
 Using pip:
 ```shell
 pip install agentUniverse
 ```
 
-## Quick Start
 We will show you how to:
-* Prepare the environment and application project
+
+* Prepare the environment and application projects
 * 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 mode components for multi-agent collaboration
+* Test and tune the execution effectiveness of an agent
+* Quickly deploy an agent as a service
 
-## Use Cases
+For more details, please read the [Quick Start](./docs/guidebook/en/1_3_Quick_Start.md).
+
+****************************************
+## Cases and Example Projects
+### 🌟 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)
+[Financial Event Analysis Based on PEER Multi-Agent Mode](./docs/guidebook/en/6_4_1_Financial_Event_Analysis_Case.md)
+
+[Andrew Ng's Reflexive Workflow Translation Agent Replication](./docs/guidebook/en/7_1_1_Translation_Case.md)
+
+#### 🚩 DataAgent - Data Autonomous Agent
+agentUniverse has launched DataAgent (Minimum Viable Product Version). DataAgent aims to empower your agent with the capability of self-assessment and evolution through the use of intelligent agent abilities. For more details, please refer to the documentation. [DataAgent - Data Autonomous Agent](./docs/guidebook/en/8_1_1_data_autonomous_agent.md)
+
+### 🌟 Example Projects
+[agentUniverse Example Projects](sample_standard_app)
+
+### 🌟 Product Cases Built with agentUniverse
+['Zhi Xiao Zhu' AI Assistant for Financial Professionals](https://zhu.alipay.com/)
+****************************************
+## More
+### Why Use agentUniverse
+💡 [Why Use agentUniverse?](./docs/guidebook/en/1_Why_Use_agentUniverse.md)
+
+### Core Features
+
+* **Rich Multi-Agent Collaboration Modes:** Provides industry-validated collaboration modes such as PEER (Plan/Execute/Express/Review) and DOE (Data-fining/Opinion-inject/Express). It also supports user-defined patterns for new modes, enabling organic collaboration among multiple agents.
+* **Customizable Components:** All framework components, including LLM, knowledge, tools, and memory, are customizable, allowing users to enhance their dedicated agents.
+* **Seamless Integration of Domain Expertise:** Offers capabilities for domain-specific prompts, knowledge construction, and management, and supports domain-level SOP orchestration and embedding, aligning agents to the expert level in their fields.
+
+💡 For more features details, see the [Core Features of agentUniverse](./docs/guidebook/en/1_Core_Features.md).
+
+### User Guide
+💡 For more detailed information, please read the [User Guide](./docs/guidebook/en/0_index.md).
+
+### API Reference
+💡 Please read the [API Reference](https://agentuniverse.readthedocs.io/en/latest/).
+
+### Support
+#### Submit Questions via GitHub Issues
+😊 We recommend submitting your queries using [GitHub Issues](https://github.com/alipay/agentUniverse/issues), we typically respond within 2 days.
+
+#### Contact Us via Discord
+😊 Join our [Discord Channel](https://discord.gg/DHFcdkWAhn) to interact with us.
+
+#### Contact Us via Administrator Email
+😊 Email: [jerry.zzw@antgroup.com](mailto:jerry.zzw@antgroup.com)
+
+#### twitter
+ID: [@agentuniverse_](https://x.com/agentuniverse_)
+
+### Citation
+The agentUniverse project is supported by the following research achievements.
+
+BibTeX formatted
+```text
+@misc{wang2024peerexpertizingdomainspecifictasks,
+      title={PEER: Expertizing Domain-Specific Tasks with a Multi-Agent Framework and Tuning Methods}, 
+      author={Yiying Wang and Xiaojing Li and Binzhu Wang and Yueyang Zhou and Han Ji and Hong Chen and Jinshi Zhang and Fei Yu and Zewei Zhao and Song Jin and Renji Gong and Wanqing Xu},
+      year={2024},
+      eprint={2407.06985},
+      archivePrefix={arXiv},
+      primaryClass={cs.AI},
+      url={https://arxiv.org/abs/2407.06985}, 
+}
+```
+Overview: This document provides a detailed introduction to the mechanisms and principles of the PEER multi-agent framework. In the experimental section, scores were assigned across seven dimensions: completeness, relevance, conciseness, factualness, logicality, structure, and comprehensiveness (each dimension has a maximum score of 5 points). The PEER model scored higher on average in each evaluation dimension compared to BabyAGI and demonstrated significant advantages in the dimensions of completeness, relevance, logicality, structure, and comprehensiveness. Additionally, the PEER model achieved a superior rate of 83% over BabyAGI using the GPT-3.5 Turbo (16k) model, and 81% using the GPT-4 model. For more details, please refer to the document.
+https://arxiv.org/pdf/2407.06985
+
+## Acknowledgements
+This project is partially built on excellent open-source projects such as langchain, pydantic, gunicorn, flask, SQLAlchemy, chromadb, etc. (The detailed dependency list can be found in pyproject.toml). We would like to extend special thanks to the related projects and contributors. 🙏🙏🙏

README_jp.md

@@ -5,7 +5,7 @@
 ![](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/)
+[![Static Badge](https://img.shields.io/badge/pypi-v0.0.10-blue?logo=pypi)](https://pypi.org/project/agentUniverse/)
 
 ![](docs/guidebook/_picture/logo_bar.jpg)
 ****************************************
@@ -45,9 +45,13 @@ pip install agentUniverse
 
 ## 使用ケース
 [法律相談Agent](./docs/guidebook/en/7_1_1_Legal_Consultation_Case.md)
+
 [Pythonコード生成と実行Agent](./docs/guidebook/en/7_1_1_Python_Auto_Runner.md)
+
 [多回多Agentによるディスカッショングループ](./docs/guidebook/en/6_2_1_Discussion_Group.md)
 
+[PEERマルチAgentモードに基づいた金融イベント分析](./docs/guidebook/en/6_4_1_Financial_Event_Analysis_Case.md)
+
 ## ガイドブック
 詳細情報については、[ガイドブック](docs/guidebook/en/0_index.md)を参照してください。
 
@@ -59,7 +63,5 @@ pip install 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
+* Discord: https://discord.gg/DHFcdkWAhn
 * WeChat公式アカウント: agentUniverse智多星
-* DingTalkグループ:
-![](./docs/guidebook/_picture/dingtalk_util20250429.png)