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OpenDerisk

Weekly Pick

OpenDerisk is an AI-native risk intelligence system designed as a 7x24H AI digital operations assistant (AI-SRE). It provides deep monitoring and protection for application systems through multi-agent collaboration, deep root cause analysis (RCA), and visual evidence chains. The system is fully open-source and leverages large datasets for dynamic problem diagnosis.

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OpenDerisk介绍- 开源地址: https://github.com/derisk-ai/OpenDeriskOpenDeRisk AI 原生风险智能系统 —— 7x24H 应用系统AI数字运维助手(AI-SRE), 我们的愿景是, 为每个应用系统提供一个7x24H的AI系统数字管家，并能与真人进行协同，7x24H处理业务问题，形成7x24H得深度护航与防护网。## 核心特性Image1. DeepResearch RCA: 通过深度分析日志、Trace、代码进行问题根因的快速定位。2. 可视化证据链： 定位诊断过程与证据链全部可视化展示，诊断过程一目了然，可以快速判断定位的准确性。3. 多智能体协同: SRE-Agent、Code-Agent、ReportAgent、Vis-Agent、Data-Agent协同工作。4. 架构开源开放: OpenDerisk采用完全开源、开放的方式构建，相关框架、代码在开源项目也能实现开箱即用。## 架构方案Image采用多Agent架构，目前代码中主要实现了绿色部分部分，告警感知采用的是微软开源的OpenRCA数据集, 数据集的大小解压后在26G左右，我们实现在26G的数据集合上，通过多Agent协同，Code-Agent动态写代码来进行最终根因的分析诊断。### 技术实现1. 数据层: 拉取Github OpenRCA的大规模数据集(20G), 解压本地处理分析。2. 逻辑层：Multi-Agent架构, 通过SRE-Agent、Code-Agent、ReportAgent、VisAgent、Data-Agent协同合作，进行深度的DeepResearch RCA(Root Cause Analyze)3. 可视化层: 采用Vis协议、动态渲染整个处理流程与证据链, 以及多角色协同切换的过程。## 运行效果Image

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