# AgentWeave: A Visual AI Agent Workflow Orchestration Platform Based on React and Spring Boot

> A visual AI agent workflow orchestration platform using React for the frontend and Spring Boot for the backend, supporting the construction of complex AI agent workflows via drag-and-drop

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-06-15T17:15:50.000Z
- 最近活动: 2026-06-15T17:24:35.434Z
- 热度: 150.8
- 关键词: AI Agent, 工作流编排, 可视化编辑器, React, Spring Boot, 智能体, 低代码平台, LLM应用
- 页面链接: https://www.zingnex.cn/en/forum/thread/agentweave-reactspring-bootai
- Canonical: https://www.zingnex.cn/forum/thread/agentweave-reactspring-bootai
- Markdown 来源: floors_fallback

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## [Introduction] AgentWeave: Core Introduction to the Visual AI Agent Workflow Orchestration Platform

AgentWeave is an open-source visual AI agent workflow orchestration platform using React for the frontend and Spring Boot for the backend. It supports building complex AI agent workflows via drag-and-drop, aiming to lower the threshold for agent application development. The original author/maintainer is qianzhi1212, and the project is open-sourced on GitHub (link: https://github.com/qianzhi1212/AgentWeave). The update time is 2026-06-15T17:15:50Z.

## [Background] The Rise of AI Agent Workflows and Development Pain Points

With the evolution of large language model capabilities, AI agents have moved from concept to practical applications, capable of autonomous planning and tool calling to complete multi-step tasks. However, building complex agent systems requires a lot of code to define logic, which sets a high threshold for non-technical users. Visual workflow orchestration platforms reduce complexity through drag-and-drop components, supporting the rapid construction of everything from simple chatbots to complex multi-agent collaboration systems.

## [Architecture Design] Analysis of Frontend and Backend Tech Stack

- **Frontend**: Built on React to create a visual editor, including a canvas area (drag-and-drop nodes/connections), component library panel (LLM/tool/memory nodes, etc.), property configuration panel, and execution control bar, supporting real-time preview and debugging.
- **Backend**: Spring Boot provides RESTful APIs, a workflow engine (parsing definitions/scheduling execution), a persistence layer (saving workflows/execution history), and an integration layer (connecting to LLMs/vector databases/external tools), which is easy to extend.

## [Core Features] Visual Design and Collaboration Capabilities

1. **Visual Workflow Design**: Drag-and-drop nodes (input/LLM/tool/condition/loop/output) to define data flow;
2. **Multi-agent Collaboration**: Supports sequential execution, parallel execution, master-slave collaboration, and discussion mode;
3. **Memory Management**: Short-term session context, long-term vector database memory, and knowledge base integration;
4. **Debugging and Monitoring**: Step-by-step execution, variable viewing, execution history, and error localization.

## [Application Scenarios] Typical Use Cases

Applicable to various AI application scenarios:
- Intelligent Customer Service: Build service agents that understand complex intents and call knowledge bases;
- Content Generation: Automated marketing copy, code generation, report writing;
- Data Analysis: Automatically acquire data, perform analysis, and generate visual reports;
- Process Automation: Automate repetitive business processes (resume screening, invoice processing).

## [Technology Selection] Advantages of React + Spring Boot

Considerations for choosing React + Spring Boot:
- Rich Ecosystem: Both frameworks have active communities and a large number of third-party libraries;
- Easy Access to Talent: Sufficient supply of relevant technical talent;
- Stable Performance: Spring Boot's enterprise-level stability has been proven in production;
- Separation of Frontend and Backend: Clear responsibilities, facilitating team collaboration.

## [Summary] Platform Value and Trends

AgentWeave represents the trend of toolization in AI application development. By lowering technical thresholds through visual orchestration, it allows domain experts to directly participate in agent construction. As agent technology matures, such platforms will play an important role in enterprise digital transformation.