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Agentic AI Framework for Java Developers

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README.md

# [Spring AI Alibaba](https://java2ai.com)

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<html>
    <h3 align="center">
      A production-ready framework for building Agentic, Workflow, and Multi-agent applications.
    </h3>
    <h3 align="center">
      <a href="https://java2ai.com/docs/quick-start/" target="_blank">Agent Framework Docs</a>,
      <a href="https://java2ai.com/docs/frameworks/graph-core/quick-start/" target="_blank">Graph Docs</a>,
      <a href="https://java2ai.com/ecosystem/spring-ai/reference/concepts/" target="_blank">Spring AI</a>,
      <a href="https://github.com/alibaba/spring-ai-alibaba/tree/main/examples" target="_blank">Examples</a>.
    </h3>
</html>

## Architecture

**Spring AI Alibaba Admin** is a one-stop Agent platform that supports visualized Agent development, observability, evaluation, and MCP management, etc. It also integrates with open-source low-code platforms like Dify, enabling rapid migration from DSL to Spring AI Alibaba project.

**Spring AI Alibaba Agent Framework** is an agent development framework that can quickly develop agents with built-in **Context Engineering** and **Human In The Loop** support. For scenarios requiring more complex process control, Agent Framework offers built-in workflows like `SequentialAgent`, `ParallelAgent`, `RoutingAgent`, `LoopAgent`.

**Spring AI Alibaba Graph** serves as the underlying runtime of the Agent Framework, providing essential capabilities such as persistence, workflow orchestration, and streaming required for long-running stateful agents. Compared to the Agent Framework, users can build more flexible multi-agent workflows based on the Graph API.

## Core Features

* **[Multi-Agent Orchestration](https://github.com/alibaba/spring-ai-alibaba/tree/main/examples/multiagent-patterns)**: Compose multiple agents with built-in patterns including `SequentialAgent`, `ParallelAgent`, `RoutingAgent`, and `LoopAgent` for complex task execution.

* **[Multimodal Support](https://github.com/alibaba/spring-ai-alibaba/tree/main/examples/multimodal)**: ReactAgent with text and media input (image understanding). ReactAgent with tool based image or audio generation.

* **[Voice Agent](https://github.com/alibaba/spring-ai-alibaba/tree/main/examples/voice-agent)**: WebSocket-based real-time voice agent that supports streaming audio or text input and responds with generated audio.

* **[Context Engineering](https://java2ai.com/docs/frameworks/agent-framework/tutorials/hooks)**: Built-in best practices for context engineering policies to improve agent reliability and performance, including human-in-the-loop, context compaction, context editing, model & tool call limit, tool retry, planning, dynamic tool selection.

* **[Graph-based Workflow](https://java2ai.com/docs/frameworks/graph-core/quick-start)**: Graph based workflow runtime and api for conditional routing, nested graphs, parallel execution, and state management. Export workflows to PlantUML and Mermaid formats.

* **[A2A Support](https://java2ai.com/docs/frameworks/agent-framework/advanced/a2a)**: Agent-to-Agent communication support with Nacos integration, enabling distributed agent coordination and collaboration across services.

* **[Rich Model, Tool and MCP Support](https://java2ai.com/integration/chatmodels/dashScope)**: Leveraging core concepts of Spring AI, supports multiple LLM providers (DashScope, OpenAI, etc.), tool calling, and Model Context Protocol (MCP).

* **[One-stop Agent Platform](https://java2ai.com/ecosystem/admin/quick-start)**: Build agent in a visualized way, deploy agent without code or export as a standalone java project.

## Getting Started

### Prerequisites

* Requires JDK 17+.
* Choose your LLM provider and get the API-KEY.

### Quickly Run a ChatBot

There's a ChatBot example provided by the community at [examples/chatbot](https://github.com/alibaba/spring-ai-alibaba/tree/main/examples/chatbot).

1. Download the code.

```shell
	git clone --depth=1 https://github.com/alibaba/spring-ai-alibaba.git
	cd spring-ai-alibaba
	```

2. Start the ChatBot.

Before starting, set API-KEY first (visit <a href="https://bailian.console.aliyun.com/?apiKey=1&tab=api#/api" target="_blank">Aliyun Bailian</a> to get API-KEY):
	```shell
	# this example uses 'spring-ai-alibaba-starter-dashscope', visit https://java2ai.com to learn how to use OpenAI/DeepSeek.
	export AI_DASHSCOPE_API_KEY=your-api-key
	```
	
	```shell
	# Maven installation is optional when using mvnw.
	./mvnw -pl examples/chatbot spring-boot:run
	```

3. Chat with ChatBot.

Open the browser and visit [http://localhost:8080/chatui/index.html](http://localhost:8080/chatui/index.html) to chat with the ChatBot.
	
<p align="center">
	<img src="./docs/imgs/chatbot-chat-ui.gif" alt="chatbot-ui" style="max-width: 740px; height: auto" />
</p>

## Chatbot Code Explained

1. Add dependencies

```xml
	<dependencies>
	  <dependency>
	    <groupId>com.alibaba.cloud.ai</groupId>
	    <artifactId>spring-ai-alibaba-agent-framework</artifactId>
	    <version>1.1.2.0</version>
	  </dependency>
	  
	  <dependency>
	    <groupId>com.alibaba.cloud.ai</groupId>
	    <artifactId>spring-ai-alibaba-starter-dashscope</artifactId>
	    <version>1.1.2.1</version>
	  </dependency>
	</dependencies>
	```

2. Define Chatbot
   
	For more details of how to write a Chatbot, please check the [Quick Start](https://java2ai.com/docs/quick-start) on our official website.

## 📚 Documentation
* [Overview](https://java2ai.com/docs/overview) - High level overview of the framework
* [Quick Start](https://java2ai.com/docs/quick-start) - Get started with a simple agent
* [Agent Framework Tutorials](https://java2ai.com/docs/frameworks/agent-framework/tutorials/agents) - Step by step tutorials
* [Use Graph API to Build Complex Workflows](https://java2ai.com/docs/frameworks/agent-framework/advanced/context-engineering) - In-depth user guide for building multi-agent and workflows
* [Spring AI Basics](https://java2ai.com/ecosystem/spring-ai/reference/concepts) - Ai Application basic concepts, including ChatModel, MCP, Tool, Messages, etc.
* [Chat Memory](https://docs.spring.io/spring-ai/reference/api/chatclient.html#chat-memory) - Spring AI reference for chat memory repositories and usage

## Project Structure

This project consists of several core components:

* spring-ai-alibaba-agent-framework: A multi-agent framework designed for building intelligent agents with built-in context engineering best practices.
* spring-ai-alibaba-graph: The underlying runtime for Agent Framework. We recommend developers to use Agent Framework but it's totally fine to use the Graph API directly.
* spring-ai-alibaba-admin: A one-stop Agent platform that supports visualized Agent development, observability, evaluation, and MCP management, etc.
* spring-ai-alibaba-studio: The embedded ui for quickly debugging agent in a visualized way.
* spring-boot-starters: Starters integrating Agent Framework with Nacos to provide A2A and dynamic config features.

## Spring AI Alibaba Ecosystem
 Repository | Description | ⭐
  --- | --- | ---
| [Spring AI Alibaba Graph](https://github.com/alibaba/spring-ai-alibaba/tree/main/spring-ai-alibaba-graph-core) | A low-level orchestration framework and runtime for building, managing, and deploying long-running, stateful agents. | ![GitHub Repo stars](https://img.shields.io/github/stars/alibaba/spring-ai-alibaba?style=for-the-badge&label=)
| [Spring AI Alibaba Admin](https://github.com/spring-ai-alibaba/spring-ai-alibaba-admin) |  Local visualization toolkit for the development of agent applications, supporting project management, runtime visualization, tracing, and agent evaluation. | ![GitHub Repo stars](https://img.shields.io/github/stars/spring-ai-alibaba/spring-ai-alibaba-admin?style=for-the-badge&label=)
| [Spring AI Extensions](https://github.com/spring-ai-alibaba/spring-ai-extensions) | Extended implementations for Spring AI core concepts, including DashScopeChatModel, MCP registry, etc. |  ![GitHub Repo stars](https://img.shields.io/github/stars/spring-ai-alibaba/spring-ai-extensions?style=for-the-badge&label=)
| [Spring AI Alibaba Examples](https://github.com/spring-ai-alibaba/examples) | Spring AI Alibaba Examples. |  ![GitHub Repo stars](https://img.shields.io/github/stars/spring-ai-alibaba/examples?style=for-the-badge&label=)
| [JManus](https://github.com/spring-ai-alibaba/jmanus) | A Java implementation of Manus built with Spring AI Alibaba, currently used in many applications within Alibaba Group. | ![GitHub Repo stars](https://img.shields.io/github/stars/spring-ai-alibaba/jmanus?style=for-the-badge&label=)
| [DataAgent](https://github.com/spring-ai-alibaba/dataagent) | A natural language to SQL project based on Spring AI Alibaba, enabling you to query databases directly with natural language without writing complex SQL. | ![GitHub Repo stars](https://img.shields.io/github/stars/spring-ai-alibaba/dataagent?style=for-the-badge&label=)
| [DeepResearch](https://github.com/spring-ai-alibaba/deepresearch) |  Deep Research implemented based on spring-ai-alibaba-graph. | ![GitHub Repo stars](https://img.shields.io/github/stars/spring-ai-alibaba/deepresearch?style=for-the-badge&label=)

## Contact Us

* Dingtalk Group (钉钉群), search `182255021470` and join.

* WeChat Group (微信公众号), scan the QR code below and follow us.

## Resources
* [AI-Native Application Architecture White Paper](https://developer.aliyun.com/ebook/8479): Co-authored by 40 frontline engineers and endorsed by 15 industry experts, this 200,000+ word white paper is the first comprehensive guide dedicated to the full DevOps lifecycle of AI-native applications. It systematically breaks down core concepts and key challenges, offering practical problem-solving approaches and architectural insights.

## Star History

[![Star History Chart](https://starchart.cc/alibaba/spring-ai-alibaba.svg?variant=adaptive)](https://starchart.cc/alibaba/spring-ai-alibaba)

---

<p align="center">
    Made with ❤️ by the Spring AI Alibaba Team

Repository info

Default branch: main
Latest version: v1.1.2.2
Created: 2024-09-09
Last activity: 2026-10-07
License: Apache-2.0
Open issues: 160
Watchers: 114

Topics

agentic artificial-intelligence context-engineering graph java multi-agent reactagent spring-ai workflow

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