spring-ai-alibaba README

The project's README from github.com/alibaba/spring-ai-alibaba. As one markdown file: README.md.

Spring AI Alibaba

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A production-ready framework for building Agentic, Workflow, and Multi-agent applications.

Agent Framework Docs, Graph Docs, Spring AI, Examples.

Architecture

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

architecture

Getting Started

Prerequisites

Quickly Run a ChatBot

There's a ChatBot example provided by the community at examples/chatbot.

  1. Download the code.

    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 Aliyun Bailian to get API-KEY):

    # 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
    
    # 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 to chat with the ChatBot.

chatbot-ui

Chatbot Code Explained

  1. Add dependencies

    <dependencies>
      <dependency>
        <groupId>com.alibaba.cloud.ai</groupId>
        <artifactId>spring-ai-alibaba-agent-framework</artifactId>
        <version>1.1.2.0</version>
      </dependency>
      <!-- Assume you are going to use DashScope Model. Refer to docs for how to choose model.-->
      <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 on our official website.

📚 Documentation

Project Structure

This project consists of several core components:

Spring AI Alibaba Ecosystem

Repository Description ⭐
Spring AI Alibaba Graph A low-level orchestration framework and runtime for building, managing, and deploying long-running, stateful agents. GitHub Repo stars
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
Spring AI Extensions Extended implementations for Spring AI core concepts, including DashScopeChatModel, MCP registry, etc. GitHub Repo stars
Spring AI Alibaba Examples Spring AI Alibaba Examples. GitHub Repo stars
JManus A Java implementation of Manus built with Spring AI Alibaba, currently used in many applications within Alibaba Group. GitHub Repo stars
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
DeepResearch Deep Research implemented based on spring-ai-alibaba-graph. GitHub Repo stars

Contact Us

Resources

Star History

Star History Chart


Made with ❤️ by the Spring AI Alibaba Team

spring-ai-alibaba (alibaba/spring-ai-alibaba)

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What is this?Spring AI Alibaba is a production-ready Java framework for building agentic, workflow, and multi-agent applications, built on top of Spring AI.
Is this a framework I build on, or a ready-made agent app?It's a Java framework with several layers: the Agent Framework for quickly building agents, the lower-level Graph runtime for custom workflows, and an optional Admin platform with a visual UI for development and observability.
How do I get a basic agent running?Download the community chatbot example from examples/chatbot, set your LLM provider API key (e.g. from Aliyun Bailian), start the app, and chat with it through the browser.
What do I need installed before trying this?JDK 17 or newer, plus an API key from an LLM provider such as DashScope or OpenAI.
Do I need the separate Admin or Studio projects to get started?No - the Agent Framework or Graph API can be used standalone as a Java library; the Admin platform and embedded Studio UI are separate, optional pieces for visualized development, debugging, and observability.
Who is this built for?Java developers who want to add agentic AI capabilities (chatbots, multi-agent workflows, voice agents) into existing Spring-based applications.
What built-in multi-agent patterns does it provide?It ships ready-made orchestration patterns including SequentialAgent, ParallelAgent, RoutingAgent, and LoopAgent for composing complex multi-step agent tasks.
Can agents talk to each other across services?Yes, the framework has A2A (Agent-to-Agent) support integrated with Nacos, enabling distributed agent coordination and collaboration across separate services.
Does it support voice interactions?Yes, there's a WebSocket-based real-time voice agent that streams audio or text input and responds with generated audio.
What is Context Engineering here?It's a set of built-in best practices to improve agent reliability, including human-in-the-loop, context compaction and editing, tool call limits, tool retry, planning, and dynamic tool selection.
Can I export my workflow diagrams?Yes, graph-based workflows can be exported to PlantUML and Mermaid formats for visualization and documentation.
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