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spring-ai-alibaba

Active·★ 11.0k·Apache-2.0·Updated 2026-10-07
★ Trending★ Essential

Spring AI Alibaba is Alibaba's production-ready framework for building agentic, workflow and multi-agent applications in Java. It builds on Spring AI concepts (ChatModel, tools, MCP, messages) and consists of three layers: an Agent Framework with built-in context engineering and human-in-the-loop support, a Graph runtime underneath that provides persistence, workflow orchestration and streaming for long-running stateful agents, and Spring AI Alibaba Admin, a platform for visual agent development, observability, evaluation and MCP management.

It suits Java and Spring Boot teams who want agents inside their existing services rather than in a separate Python stack. Multi-agent orchestration comes with built-in patterns such as sequential and parallel agents; ReAct agents support text and image input and tool-based image or audio generation; a WebSocket-based realtime voice agent is included; and A2A support with Nacos integration enables distributed agent collaboration. It supports multiple model providers, including Alibaba Cloud DashScope, OpenAI and DeepSeek.

Getting started: requires JDK 17+ and an API key from your model provider. Clone the repository and run the chatbot example with `./mvnw -pl examples/chatbot spring-boot:run`, or add the `spring-ai-alibaba-agent-framework` dependency and a model starter to your Spring Boot project.

#AI Agents#Workflow Orchestration#Multi-agent Systems#Spring AI#Java
↗ Visit site★ GitHub
01

Features

01Multi-Agent Orchestration
02Context Engineering
03Graph-based Workflow Runtime
04Agent-to-Agent Communication
05Rich LLM and Tool Support
02

Why choose it

+Native fit for Java and Spring Boot teams, building on familiar Spring AI concepts.
+Graph runtime with persistence and streaming for long-running, stateful agents.
+Multi-agent patterns, realtime voice and A2A with Nacos for distributed setups.
+Admin platform for visual development, observability and evaluation; Apache-2.0 licensed.
03

Trade-offs

!Examples and defaults centre on Alibaba Cloud DashScope; using other providers needs extra configuration.
!Requires the Java and Spring ecosystem, which is heavier than lightweight Python frameworks for quick experiments.
!Much of the most detailed documentation is published on the project's own site rather than in the repository.
04

Compatibility

DashScope
Native
Verified via docs
OpenAI
Supported
Verified via docs
DeepSeek
Supported
Verified via docs
Spring AI
Native
Verified via docs
05

Use cases

↳Building complex AI-native applications with multiple interacting agents.
↳Orchestrating sophisticated workflows for long-running stateful AI agents.
↳Developing intelligent agents requiring advanced context management and human-in-the-loop capabilities.
06

How it compares

≈vs Microsoft Agent Framework: Agent Framework serves Python and .NET; Spring AI Alibaba serves Java and Spring Boot.
≈vs Google ADK: ADK also offers a Java version but is oriented to Google Cloud; Spring AI Alibaba integrates with Alibaba Cloud and Nacos.
≈vs AgentScope: both come from the Alibaba ecosystem; AgentScope is a Python framework, Spring AI Alibaba the Java option.
07

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On this page
01Features02Why choose it03Trade-offs04Compatibility05Use cases06How it compares07Alternatives
Stats
GitHub Stars★ 11.0k
Last commit2d ago
StatusActive
LicenseApache-2.0
CategoryMulti-Agent
Trend (30d)
+0.4k↑ 4.4%
Links
Documentation↗Discussion↗Issues↗Releases↗

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