# alibaba/spring-ai-alibaba

Agentic AI Framework for Java Developers

Repository: https://github.com/alibaba/spring-ai-alibaba
Canonical: https://ross.abutalabs.com/products/spring-ai-alibaba
Homepage: https://java2ai.com
Language: Java
License: Apache-2.0
License Family: permissive
Topics: artificial-intelligence, java, spring-ai, agentic, context-engineering, multi-agent, workflow, graph, reactagent
Last push: 2026-08-25T15:40:28+00:00

## Health v2 (maintenance only)
Score: 76/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 62, longevity 51
- inputs: {"age_days": 724, "days_push": 8, "days_rel": 176, "gap_med": 33, "n_releases_24m": 18}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 10712, forks 2377 (observed 2026-08-28T04:10:43.831282+00:00)

## What it is
Spring AI Alibaba is a production-ready agentic AI framework for Java developers, built on Spring AI and a DAG-based Graph runtime. It provides a ReactAgent abstraction, multi-agent orchestration patterns (sequential, parallel, routing, loop), workflow orchestration, context engineering, human-in-the-loop support, and companion tooling like Studio and Admin for visualization and evaluation.

## Use cases
- build ai agents in java
- orchestrate multi-agent workflows
- create a react agent with tool calling
- build long-running stateful agent workflows
- add llm chat and rag to a spring boot app
- visualize and evaluate agent runs
- migrate dify dsl to java code
- build a deep research or text-to-sql agent

## When to choose
- you are a Java/Spring developer building LLM-powered agent applications
- you need multi-agent orchestration with built-in patterns and graph-based state control
- you want persistence, streaming, and human-in-the-loop for long-running agents
- you use Alibaba Cloud DashScope / Tongyi models or want Spring AI ecosystem integration

## When to avoid
- you work primarily in Python and want the richer ReactAgent paradigm (the project points such users to AgentScope)
- you need a language-agnostic or non-JVM stack
- you only need simple LLM API calls without agent or workflow orchestration
- you want a fully managed no-code agent platform rather than a code framework

## Facets
- artifact type: framework
- maturity: active
- function: agent-framework, llm-inference, rag, workflow-automation, mcp, chatbot, web-framework
- domain: artificial-intelligence, large-language-models, developer-tools, web-development
- platform: jvm, cross-platform, self-hosted
- tags: spring-ai, spring-boot, multi-agent, react-agent, graph-orchestration, dashscope, context-engineering, human-in-the-loop, java-ai, langgraph-alternative, ai-agents, retrieval-augmented-generation

## Member repositories
- alibaba/spring-ai-alibaba (main) score 76

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:43.831282+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:17:57.025555+00:00, confidence not recorded.
  - readme: https://github.com/alibaba/spring-ai-alibaba (fetched 2026-08-28T04:10:43.831282+00:00, sha 0d2e036e699c)
  - homepage: https://java2ai.com (fetched 2026-08-29T08:17:29.092876+00:00, sha d394853079be)
  - site_page: https://java2ai.com/docs/overview (fetched 2026-08-29T08:17:29.102287+00:00, sha 0cdc71036b07)
  - site_page: https://java2ai.com/docs/quick-start (fetched 2026-08-29T08:17:29.104658+00:00, sha 22b84ed36987)
  - site_page: https://java2ai.com/docs/frameworks/agent-framework/tutorials/agents (fetched 2026-08-29T08:17:29.107210+00:00, sha 895cd6b3c29f)
  - site_page: https://java2ai.com/docs/frameworks/graph-core/quick-start (fetched 2026-08-29T08:17:29.110116+00:00, sha 44622a6a4b5a)
- Data as of 2026-08-30T08:39:29.467469+00:00.