#34 · Primary category: LLM Application Frameworks

spring-ai-alibaba

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

Agentic AI Framework for Java Developers

Project last updated:08/25/26

GitHub Stars

10.7K

Forks

2.4K

Contributors

275

License

Apache-2.0

Why we included this project

Java shops already invested in Spring can build LLM-powered applications without leaving the ecosystem they know. The framework ships a production-oriented agent stack with context engineering and human-in-the-loop built in, so things like context compaction, tool retries, and dynamic tool selection work out of the box instead of requiring custom wiring. When a single agent is not enough, ready-made orchestration patterns cover sequential, parallel, routing, and loop flows, and the graph-based runtime underneath adds persistence, streaming, and conditional routing for long-running stateful agents. Teams that outgrow the high-level API can drop to the Graph API for fully custom multi-agent designs, or use the included admin platform to build and deploy agents visually. It is a solid choice for Spring-centric teams that want a clear path from a simple chatbot to distributed, tool-using agents.

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