spring-projects/spring-ai
An Application Framework for AI Engineering observed · 2026-08-28
Health v2 · maintenance only
95/100
- Activity 98
- Release rhythm 98
- Longevity 83
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 11
- age_days: 1163
- days_rel: 12
- days_push: 12
- n_releases_24m: 20
Adoption not part of the score
9358 stars · 2855 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
Spring AI is an application framework for AI engineering that provides Spring-friendly, portable abstractions for integrating AI models into Java applications. It offers unified APIs for chat completion, embeddings, text-to-image, vector stores, function calling, and structured output mapping across all major AI providers.
Use cases
- build a chatbot in Java with Spring Boot
- switch between OpenAI, Anthropic, and Ollama with minimal code changes
- map LLM responses to Java POJOs with structured outputs
- implement RAG with vector databases like PGVector, Milvus, or Pinecone
- add function calling so a model can invoke Java methods
- build an ETL pipeline for document ingestion and embedding
- add observability to AI operations in enterprise apps
When to choose
- you are building AI features in a Java/Spring Boot application
- you want portable abstractions to avoid vendor lock-in across AI model providers
- you need typed, POJO-based APIs instead of raw HTTP calls to AI services
- you want Spring ecosystem integration for dependency injection, configuration, and observability
When to avoid
- you are a Python developer who prefers LangChain or LlamaIndex
- you need a lightweight, framework-free client for a single AI provider
- your project does not use the JVM or Spring ecosystem
- you need cutting-edge agent features that only exist in Python AI tooling first
Facets
framework · maturity active
agent-framework rag llm-inference llm-training machine-learning etl sdk middleware artificial-intelligence large-language-models machine-learning backend developer-tools jvm cross-platform spring java chat-completion embeddings vector-stores function-calling structured-outputs observability generative-ai retrieval-augmented-generation ai-agents spring-boot
9 sources
- readme: https://github.com/spring-projects/spring-ai · fetched 2026-08-28 · 6be9e9424708
- homepage: https://spring.io/projects/spring-ai · fetched 2026-08-29 · 7ab62caa152d
- site_page: https://spring.io/quickstart · fetched 2026-08-29 · fc64dd950363
- site_page: https://spring.io/projects/spring-restdocs · fetched 2026-08-29 · 1e2a101b77d3
- site_page: https://docs.spring.io/spring-ai/reference/api/chatmodel.html · fetched 2026-08-29 · 8ca24d2bcb6d
- site_page: https://docs.spring.io/spring-ai/reference/index.html · fetched 2026-08-29 · 0d7ff2946095
- site_page: https://docs.spring.io/spring-ai/reference/getting-started.html · fetched 2026-08-29 · 05d07c256097
- site_page: https://enterprise.spring.io · fetched 2026-08-29 · 85ac7d6d5114
- site_page: https://enterprise.spring.io/lts-releases · fetched 2026-08-29 · 3251cc8760b6
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| spring-projects/spring-ai | main | 95 |
For agents
markdown · JSON · MCP: product_card(name="spring-projects/spring-ai")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem