Spring AI iconSpring AI

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Spring Framework's official AI integration bringing familiar Spring idioms to GenAI with support for all major LLM providers

api available rag self hosted
8.8K+ GitHub Stars
15+ AI Providers
1.0 GA Production Ready

Overview

Spring AI is the official Spring Framework project for building AI-powered applications in Java and Kotlin. Developed by VMware (now Broadcom), it brings familiar Spring programming idioms like dependency injection, auto-configuration, and portable abstractions to generative AI development. Spring AI provides unified APIs across 15+ LLM providers (OpenAI, Anthropic, Azure OpenAI, Google Vertex AI, Amazon Bedrock, Ollama, and more), built-in support for RAG patterns with vector store integrations, function calling, and observability through Micrometer. It reached General Availability with version 1.0 in late 2024, making it production-ready for enterprise Java applications.

The Verdict

Who Should Use Spring AI?

Best For

  • Java/Kotlin enterprise teams already using Spring Boot
  • Organizations with existing Spring infrastructure
  • Teams requiring vendor-agnostic LLM abstractions
  • Enterprise apps needing observability & security
  • Building RAG applications in the JVM ecosystem

Not Ideal For

  • Python-first teams (use LangChain/LlamaIndex)
  • Quick prototypes (Python is faster to iterate)
  • Bleeding-edge experimental features
  • Non-Spring Java projects (adds complexity)
  • Serverless/FaaS with cold start constraints

What's Great

  • Native Spring Boot integration with auto-configuration
  • Unified API across 15+ LLM providers (easy switching)
  • Production-ready with 1.0 GA release
  • Built-in RAG support with multiple vector stores
  • Function calling with Spring's @Bean definitions
  • Micrometer observability out of the box
  • Type-safe, compile-time verified configurations
  • Enterprise-grade reliability from Spring team
Spring.io · GitHub

Watch Out For

  • Smaller community than Python alternatives
  • Fewer tutorials and examples available
  • JVM startup time for serverless use cases
  • Newer project, still evolving rapidly
  • Some advanced features lag Python frameworks
  • Requires Spring Boot knowledge
GitHub Issues · Stack Overflow

Pricing

Open Source
Free
Apache 2.0 License, full framework access
VMware Tanzu
Commercial
Enterprise support via Tanzu subscription
View all features & details

Core Features

  • ChatClient fluent API for conversations
  • Prompt templates with variable substitution
  • Output parsers (JSON, List, Bean mapping)
  • Function/Tool calling support
  • Streaming responses via Flux
  • Multimodal support (images, audio)
  • Embedding generation
  • Model evaluation tools

Supported LLM Providers

  • OpenAI (GPT-4, GPT-4o)
  • Anthropic (Claude 3/4)
  • Azure OpenAI
  • Google Vertex AI (Gemini)
  • Amazon Bedrock
  • Ollama (local models)
  • Mistral AI
  • HuggingFace
  • MiniMax, ZhiPu, QianFan

Vector Store Integrations

  • PGVector (PostgreSQL)
  • Pinecone
  • Milvus
  • Chroma
  • Weaviate
  • Qdrant
  • Redis Vector
  • Neo4j
  • Elasticsearch
  • Azure AI Search

RAG Features

  • Document readers (PDF, HTML, JSON, etc.)
  • Text splitters with overlap control
  • Embedding transformers
  • Vector store retrieval
  • Question answering chains
  • Metadata filtering

Observability

  • Micrometer metrics integration
  • Trace context propagation
  • Token usage tracking
  • Latency measurements
  • Spring Boot Actuator endpoints

Platforms

  • Spring Boot 3.2+
  • Java 17+ / Kotlin
  • GraalVM Native Image
  • Any JVM deployment target
  • Kubernetes / Cloud Foundry

How It Compares

Feature Spring AI LangChain (Python) LlamaIndex
Language Java/Kotlin Python/JS Python/TS
LLM Providers 15+ 50+ 40+
Vector Stores 10+ 50+ 30+
Spring Integration Native None None
Enterprise Ready Yes (Spring) Growing Growing
Community Size Small Very Large Large
Maturity 1.0 GA (2024) Mature (2022) Mature (2022)
Function Calling @Bean based Decorators Tools
Observability Micrometer LangSmith LlamaTrace
Best For Java enterprise Python rapid dev RAG-focused apps

Real-World Usage

Community & Adoption

  • Active VMware/Broadcom backing
  • Regular Spring Office Hours coverage
  • Growing enterprise adoption
GitHub, June 2026

Example Use Cases

  • Customer support chatbots
  • Document search & QA systems
  • Code analysis tools
  • Internal knowledge bases
Spring AI Samples

Code Example

@RestController
public class ChatController {

    private final ChatClient chatClient;

    public ChatController(ChatClient.Builder builder) {
        this.chatClient = builder.build();
    }

    @GetMapping("/chat")
    public String chat(@RequestParam String message) {
        return chatClient.prompt()
            .user(message)
            .call()
            .content();
    }
}

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