spring ai
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Enterprise Java
A Guide to Using Recursive Advisors in Spring AI
AI applications often require iterative interactions with language models to refine outputs, execute tools, or validate responses. Instead of manually…
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Enterprise Java
Spring AI 1.1 and theModel Context Protocol:Building Production AI AgentsWithout the Python Tax
Spring AI 1.0 shipped in May 2025. The 1.1 follow-up added full MCP integration, 20+ AI model backends, and a…
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Enterprise Java
Spring Boot 4, Spring AI, and AI-First Java Development
Jakarta EE 11, built-in API versioning, full modularisation, and LLM integration are all here now. Not on a roadmap —…
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Enterprise Java
MCP Annotations in Spring AI
Spring AI introduces first-class support for the Model Context Protocol (MCP), enabling AI models to discover tools, data, and prompts…
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Enterprise Java
Building Semantic Caching with Spring AI
Traditional caching relies on exact key matching. This approach works well for deterministic inputs but fails when dealing with natural…
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Enterprise Java
Building AI-Powered Applications with Spring AI and LangChain4j
1. Introduction: Java Enters the AI Arena For years, Python dominated AI development while Java—the backbone of enterprise systems—remained on…
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Enterprise Java
Managing Multiple LLM Integrations with Spring AI
Integrating multiple Large Language Models (LLMs) in a single Spring Boot application has become a sought-after architectural pattern for AI-driven…
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Enterprise Java
Designing Intelligent Agents with Spring AI
Spring AI is a powerful framework that seamlessly integrates AI capabilities into Spring Boot applications. It abstracts complex AI workflows…
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Enterprise Java
Real-Time Streaming with Spring AI ChatClient
Streaming response in Spring AI ChatClient enables progressive delivery of AI-generated content, allowing clients to receive partial data as it…
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