Spring AI

Spring AI + Milvus: Self-Hosted Vector Database Setup

20 December 2025·1687 words·8 mins

Spring AI Vector Databases DevOps Spring AI Milvus RAG Docker Java 21 Self-Hosted Vector Search LLM

Stop paying for cloud vector storage. Learn how to deploy a high-performance Milvus instance via Docker and integrate it seamlessly with Spring AI 1.0.0+ to build cost-effective, private Retrieval-Augmented Generation (RAG) applications.

Spring AI + PostgreSQL pgvector: Low-Cost RAG Solution

16 December 2025·1820 words·9 mins

Spring AI Architecture Spring AI PostgreSQL Pgvector RAG GenAI Java Vector Database Backend Development

Why buy a specialized Vector DB when you already have PostgreSQL? This deep dive explores how to implement a cost-effective, production-grade RAG architecture using Spring AI’s PgvectorVectorStore, covering setup, HNSW indexing strategies, metadata filtering, and full implementation details.

Error Handling and Retry Strategies in Spring AI Applications

6 December 2025·1375 words·7 mins

Spring AI Backend Engineering Spring AI Error Handling Resilience4j Microservices LLM Ops Java Retry Patterns

Integrating LLMs into production systems introduces unique instability challenges. This guide explores advanced error handling patterns in Spring AI, covering exponential backoff, circuit breakers, structured output recovery, and multi-model fallback strategies to ensure enterprise-grade reliability.

Spring AI Prompt Engineering: Best Practices and Templates

5 November 2025·1383 words·7 mins

Spring AI Prompt Engineering Spring AI Java LLM PromptTemplate GenAI Best Practices Backend Development

Moving beyond simple strings: How to engineer robust, type-safe, and secure prompts using Spring AI’s PromptTemplate and BeanOutputParser for enterprise Java applications.

Getting Started with Spring AI: A Complete Step-by-Step Guide

1 September 2025·1556 words·8 mins

Spring AI Spring AI RAG LLM Spring Boot

Overview # Spring AI is a powerful library that integrates large language models (LLMs) like OpenAI, Hugging Face, and Azure OpenAI into Spring Boot applications. It simplifies LLM calls to be as intuitive as operating a database (similar to JdbcTemplate), enabling developers to quickly build intelligent features like chatbots, question-answering systems, and content generators.