AI Document Search with Spring Boot Using OpenAI and Redis Vector Store AI for developers and Programmers java Redis Spring Spring AI Spring Boot by devs5003 - July 22, 2026July 25, 20260 AI Document Search with Spring Boot Using OpenAI and Redis Vector Store 2026 Keyword search finds documents that contain your exact words. AI-powered document search finds documents that match what you mean, even when the wording is completely different. In this tutorial, we'll build a working document search API in Spring Boot that stores document embeddings in Redis and ranks results by meaning, not keywords. By the end you'll have a /api/search endpoint, a document ingestion pipeline, and a bonus RAG endpoint that answers questions using your own documents. What You Will Learn What embeddings and vector similarity search actually are, in plain terms How to wire Spring AI's OpenAI starter and Redis Vector Store starter into a Spring Boot 4.1 project
How to Implement AI Chat Memory in Spring Boot Using Spring AI AI for developers and Programmers Core Java Spring AI Spring Boot by devs5003 - July 16, 2026July 22, 20260 How to Implement AI Chat Memory in Spring Boot Using Spring AI Imagine asking an AI assistant, "My name is John," followed by "What's my name?" If the assistant replies, "I don't know," your application feels broken. Modern AI applications must remember previous conversations to provide natural, context-aware interactions. This is exactly what Spring AI Chat Memory solves. Instead of manually storing and appending every previous message, Spring AI offers a clean abstraction that automatically manages conversation history. With just a few configuration changes, your chatbot can remember user preferences, previous questions, and ongoing discussions. In this tutorial, we'll build a production-ready AI chatbot with memory using Spring Boot and Spring AI. By default, large language models are stateless: they forget everything the moment a
How to Build RAG with Spring AI and pgvector AI for developers and Programmers java RAG in AI Spring Spring AI Spring Boot by devs5003 - July 6, 2026July 22, 20260 How to Build RAG with Spring AI and pgvector: Full Tutorial 2026 Every large language model has a hard cutoff. Ask it about your company's internal onboarding policy, a document uploaded yesterday, or last week's product release, and it either admits it does not know or, worse, makes something up that sounds confident and correct. Your LLM cannot answer questions about last week's internal policy update, your product's latest release notes, or a PDF sitting in your company's document store. It only knows what it was trained on. RAG fixes that by handing the model your own data at query time, and Spring AI makes the whole pipeline buildable in plain Java. What You Will Learn A Retrieval-Augmented Generation application built with Spring AI
Build Your First MCP Server with Spring Boot 4.1 and Spring AI 2.0 AI for developers and Programmers java MCP Spring AI by devs5003 - July 1, 2026July 6, 20260 Build Your First MCP Server with Spring Boot and Spring AI 2.0 Your Spring Boot services already hold years of business logic. The Model Context Protocol (MCP) is the protocol that lets AI models like Claude, GPT-4, or GitHub Copilot reach into those services and use them as callable tools. This tutorial shows you exactly how to build an MCP server using Spring Boot 4.1 and the brand-new Spring AI 2.0 GA (released June 2026). No prior AI experience needed. If you know Spring Boot, you are already most of the way there. (Java 21 + Spring Boot 4.1 + Spring AI 2.0) Spring AI 2.0.0 went GA on June 12, 2026, a major release that introduces the @McpTool/@McpResource annotation API, deprecates SSE transport
AI Agents in Spring Boot: Building Autonomous Workflows with Spring AI AI Agents java Spring AI Spring Boot 3 by devs5003 - June 24, 2026July 6, 20260 AI Agents in Spring Boot: Building Autonomous Workflows with Spring AI Your Spring Boot application already talks to databases, APIs, and message queues. Now imagine it could think, decide, and act on its own. That is exactly what AI Agents do. Most developers stop at chatbots, send a prompt, get a response. But a chatbot has no memory, no tools, and no goals. An AI Agent is different. It receives an objective, breaks it into steps, calls your Java methods when needed, evaluates the result, and keeps going until the job is done. With Spring AI, you do not need Python, LangChain, or a completely new tech stack. You build agents right inside your existing Spring Boot project, using the same annotations, beans,
Spring AI with Gemini Free Tier: Build AI-Powered Java Apps AI for developers and Programmers Google Gemini java Spring Spring AI Spring Boot by devs5003 - May 6, 2026May 8, 20260 Spring AI with Gemini (Free Tier): Build AI-Powered Java Apps Without Spending a Penny If you've been working to add AI capabilities to your Spring Boot applications but didn't want to deal with billing accounts or complex cloud setups, this guide is exactly for you. Google provides a free tier for its Gemini models via Google AI Studio, and Spring AI makes consuming it surprisingly simple. No Vertex AI. No Google Cloud project. Just an API key and a few lines of Java code. Let's walk through everything from scratch. What is Spring AI? Spring AI is a framework that brings the power of Large Language Models (LLMs) into the familiar world of Spring Boot. Think of it like Spring Data, but for AI;
How to Write Effective AI Prompts for Java Developers and Architects AI for developers and Programmers ChatGPT Claude Core Java Google Gemini java Spring AI by devs5003 - February 2, 2026April 4, 20260 How to Write Effective AI Prompts for Java Developers and Architects: A Practical, Beginner-Friendly, Real-World Guide with Examples Imagine you have inexperienced junior developers in your team. If you simply hand them a snippet of code and say, "Fix this," without telling them the Java version, the framework, the goal of the application, or the constraints (like "must be thread-safe"), the result will be unpredictable, often wrong, and require significant rework. Most junior Java developers, habitual to the correctness of a compiler, treat AI like a search engine or a simple command-line tool. They use unclear, context-less instructions such as: "Fix this code," "Explain Spring AI," or "Optimize this method." This approach fails because AI does not work like Google. It works
Google Gemini for Java Developers and Architects: The Complete 2026 Guide AI for developers and Programmers Core Java Developer Tools Gemini 3 Pro Google Gemini java Spring AI by devs5003 - January 18, 2026May 6, 20260 Google Gemini for Java Developers and Architects For Java professionals building robust, scalable systems, Google Gemini turns out as a powerful AI partner with a unique approach to architecture and development. Although many AI tools focus on quick code generation, Gemini offers a distinctive balance of deep technical understanding and practical problem-solving that aligns well with Java's enterprise ecosystem. If you imagine AI assistants on a spectrum, Gemini positions itself as the analytical systems thinker. It doesn't just generate code, it understands how Java components interconnect in larger systems. This makes it particularly valuable for architects and senior developers who need to consider the broader implications of every design decision. Let's explore all about it in this article 'Google Gemini for Java Developers and
Claude for Java Developers and Architects in 2026 AI for developers and Programmers Claude Core Java Developer Tools java Microservices Spring Spring AI by devs5003 - January 11, 2026April 26, 20260 Claude for Java Developers and Architects The pillars of Architecture, Design, and Reasoning have important values in the context of an enterprise Java development. Crafting robust, scalable, and maintainable Java systems demands not only technical skill, but also a flawless approach to structural integrity and decision-making. As Artificial Intelligence (AI) increasingly integrates into software engineering workflows, tools like Claude, developed by Anthropic, are emerging as specialized partners for Java developers and architects. Although many AI tools focus on rapid code generation or brainstorming, Claude, developed by Anthropic, offers a distinct and highly valuable perspective, particularly for the world of Java architecture. This article delves into Claude's unique strengths, its application in the Java ecosystem, and how it serves as an essential partner
Best AI Tools for Java Developers by Development Phase AI for developers and Programmers ChatGPT Gemini 3 Pro Google Gemini java Spring AI by devs5003 - January 5, 2026May 1, 20260 A categorized guide to use Best AI tools for Java Developers by Development Phase covering architecture, coding, security, AI frameworks, and deployment. For modern Java developers, AI tools are now used throughout the entire application development lifecycle: from early architecture decisions and coding to security validation, AI integration, and deployment. Instead of presenting another generic “Top AI Tools” list, this article categorizes AI tools based on how Java developers actually build applications using step by step phases of a development lifecycle. It maps each tool to a specific phase of the development lifecycle, that makes it easier to choose the right tool for the right job. However, one of the biggest challenges developers face today is tool overload. There are AI tools that