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Spring AI is a Spring ecosystem project that simplifies building AI-powered applications by integrating large language models, embeddings, and vector databases into familiar Spring Boot patterns. Browse the latest and most valuable Spring AI articles handpicked from across the web. Learn from top blogs and industry experts. Share your resource

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Build autonomous AI agents with Amazon Bedrock and Spring AI

Learn how Java developers can build production-ready autonomous AI agents using Amazon Bedrock and Spring AI. This post walks through tool calling, conversation memory, resilience patterns, and multi-agent orchestration, then deploys the agent to AWS

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Spring AI RAG example: index source code with PgVector

Build a Spring AI RAG example that indexes dependency source code with PgVector, deduplicates and chunks documents, and returns grounded file citations

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Slashing LLM Latency by 80%: Using OpenAI Predicted Outputs in Spring AI

Slashing LLM Latency by 80%: Using OpenAI Predicted Outputs in Spring AI In 2026, treating...

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Spring AI for beginners: build your first AI app in Java

Spring AI for beginners: build your first AI app in Java. Make a model calls with ChatClient, then add RAG and memory to Spring Boot app.

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Spring AI 2.1.0-RC2 Available Now

On behalf of the Spring AI team and everyone who has contributed, I'm happy to announce that Spring AI 2.1.0-RC2 has been released and is now available from Maven Central! Release notes | Upgrade notes | Reference documentation 2.1.0-RC2 builds on 2.

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Spring AI 2.0.0-M8

⭐ New Features Use dash-separated convention for Spring Boot properties #6186 Make ChatOptions#mutate overrides return type specific #6127 Exclude jackson-dataformat-yaml from json-schema-validator #6090 Improve MistralAiApi Jackson mapping for messa

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Spring AI 2.0.1

For upgrading from 2.0.0 to 2.0.1, please refer to the upgrade notes here. For the detailed reference documentation on 2.0.1, please refer here ⭐ New Features Harden Ollama integration tests against flakiness #6776 Retire deprecated Mistral AI chat m

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Spring AI 2.1 Message Parts: Reasoning That Survives the Round Trip

Spring AI: Message Parts Doc | Upgrade Notes | OpenAI Responses Doc | Session Doc Reasoning models do more than think before they answer. They hand part of that thinking back to you and expect to get it back on the next request. Claude signs its thin

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Using Your Own Embeddings in Spring AI 2.1

VectorStore.add() takes text documents, generates embeddings with the store's configured model, and saves both. Spring AI 2.1 adds upsert for applications that already have embeddings or generate them from images, video, or audio. It accepts document

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Spring AI 2.1 Session Memory: Build a Restart-Safe Agent with JDBC

A support assistant can remember the last message perfectly and still forget the customer as soon as...

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7 Tiny AI Models for Raspberry Pi

This is a list of top LLM and VLMs that are fast, smart, and small enough to run locally on devices as small as a Raspberry Pi or even a smart fridge.

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The Best Agentic AI Browsers to Look For in 2026

A quick look at the top 7 agentic AI browsers that can search the web for you, fill forms automatically, handle research, draft content, and streamline your entire workflow.

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Don't Let the AI Find Your Bugs. Let It Judge Them.

My vulnerability scanner flagged this Java method as SQL injection: String id =...

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LLM optimization integration for Amazon SageMaker Python SDK

The Amazon SageMaker Python SDK v3 now exposes generative AI inference recommendations in Amazon SageMaker AI directly in your notebook. Benchmark an endpoint, generate data-driven deployment recommendations, and deploy the recommended configuration

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⚰️Spring Boot Postmortem#1

How Java Accidentally Created a Framework Empire 👑 If Java is so powerful…why did we need Spring?...

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Building and connecting a production-ready ecommerce MCP server using Amazon Bedrock AgentCore and

In this post, you build and connect that server end to end. You will implement MCP tools, set up two-layer JSON Web Token (JWT) authentication, deploy with AWS Cloud Development Kit (AWS CDK), and connect the result to Mistral AI’s Vibe. The post als

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Monitoring discriminative ML models using Amazon SageMaker AI with MLflow

Implementing a data and model monitoring solution is necessary to maintain prediction accuracy and help achieve the best outcome for your machine learning use case. This post shows how you can use open source Evidently together with Amazon SageMaker

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LangChain Isn’t Just a Framework — It’s an AI Application Architecture

Discover how LangChain simplifies LLM application development with modular design, vector database integration, and intelligent task… Continue reading on Medium »

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How to Add ChatGPT to a Flutter App (Step-by-Step Guide for Developers)

Learn how to integrate the OpenAI ChatGPT API into your Flutter app with real code examples, clean architecture, and production-ready best… Continue reading on Medium »

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The Zero-Cost Litigation Threat

How small vendors use AI to challenge enterprise decisions for free. Continue reading on Medium »

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