AI implementation using langchain4j and springAI frameworks with Java

Workshop for Talent Arena 2025

Showcases how to integrate Spring AI's support for MCP (Model Context Protocol) within Spring Boot applications, covering both server-side and client-side implementations.

Run a RAG-LLM locally with spring AI

Java and Spring-Boot based AI app allowing users to create artificial profiles, add them as friends and chat with them with help of locally hosted LLM models & Spring AI. Features microservices architecture powered by Spring Cloud, OAuth2 security with Keycloak, MongoDB storage and a React-based frontend, all containerized with Docker.

This project integrates SpringAI with the Ollama Mistral model in a Java Spring Boot application to leverage generative AI capabilities. It provides an API for interacting with the Mistral model, enabling AI-powered text generation and processing.

Spring AI Functions With Local Ollama and Mistral

LLM Model Context Protocol (MCP) demo using Spring AI

S1E1 - Quick Start

Access to AI model hosted in local Ollama using Spring AI

Spring AI, Ollama, model llama3.1

Project to demonstrate how to use my own document to feed AI generative chat model and then ask local question related to that document for specific and effective answers. In technical term, using RAG with springboot AI. Ollama is used locally to run deepseek-r1 model.

Spring AI, Ollama, llama3.1, nomic-embed-text, PGVector

Spring AI — Ollama & Stability AI - This repository demonstrates how to build AI-powered backend systems seamlessly integrated with REST APIs, making it easy to develop, test, and deploy AI solutions in real-world scenarios.

Demo Spring Boot project with Kotlin based on Josh Long's demo scenario

This project is a Spring Boot application that demonstrates an REST API using Ollama AI. It features embedding vectors, function calling, and streaming capabilities.

Basic project to use open source LLM model with Spring AI.

AGPL-3.0 Use Spring AI to create an Ollama Chatbot Client