From Java Dev to AI Engineer: Spring AI Fast Track
Easily get started with Spring-AI to develop various AI applications, including TextToSQL and private data AI application development. In addition to these capabilities, Spring-AI also supports integration with several other advanced AI technologies and platforms such as DeepSeek, Azure, Ollama, Vector Databases, Function Calling, MCP and RAG.
AI implementation using langchain4j and springAI frameworks with Java
Workshop for Talent Arena 2025
This repository is designed to take you from Java fundamentals to production-grade enterprise systems, while also preparing you for coding rounds, system design interviews, and real-world backend roles.
Building an AI-Powered Chat Application with Spring AI 1.0, Ollama, and RAG: A Practical Guide
Exploring interactions with LLMs : Practical insights 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.
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.
An enterprise grade RAG (Retrieval Augmented Generation) system built with Spring Boot 3.x, demonstrating advanced backend engineering and modern AI integration.
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.
Repository for web development sample projects
Run a RAG-LLM locally with spring AI
Spring AI, Ollama, llama3.1, nomic-embed-text, PGVector
A ready-to-run Maven project demonstrating how to use Ollama's local LLMs (Llama2, Mistral) with Spring AI
Spring AI Practice & Smart Email Assistant – This repo has two parts: practice examples using Spring AI with local Ollama models, and a full-stack email assistant project. The backend uses Spring Boot + Spring AI for smart email replies, and the frontend is built with ReactJS for an easy-to-use interface.
AI-powered tool that generates comprehensive, human-readable documentation from OpenAPI/Swagger specifications using large language models.
Document Search & Insights Platform (Local AI Chat + Document ETL + Model Management Platform)
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