UltraCodeAI is an innovative AI-powered IntelliJ plugin that transforms coding with seamless assistance. It supports local/cloud LLMs like Ollama, OpenAI, and Groq for context-aware prompts, auto code error analysis, and RAG-enhanced insights. Features includes tabbed UI for chat, diagnostics, and recommendations; hover explanations; design pattern

Redis Vector Library (RedisVL) -- the AI-native Python client for Redis.

Gebo.ai, the open source enterprise retrieve augmented generation platform

UltraCodeAI is an innovative AI-powered IntelliJ plugin that transforms coding with seamless assistance. It supports local/cloud LLMs like Ollama, OpenAI, and Groq for context-aware prompts, auto code error analysis, and RAG-enhanced insights. Features includes tabbed UI for chat, diagnostics, and recommendations; hover explanations; design pattern

Identity and Authorization Service with Vector and AI Integration

springAiTest- a simple server, runs models with live websearch and rag system and custom knowledge base

An academic project on a medical news system, developed using Spring Boot and ReactJS with TSX, implementing RAG to build a disease diagnosis chatbot based on data crawled using Selenium.

Medical Insight RAG with Spring AI

Ollama LLM Interface with RAG in java swing.

🗺️ Visualize and explore large embeddings interactively, enabling easy navigation, clustering, and density analysis of your data.

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.

RAG based spring boot application

TLand-Backend provides RESTful APIs and core business logic for the TLand platform using a microservice architecture.

Laptop Recommendation System (Integrated Information Retrieval and Large Language Model)

Spring boot application using RAG

Este projeto implementa uma API de Recuperação Aumentada por Geração (RAG) utilizando Spring Boot, Spring AI, Ollama e Postgres com extensão pgvector

A simple bookshop AI agent powered by Spring AI and enhanced with Retrieval Augmented Generation (RAG)