Samples showing how to build Java applications powered by Generative AI and LLMs using Spring AI and Spring Boot.

A project to show howto use SpringAI with OpenAI to chat with the documents in a library. Documents are stored in a normal/vector database. The AI is used to create embeddings from documents that are stored in the vector database. The vector database is used to query for the nearest document. That document is used by the AI to generate the answer.

Java version of LangChain

Spring AI, chat client, vector store, RAG, multimodality samples

Spring Petclinic application with a chatbot powered by OpenAI's Generative AI and the LangChain4j project

Dust Actor library for interacting with LLMs and embedding engines

Example of IBM watsonx.ai with Spring AI

Example of using a conversational AI with embeddings with Java

TicketScout is a ticket system for professionals in specialized tech domains, not just software teams. It simplifies ticketing with easy creation and updates using only a title and description. Its AI-powered semantic search understands ticket context, allowing intuitive searches without specific keywords.

A collection of Spring AI examples

Experimenting using low level python c ABI with project panama and spring boot

A TDD api for the "Farmer the Farms".

Java client library for Aleph Alpha

Simple Quarkus RAG - Milvus

Semantic search engine written in Java as a university project

Higher Level Primitives for working with LLMs in Java

A high-performance Java Implementation of RDF2Vec

An implementation of the Watset clustering algorithm in Java.

An advertisement system based on Java spring cloud microservices and C++ FAISS embedding search

compute semantic similarity between arbitrary words and phrases in many languages