LangChain4j is an open-source Java library that simplifies the integration of LLMs into Java applications through a unified API, providing access to popular LLMs and vector databases. It makes implementing RAG, tool calling (including support for MCP), and agents easy. LangChain4j integrates seamlessly with various enterprise Java frameworks.

Practical Llama 3 inference in Java

An open-source, code-first Java toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

LangChain Expression Language (LCEL) As NiFi Processors

AI Tasks. A LLM integrated agent orchestration tool for Liferay.

Deepdesk is an enterprise-grade platform for empowering business with AI agents.

Rage4j is a java library thats helps evaluate LLM's based on scientifically grounded metrics

A Vert.x MCP Server built on top of MCP Java SDK

Examples for using Ollama4j to connect and interact with Ollama models.

A GenAI-powered mobile app dedicated to fostering environmental awareness and facilitating community-driven initiatives.

This is an Android application for ecommerce. Users can browse products, add them to their cart, purchase, track orders and chat with AI RAG.

Module that connects a llm repOK generator with a randoop verifier to generate representation invariants for Java classes.

An android chatbot that integrates open ai API for GPT 3.5 .This chatbot also has exception handling handling for network errors as we tend to face lots of network problems in Africa

Evolutionary algorithms generates the code automatically and generative ai makes it readable.

🔎📚 This document processing system is designed to efficiently analyze user documents and provide accurate responses to user queries related to the content. Powered by advanced algorithms, it offers a seamless experience for users seeking insights or information within their documents.

Java-port of qwen3.c

Demonstrate two types of chat interactions with a Mattermost instance leveraging Mattermost OpenAPI v3 spec and Spring AI.

Application agentique multimodale intégrant Spring AI, le protocole MCP, Node.js, Python et un LLM (OpenAI, Claude, LLaMA) pour permettre à une IA d'interagir dynamiquement avec des outils réels via un protocole commun et multi-langage.

Community Spring Boot and Spring AI building blocks for conversations between humans and artificial intelligence.