This repository contains the source code of a chatbot for a medical practice. It is based on a microservices architecture and uses a large language model to generate relevant and natural responses, following the RAG principle.

This repository contains a documentation bot powered by an LLM using @langchain4j to swiftly find answers to your Spring Boot questions. It provides easy browsing of Spring documentation and leverages the RAG technique to retrieve relevant details on demand.

Simple local RAG sample using Spring-AI, Ollama LLMs and Vespa-AI

AEM Rockstars 2024 Project - ChatAEM AEM Integration

Large Language Model Retrieval Augmented Generation (LLM-RAG) with Spring AI.

Retrieval Augmented Generation, Function Calling and Code Generation on GitHub Projects with Java

AI Assistant using RAG technique to give contextualized responses

A dynamic learning assistant designed to simplify the onboarding and training process for new hires. Users can upload documents or enter URLs for training materials. Built with Spring Boot, @langchain4j and spring-ai

This demo demonstrates the integration of a local LLama3 model for handling JSON responses within the Spring AI framework, positioning the model as a 'business logic' executor

Retrieval Augmented Generation QnA application with Azure OpenAI and SpringAI

Retrieval Augmented Generation QnA application with OpenAI and SpringAI

a rag implementation example for document-based QA, using spring-ai, ollama, and postgres-pgvector vetor db.

a rag implementation example for document-based QA, using spring-ai, ollama, and postgres-pgvector vetor db.

Sample console chat to ask OpenAI for question from predefined source with the help of RAG

🔎📚 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.

All-in-One LLM AI Assistant

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

RAG (Retrieval Augmented Generation) on Android

A chat bot for domain specific knowledge. Headless RAG for the enterprise. RAG as a service.

This demo application showcases the implementation of Spring Boot microservices, highlighting their powerful features and capabilities, with a particular emphasis on integrating OpenAI for advanced AI functionalities.