Java version of LangChain

CrateDB is a distributed and scalable SQL database for storing and analyzing massive amounts of data in near real-time, even with complex queries. It is PostgreSQL-compatible, and based on Lucene.

A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ultra-low latency.

Official Java client for Qdrant

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.

A multi-modal vector database that supports upserts and vector queries using unified SQL (MySQL-Compatible) on structured and unstructured data, while meeting the requirements of high concurrency and ultra-low latency.

A vector similarity database

VTS (short for Vector Transport Service) is an open-source tool for moving vectors and unstructured data. It is developed based on Apache Seatunnel by the Zilliz team, creators of the open-source Milvus vector database.

A collection of Spring AI examples

腾讯 APIJSON 的 Milvus AI 向量数据库插件。A Milvus plugin for Tencent APIJSON.

人像搜索，支持向量引擎，单台服务器十亿级数据的毫秒级搜索 | Provides face search, Utilizes feature vector similarity search at the core，Millisecond-level search on a single server for billions of data entries

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 simple vector database for RAG applications

🔎📚 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.

Extends of Apache Ignite， add feathers：Mongodb protocol，Gremlin protocol, vector search，fulltext search，graph compute

Semantic search engine written in Java as a university project

Exploring features of Spring AI for building intelligent apps

Java Client for the Pinecone Vector Database

Spring AI RAG vector store sentiment search on custom data loaded by tiko with a REST API.

Example of an AI recommendation expert in finding relevant vacancies based on cv