JAVA版本的检索增强生成(RAG)项目,包括知识库、搜索 | JAVA version of retrieval enhancement generation(RAG) project ,including knowledge base, search
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Updated
Aug 21, 2024 - Java
JAVA版本的检索增强生成(RAG)项目,包括知识库、搜索 | JAVA version of retrieval enhancement generation(RAG) project ,including knowledge base, search
Samples showing how to build Java applications powered by Generative AI and LLMs using Spring AI and Spring Boot.
Odin Runes, a java-based GPT client, facilitates interaction with your preferred GPT model right through your favorite text editor. There is more: It also facilitates prompt-engineering by extracting context from diverse sources using technologies such as OCR, enhancing overall productivity and saving costs.
《动手学SpringAI》包含SSE流/Agent智能体/知识图谱RAG/FunctionCall/历史消息/图片生成/图片理解/Embedding/VectorDatabase/RAG
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.
AI Assistant using RAG technique to give contextualized responses
Retrieval Augmented Generation, Function Calling and Code Generation on GitHub Projects with Java
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
Java Examples using Deep Learning 4 Java & LangChain4J for Generative AI using ChatGPT LLM, RAG and other open source LLMs. Sentiment Analysis, Application Context based ChatBots. Custom Data Handling. LLMs - GPT 3.5 / 4o, Gemini, Claude 3, Llama3, Phi-3, Gemma, Falcon 2, Mistral, Wizard Math
A chat bot for domain specific knowledge. Headless RAG for the enterprise. RAG as a service.
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.
Simple local RAG sample using Spring-AI, Ollama LLMs and Vespa-AI
Retrieval Augmented Generation QnA application with Azure OpenAI and SpringAI
springboot案例 security milvus langchain spring-ai
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