quarkus-langchain4j-workshop
@quarkusio
quarkus-langchain4j-workshop について
Quarkus LangChain4J Workshop that demonstrates both single AI service capabilities and Agentic AI orchestration
基本情報
設定
ツール
ツールは検出されませんでした
ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。
概要
What is quarkus-langchain4j-workshop?
quarkus-langchain4j-workshop is a hands-on workshop to learn how to build AI-infused applications using Quarkus and LangChain4j. It is divided into several steps, with final code available in step-XX directories.
How to use quarkus-langchain4j-workshop?
Follow the instructions on the workshop website or serve them locally using the docs/README file. To run the final state of a step, navigate to its directory and run ./mvnw quarkus:dev; the application runs on localhost:8080.
Key features of quarkus-langchain4j-workshop
- Step-by-step workshop for building AI-infused applications
- Uses Quarkus and LangChain4j frameworks
- Final state of each step available in step-XX directories
- Run locally with Maven and Quarkus dev mode
Use cases of quarkus-langchain4j-workshop
- Learning to integrate LangChain4j with Quarkus
- Building AI-infused Java applications
- Following a structured workshop to progress from simple to complex AI features
FAQ from quarkus-langchain4j-workshop
What programming environment is required?
The workshop assumes Java, Maven, and a Quarkus development environment. The application runs with ./mvnw quarkus:dev which uses Maven wrapper.
How are the workshop steps organized?
Each step has a dedicated directory named step-XX containing the final state of that step.
Where can I find the workshop instructions?
Instructions are available on the workshop website or locally by following the docs/README file.
「推論」の他のコンテンツ
Part 1. Real-Time LangGraph Agent with MCP Tool Execution
junfanz1This project demonstrates a decoupled real-time agent architecture that connects LangGraph agents to remote tools served by custom MCP (Modular Command Protocol) servers. The architecture enables a flexible and scalable multi-agent system where each tool can be hosted independent
Agentic Radar
splx-aiA security scanner for your LLM agentic workflows
Deno Sandbox MCP Server
bewt85An MCP server that allows you to run TypeScript, JavaScript, and Python code in a sandbox on your local machine using the Deno® sandbox. This server provides a controlled environment for executing code with explicit permission controls.
iFlytek Workflow MCP Server
iflytekThis a simple implementation of an MCP server using iFlytek. It enables calling iFlytek workflows through MCP tools.
Task Planner MCP Server
CaptainCrouton89An MCP (Model Context Protocol) server that helps AI assistants (like Claude) break down complex tasks into manageable steps, track progress, and manage a hierarchical task list.
コメント