4298 related articles

A comprehensive guide to LangChain: core concepts, RAG applications, Agent development, version selection (0.3/1.0), and career opportunities for Java/Python developers entering LLM development.

An in-depth look at LangChain V1.3's core philosophy: from RAG to multi-agent workflows. Master LangGraph, Chain, and DeepAgent, learn token control and Human-in-the-loop, and become a true master of AI app development.

Resume full of RAG and Agent but keep failing interviews? The issue is you only run demos and can't explain production engineering challenges. This article breaks down data cleaning, hybrid retrieval, hallucination protection, and agent loop breakers.

Oragent (Dingyi ORA Agent) is an AI agent built for foreign trade, generating in-depth market analysis reports covering product selection, regulatory risks, and marketing calendars in just 5 minutes.

Learn how to pick the best LLM, RAG, and AI Agent courses. Discover 4 key criteria for hands-on AI learning and top resources for developers.

Want to break into AI application development? This guide covers the full learning path — from Agents and RAG to Prompt Engineering — helping you master LLM engineering skills and land the job.

Open-source AI Agent tutorial project with 2600+ GitHub Stars covering multi-agent systems, memory, planning, and reasoning loops via Jupyter Notebooks for hands-on learning.

Deep dive into OpenAgent, an open-source AI assistant featuring Computer Use, Browser Use, and Coding Agent capabilities, built on LLM + RAG + Agent Loops.

Learn how MCP protocol and Skills framework upgrade traditional RAG into autonomous agents for energy storage, connecting SCADA, BMS, and EMS systems.
TutorialsDeep dive into the technical differences between traditional RAG and Agentic RAG, covering offline/online pipeline principles, tool-based autonomous decision mechanisms, and a LangGraph-based Agentic RAG implementation via the ChatBox open-source project.
TutorialsLearn how Zion's no-code platform lets you build AI agents via drag-and-drop, with a hands-on prompt optimization assistant tutorial covering knowledge base integration, UI building, and API access.
TutorialsDeep dive into an open-source multi-Agent diagnostic system built on modified OneCall, featuring MCP real-time interaction, RAG-enhanced Q&A, and Skill routing to minimize Token consumption.
TutorialsDeep dive into traditional RAG limitations and Agentic RAG upgrades, with ChatBox source code analysis covering core tool design, intelligent decision flows, and LangGraph implementation for enterprise deployment.
TutorialsHow to start LLM application development from scratch? A complete roadmap covering Python basics, RAG knowledge bases, and Agent development with LangChain.
TutorialsPractical guide to Session Event engineering in production Agent platforms: Universal Event abstraction, three-party streaming transport with fault tolerance, and PostgreSQL storage evolution.
TutorialsA dedicated AI learning roadmap for Java developers covering Spring AI, LangChain4J, RAG, and Agent development — from fundamentals to production deployment.
TutorialsA systematic learning path for LangChain Agent development covering RAG, autonomous Agent decision-making, and tool calling—from zero to production-ready projects.
TutorialsA complete guide to building a multi-agent medical consultation system with RAG knowledge retrieval, local LLM deployment, and multi-agent architecture design.
TutorialsA detailed guide to building an AI crop pest early warning system for graduation projects, covering image recognition, RAG knowledge retrieval, Agent-based alerting, data visualization, and weather monitoring.
TutorialsStep-by-step RAGFlow deployment guide: Docker setup, DeepSeek model integration, knowledge base creation, document parsing, chat assistants, and Agent workflow orchestration with website embedding and API usage.