面向TypeScript开发者，系统学习LangChain.js构建AI应用：从提示词模板到RAG检索增强、Agents智能体及LangGraph多智能体工作流，全程项目实战。
原始标题：LangChain with TypeScript: Build AI Apps, RAG & Agents
本课程是一门专为 JavaScript/TypeScript 开发者量身打造的 LangChain.js 全栈 AI 应用开发实战课程，旨在帮助具备 Node.js 基础的工程师告别简单的 LLM API 调用，深度掌握现代 AI 应用的工程化开发。课程采用循序渐进的系统化教学路径，从 LangChain 基础构件（提示词模板、结构化输出解析）出发，逐步攻克核心的 RAG（检索增强生成）技术，涵盖文本嵌入（Embeddings）、向量数据库（Vector Stores）和高级检索器（Retrievers）的构建与应用，帮助开发者跨越市面上 Python 教程泛滥的行业痛点，用原生 TS 构建起坚实的 AI 知识库研发能力。
在夯实基础后，课程将带你进阶至智能体与高级工作流的核心生态，深入剖析工具（Tools）、智能体（Agents）与传统工作流的本质区别，赋予 AI 独立调用外部 API 和函数执行的能力。最终，你将攻克 LangChain 生态中的前沿利器 LangGraph，掌握如何设计并落地复杂的、具备状态控制和循环决策的图架构多智能体工作流。整门课程完全脱离枯燥的孤立概念，全流程通过构建真实世界的 AI 应用程序进行实战驱动，非常适合全栈工程师、Node.js 开发者以及渴望向现代大模型（LLM）应用架构师转型的工程人员。
Published 9/2026
Created by Haider Malik
MP4 | Video: h264, 2560×1440 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Intermediate | Genre: eLearning | Language: English | Duration: 135 Lectures ( 6h 33m ) | Size: 4.8 GB
Learn LangChain.js, RAG, Tools, Agents, and LangGraph by building real-world AI applications with TypeScript
What you’ll learn
⚡ Build AI applications with LangChain.js and TypeScript using modern LLM development patterns.
⚡ Build Retrieval-Augmented Generation (RAG) applications using embeddings, vector stores, and retrievers.
⚡ Build AI agents that use tools and understand how tools, agents, and workflows work together.
⚡ Build advanced agentic workflows with LangGraph and understand how it fits into the LangChain ecosystem.
Requirements
❗ Basic JavaScript or TypeScript programming knowledge. Familiarity with Node.js and npm is recommended. You should have a computer with internet access. No prior LangChain, RAG, or AI agent experience is required.
Description
Build real-world AI applications withLangChain.js, TypeScript, RAG, Tools, Agents, and LangGraph.
In this course, you’ll learn how to use LangChain with TypeScript to build modern AI applications step by step. Instead of jumping directly into complex agents, you’ll build a strong foundation and gradually move toward more advanced AI application patterns.
You’ll start by understanding the core concepts of LangChain and then progress through prompts, output parsers, embeddings, memory, vector stores, retrievers, and RAG. From there, you’ll learn how tools work, how agents use tools, and how LangGraph can be used to build more advanced agentic workflows.
What you’ll learn
✨ Build AI applications usingLangChain.js and TypeScript
✨ Understand LangChain’s core building blocks and how they fit together
✨ Work with prompts and prompt templates
✨ Parse and structure model outputs
✨ Understand embeddings and how they are used in AI applications
✨ Work with vector stores and similarity search
✨ Build retrieval-augmented generation (RAG) applications
✨ Understand retrievers and how they work with RAG
✨ Give AI applications access to external tools and functions
✨ Understand the difference between tools, agents, and workflows
✨ Build AI agents using LangChain
✨ Understand how LangGraph fits into modern AI application development
✨ Build practical AI applications instead of only learning isolated concepts
A practical, step-by-step approach
Many AI tutorials jump straight into building an agent without explaining the concepts underneath it. This course takes a different approach.
You’ll progressively build your knowledge
LangChain fundamentals → Prompts → Output Parsers → Embeddings → Vector Stores → Retrievers → RAG → Tools → Agents → LangGraph
This progression helps you understand not onlyhow to use LangChain, but alsowhy these different components exist and when you should use them.
Who is this course for?
This course is for developers who want to build AI-powered applications usingTypeScript and JavaScript.
It’s a good fit if you’re a
✨ TypeScript or JavaScript developer
✨ Node.js developer
✨ Full-stack developer
✨ Developer interested in LLM applications
✨ Developer who wants to learn RAG and AI agents
✨ Developer who wants to use LangChain.js rather than learning only Python-based examples
You don’t need to become an AI researcher to follow this course. The focus is on understanding the concepts and applying them to real software development.
What you’ll build
Throughout the course, you’ll work with practical examples and progressively combine the concepts you’ve learned to build AI application functionality.
By the end of the course, you’ll have a much clearer understanding of how the pieces of a modern LLM application fit together—from calling models and structuring outputs to retrieval, RAG, tools, agents, and graph-based workflows.
If you’re a TypeScript developer who wants to move beyond basic LLM API calls and learn how to build more capable AI applications withLangChain.js, this course is for you.
Who this course is for
⭐ JavaScript and TypeScript developers who want to build AI-powered applications with LangChain.js. Ideal for Node.js and full-stack developers interested in RAG, AI agents, tools, and LangGraph.
百度网盘下载：
