外部指南

¥External guides

以下是指向 LangChain.js 的外部教程和课程的链接。有关如何对 DSQL 进行身份验证和授权的选项，请查看 tutorials。

¥Below are links to external tutorials and courses on LangChain.js. For other written guides on common use cases for LangChain.js, check out the tutorials and how to sections.

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Deeplearning.ai

我们与 Deeplearning.ai 和 Andrew Ng 合作开发了 LangChain.js 短期课程。

¥We've partnered with Deeplearning.ai and Andrew Ng on a LangChain.js short course.

它涵盖了 LCEL 和其他可以组合以构建更复杂链的构建块，以及为检索增强生成 (RAG) 加载数据的基础知识。在下面免费试用：

¥It covers LCEL and other building blocks you can combine to build more complex chains, as well as fundamentals around loading data for retrieval augmented generation (RAG). Try it for free below:

• 使用 LangChain.js 构建 LLM 应用

  ¥Build LLM Apps with LangChain.js

Scrimba 交互指南

¥Scrimba interactive guides

Scrimba 是一个代码学习平台，允许你在观看视频演示的同时以交互方式编辑和运行代码。

¥Scrimba is a code-learning platform that allows you to interactively edit and run code while watching a video walkthrough.

我们与 Scrimba 合作开发了课程材料（称为 "scrims"），教授使用 LangChain.js 构建的基础知识。 - 查看下面的内容，并在更多可用内容发布时回来查看！

¥We've partnered with Scrimba on course materials (called "scrims") that teach the fundamentals of building with LangChain.js - check them out below, and check back for more as they become available!

学习 LangChain.js

¥Learn LangChain.js

• 在 Scrimba 上学习 LangChain.js

  ¥Learn LangChain.js on Scrimba

一个完整的端到端课程，讲解如何构建一个能够回答所提供文档相关问题的聊天机器人。这是一个很棒的 LangChain 入门项目，也是学习如何使用 LangChain 表达式语言原语执行检索的绝佳入门项目！

¥An full end-to-end course that walks through how to build a chatbot that can answer questions about a provided document. A great introduction to LangChain and a great first project for learning how to use LangChain Expression Language primitives to perform retrieval!

LangChain 表达式语言 (LCEL)

¥LangChain Expression Language (LCEL)

• 基础知识 (PromptTemplate + LLM)

  ¥The basics (PromptTemplate + LLM)

• 添加输出解析器

  ¥Adding an output parser

• 将函数调用附加到模型

  ¥Attaching function calls to a model

• 组合多个链

  ¥Composing multiple chains

• 检索链

  ¥Retrieval chains

• 对话检索链 ("与文档聊天")

  ¥Conversational retrieval chains ("Chat with Docs")

深入探索

¥Deeper dives

• 设置新的 PromptTemplate

  ¥Setting up a new PromptTemplate

• 设置 ChatOpenAI 参数

  ¥Setting up ChatOpenAI parameters

• 附加停止序列

  ¥Attaching stop sequences

Neo4j GraphAcademy

Neo4j 编写了一门实践课程，展示了如何在 Next.js 中构建电影推荐聊天机器人。它涵盖了检索增强生成 (RAG)、跟踪历史记录等。查看以下内容：

¥Neo4j has put together a hands-on, practical course that shows how to build a movie-recommending chatbot in Next.js. It covers retrieval-augmented generation (RAG), tracking history, and more. Check it out below:

• 使用 TypeScript 构建基于 Neo4j 的聊天机器人

  ¥Build a Neo4j-backed Chatbot with TypeScript

LangChain.js x AI SDK

如何将 LangChain.js 与 AI SDK 和 React 服务器组件一起使用。

¥How to use LangChain.js with AI SDK and React Server Components.

• 将代理数据流式传输到客户端

  ¥Streaming agentic data to the client

• 将工具响应流式传输到客户端

  ¥Streaming tool responses to the client

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