Agent skill · DevOps & Cloud

langchain-chat-models

使用 LangChain 中的聊天模型集成指南，包括 OpenAI、Anthropic、Google、Azure 和 Bedrock

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill langchain-integrations-chat-models --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 9 KB
Bundled scripts: none
Path: skills/ai-llm/langchain-integrations-chat-models/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# langchain-chat-models (JavaScript/TypeScript) ## 概述 LangChain 中的聊天模型为与各种 LLM 提供商交互提供了统一接口。它们接受消息序列作为输入，并返回 AI 生成的消息作为输出。聊天模型支持工具调用、结构化输出和流式传输等功能。 ### 核心概念 - **聊天模型**：接受消息（具有角色：system、user、assistant）并返回生成的响应 - **提供商**：提供 LLM API 的不同 AI 公司（OpenAI、Anthropic、Google、Azure、Bedrock 等） - **工具调用**：模型可以根据用户查询调用函数/工具 - **流式传输**：实时逐令牌响应生成 - **结构化输出**：模型可以返回特定格式的响应（JSON、TypeScript 类型） ## 提供商选择决策表 | 提供商 | 最适合 | 模型示例 | 包 | 主要特性 | |----------|----------|----------------|---------|--------------| | **OpenAI** | 通用、函数调用 | gpt-4、gpt-4-turbo、gpt-3.5-turbo | `@langchain/openai` | 强大的函数调用、视觉、快速 | | **Anthropic** | 长上下文、安全性、分析 | claude-3-opus、claude-3-sonnet、claude-3-haiku | `@langchain/anthropic` | 200k 上下文、工具使用、提示缓存 | | **Google GenAI** | 多模态、免费层 | gemini-pro、gemini-pro-vision | `@langchain/google-genai` | 视觉、提供免费层 | | **Azure OpenAI** | 企业、合规性 | gpt-4、gpt-35-turbo（Azure 部署） | `@langchain/openai` | 企业 SLA、数据驻留 | | **AWS Bedrock** | AWS 生态系统、多样性 | claude、llama、titan 模型 | `@langchain/aws` | 多个模型、AWS 集成 | | **Google Vertex AI** | GCP 生态系统、企业 | gemini-pro、palm 模型 | `@langchain/google-vertexai` | 企业功能、GCP 集成 | ### 何时选择每个提供商 **选择 OpenAI 如果：** - 您需要强大的函数/工具调用能力 - 您希望快速的响应时间 - 您正在构建通用应用程序 **选择 Anthropic 如果：*

What's inside
Steps it walks through
  1. 概述
  2. 核心概念
  3. 提供商选择决策表
  4. 何时选择每个提供商
  5. 代码示例
  6. OpenAI 聊天模型
  7. Anthropic 聊天模型
  8. Azure OpenAI 聊天模型
  9. AWS Bedrock 聊天模型
  10. Google Generative AI
  11. 使用 initChatModel（推荐）
  12. 工具调用示例
  13. 边界
  14. 代理可以做什么
Ships with 1 file
  • metadata.json
Commands it runs
OpenAI
npm install @langchain/openai
Anthropic
npm install @langchain/anthropic
AWS (Bedrock)
npm install @langchain/aws
Google
npm install @langchain/google-genai
npm install @langchain/google-vertexai
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About this skill
What does the langchain-chat-models skill do?

使用 LangChain 中的聊天模型集成指南，包括 OpenAI、Anthropic、Google、Azure 和 Bedrock

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill langchain-integrations-chat-models --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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