Agent Skills › langchain-ai/langchain-skills › langchain-python-quickstart

langchain-python-quickstart

GitHub

指导用户基于官方文档快速搭建本地 LangChain Agent。通过询问模型提供商，在独立目录中配置环境、安装依赖并运行示例，实现最小化且模型无关的 AI 应用原型开发。

config/skills/langchain-python-quickstart/SKILL.md langchain-ai/langchain-skills

触发场景

用户希望快速尝试或构建 LangChain Agent 需要初始化 Python 环境的 LangChain 项目

安装

npx skills add langchain-ai/langchain-skills --skill langchain-python-quickstart -g -y

更多选项

非标准路径

npx skills add https://github.com/langchain-ai/langchain-skills/tree/main/config/skills/langchain-python-quickstart -g -y

不安装直接使用

npx skills use langchain-ai/langchain-skills@langchain-python-quickstart

指定 Agent (Claude Code)

npx skills add langchain-ai/langchain-skills --skill langchain-python-quickstart -a claude-code -g -y

安装 repo 全部 skill

npx skills add langchain-ai/langchain-skills --all -g -y

预览 repo 内 skill

npx skills add langchain-ai/langchain-skills --list

SKILL.md

Frontmatter

{
    "name": "langchain-python-quickstart",
    "description": "Scaffold a minimal local LangChain agent in Python by following the official quickstart. Use when the user wants to quickly build or try a LangChain agent locally."
}

LangChain Python quickstart

Follow the live docs — do not invent an alternate API from memory:

https://docs.langchain.com/oss/python/langchain/quickstart

Fetch that page (Docs MCP or HTTP) and implement what it shows (weather agent + create_agent).

Local setup constraints

Apply these on top of the quickstart (they keep setup minimal and model-agnostic):

Ask which provider/model to use. Showcase that LangChain is model-agnostic. Suggested prompt:

Which model should this agent use? Pass a provider:model string — e.g. openai:gpt-5.5, anthropic:claude-sonnet-5, google_genai:gemini-2.5-flash-lite. Default if you're unsure: anthropic:claude-sonnet-5.

Swap the quickstart's model string for their choice (or the default).
Create a new directory (e.g. langchain-agent/) and do all work there — do not pollute the open project.
Only secret: the provider API key in .env (gitignored). No LangSmith / Tavily unless they ask. Prefer they edit .env themselves — don't paste keys into chat.
Install the provider package needed for their model if the quickstart's base install isn't enough.
Run the example, show output, then stop. Point to langchain-fundamentals for next steps.