langchain-python-quickstart
GitHub指导用户快速搭建本地 LangChain Agent,通过读取官方文档并遵循最小化设置约束(如模型无关、隔离目录、安全处理密钥)实现基础示例。
触发场景
安装
npx skills add langchain-ai/langchain-skills --skill langchain-python-quickstart -g -y
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:modelstring — 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.envthemselves — 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-fundamentalsfor next steps.
版本历史
- f3ea282 当前 2026-08-02 21:50


