langchain-python-quickstart

Original：🇺🇸 English

Translated

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.

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Sourcelangchain-ai/langchain-skills

Added on2026-07-24

NPX Install

npx skill4agent add langchain-ai/langchain-skills langchain-python-quickstart

SKILL.md Content

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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.

langchain-python-quickstart

NPX Install

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SKILL.md Content

LangChain Python quickstart

Local setup constraints