| 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.