langchain-python-quickstart
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.
Datos de origen
- Repositorio
- langchain-ai/langchain-skills
- Última actividad en el origen
- 22 de julio de 2026 a las 19:32
- Idioma detectado de SKILL.md
- inglés
- Estrellas
- 1316
- Forks
- 106
Opciones de instalación
De forma predeterminada está seleccionado el prompt que primero revisa el origen. Puedes cambiar a un comando directo o descargar una copia local.
Revisa los archivos de origen
Lee SKILL.md y los archivos complementarios que muestra SkillsMP antes de decidir si quieres instalarlo.
Mostrando SKILL.md
SKILL.md
Instrucciones de origen · Vista previa de solo lectura- 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):
1. **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).
2. Create a **new** directory (e.g. `langchain-agent/`) and do all work there — do not pollute the open project.
3. 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.
4. Install the provider package needed for their model if the quickstart's base install isn't enough.
5. Run the example, show output, then stop. Point to `langchain-fundamentals` for next steps.
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