Como usar
- Copie o comando e verifique o pacote antes de instalar no seu ambiente de agente.
- Consulte no original as ferramentas, credenciais e ambientes necessários.
- Descreva os dados de entrada e a entrega esperada; confira a saída com as fontes.
npx skills add https://github.com/langchain-ai/langchain-skills --skill langchain-python-quickstartAntes de começar
- A instalação não inclui assinatura de modelo, franquia API ou acesso aos seus arquivos.
- Estrelas e instalações indicam atividade, não um teste independente de qualidade ou segurança.
Documento original do Skill
Renderizado do repositório de origem, preservando títulos, exemplos, código, tabelas, links e imagens.
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 aprovider: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.
