Skill · em Dados, IA e pesquisa

langchain

Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous…

Procedência

Antes de instalar

4 arquivos · 50,6 KB · só texto, nenhum script

Instalar na sua CLI

O comando baixa a versão fixada (commit 57f899e) direto da origem, para a pasta que a CLI lê. Precisa de curl (macOS e Linux); no Windows não há comando, porque o Rook Labs é para macOS.

Claude Code

Neste projeto: instala em .claude/skills/langchain/.

d=".claude/skills/langchain"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/agents-langchain"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/agents.md" "$u/references/agents.md" \
  -o "$d/references/integration.md" "$u/references/integration.md" \
  -o "$d/references/rag.md" "$u/references/rag.md"

Global: instala em ~/.claude/skills/langchain/.

d="$HOME/.claude/skills/langchain"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/agents-langchain"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/agents.md" "$u/references/agents.md" \
  -o "$d/references/integration.md" "$u/references/integration.md" \
  -o "$d/references/rag.md" "$u/references/rag.md"

Codex

Neste projeto: instala em .agents/skills/langchain/.

d=".agents/skills/langchain"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/agents-langchain"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/agents.md" "$u/references/agents.md" \
  -o "$d/references/integration.md" "$u/references/integration.md" \
  -o "$d/references/rag.md" "$u/references/rag.md"

Global: instala em ~/.agents/skills/langchain/.

d="$HOME/.agents/skills/langchain"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/agents-langchain"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/agents.md" "$u/references/agents.md" \
  -o "$d/references/integration.md" "$u/references/integration.md" \
  -o "$d/references/rag.md" "$u/references/rag.md"

Antigravity

Neste projeto: instala em .agents/skills/langchain/.

d=".agents/skills/langchain"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/agents-langchain"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/agents.md" "$u/references/agents.md" \
  -o "$d/references/integration.md" "$u/references/integration.md" \
  -o "$d/references/rag.md" "$u/references/rag.md"

Global: instala em ~/.gemini/antigravity-cli/skills/langchain/.

d="$HOME/.gemini/antigravity-cli/skills/langchain"
u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/agents-langchain"
curl -fsSL --create-dirs \
  -o "$d/SKILL.md" "$u/SKILL.md" \
  -o "$d/references/agents.md" "$u/references/agents.md" \
  -o "$d/references/integration.md" "$u/references/integration.md" \
  -o "$d/references/rag.md" "$u/references/rag.md"

Peça ao Rook

Já usa o Rook Labs? Cole no chat do Rook: instale a skill https://rooklabs.sh/marketplace/cct.langchain

Prévia do SKILL.md

---
name: langchain
description: Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or R…
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [Agents, LangChain, RAG, Tool Calling, ReAct, Memory Management, Vector Stores, LLM Applications, Chatbots, Production]
dependencies: [langchain, langchain-core, langchain-openai, langchain-anthropic]
---

# LangChain - Build LLM Applications with Agents & RAG

The most popular framework for building LLM-powered applications.

## When to use LangChain

**Use LangChain when:**
- Building agents with tool calling and reasoning (ReAct pattern)
- Implementing RAG (retrieval-augmented generation) pipelines
- Need to swap LLM providers easily (OpenAI, Anthropic, Google)
- Creating chatbots with conversation memory
- Rapid prototyping of LLM applications
- Production deployments with LangSmith observability

**Metrics**:
- **119,000+ GitHub stars**
- **272,000+ repositories** use LangChain
- **500+ integrations** (models, vector stores, tools)
- **3,800+ contributors**

**Use alternatives instead**:
- **LlamaIndex**: RAG-focused, better for document Q&A
- **LangGraph**: Complex stateful workflows, more control
- **Haystack**: Production search pipelines
- **Semantic Kernel**: Microsoft ecosystem

## Quick start

### Installation
…

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