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
- Origem: davila7/claude-code-templates
- Caminho:
cli-tool/components/skills/ai-research/agents-langchain - Versão fixada:
57f899e5394bb8ca166f38eacae8f0853cbfe033 - Licença: MIT
- Espelhado em 25/09/2026
- 23 downloads no Claude Code Templates (lido em 25/09/2026)
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
…