Emanuel Almeida
2cb3210962
Plugins: automacao, crm-ops, design-media, dev-tools, gestao, infraestrutura, marketing, negocio, perfex-dev, project-manager, wordpress + hello-plugin (existente). Totais: 83 skills, 44 agents, 12 datasets.json Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
280 lines
4.8 KiB
Markdown
280 lines
4.8 KiB
Markdown
# /n8n-chatbot - Chatbots e AI Agents n8n
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Criar chatbots e workflows com AI usando LangChain.
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---
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## Uso
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```
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/n8n-chatbot create <descrição> # Criar chatbot
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/n8n-chatbot agent <tipo> # Criar AI agent
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/n8n-chatbot rag <knowledge_base> # Criar sistema RAG
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```
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---
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## Workflow Obrigatório
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```
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1. Health check → mcp__n8n__n8n_health_check()
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2. Pesquisar template → mcp__n8n__search_templates({ task: "ai_automation" })
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3. Se template OK → mcp__n8n__n8n_deploy_template()
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4. Se criar do zero → Seguir fluxo abaixo
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```
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---
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## Nodes LangChain
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### Core
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| Node | Uso |
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|------|-----|
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| `@n8n/n8n-nodes-langchain.agent` | AI Agent principal |
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| `@n8n/n8n-nodes-langchain.chainLlm` | Chain LLM simples |
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| `@n8n/n8n-nodes-langchain.chainRetrievalQa` | RAG Q&A |
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### Modelos
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| Node | Provider |
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|------|----------|
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| `@n8n/n8n-nodes-langchain.lmChatOpenAi` | OpenAI GPT |
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| `@n8n/n8n-nodes-langchain.lmChatAnthropic` | Claude |
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| `@n8n/n8n-nodes-langchain.lmChatOllama` | Ollama local |
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### Memória
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| Node | Tipo |
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|------|------|
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| `@n8n/n8n-nodes-langchain.memoryBufferWindow` | Últimas N mensagens |
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| `@n8n/n8n-nodes-langchain.memoryPostgresChat` | PostgreSQL |
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| `@n8n/n8n-nodes-langchain.memoryRedisChat` | Redis |
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### Tools
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| Node | Função |
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|------|--------|
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| `@n8n/n8n-nodes-langchain.toolCalculator` | Cálculos |
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| `@n8n/n8n-nodes-langchain.toolCode` | Executar código |
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| `@n8n/n8n-nodes-langchain.toolHttpRequest` | Chamar APIs |
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| `@n8n/n8n-nodes-langchain.toolWorkflow` | Chamar workflows |
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### Vector Stores (RAG)
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| Node | Sistema |
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|------|---------|
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| `@n8n/n8n-nodes-langchain.vectorStoreSupabase` | Supabase |
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| `@n8n/n8n-nodes-langchain.vectorStorePinecone` | Pinecone |
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| `@n8n/n8n-nodes-langchain.vectorStorePgVector` | PostgreSQL |
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---
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## Chatbot Básico
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### Estrutura
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```
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Webhook/Trigger
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↓
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LLM Chat Model (OpenAI/Claude)
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↓
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Memory (Buffer)
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↓
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Agent
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↓
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Resposta
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```
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### Implementação
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```javascript
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// 1. Modelo LLM
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mcp__n8n__get_node({
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nodeType: "@n8n/n8n-nodes-langchain.lmChatOpenAi",
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detail: "standard"
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})
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// 2. Memória
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mcp__n8n__get_node({
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nodeType: "@n8n/n8n-nodes-langchain.memoryBufferWindow",
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detail: "standard"
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})
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// 3. Agent
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mcp__n8n__get_node({
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nodeType: "@n8n/n8n-nodes-langchain.agent",
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detail: "standard"
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})
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```
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---
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## RAG (Retrieval Augmented Generation)
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### Estrutura
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```
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Documentos
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↓
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Embeddings
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↓
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Vector Store
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↓
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Query (pergunta)
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↓
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Retriever
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↓
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LLM (resposta contextualizada)
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```
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### Configuração Vector Store
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```javascript
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mcp__n8n__validate_node({
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nodeType: "@n8n/n8n-nodes-langchain.vectorStoreSupabase",
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config: {
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mode: "insert", // ou "retrieve"
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tableName: "documents",
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queryName: "match_documents"
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},
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mode: "minimal"
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})
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```
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---
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## AI Agent com Tools
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### Estrutura
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```
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Input
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↓
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Agent
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├── Tool: Calculator
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├── Tool: HTTP Request
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├── Tool: Code
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└── Tool: Workflow
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↓
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Output
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```
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### Configuração Agent
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```javascript
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mcp__n8n__validate_node({
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nodeType: "@n8n/n8n-nodes-langchain.agent",
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config: {
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agentType: "conversationalAgent",
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systemMessage: "Tu és um assistente prestável...",
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options: {
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returnIntermediateSteps: true
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}
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},
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mode: "minimal"
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})
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```
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---
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## Exemplos Práticos
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### Chatbot de Suporte
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```
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Webhook (mensagem cliente)
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↓
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Memory PostgreSQL (histórico)
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↓
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Vector Store (docs suporte)
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↓
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Chain Retrieval QA
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↓
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Webhook Response
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```
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### Agent CRM
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```
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Webhook (comando)
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↓
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Agent
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├── Tool: Pesquisar clientes
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├── Tool: Criar lead
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└── Tool: Actualizar tarefa
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↓
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Slack (resultado)
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```
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### Resumo de Documentos
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```
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Webhook (upload PDF)
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↓
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PDF Extract
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↓
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Text Splitter
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↓
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LLM Chain (resumo)
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↓
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Email (enviar resumo)
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```
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---
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## Templates Recomendados
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```javascript
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// AI templates
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mcp__n8n__search_templates({
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searchMode: "by_task",
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task: "ai_automation"
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})
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// Por keyword
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mcp__n8n__search_templates({
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searchMode: "keyword",
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query: "chatbot langchain openai"
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})
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```
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---
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## Credenciais Necessárias
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| Provider | Credencial | Node |
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|----------|------------|------|
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| OpenAI | API Key | lmChatOpenAi |
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| Anthropic | API Key | lmChatAnthropic |
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| Supabase | URL + Key | vectorStoreSupabase |
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| Pinecone | API Key | vectorStorePinecone |
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---
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## Boas Práticas
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| Prática | Razão |
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|---------|-------|
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| System prompt claro | Define comportamento |
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| Temperatura baixa (0.1-0.3) | Respostas consistentes |
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| Memória limitada | Performance |
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| Retry on error | Resiliência |
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| Logs de conversas | Debug e melhoria |
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---
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## Troubleshooting
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| Problema | Solução |
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|----------|---------|
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| Respostas inconsistentes | Baixar temperatura |
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| Contexto perdido | Verificar memória |
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| RAG não encontra | Verificar embeddings |
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| Timeout | Aumentar limite |
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| Token limit | Resumir contexto |
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---
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*Skill v1.0 | Descomplicar®*
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