Agente de gestión para principiantes con herramientas de subagentes
Este es unEngineering, Multimodal AIflujo de automatización del dominio deautomatización que contiene 13 nodos.Utiliza principalmente nodos como Agent, AgentTool, LmChatOpenAi, MemoryBufferWindow. Agente de gestión para principiantes con herramientas de subagentes
- •Clave de API de OpenAI
Nodos utilizados (13)
Categoría
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"nodes": [
{
"id": "e816ff5f-d3d4-4416-96d9-961a078fb188",
"name": "Modelo de chat OpenAI",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
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"credentials": {
"openAiApi": {
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"name": "OpenAi account 4"
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{
"id": "9b121aea-be80-46a0-879d-5732b7d4d4f3",
"name": "Simple Memoria",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
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"parameters": {},
"typeVersion": 1.3
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"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
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{
"id": "c07ce435-64a0-4939-918b-9954e7e663e3",
"name": "Modelo de chat OpenAI1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
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"model": {
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"mode": "list",
"value": "gpt-4o-mini",
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"credentials": {
"openAiApi": {
"id": "4l6TDfLZVFS24g3X",
"name": "OpenAi account 4"
}
},
"typeVersion": 1.2
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{
"id": "20c108c9-221d-4dde-92ff-028ab4b12c2b",
"name": "Modelo de chat OpenAI2",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
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"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini",
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"credentials": {
"openAiApi": {
"id": "4l6TDfLZVFS24g3X",
"name": "OpenAi account 4"
}
},
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{
"id": "263bd596-d242-4a3e-8555-d23e172b23ef",
"name": "DataAgente (Insight Generator)",
"type": "@n8n/n8n-nodes-langchain.agentTool",
"position": [
1184,
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],
"parameters": {
"text": "{{json.query}}",
"options": {},
"toolDescription": "Role: Responds to instructions requiring metrics, summaries, or data analysis explanations."
},
"typeVersion": 2.2
},
{
"id": "2efc2325-6fee-4fce-a4ba-8b9b72701a8d",
"name": "Simple Memoria2",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
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"parameters": {},
"typeVersion": 1.3
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{
"id": "8c0e14bd-e64f-473f-9f31-0b0d2c800669",
"name": "ManagerAgente (Routing + Instruction Generator)",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
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"parameters": {
"options": {
"systemMessage": "You are an AI Manager that delegates tasks to specialized agents. Your job is to analyze the user's message and decide whether it requires:\n\nAn EmailAgent for writing outreach, follow-up, or templated emails, or\n\nA DataAgent for tasks involving data summaries, metrics, or analysis.\n\nsend the instructions to the sub agents. \n\n"
}
},
"typeVersion": 2.2
},
{
"id": "ee67ff1c-5651-43bb-a836-f48cf0f4c2bd",
"name": "Correo electrónicoAgent (Communication Specialist)",
"type": "@n8n/n8n-nodes-langchain.agentTool",
"position": [
656,
512
],
"parameters": {
"text": "={{ $fromAI('Prompt__User_Message_', ``, 'string') }}",
"options": {
"systemMessage": "You are a professional Email Writing Assistant. You write polished, effective emails for tasks such as outreach, follow-ups, and client communication. Follow the instruction provided exactly and return only the email content. Use a warm, business-appropriate tone."
},
"toolDescription": "Role: Writes professional, friendly, or action-oriented emails based on instructions."
},
"typeVersion": 2.2
},
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"parameters": {
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"content": "## 📬 Need Help or Want to Customize This?\n📧 [robert@ynteractive.com](mailto:robert@ynteractive.com) \n🔗 [LinkedIn](https://www.linkedin.com/in/robert-breen-29429625/)"
},
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"name": "Nota adhesiva",
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"parameters": {
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"content": "## 🔧 Step 1: Set Up the Manager Agent\n\nStart by dragging in an **Agent** node and name it something like `ManagerAgent`. This agent will act as the “brain” of your system, analyzing the user's input and determining whether it should be handled by the email-writing sub-agent or the data-summary sub-agent.\n\nOpen the node’s settings and paste the following into the **System Message**:\n\nYou are an AI Manager that delegates tasks to specialized agents. Your job is to analyze the user's message and decide whether it requires:\n\nAn EmailAgent for writing outreach, follow-up, or templated emails, or\n\nA DataAgent for tasks involving data summaries, metrics, or analysis.\n\nSend the instructions to the sub agents.\n\n\nThis instruction gives the Manager Agent clarity on what roles exist and what types of tasks belong to each one.\n\n"
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"content": "## 📊 Step 3: Create the Data Agent Tool\n\nRepeat the same steps, but this time for data summaries and analysis.\n\nAdd another **Agent Tool** node and name it `DataAgent`. In the **Tool Description**, write something like:\n\nResponds to instructions requiring metrics, summaries, or data analysis explanations.\n\nFor its input text field, you can use:\n\n{{json.query}}\n\nIf desired, provide a system message that gives the agent more detailed instruction on how to behave:\n\nNow the Manager Agent has two tools it can delegate to: one for communication and one for insights.\n\n"
},
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"name": "Nota adhesiva1",
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"content": "\n## ✉️ Step 4: Create the Email Agent Tool\n\nNow you’ll create a specialized sub-agent that only writes emails.\n\nAdd an **Agent Tool** node and call it `EmailAgent`. In the tool’s settings, describe its job clearly. For example:\n\n```\nWrites professional, friendly, or action-oriented emails based on instructions.\n```\n\nThen scroll down to the **System Message** section and enter the message\n\nFor the text input field, use the expression:\n\n{{ $fromAI('Prompt__User_Message_', ``, 'string') }}\n\nThis allows the Email Agent to receive exactly what the Manager Agent wants it to handle.\n\n\nFinally, connect this entire EmailAgent setup back to the `ManagerAgent` by attaching it to its `ai_tool` input.\n\n"
},
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],
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"connections": {
"Simple Memory": {
"ai_memory": [
[
{
"node": "EmailAgent (Communication Specialist)",
"type": "ai_memory",
"index": 0
}
]
]
},
"Simple Memory1": {
"ai_memory": [
[
{
"node": "DataAgent (Insight Generator)",
"type": "ai_memory",
"index": 0
}
]
]
},
"Simple Memory2": {
"ai_memory": [
[
{
"node": "ManagerAgent (Routing + Instruction Generator)",
"type": "ai_memory",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "ManagerAgent (Routing + Instruction Generator)",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"OpenAI Chat Model1": {
"ai_languageModel": [
[
{
"node": "EmailAgent (Communication Specialist)",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"OpenAI Chat Model2": {
"ai_languageModel": [
[
{
"node": "DataAgent (Insight Generator)",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"DataAgent (Insight Generator)": {
"ai_tool": [
[
{
"node": "ManagerAgent (Routing + Instruction Generator)",
"type": "ai_tool",
"index": 0
}
]
]
},
"EmailAgent (Communication Specialist)": {
"ai_tool": [
[
{
"node": "ManagerAgent (Routing + Instruction Generator)",
"type": "ai_tool",
"index": 0
}
]
]
}
}
}¿Cómo usar este flujo de trabajo?
Copie el código de configuración JSON de arriba, cree un nuevo flujo de trabajo en su instancia de n8n y seleccione "Importar desde JSON", pegue la configuración y luego modifique la configuración de credenciales según sea necesario.
¿En qué escenarios es adecuado este flujo de trabajo?
Intermedio - Ingeniería, IA Multimodal
¿Es de pago?
Este flujo de trabajo es completamente gratuito, puede importarlo y usarlo directamente. Sin embargo, tenga en cuenta que los servicios de terceros utilizados en el flujo de trabajo (como la API de OpenAI) pueden requerir un pago por su cuenta.
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Robert Breen
@rbreenProfessional services consultant with over 10 years of experience solving complex business problems across industries. I specialize in n8n and process automation—designing custom workflows that integrate tools like Google Calendar, Airtable, GPT, and internal systems. Whether you need to automate scheduling, sync data, or streamline operations, I build solutions that save time and drive results.
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