AutomationFlowsAI & RAG › AI Chat Agent with Data Tables

AI Chat Agent with Data Tables

Original n8n title: Agente Data Tables

Agente Data Tables. Uses chatTrigger, agent, lmChatOpenAi, dataTableTool. Chat trigger; 4 nodes.

Chat trigger trigger★★☆☆☆ complexityAI-powered4 nodesChat TriggerAgentOpenAI ChatData Table Tool
AI & RAG Trigger: Chat trigger Nodes: 4 Complexity: ★★☆☆☆ AI nodes: yes Added:

This workflow follows the Agent → Chat Trigger recipe pattern — see all workflows that pair these two integrations.

The workflow JSON

Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →

Download .json
{
  "nodes": [
    {
      "parameters": {
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "typeVersion": 1.4,
      "position": [
        0,
        0
      ],
      "id": "640335cf-ed79-4dd6-bce3-dd9ef0b00cc4",
      "name": "When chat message received"
    },
    {
      "parameters": {
        "options": {
          "systemMessage": "Sos un asistente que siempre le dice al usuario \"Esper\u00e1 un momentito, ...\" y luego una excusa como que hay un transistor que no te anda o cosas as\u00ed. Luego siempre us\u00e1 la tool para registrar el chat en la data table y guardar de manera estructurada."
        }
      },
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 3,
      "position": [
        208,
        0
      ],
      "id": "a8114eaa-0393-4376-80a3-adff593a7689",
      "name": "AI Agent"
    },
    {
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4.1-mini"
        },
        "builtInTools": {},
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "typeVersion": 1.3,
      "position": [
        144,
        240
      ],
      "id": "05b1b947-8883-4362-abe5-c1f86aef45b7",
      "name": "OpenAI Chat Model",
      "credentials": {
        "openAiApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "descriptionType": "manual",
        "toolDescription": "Insertar conclusiones de cada chat con esta herramienta",
        "dataTableId": {
          "__rl": true,
          "value": "8Zr9k18qXMnYQKb0",
          "mode": "list",
          "cachedResultName": "demo",
          "cachedResultUrl": "/projects/gnqQBQv4EN1Wf8nw/datatables/8Zr9k18qXMnYQKb0"
        },
        "columns": {
          "mappingMode": "defineBelow",
          "value": {
            "sessionId": "={{ $json.sessionId }}",
            "conclusiones": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('conclusiones', ``, 'string') }}"
          },
          "matchingColumns": [],
          "schema": [
            {
              "id": "sessionId",
              "displayName": "sessionId",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "readOnly": false,
              "removed": false
            },
            {
              "id": "conclusiones",
              "displayName": "conclusiones",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "readOnly": false,
              "removed": false
            }
          ],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {
          "optimizeBulk": false
        }
      },
      "type": "n8n-nodes-base.dataTableTool",
      "typeVersion": 1,
      "position": [
        416,
        256
      ],
      "id": "697a1dca-4616-4a99-abb6-a9ae4098346f",
      "name": "insertar en data table",
      "notes": "Insertar conclusiones de cada chat con esta herramienta"
    }
  ],
  "connections": {
    "When chat message received": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "insertar en data table": {
      "ai_tool": [
        [
          {
            "node": "AI Agent",
            "type": "ai_tool",
            "index": 0
          }
        ]
      ]
    }
  },
  "meta": {
    "templateCredsSetupCompleted": true
  }
}

Credentials you'll need

Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.

Pro

For the full experience including quality scoring and batch install features for each workflow upgrade to Pro

About this workflow

Agente Data Tables. Uses chatTrigger, agent, lmChatOpenAi, dataTableTool. Chat trigger; 4 nodes.

Source: https://github.com/mnsosa/automatizacion-n8n/blob/2421d3534f43e49aceff37acd7e38f962940053b/templates/agente_data_tables.json — original creator credit. Request a take-down →

More AI & RAG workflows → · Browse all categories →

Related workflows

Workflows that share integrations, category, or trigger type with this one. All free to copy and import.

AI & RAG

This workflow serves a Question and Answer chat experience to an end user. It uses an AI Agent with a tool to fetch Question and Answer pairs stored in a Data Table (to serve the user answers grounded

Chat Trigger, Agent, OpenAI Chat +2
AI & RAG

This project is an automation workflow that generates a personalized resume and cover letter for each job listing. Generates an HTML resume from your data. Hosts it live on GitHub Pages. Converts it t

HTTP Request, Agent, OpenAI Chat +10
AI & RAG

AI Agent : Google calendar assistant using OpenAI. Uses chatTrigger, lmChatOpenAi, memoryBufferWindow, googleCalendarTool. Chat trigger; 13 nodes.

Chat Trigger, OpenAI Chat, Memory Buffer Window +2
AI & RAG

OpenSea AI-Powered Insights via Telegram. Uses chatTrigger, telegramTrigger, lmChatOpenAi, memoryBufferWindow. Chat trigger; 13 nodes.

Chat Trigger, Telegram Trigger, OpenAI Chat +4
AI & RAG

Build an MCP server with Airtable. Uses chatTrigger, agent, memoryBufferWindow, mcpClientTool. Chat trigger; 13 nodes.

Chat Trigger, Agent, Memory Buffer Window +4