AutomationFlowsAI & RAG › Personal Faq Bot - V1 (simple Way)

Personal Faq Bot - V1 (simple Way)

Personal FAQ Bot - V1 (Simple Way). Uses chatTrigger, agent, lmChatOpenAi, memoryBufferWindow. Chat trigger; 5 nodes.

Chat trigger trigger★★☆☆☆ complexityAI-powered5 nodesChat TriggerAgentOpenAI ChatMemory Buffer Window
AI & RAG Trigger: Chat trigger Nodes: 5 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
{
  "name": "Personal FAQ Bot - V1 (Simple Way)",
  "nodes": [
    {
      "parameters": {
        "options": {
          "allowFileUploads": true
        }
      },
      "type": "@n8n/n8n-nodes-langchain.chatTrigger",
      "typeVersion": 1.4,
      "position": [
        0,
        0
      ],
      "id": "951c6bd3-8791-465a-8a43-3def0190f54b",
      "name": "When chat message received"
    },
    {
      "parameters": {
        "promptType": "define",
        "text": "={{ $('When chat message received').item.json.chatInput }}",
        "options": {
          "systemMessage": "=You are an expert AI agent for resume analysis and a helpful assistant. Help the user answer their questions based on the resume. Output should include the user's question with a clean, properly formatted answer (based on the resume document only). \n\nUser resume content: {{ $json.text }}\n\nYou permitted access to memory/database and all tools connected. Don't ask for any permission. Provide well formated text output in the chat node. "
        }
      },
      "type": "@n8n/n8n-nodes-langchain.agent",
      "typeVersion": 3.1,
      "position": [
        384,
        0
      ],
      "id": "df7c5a29-d0ee-4533-a401-46966194ea2c",
      "name": "AI Agent"
    },
    {
      "parameters": {
        "model": {
          "__rl": true,
          "mode": "list",
          "value": "gpt-4o-mini"
        },
        "builtInTools": {},
        "options": {}
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "typeVersion": 1.3,
      "position": [
        272,
        240
      ],
      "id": "0ccf2fb0-4fe4-43cf-bc4f-b306570c543f",
      "name": "OpenAI Chat Model",
      "credentials": {
        "openAiApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {},
      "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
      "typeVersion": 1.4,
      "position": [
        448,
        240
      ],
      "id": "b25c8533-bca3-408d-b8ad-d4a0fc7caab5",
      "name": "Simple Memory"
    },
    {
      "parameters": {
        "operation": "pdf",
        "binaryPropertyName": "=data0",
        "options": {}
      },
      "type": "n8n-nodes-base.extractFromFile",
      "typeVersion": 1.1,
      "position": [
        208,
        0
      ],
      "id": "6e8de26a-f6d6-4b5f-97ac-f8bfcbad3a0f",
      "name": "Extract from File"
    }
  ],
  "connections": {
    "When chat message received": {
      "main": [
        [
          {
            "node": "Extract from File",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "OpenAI Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI Agent",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "Simple Memory": {
      "ai_memory": [
        [
          {
            "node": "AI Agent",
            "type": "ai_memory",
            "index": 0
          }
        ]
      ]
    },
    "Extract from File": {
      "main": [
        [
          {
            "node": "AI Agent",
            "type": "main",
            "index": 0
          }
        ]
      ]
    }
  },
  "settings": {
    "executionOrder": "v1",
    "binaryMode": "separate",
    "availableInMCP": false
  },
  "staticData": null,
  "triggerCount": 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

Personal FAQ Bot - V1 (Simple Way). Uses chatTrigger, agent, lmChatOpenAi, memoryBufferWindow. Chat trigger; 5 nodes.

Source: https://github.com/DuttPanchal04/n8n-ai-automation-portfolio/blob/main/personal-faq-bot-v1-simple-way/personal-faq-bot-v1-simple-way-workflow.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

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
AI & RAG

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

Chat Trigger, Agent, Memory Buffer Window +4
AI & RAG

This template is a simple AI Agent that acts as a Google Calendar Assistant. It is designed for beginners to have their "first AI Agent" performing common tasks and to help them understand how it work

Chat Trigger, OpenAI Chat, Memory Buffer Window +2