{
  "workflow": {
    "id": 4875,
    "name": "Create a Telegram customer support bot with GPT4-mini and Google Docs knowledge",
    "views": 7654,
    "recentViews": 2,
    "totalViews": 7654,
    "createdAt": "2025-06-11T14:02:23.307Z",
    "description": "🤖 AI Customer Support Agent with Google Docs Knowledge (Telegram + OpenAI)\n\nThis no-code workflow turns your Telegram bot into an intelligent, always-on AI support agent that references your business documentation in Google Docs to respond to customer queries—instantly and accurately.\n\nWatch full step-by-step video tutorial of the build here:\nhttps://youtu.be/Mlv7CjGO7wI\n\n🔧 How it works:\nTelegram Trigger – Captures incoming messages from users on your Telegram bot\n\nLangchain AI Agent (OpenAI GPT) – Interprets the message and uses RAG (retrieval-augmented generation) techniques to craft an answer\n\nGoogle Docs Tool – Connects to and retrieves context from your specified Google Doc (e.g. FAQ, SOPs, policies)\n\nMemory Buffer – Keeps track of recent chat history for more human-like conversations\n\nTelegram Reply Node – Sends the AI-generated response back to the user\n\n💡 Use Cases:\nE-commerce customer service\n\nSaaS product onboarding\n\nInternal helpdesk bot for teams\n\nWhatsApp-style support for digital businesses\n\n🧠 What makes this powerful:\nSupports complex questions by referencing a live Google Doc knowledge base\n\nWorks in plain conversational language (no buttons or forms needed)\n\nRuns 24/7 with zero code\n\nEasily extendable to Slack, WhatsApp, or email support\n\n🛠️ Tools used:\nTelegram Node (trigger + send)\n\nLangchain Agent with OpenAI GPT\n\nGoogle Docs Tool\n\nMemory Buffer\n\nSticky Notes for easy understanding",
    "workflow": {
      "id": "",
      "meta": {},
      "name": "My workflow",
      "tags": [],
      "nodes": [
        {
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          "name": "OpenAI Chat Model",
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          "parameters": {
            "model": {
              "__rl": true,
              "mode": "list",
              "value": "gpt-4o-mini",
              "cachedResultName": "gpt-4o-mini"
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            "options": {}
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        {
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          "name": "Simple Memory",
          "type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
          "position": [
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          ],
          "parameters": {
            "sessionKey": "={{ $json.message.chat.id }}",
            "sessionIdType": "customKey"
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        {
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          "type": "n8n-nodes-base.googleDocsTool",
          "position": [
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          "parameters": {
            "operation": "get",
            "documentURL": "https://docs.google.com/document/d/1os02TMG0h74DYE_mmv5utPr68LtV946otozP1YZTNr0/edit?tab=t.0"
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          "parameters": {
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          "webhookId": "cfeeb7fc-6dad-4482-b8c7-73998bfc613f",
          "parameters": {
            "text": "={{ $json.output }}",
            "chatId": "={{ $('Telegram Trigger').item.json.message.chat.id }}",
            "additionalFields": {
              "appendAttribution": false
            }
          },
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        },
        {
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          "name": "Customer Support AI Agent",
          "type": "@n8n/n8n-nodes-langchain.agent",
          "position": [
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          "parameters": {
            "text": "={{ $json.message.text }}",
            "options": {
              "systemMessage": "You are a helpful Customer Support Agent, cross-reference the Google Doc for any customer queries for relevant information. If relevant information is not found, do not make up facts. Plainly let the user know that the information isn't available. \n\n#Tonality\nFriendly, casual and helpful. if user or customer says hi, inform them that you are a Friendly Customer Support Agent"
            },
            "promptType": "define"
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        },
        {
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          "position": [
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            "width": 360,
            "height": 500,
            "content": "🤖 AI Customer Support Agent with Google Docs Knowledge (Telegram + OpenAI)\n\nThis no-code workflow turns your Telegram bot into an intelligent, always-on AI support agent that references your business documentation in Google Docs to respond to customer queries—instantly and accurately.\n\nWatch full step-by-step video tutorial of the build here:\nhttps://www.youtube.com/@Automatewithmarc\n\n🔧 How it works:\nTelegram Trigger – Captures incoming messages from users on your Telegram bot\n\nLangchain AI Agent (OpenAI GPT) – Interprets the message and uses RAG (retrieval-augmented generation) techniques to craft an answer\n\nGoogle Docs Tool – Connects to and retrieves context from your specified Google Doc (e.g. FAQ, SOPs, policies)\n\nMemory Buffer – Keeps track of recent chat history for more human-like conversations\n\nTelegram Reply Node – Sends the AI-generated response back to the user\n\n💡 Use Cases:\nE-commerce customer service\n\nSaaS product onboarding\n\nInternal helpdesk bot for teams\n\nWhatsApp-style support for digital businesses\n\n🧠 What makes this powerful:\nSupports complex questions by referencing a live Google Doc knowledge base\n\nWorks in plain conversational language (no buttons or forms needed)\n\nRuns 24/7 with zero code\n\nEasily extendable to Slack, WhatsApp, or email support\n\n🛠️ Tools used:\nTelegram Node (trigger + send)\n\nLangchain Agent with OpenAI GPT\n\nGoogle Docs Tool\n\nMemory Buffer\n\nSticky Notes for easy understanding"
          },
          "typeVersion": 1
        }
      ],
      "active": true,
      "pinData": {},
      "settings": {
        "executionOrder": "v1"
      },
      "versionId": "",
      "connections": {
        "Google Docs": {
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        },
        "Simple Memory": {
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        },
        "Telegram Trigger": {
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              }
            ]
          ]
        },
        "OpenAI Chat Model": {
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        "Customer Support AI Agent": {
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                "node": "Telegram",
                "type": "main",
                "index": 0
              }
            ]
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        }
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    },
    "lastUpdatedBy": 29,
    "workflowInfo": {
      "nodeCount": 10,
      "nodeTypes": {
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        },
        "n8n-nodes-base.stickyNote": {
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        "@n8n/n8n-nodes-langchain.agent": {
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        },
        "n8n-nodes-base.telegramTrigger": {
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        "@n8n/n8n-nodes-langchain.lmChatOpenAi": {
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        },
        "@n8n/n8n-nodes-langchain.memoryBufferWindow": {
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        }
      }
    },
    "status": "published",
    "user": {
      "name": "Automate With Marc",
      "username": "marconi",
      "bio": "Automating Start-Up and Business processes. \nHelping non-techies understand and leverage Agentic AI with easy to understand step-by-step tutorials.\nCheck out my educational content:\nhttps://www.youtube.com/@Automatewithmarc\n",
      "verified": true,
      "links": [
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      "avatar": "https://gravatar.com/avatar/b9654a0dd147e6f3fa7e6eb601b6572b8051c8ab4cb693774451adf9a6294798?r=pg&d=retro&size=200"
    },
    "nodes": [
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        "icon": "file:telegram.svg",
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            ],
            "resources": {
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                  "url": "https://n8n.io/blog/why-business-process-automation-with-n8n-can-change-your-daily-life/",
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                  "label": "Why business process automation with n8n can change your daily life"
                },
                {
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                  "icon": "🤬",
                  "label": "Create a toxic language detector for Telegram in 4 step"
                },
                {
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                  "icon": "🧾",
                  "label": "Automatically Adding Expense Receipts to Google Sheets with Telegram, Mindee, Twilio, and n8n"
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                  "icon": "store",
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                },
                {
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                  "icon": "📜",
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        },
        "group": "[\"output\"]",
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            "nodeVersion": "1.0",
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        },
        "group": "[\"trigger\"]",
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          }
        },
        "group": "[\"input\"]",
        "defaults": {
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          "color": "#FFD233"
        },
        "iconData": {
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