Konstantin This workflow corresponds to n8n.io template #12228 — we link there as the canonical source.
This workflow follows the Agent → Documentdefaultdataloader 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 →
{
"meta": {
"templateCredsSetupCompleted": true
},
"nodes": [
{
"id": "5496c2ac-9017-47e4-9c7f-666e08008ae2",
"name": "New File Trigger",
"type": "n8n-nodes-base.googleDriveTrigger",
"notes": "Triggers when a new file is created in the specified Google Drive folder",
"position": [
480,
1296
],
"parameters": {
"event": "fileCreated",
"options": {},
"pollTimes": {
"item": [
{
"mode": "everyX",
"unit": "minutes",
"value": 15
}
]
},
"triggerOn": "specificFolder",
"folderToWatch": {
"__rl": true,
"mode": "list",
"value": "1FHG5g1T1CyctyPwwVsc64E-uIOlMLcTl",
"cachedResultUrl": "https://drive.google.com/drive/folders/1FHG5g1T1CyctyPwwVsc64E-uIOlMLcTl",
"cachedResultName": "Qdranttest"
}
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 1
},
{
"id": "a70a0164-2aef-419d-b289-9ad150204c41",
"name": "Download File",
"type": "n8n-nodes-base.googleDrive",
"notes": "Downloads the file from Google Drive",
"position": [
720,
1296
],
"parameters": {
"fileId": {
"__rl": true,
"mode": "id",
"value": "={{ $json.id }}"
},
"options": {},
"operation": "download"
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 3
},
{
"id": "e34f840a-2282-4f70-8e96-5ed82b4527fd",
"name": "Move to Processed Folder",
"type": "n8n-nodes-base.googleDrive",
"notes": "Moves the processed file to the 'Qdrant Ready' folder",
"position": [
1360,
1296
],
"parameters": {
"fileId": {
"__rl": true,
"mode": "id",
"value": "={{ $('Download File').item.json.id }}"
},
"driveId": {
"__rl": true,
"mode": "list",
"value": "My Drive",
"cachedResultUrl": "https://drive.google.com/drive/my-drive",
"cachedResultName": "My Drive"
},
"folderId": {
"__rl": true,
"mode": "list",
"value": "18ULhOgNCVhhbD0hvtCKBVoBGiCYQ8Dfp",
"cachedResultUrl": "https://drive.google.com/drive/folders/18ULhOgNCVhhbD0hvtCKBVoBGiCYQ8Dfp",
"cachedResultName": "Qdrant \u0433\u043e\u0442\u043e\u0432\u043e"
},
"operation": "move"
},
"credentials": {
"googleDriveOAuth2Api": {
"name": "<your credential>"
}
},
"typeVersion": 3
},
{
"id": "f20a76ba-27f4-4719-8522-5baa43254f26",
"name": "Load Document Data",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"notes": "Loads binary data from the file for processing",
"position": [
976,
1472
],
"parameters": {
"options": {},
"dataType": "binary"
},
"typeVersion": 1
},
{
"id": "2c24bf63-4e8a-4364-8206-29e674d794cd",
"name": "Split Text into Chunks",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"notes": "Splits document text into chunks of 3000 characters with 300 character overlap",
"position": [
960,
1600
],
"parameters": {
"options": {},
"chunkSize": 3000,
"chunkOverlap": 300
},
"typeVersion": 1
},
{
"id": "b1b3c4f8-cc1d-4d72-b24f-e41157780bce",
"name": "Insert into Qdrant",
"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
"notes": "Inserts document embeddings into Qdrant vector database",
"position": [
1024,
1296
],
"parameters": {
"mode": "insert",
"options": {},
"qdrantCollection": {
"__rl": true,
"mode": "list",
"value": "Test-youtube-adept-ecom",
"cachedResultName": "Test-youtube-adept-ecom"
},
"embeddingBatchSize": 100
},
"credentials": {
"qdrantApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "6002eaf2-5fe5-40d8-aa98-a218b1b4edd3",
"name": "Telegram Message Trigger",
"type": "n8n-nodes-base.telegramTrigger",
"notes": "Triggers when a new message is received in Telegram",
"position": [
560,
688
],
"parameters": {
"updates": [
"message"
],
"additionalFields": {}
},
"credentials": {
"telegramApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "d790616b-48ae-4942-ac29-c2212b7245e9",
"name": "Filter Authorized User",
"type": "n8n-nodes-base.filter",
"notes": "Filters messages to only allow authorized user (chat ID 26899549)",
"position": [
816,
688
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 3,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "9305ec69-4e34-4103-80d8-4f57c4bc52b7",
"operator": {
"type": "number",
"operation": "equals"
},
"leftValue": "={{ $json.message.chat.id }}",
"rightValue": 26899549
}
]
}
},
"typeVersion": 2.3
},
{
"id": "babb633c-8642-4148-af59-f82aa911b506",
"name": "OpenAI Embeddings",
"type": "@n8n/n8n-nodes-langchain.embeddingsOpenAi",
"notes": "Generates embeddings for vector storage and retrieval",
"position": [
1248,
1520
],
"parameters": {
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "017367c9-eae7-4b87-9767-545dc16be347",
"name": "Send Response to Telegram",
"type": "n8n-nodes-base.telegram",
"notes": "Sends AI-generated response back to Telegram chat",
"position": [
1440,
688
],
"parameters": {
"text": "={{ $json.output }}",
"chatId": "={{ $('Telegram Message Trigger').item.json.message.chat.id }}",
"additionalFields": {
"appendAttribution": false
}
},
"credentials": {
"telegramApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.2
},
{
"id": "46aa9b8d-9e1d-4030-83a5-7c972bc9e206",
"name": "Qdrant Knowledge Base",
"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
"notes": "Retrieves relevant information from Qdrant vector database as a tool for AI agent",
"position": [
1248,
976
],
"parameters": {
"mode": "retrieve-as-tool",
"options": {},
"toolDescription": "\u0418\u0441\u043f\u043e\u043b\u044c\u0437\u0443\u0439\u0442\u0435 \u044d\u0442\u0443 \u0431\u0430\u0437\u0443 \u0437\u043d\u0430\u043d\u0438\u0439, \u0447\u0442\u043e\u0431\u044b \u043e\u0442\u0432\u0435\u0447\u0430\u0442\u044c \u043d\u0430 \u0432\u043e\u043f\u0440\u043e\u0441\u044b \u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u0442\u0435\u043b\u044f",
"qdrantCollection": {
"__rl": true,
"mode": "list",
"value": "Test-youtube-adept-ecom",
"cachedResultName": "Test-youtube-adept-ecom"
},
"includeDocumentMetadata": false
},
"credentials": {
"qdrantApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "0a8ba3f7-46f9-4485-ae39-72336cab4c9a",
"name": "AI Agent1",
"type": "@n8n/n8n-nodes-langchain.agent",
"notes": "Processes user messages using AI with access to vector database knowledge base",
"position": [
1088,
688
],
"parameters": {
"text": "={{ $json.message.text }}",
"options": {
"systemMessage": "=You are an expert in business process automation using N8N, specializing in e-commerce and AI integration. \n\nYOUR COMMUNICATION STYLE:\n\n1. Tone and mood:\n- Friendly and energetic, but professional\n - You sound like an experienced practitioner, not a theorist.\n - Sharing personal experiences and real-life cases\n- Inspiring and motivating the audience to act\n\n2. Visual design:\n- You actively use emojis for visual accents (\ud83d\ude80 \u26a1\ufe0f \u2728 \ud83d\udca1 \ud83d\udd25 \ud83d\udc4b)\n- You use emojis logically: at the beginning, to attract attention, to mark lists, for emotional accents\n- The average number of emojis: 6-10 per post\n\n3. Content structure:\n- You start with a bright headline or a hook that attracts attention\n - Use short paragraphs (2-4 sentences)\n- Use structured lists with emoji markers (\u2728, \ud83c\udfaf, \ud83d\udccc)\n- Highlight key thoughts in bold or capital letters\n- End with a call to action or a question for engagement\n\n4. Language and presentation:\n - Explain complex technical concepts in simple, understandable language\n- Avoid unnecessary jargon, but use professional terminology where necessary\n - You give specific examples and figures (not abstractions)\n- You use metaphors and analogies to explain complex things\n\n5. Content and Value:\n - You always provide practical benefits: you teach, share insights, and offer solutions\n - You focus on real problems and their solutions\n- You show \"how\" (step-by-step instructions), not just \"what\"\n- You honestly talk about the pitfalls and nuances\n\n6. Audience engagement:\n- Asking thought-provoking questions\n - Use calls to action (CTA)\n- Encourage discussion in the comments\n - You create interactivity (voting, challenges, conditions for bonuses)\n\n7. Text formatting:\n- Use bold highlighting for section headings\n - You use bulleted lists for transfers\n - Add empty lines between semantic blocks\n- Group related information\n \n IMPORTANT for Telegram:\n- DO NOT use quotation marks around quotes - they look ugly\n - Put quotes in italics or just a new line with indentation.\n - Avoid long blocks of text in quotation marks\n - Instead of \"(c) Source\" use \"\u2014 Source\" at the end of the quote\n\nYOUR MAIN TOPICS:\n- n8n and business process automation\n- Integration of AI and neural networks into workflow\n- E-commerce and marketing\n- Practical cases and workflow\n- Training materials and tutorials\n- News and updates in the automation world\n- Personal experience and insights\n\nEXAMPLES OF TYPICAL ELEMENTS OF YOUR POSTS:\n- \"Friends, hello everyone! \ud83d\udc4b\"\n- \"What awaits you in the video:\"\n- \"I think it's important!\"\n- \"I'll be glad to hear your comments!\"\n- \"If this post gets X likes, then...\"\n- \"Useful links:\"\n- Hashtags at the end of posts\n\nUSING THE QDRANT VECTOR STORE:\n- You have access to the Qdrant Vector Store tool\n- ALWAYS use it before generating content to search for relevant information.\n- First formulate a search query based on the topic of the post\n- Search the vector database for similar posts, cases, and examples\n- Use the information you find to enrich your answer.\n- If there is relevant data in the database, be sure to use it in the post.\n- It helps to maintain consistency of style and use proven formulations.\n\nThe algorithm of operation:\n1. You receive a request from the user\n2. You create a search query for Qdrant (keywords of the topic)\n3. Looking for relevant posts/materials in the vector database\n4. Analyze the results you found\n5. You generate a post using information from the database + your knowledge\n6. You give the final result\n\nimportant:\n- You don't just share information, you build a community.\n- Your goal is to help people solve real problems through automation\n- You show that complex things can be explained simply.\n- You inspire people to experiment and create their own solutions.\n- Vector knowledge base is your reliable assistant for generating high-quality content"
},
"promptType": "define"
},
"typeVersion": 3
},
{
"id": "d4d61680-f231-4a58-9bab-ff3831b75595",
"name": "OpenAI Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"notes": "Fine-tuned GPT-4.1 model for generating content",
"position": [
1056,
976
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "ft:gpt-4.1-2025-04-14:aimagine:adept3:CrV9Ir4p",
"cachedResultName": "ft:gpt-4.1-2025-04-14:aimagine:adept3:CrV9Ir4p"
},
"options": {},
"builtInTools": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.3
},
{
"id": "140df8cd-b802-4687-b07d-21ce4fa52ebf",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-48,
480
],
"parameters": {
"width": 448,
"height": 896,
"content": "# How it works\n\nThis workflow creates an intelligent Telegram bot with a knowledge base powered by Qdrant vector database. It has two independent flows:\n\n**Document Processing Flow** automatically monitors a Google Drive folder, downloads new files, splits them into chunks, generates embeddings, and stores them in Qdrant. Processed files are moved to a \"Ready\" folder.\n\n**Telegram Chat Flow** receives messages, filters authorized users, and uses an AI Agent with access to the vector database to answer questions. The bot maintains conversation history per chat and uses a fine-tuned GPT-4.1 model.\n\n# Setup steps\n\n1. **Google Drive:** Add OAuth2 credentials to all Google Drive nodes. Create two folders (incoming/processed) and update folder IDs.\n2. **Qdrant:** Add API credentials and create a collection. Update collection name in both Qdrant nodes.\n3. **OpenAI:** Add API credentials. Optionally replace the fine-tuned model with standard GPT-4.\n4. **Telegram:** Create a bot via @BotFather, add credentials, and update the authorized chat ID in the filter node.\n5. Activate the workflow and test by uploading a file and sending a Telegram message.\n\n# Customization\n\nModify the system prompt in the AI Agent node to customize your bot's personality and expertise domain."
},
"typeVersion": 1
},
{
"id": "cbc312cc-e573-4cea-bdbb-370a4269d793",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
432,
1168
],
"parameters": {
"color": 7,
"width": 1152,
"height": 640,
"content": "## Document Processing Flow\n\nMonitors Google Drive \u2192 Downloads files \u2192 Splits text \u2192 Creates embeddings \u2192 Stores in Qdrant \u2192 Moves to processed folder"
},
"typeVersion": 1
},
{
"id": "d8d03518-dac3-49f1-942f-902b52a50533",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
432,
480
],
"parameters": {
"color": 7,
"width": 1152,
"height": 384,
"content": "## Telegram Chat Flow\n\nReceives messages \u2192 Filters authorized users \u2192 AI Agent with vector search \u2192 Generates response \u2192 Sends to Telegram"
},
"typeVersion": 1
},
{
"id": "442eec9e-55f6-4d7a-ab11-0c58cf1a3115",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
432,
880
],
"parameters": {
"color": 7,
"width": 1152,
"height": 272,
"content": "## AI Components\n\nFine-tuned GPT-4.1 model, conversation memory per chat, OpenAI embeddings, and Qdrant knowledge base retrieval tool"
},
"typeVersion": 1
},
{
"id": "f994cbde-baf0-44ea-bdad-3dc7541d62ac",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
720,
608
],
"parameters": {
"color": 3,
"width": 288,
"height": 256,
"content": "\u26a0\ufe0f Update this chat ID to your own Telegram user ID to authorize yourself. Find your ID by messaging @userinfobot"
},
"typeVersion": 1
},
{
"id": "920b4a69-8d22-41c2-927d-3f0fd0768bb6",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
1232,
272
],
"parameters": {
"width": 352,
"height": 208,
"content": "@[youtube](7oDXXBYKKps)"
},
"typeVersion": 1
}
],
"connections": {
"AI Agent1": {
"main": [
[
{
"node": "Send Response to Telegram",
"type": "main",
"index": 0
}
]
]
},
"Download File": {
"main": [
[
{
"node": "Insert into Qdrant",
"type": "main",
"index": 0
}
]
]
},
"New File Trigger": {
"main": [
[
{
"node": "Download File",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Embeddings": {
"ai_embedding": [
[
{
"node": "Insert into Qdrant",
"type": "ai_embedding",
"index": 0
},
{
"node": "Qdrant Knowledge Base",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Insert into Qdrant": {
"main": [
[
{
"node": "Move to Processed Folder",
"type": "main",
"index": 0
}
]
]
},
"Load Document Data": {
"ai_document": [
[
{
"node": "Insert into Qdrant",
"type": "ai_document",
"index": 0
}
]
]
},
"OpenAI Chat Model1": {
"ai_languageModel": [
[
{
"node": "AI Agent1",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Qdrant Knowledge Base": {
"ai_tool": [
[
{
"node": "AI Agent1",
"type": "ai_tool",
"index": 0
}
]
]
},
"Filter Authorized User": {
"main": [
[
{
"node": "AI Agent1",
"type": "main",
"index": 0
}
]
]
},
"Split Text into Chunks": {
"ai_textSplitter": [
[
{
"node": "Load Document Data",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"Telegram Message Trigger": {
"main": [
[
{
"node": "Filter Authorized User",
"type": "main",
"index": 0
}
]
]
}
}
}
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.
googleDriveOAuth2ApiopenAiApiqdrantApitelegramApi
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
This workflow creates an intelligent Telegram bot with a knowledge base powered by Qdrant vector database. The bot automatically processes documents uploaded to Google Drive, stores them as embeddings, and uses this knowledge to answer questions in Telegram. It consists of two…
Source: https://n8n.io/workflows/12228/ — original creator credit. Request a take-down →
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