This workflow follows the Chainllm → OpenAI Chat recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
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{
"nodes": [
{
"id": "9320d08a-4868-4103-abdf-3f8f54a7a0a0",
"name": "Webhook",
"type": "n8n-nodes-base.webhook",
"position": [
0,
0
],
"parameters": {
"path": "ytube",
"options": {},
"httpMethod": "POST",
"responseMode": "responseNode"
},
"typeVersion": 2
},
{
"id": "a5cc8922-8124-4269-9cfd-e891b29cc2b7",
"name": "YouTube Transcript",
"type": "n8n-nodes-youtube-transcription.youtubeTranscripter",
"position": [
800,
0
],
"parameters": {},
"typeVersion": 1
},
{
"id": "ff3c0fd1-36d8-4d64-b405-0600efd4d93b",
"name": "Split Out",
"type": "n8n-nodes-base.splitOut",
"position": [
200,
260
],
"parameters": {
"options": {},
"fieldToSplitOut": "transcript"
},
"typeVersion": 1
},
{
"id": "423276e0-81bf-487a-bbdd-26e9b84fa755",
"name": "Respond to Webhook",
"type": "n8n-nodes-base.respondToWebhook",
"position": [
1200,
140
],
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "27344649-8029-48ae-867b-7363d904fc59",
"name": "Telegram",
"type": "n8n-nodes-base.telegram",
"position": [
1200,
380
],
"parameters": {
"text": "={{ $json.title }}\n{{ $json.youtubeUrl }}",
"additionalFields": {
"parse_mode": "HTML",
"appendAttribution": false
}
},
"typeVersion": 1.2
},
{
"id": "230c0325-d22a-4070-9460-748a6fef48d5",
"name": "Get YouTube URL",
"type": "n8n-nodes-base.set",
"position": [
200,
0
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "3ee42e4c-3cee-4934-97e7-64c96b5691ed",
"name": "youtubeUrl",
"type": "string",
"value": "={{ $json.body.youtubeUrl }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "420e90c3-9dfa-4f41-825a-9874b5ebe43a",
"name": "YouTube Video ID",
"type": "n8n-nodes-base.code",
"position": [
400,
0
],
"parameters": {
"jsCode": "const extractYoutubeId = (url) => {\n // Regex pattern that matches both youtu.be and youtube.com URLs\n const pattern = /(?:youtube\\.com\\/(?:[^\\/]+\\/.+\\/|(?:v|e(?:mbed)?)\\/|.*[?&]v=)|youtu\\.be\\/)([^\"&?\\/\\s]{11})/;\n const match = url.match(pattern);\n return match ? match[1] : null;\n};\n\n// Input URL from previous node\nconst youtubeUrl = items[0].json.youtubeUrl; // Adjust this based on your workflow\n\n// Process the URL and return the video ID\nreturn [{\n json: {\n videoId: extractYoutubeId(youtubeUrl)\n }\n}];\n"
},
"typeVersion": 2
},
{
"id": "a4171c3e-1ff2-40de-af7f-b3971a1ebe79",
"name": "Get YouTube Video",
"type": "n8n-nodes-base.youTube",
"position": [
600,
0
],
"parameters": {
"options": {},
"videoId": "={{ $json.videoId }}",
"resource": "video",
"operation": "get"
},
"typeVersion": 1
},
{
"id": "73e6bfc5-8b62-4880-acd4-292f2f692540",
"name": "gpt-4o-mini",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
620,
440
],
"parameters": {
"options": {}
},
"typeVersion": 1
},
{
"id": "ea14e296-b30c-46f7-b283-746822ae1af4",
"name": "Summarize & Analyze Transcript",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
600,
260
],
"parameters": {
"text": "=Please analyze the given text and create a structured summary following these guidelines:\n\n1. Break down the content into main topics using Level 2 headers (##)\n2. Under each header:\n - List only the most essential concepts and key points\n - Use bullet points for clarity\n - Keep explanations concise\n - Preserve technical accuracy\n - Highlight key terms in bold\n3. Organize the information in this sequence:\n - Definition/Background\n - Main characteristics\n - Implementation details\n - Advantages/Disadvantages\n4. Format requirements:\n - Use markdown formatting\n - Keep bullet points simple (no nesting)\n - Bold important terms using **term**\n - Use tables for comparisons\n - Include relevant technical details\n\nPlease provide a clear, structured summary that captures the core concepts while maintaining technical accuracy.\n\nHere is the text: {{ $json.concatenated_text\n }}",
"promptType": "define"
},
"typeVersion": 1.4
},
{
"id": "90e3488f-f854-483e-9106-a5760d0c0457",
"name": "Concatenate",
"type": "n8n-nodes-base.summarize",
"position": [
400,
260
],
"parameters": {
"options": {},
"fieldsToSummarize": {
"values": [
{
"field": "text",
"separateBy": " ",
"aggregation": "concatenate"
}
]
}
},
"typeVersion": 1
},
{
"id": "9c5c249c-5eeb-4433-ba93-ace4611f4858",
"name": "Response Object",
"type": "n8n-nodes-base.set",
"position": [
960,
260
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "bf132004-6636-411f-9d85-0c696fda84c4",
"name": "summary",
"type": "string",
"value": "={{ $json.text }}"
},
{
"id": "63c8d0e3-685c-488a-9b45-363cf52479ea",
"name": "topics",
"type": "array",
"value": "=[]"
},
{
"id": "171f30cf-34e9-42f3-8735-814024bfde0b",
"name": "title",
"type": "string",
"value": "={{ $('Get YouTube Video').item.json.snippet.title }}"
},
{
"id": "7f26f5a3-e695-49d1-b1e8-9260c31f1b3d",
"name": "description",
"type": "string",
"value": "={{ $('Get YouTube Video').item.json.snippet.description }}"
},
{
"id": "d0594232-cb39-453c-b015-3b039c098e1f",
"name": "id",
"type": "string",
"value": "={{ $('Get YouTube Video').item.json.id }}"
},
{
"id": "17b6ca08-ce89-4467-bd25-0d2d182f7a8b",
"name": "youtubeUrl",
"type": "string",
"value": "={{ $('Webhook').item.json.body.youtubeUrl }}"
}
]
}
},
"typeVersion": 3.4
}
],
"connections": {
"Webhook": {
"main": [
[
{
"node": "Get YouTube URL",
"type": "main",
"index": 0
}
]
]
},
"Split Out": {
"main": [
[
{
"node": "Concatenate",
"type": "main",
"index": 0
}
]
]
},
"Concatenate": {
"main": [
[
{
"node": "Summarize & Analyze Transcript",
"type": "main",
"index": 0
}
]
]
},
"gpt-4o-mini": {
"ai_languageModel": [
[
{
"node": "Summarize & Analyze Transcript",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Get YouTube URL": {
"main": [
[
{
"node": "YouTube Video ID",
"type": "main",
"index": 0
}
]
]
},
"Response Object": {
"main": [
[
{
"node": "Respond to Webhook",
"type": "main",
"index": 0
},
{
"node": "Telegram",
"type": "main",
"index": 0
}
]
]
},
"YouTube Video ID": {
"main": [
[
{
"node": "Get YouTube Video",
"type": "main",
"index": 0
}
]
]
},
"Summarize & Analyze Transcript": {
"main": [
[
{
"node": "Response Object",
"type": "main",
"index": 0
}
]
]
}
}
}
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How this works
Streamline your Telegram bot interactions by automatically extracting and processing YouTube video transcripts from incoming messages, delivering concise summaries or insights without manual effort. This workflow suits content creators, educators, or community managers handling video discussions in Telegram groups, saving hours on transcription and analysis. The key step involves the YouTube Transcript node pulling the video content, followed by AI-driven processing via OpenAI to generate responses, all triggered by a simple webhook from Telegram.
Use this workflow when your Telegram bot receives frequent YouTube links needing quick transcription and summarisation, such as in educational channels or support chats. Avoid it for non-video content or high-volume scenarios without rate limiting, as it relies on YouTube API quotas. Common variations include swapping OpenAI for another LLM or adding sentiment analysis on transcripts for enhanced engagement.
About this workflow
Telegram Splitout. Uses n8n-nodes-youtube-transcription, splitOut, respondToWebhook, telegram. Webhook trigger; 12 nodes.
Source: https://github.com/Zie619/n8n-workflows — original creator credit. Request a take-down →
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