소셜 미디어 AI 에이전트 - Telegram
고급
이것은AI, Marketing분야의자동화 워크플로우로, 26개의 노드를 포함합니다.주로 Code, Wait, Merge, Filter, Twitter 등의 노드를 사용하며인공지능 기술을 결합하여 스마트 자동화를 구현합니다. AI 기반 소셜 미디어 증폭기
사전 요구사항
- •Twitter API 인증 정보
- •Airtable API Key
- •LinkedIn API 인증 정보
- •Telegram Bot Token
- •대상 API의 인증 정보가 필요할 수 있음
- •OpenAI API Key
사용된 노드 (26)
워크플로우 미리보기
노드 연결 관계를 시각적으로 표시하며, 확대/축소 및 이동을 지원합니다
워크플로우 내보내기
다음 JSON 구성을 복사하여 n8n에 가져오면 이 워크플로우를 사용할 수 있습니다
{
"id": "ZeSJSbwXI593H1Qj",
"meta": {
"instanceId": "8e1a7e3413df437923cda0e92c098469371d84f7001856e525beaff17be8b941",
"templateCredsSetupCompleted": true
},
"name": "Social Media AI Agent - Telegram",
"tags": [],
"nodes": [
{
"id": "814303e0-5fe9-474e-a4ed-e4a728fd4acf",
"name": "HN 홈 크롤링",
"type": "n8n-nodes-base.httpRequest",
"position": [
-1540,
1640
],
"parameters": {
"url": "https://news.ycombinator.com/",
"options": {
"response": {
"response": {
"neverError": true,
"fullResponse": true
}
}
}
},
"executeOnce": true,
"typeVersion": 4.2,
"alwaysOutputData": true
},
{
"id": "32e20b1d-b3f1-4ed2-acbf-4d5bd56b0d8b",
"name": "메타 데이터 추출",
"type": "n8n-nodes-base.code",
"position": [
-1260,
1720
],
"parameters": {
"language": "python",
"pythonCode": "# Import necessary modules\nimport asyncio\nimport micropip\n\n# Define an asynchronous function to install packages\nasync def install_packages():\n await micropip.install(\"beautifulsoup4\")\n await micropip.install(\"simplejson\")\n\n# Run the asynchronous package installation\nasyncio.get_event_loop().run_until_complete(install_packages())\n\n# Now, import the installed packages\nimport simplejson as json\nfrom bs4 import BeautifulSoup\n\n# Retrieve the HTML content from the first item in the input\n# Assuming n8n passes data as a list of items, each with a 'json' key\nhtml_content = items[0].get('json', {}).get('data', '')\n\n# Initialize BeautifulSoup with the HTML content\nsoup = BeautifulSoup(html_content, 'html.parser')\n\n# Initialize a list to store metadata of GitHub posts\ngithub_posts = []\n\n# Find all 'tr' elements with class 'athing submission'\nposts = soup.find_all('tr', class_='athing submission')\n\nfor post in posts:\n post_id = post.get('id')\n title_line = post.find('span', class_='titleline')\n if not title_line:\n continue # Skip if titleline is not found\n\n # Extract the title and URL\n title_tag = title_line.find('a')\n if not title_tag:\n continue # Skip if title tag is not found\n\n title = title_tag.get_text(strip=True)\n url = title_tag.get('href', '')\n\n # Check if the URL is a GitHub link\n if 'github.com' not in url.lower():\n continue # Skip if not a GitHub link\n\n # Extract the site domain (e.g., github.com/username/repo)\n site_bit = title_line.find('span', class_='sitebit comhead')\n site = site_bit.find('span', class_='sitestr').get_text(strip=True) if site_bit else ''\n\n # The subtext is in the next 'tr' element\n subtext_tr = post.find_next_sibling('tr')\n if not subtext_tr:\n continue # Skip if subtext row is not found\n\n subtext_td = subtext_tr.find('td', class_='subtext')\n if not subtext_td:\n continue # Skip if subtext td is not found\n\n # Extract score\n score_span = subtext_td.find('span', class_='score')\n score = score_span.get_text(strip=True) if score_span else '0 points'\n\n # Extract author\n author_a = subtext_td.find('a', class_='hnuser')\n author = author_a.get_text(strip=True) if author_a else 'unknown'\n\n # Extract age\n age_span = subtext_td.find('span', class_='age')\n age_a = age_span.find('a') if age_span else None\n age = age_a.get_text(strip=True) if age_a else 'unknown'\n\n # Extract comments\n comments_a = subtext_td.find_all('a')[-1] if subtext_td.find_all('a') else None\n comments_text = comments_a.get_text(strip=True) if comments_a else '0 comments'\n\n # Construct the Hacker News URL\n hn_url = f\"https://news.ycombinator.com/item?id={post_id}\"\n\n # Compile the metadata\n post_metadata = {\n 'Post': post_id,\n 'title': title,\n 'url': url,\n 'site': site,\n 'score': score,\n 'author': author,\n 'age': age,\n 'comments': comments_text,\n 'hn_url': hn_url\n }\n\n # Append to the list of GitHub posts\n github_posts.append(post_metadata)\n\n# Prepare the output for n8n\noutput = [{'json': post} for post in github_posts]\n\n# Return the output\nreturn output\n"
},
"executeOnce": true,
"typeVersion": 2,
"alwaysOutputData": true
},
{
"id": "b54cf663-b823-4613-a812-764942b95b9d",
"name": "미게시 항목 필터링",
"type": "n8n-nodes-base.code",
"position": [
-680,
1640
],
"parameters": {
"jsCode": "const items = [];\n\n// Step 1: Collect all Post IDs from input1 items (those with 'id')\nconst processedPosts = new Set(\n $input.all()\n .filter(item => item.json.id)\n .map(item => item.json.Post)\n);\n\n// Step 2: Iterate over all items and filter out duplicates\nfor (const item of $input.all()) {\n \n // Only process items without 'id' (input2 items)\n if(!item.json.id){\n \n // Check if the Post ID is already processed\n if(!processedPosts.has(item.json.Post) && item.json.Post!=undefined){\n items.push(item);\n }\n }\n}\n\nreturn items;\n"
},
"typeVersion": 2
},
{
"id": "d7ac7121-8da7-4e45-9b74-daf07fbf15fb",
"name": "GH 페이지 방문",
"type": "n8n-nodes-base.httpRequest",
"position": [
-420,
1420
],
"parameters": {
"url": "={{ $json.url }}",
"options": {}
},
"typeVersion": 4.2
},
{
"id": "f156ca8e-7963-42b9-9612-9ab5efc53be4",
"name": "HTML을 마크다운으로 변환",
"type": "n8n-nodes-base.markdown",
"position": [
-240,
1700
],
"parameters": {
"html": "={{ $json.data }}",
"options": {}
},
"typeVersion": 1,
"alwaysOutputData": true
},
{
"id": "86221ed0-29fa-4775-ba36-8ffdf614977c",
"name": "오류 항목 필터링",
"type": "n8n-nodes-base.filter",
"position": [
380,
1440
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "7776cb97-e02d-418e-a168-612bf92d4160",
"operator": {
"type": "string",
"operation": "empty",
"singleValue": true
},
"leftValue": "={{ $json.error }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "f08c4f61-17a5-4899-ab3d-4e3ff5d1b8b7",
"name": "작업 없음",
"type": "n8n-nodes-base.noOp",
"position": [
1760,
1540
],
"parameters": {},
"typeVersion": 1
},
{
"id": "48856b3b-a951-4e7f-a0b8-410a71e9b0a7",
"name": "X 상태 업데이트",
"type": "n8n-nodes-base.airtable",
"position": [
1500,
1400
],
"parameters": {
"base": {
"__rl": true,
"mode": "list",
"value": "app7fh2kmMzPKS4RZ",
"cachedResultUrl": "https://airtable.com/app7fh2kmMzPKS4RZ",
"cachedResultName": "Twitter Agent"
},
"table": {
"__rl": true,
"mode": "list",
"value": "tblf0cODJFdvDj7vU",
"cachedResultUrl": "https://airtable.com/app7fh2kmMzPKS4RZ/tblf0cODJFdvDj7vU",
"cachedResultName": "My Tweets"
},
"columns": {
"value": {
"id": "={{ $('Create Item').item.json.id }}",
"TDone": true
},
"schema": [
{
"id": "id",
"type": "string",
"display": true,
"removed": false,
"readOnly": true,
"required": false,
"displayName": "id",
"defaultMatch": true
},
{
"id": "Post",
"type": "string",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "Post",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Title",
"type": "string",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "Title",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Url",
"type": "string",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "Url",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Tweet",
"type": "string",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "Tweet",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "LinkedIn",
"type": "string",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "LinkedIn",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Date",
"type": "string",
"display": true,
"removed": true,
"readOnly": true,
"required": false,
"displayName": "Date",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Last Modified",
"type": "string",
"display": true,
"removed": true,
"readOnly": true,
"required": false,
"displayName": "Last Modified",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "TDone",
"type": "boolean",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "TDone",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "LDone",
"type": "boolean",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "LDone",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"id"
]
},
"options": {
"typecast": true
},
"operation": "update"
},
"credentials": {
"airtableTokenApi": {
"id": "BxLldDZTAZvuWVbr",
"name": "Airtable Personal Access Token account"
}
},
"typeVersion": 2.1
},
{
"id": "c31bb906-2a0d-406a-a7cd-6fc4adfcb67b",
"name": "LinkedIn",
"type": "n8n-nodes-base.linkedIn",
"position": [
1200,
1820
],
"parameters": {
"text": "={{ $('Filter Errored').item.json.message.content.linkedin }}",
"person": "afi4Hy9wlI",
"additionalFields": {}
},
"credentials": {
"linkedInOAuth2Api": {
"id": "S7G2oyLAmzhWuYFQ",
"name": "LinkedIn account"
}
},
"typeVersion": 1
},
{
"id": "4aab4cc2-4a51-432a-aa21-ba469c027ac6",
"name": "L 상태 업데이트",
"type": "n8n-nodes-base.airtable",
"position": [
1520,
1680
],
"parameters": {
"base": {
"__rl": true,
"mode": "list",
"value": "app7fh2kmMzPKS4RZ",
"cachedResultUrl": "https://airtable.com/app7fh2kmMzPKS4RZ",
"cachedResultName": "Twitter Agent"
},
"table": {
"__rl": true,
"mode": "list",
"value": "tblf0cODJFdvDj7vU",
"cachedResultUrl": "https://airtable.com/app7fh2kmMzPKS4RZ/tblf0cODJFdvDj7vU",
"cachedResultName": "My Tweets"
},
"columns": {
"value": {
"id": "={{ $('Create Item').item.json.id }}",
"LDone": true
},
"schema": [
{
"id": "id",
"type": "string",
"display": true,
"removed": false,
"readOnly": true,
"required": false,
"displayName": "id",
"defaultMatch": true
},
{
"id": "Post",
"type": "string",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "Post",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Title",
"type": "string",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "Title",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Url",
"type": "string",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "Url",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Tweet",
"type": "string",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "Tweet",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "LinkedIn",
"type": "string",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "LinkedIn",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Date",
"type": "string",
"display": true,
"removed": true,
"readOnly": true,
"required": false,
"displayName": "Date",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Last Modified",
"type": "string",
"display": true,
"removed": true,
"readOnly": true,
"required": false,
"displayName": "Last Modified",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "TDone",
"type": "boolean",
"display": true,
"removed": true,
"readOnly": false,
"required": false,
"displayName": "TDone",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "LDone",
"type": "boolean",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "LDone",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"id"
]
},
"options": {
"typecast": true
},
"operation": "update"
},
"credentials": {
"airtableTokenApi": {
"id": "BxLldDZTAZvuWVbr",
"name": "Airtable Personal Access Token account"
}
},
"typeVersion": 2.1
},
{
"id": "72dd9714-c11d-4417-8710-89e416ac44c9",
"name": "항목 검색",
"type": "n8n-nodes-base.airtable",
"position": [
-1100,
1240
],
"parameters": {
"base": {
"__rl": true,
"mode": "list",
"value": "app7fh2kmMzPKS4RZ",
"cachedResultUrl": "https://airtable.com/app7fh2kmMzPKS4RZ",
"cachedResultName": "Twitter Agent"
},
"table": {
"__rl": true,
"mode": "list",
"value": "tblf0cODJFdvDj7vU",
"cachedResultUrl": "https://airtable.com/app7fh2kmMzPKS4RZ/tblf0cODJFdvDj7vU",
"cachedResultName": "My Tweets"
},
"options": {
"fields": [
"Title",
"Url",
"Tweet",
"Date",
"Post"
]
},
"operation": "search",
"filterByFormula": "={Post}= {{ $json.Post }}"
},
"credentials": {
"airtableTokenApi": {
"id": "BxLldDZTAZvuWVbr",
"name": "Airtable Personal Access Token account"
}
},
"typeVersion": 2.1,
"alwaysOutputData": true
},
{
"id": "f89fbada-0e53-44f0-a09b-119869fabd10",
"name": "항목 생성",
"type": "n8n-nodes-base.airtable",
"position": [
580,
1660
],
"parameters": {
"base": {
"__rl": true,
"mode": "list",
"value": "app7fh2kmMzPKS4RZ",
"cachedResultUrl": "https://airtable.com/app7fh2kmMzPKS4RZ",
"cachedResultName": "Twitter Agent"
},
"table": {
"__rl": true,
"mode": "list",
"value": "tblf0cODJFdvDj7vU",
"cachedResultUrl": "https://airtable.com/app7fh2kmMzPKS4RZ/tblf0cODJFdvDj7vU",
"cachedResultName": "My Tweets"
},
"columns": {
"value": {
"Url": "={{ $('Filter Unposted Items').item.json.url }}",
"Post": "={{ $('Filter Unposted Items').item.json.Post }}",
"Title": "={{ $('Filter Unposted Items').item.json.title }}",
"Tweet": "={{ $json.message.content.twitter }}",
"LinkedIn": "={{ $json.message.content.linkedin }}"
},
"schema": [
{
"id": "Post",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Post",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Title",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Title",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Url",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Url",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Tweet",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "Tweet",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "LinkedIn",
"type": "string",
"display": true,
"removed": false,
"readOnly": false,
"required": false,
"displayName": "LinkedIn",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "Date",
"type": "string",
"display": true,
"removed": false,
"readOnly": true,
"required": false,
"displayName": "Date",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": []
},
"options": {},
"operation": "create"
},
"credentials": {
"airtableTokenApi": {
"id": "BxLldDZTAZvuWVbr",
"name": "Airtable Personal Access Token account"
}
},
"typeVersion": 2.1
},
{
"id": "51a2c3d3-3e75-4375-b2b6-4bb86fa71855",
"name": "X",
"type": "n8n-nodes-base.twitter",
"onError": "continueRegularOutput",
"position": [
1180,
1380
],
"parameters": {
"text": "={{ $('Filter Errored').item.json.message.content.twitter }}",
"additionalFields": {}
},
"credentials": {
"twitterOAuth2Api": {
"id": "YQyS9lQTpZtZkefS",
"name": "X account"
}
},
"executeOnce": false,
"typeVersion": 2
},
{
"id": "58869c5b-9fb2-4f76-8788-68056cda45b0",
"name": "생성 콘텐츠 검증",
"type": "n8n-nodes-base.code",
"onError": "continueRegularOutput",
"position": [
180,
1680
],
"parameters": {
"mode": "runOnceForEachItem",
"jsCode": "if ($json.message.content.twitter && $json.message.content.linkedin) {\n \n return $json;\n} else {\n\n const parsedContent = JSON.parse($json.message.content);\n if ($json.message.content.twitter && $json.message.content.linkedin) {\n return parsedContent;\n }\n\n console.log(\"Invalid formatting\")\n return {}\n}"
},
"typeVersion": 2
},
{
"id": "527fd640-8bc8-4043-92a6-52fbea8de63f",
"name": "스케줄 트리거",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-1780,
1640
],
"parameters": {
"rule": {
"interval": [
{
"field": "hours",
"hoursInterval": 6
}
]
}
},
"typeVersion": 1.2
},
{
"id": "f00c1de5-d5bd-4d78-8717-d26dd739adc7",
"name": "병합",
"type": "n8n-nodes-base.merge",
"position": [
-840,
1420
],
"parameters": {},
"typeVersion": 3,
"alwaysOutputData": true
},
{
"id": "3529fba4-173c-4378-ae69-43a3bae0813f",
"name": "콘텐츠 생성",
"type": "@n8n/n8n-nodes-langchain.openAi",
"position": [
-120,
1440
],
"parameters": {
"modelId": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini",
"cachedResultName": "GPT-4O-MINI"
},
"options": {},
"messages": {
"values": [
{
"role": "system",
"content": "You are an AI-powered social media assistant specialized in crafting short-form, engaging posts for Twitter and LinkedIn. Your tone should blend the enthusiasm of a Tech Evangelist with the narrative depth of a Storyteller. The goal is to highlight technological and open-source projects in a friendly, forward-thinking manner, connecting them to real-world use cases. \n\nGuidelines:\n1. Output must be in JSON with separate fields for “twitter” and “linkedin.”\n2. Do not include emojis or marketing buzzwords (“cutting-edge,” “disruptive,” etc.).\n3. Write naturally and concisely. Avoid overly formal or robotic language.\n4. Twitter posts must be under 280 characters (including spaces and URL).\n5. LinkedIn posts should be slightly longer, yet still succinct, and focus on storytelling and real-world applications.\n6. Provide a single call-to-action in each post.\n7. Do not imply ownership of the project unless explicitly stated.\n8. Maintain a professional yet approachable tone in both outputs.\n"
},
{
"content": "=Using the following details, generate two posts—one for Twitter and one for LinkedIn—incorporating an enthusiastic yet narrative-driven style:\n\nTitle: {{ $('Filter Unposted Items').item.json.title }}\nDetails in markdown: {{ $json.data }}\nRepository Link: {{ $('Filter Unposted Items').item.json.url }} (this is the actual link you want to be inserted)\n\nConstraints:\n- No emojis.\n- Keep the Twitter post under 280 characters (including the link).\n- Use a friendly, forward-thinking tone that weaves in a short narrative where possible.\n- Highlight how the project solves a real problem or benefits the user.\n- End each post with one clear CTA (e.g., “Check it out!” or “Learn more.”).\n- **Ensure the tone is neutral and does not imply personal involvement** (e.g., avoid phrases like \"my journey\" or \"I found it fascinating\").\n- **LinkedIn post should be more detailed**: Provide context, explain the key features, highlight how it can be useful to different audiences, and elaborate on the problem it solves or the impact it can have.\n- Output your response in JSON with the structure:\n```json\n{\n \"twitter\": \"Your Twitter post here\",\n \"linkedin\": \"Your LinkedIn post here\"\n}\n"
}
]
},
"jsonOutput": true
},
"credentials": {
"openAiApi": {
"id": "IfJo4dG8AUORk6f0",
"name": "OpenAi account"
}
},
"typeVersion": 1.7,
"alwaysOutputData": true
},
{
"id": "2dfd7849-877c-4bd3-b248-94140a1fe209",
"name": "스티커 노트",
"type": "n8n-nodes-base.stickyNote",
"position": [
-320,
960
],
"parameters": {
"width": 619.8433261701165,
"height": 97.20332107671479,
"content": "Automate the curation and sharing of trending GitHub discussions from Hacker News to Twitter and LinkedIn. This workflow leverages AI to generate engaging posts, streamlining your social media content creation and distribution.\n\n"
},
"typeVersion": 1
},
{
"id": "20704a99-1234-46dc-b8c8-860b051b3b85",
"name": "스티커 노트1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1620,
1520
],
"parameters": {
"color": 5,
"width": 524.8824946275869,
"height": 420.37647358435385,
"content": "I crawl Hacker News and extract Github links."
},
"typeVersion": 1
},
{
"id": "5cfa2c30-6c88-429a-8b5f-0034d2352cc2",
"name": "스티커 노트2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-480,
1280
],
"parameters": {
"color": 5,
"width": 828.144505037599,
"height": 670.031562962293,
"content": "This is where the magic happens. I use the Github url extracted earlier and visit Github page to get more insights in the project being shared. Then I ask Chat GPT very nicely to help me get a Tweet and a LinkedIn post"
},
"typeVersion": 1
},
{
"id": "caec3df6-ddcc-4959-94e1-18163cf3128f",
"name": "스티커 노트3",
"type": "n8n-nodes-base.stickyNote",
"position": [
1100,
1280
],
"parameters": {
"color": 5,
"width": 285.9487894560623,
"height": 751.2077576680031,
"content": "One last magic trick, Send the generated Tweet and the post to the respective platforms."
},
"typeVersion": 1
},
{
"id": "89c8472d-3329-4f94-a656-2539e061eeb0",
"name": "알림 보내기",
"type": "n8n-nodes-base.telegram",
"position": [
720,
1420
],
"parameters": {
"text": "=Hi There, here is your readymade tweet - \n\n {{ $json.fields.Tweet }}\n\nAnd your readymade LinkedIn post -\n\n {{ $json.fields.LinkedIn }}\n\n",
"chatId": "1297549992",
"additionalFields": {}
},
"credentials": {
"telegramApi": {
"id": "1RZApQ3BwJxFn9jp",
"name": "Telegram account"
}
},
"typeVersion": 1.2
},
{
"id": "b1444e6d-0cab-4082-af42-a8decc97d9b4",
"name": "스티커 노트4",
"type": "n8n-nodes-base.stickyNote",
"position": [
640,
1300
],
"parameters": {
"color": 5,
"width": 264.5060210432334,
"height": 307.03612625939974,
"content": "Just pinging the owner that something is about to be posted and wait for 5 mins before final posting."
},
"typeVersion": 1
},
{
"id": "01c2f7ff-ff6c-4a60-9581-f8c5f3985792",
"name": "게시 전 5분 대기",
"type": "n8n-nodes-base.wait",
"position": [
880,
1660
],
"webhookId": "0c7ee388-30cf-4a99-9bb0-0fd85171c794",
"parameters": {
"unit": "minutes"
},
"typeVersion": 1.1
},
{
"id": "909c7e7d-ea84-4612-a322-b1fa889b2efb",
"name": "스티커 노트5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-920,
1380
],
"parameters": {
"width": 400.8207630962184,
"height": 392.80719991071624,
"content": "CHORE"
},
"typeVersion": 1
},
{
"id": "04ab5b63-8def-4d49-9360-596261eb051c",
"name": "스티커 노트6",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1140,
1140
],
"parameters": {
"color": 5,
"width": 195.58283685913963,
"height": 285.5933578465706,
"content": "Make sure we don't post the same content again."
},
"typeVersion": 1
}
],
"active": true,
"pinData": {
"Schedule Trigger": [
{
"json": {
"Hour": "18",
"Year": "2024",
"Month": "December",
"Minute": "00",
"Second": "17",
"Timezone": "America/New_York (UTC-05:00)",
"timestamp": "2024-12-27T18:00:17.035-05:00",
"Day of week": "Friday",
"Day of month": "27",
"Readable date": "December 27th 2024, 6:00:17 pm",
"Readable time": "6:00:17 pm"
}
}
]
},
"settings": {
"executionOrder": "v1"
},
"versionId": "4c28d47d-811e-4b89-adeb-47da12abd378",
"connections": {
"51a2c3d3-3e75-4375-b2b6-4bb86fa71855": {
"main": [
[
{
"node": "48856b3b-a951-4e7f-a0b8-410a71e9b0a7",
"type": "main",
"index": 0
}
]
]
},
"f00c1de5-d5bd-4d78-8717-d26dd739adc7": {
"main": [
[
{
"node": "b54cf663-b823-4613-a812-764942b95b9d",
"type": "main",
"index": 0
}
]
]
},
"89c8472d-3329-4f94-a656-2539e061eeb0": {
"main": [
[
{
"node": "01c2f7ff-ff6c-4a60-9581-f8c5f3985792",
"type": "main",
"index": 0
}
]
]
},
"c31bb906-2a0d-406a-a7cd-6fc4adfcb67b": {
"main": [
[
{
"node": "4aab4cc2-4a51-432a-aa21-ba469c027ac6",
"type": "main",
"index": 0
}
]
]
},
"f89fbada-0e53-44f0-a09b-119869fabd10": {
"main": [
[
{
"node": "89c8472d-3329-4f94-a656-2539e061eeb0",
"type": "main",
"index": 0
}
]
]
},
"72dd9714-c11d-4417-8710-89e416ac44c9": {
"main": [
[
{
"node": "f00c1de5-d5bd-4d78-8717-d26dd739adc7",
"type": "main",
"index": 0
}
]
]
},
"32e20b1d-b3f1-4ed2-acbf-4d5bd56b0d8b": {
"main": [
[
{
"node": "72dd9714-c11d-4417-8710-89e416ac44c9",
"type": "main",
"index": 0
},
{
"node": "f00c1de5-d5bd-4d78-8717-d26dd739adc7",
"type": "main",
"index": 1
}
]
]
},
"814303e0-5fe9-474e-a4ed-e4a728fd4acf": {
"main": [
[
{
"node": "32e20b1d-b3f1-4ed2-acbf-4d5bd56b0d8b",
"type": "main",
"index": 0
}
]
]
},
"d7ac7121-8da7-4e45-9b74-daf07fbf15fb": {
"main": [
[
{
"node": "f156ca8e-7963-42b9-9612-9ab5efc53be4",
"type": "main",
"index": 0
}
]
]
},
"86221ed0-29fa-4775-ba36-8ffdf614977c": {
"main": [
[
{
"node": "f89fbada-0e53-44f0-a09b-119869fabd10",
"type": "main",
"index": 0
}
]
]
},
"4aab4cc2-4a51-432a-aa21-ba469c027ac6": {
"main": [
[
{
"node": "f08c4f61-17a5-4899-ab3d-4e3ff5d1b8b7",
"type": "main",
"index": 0
}
]
]
},
"48856b3b-a951-4e7f-a0b8-410a71e9b0a7": {
"main": [
[
{
"node": "f08c4f61-17a5-4899-ab3d-4e3ff5d1b8b7",
"type": "main",
"index": 0
}
]
]
},
"3529fba4-173c-4378-ae69-43a3bae0813f": {
"main": [
[
{
"node": "58869c5b-9fb2-4f76-8788-68056cda45b0",
"type": "main",
"index": 0
}
]
]
},
"527fd640-8bc8-4043-92a6-52fbea8de63f": {
"main": [
[
{
"node": "814303e0-5fe9-474e-a4ed-e4a728fd4acf",
"type": "main",
"index": 0
}
]
]
},
"b54cf663-b823-4613-a812-764942b95b9d": {
"main": [
[
{
"node": "d7ac7121-8da7-4e45-9b74-daf07fbf15fb",
"type": "main",
"index": 0
}
]
]
},
"f156ca8e-7963-42b9-9612-9ab5efc53be4": {
"main": [
[
{
"node": "3529fba4-173c-4378-ae69-43a3bae0813f",
"type": "main",
"index": 0
}
]
]
},
"58869c5b-9fb2-4f76-8788-68056cda45b0": {
"main": [
[
{
"node": "86221ed0-29fa-4775-ba36-8ffdf614977c",
"type": "main",
"index": 0
}
]
]
},
"01c2f7ff-ff6c-4a60-9581-f8c5f3985792": {
"main": [
[
{
"node": "51a2c3d3-3e75-4375-b2b6-4bb86fa71855",
"type": "main",
"index": 0
},
{
"node": "c31bb906-2a0d-406a-a7cd-6fc4adfcb67b",
"type": "main",
"index": 0
}
]
]
}
}
}자주 묻는 질문
이 워크플로우를 어떻게 사용하나요?
위의 JSON 구성 코드를 복사하여 n8n 인스턴스에서 새 워크플로우를 생성하고 "JSON에서 가져오기"를 선택한 후, 구성을 붙여넣고 필요에 따라 인증 설정을 수정하세요.
이 워크플로우는 어떤 시나리오에 적합한가요?
고급 - 인공지능, 마케팅
유료인가요?
이 워크플로우는 완전히 무료이며 직접 가져와 사용할 수 있습니다. 다만, 워크플로우에서 사용하는 타사 서비스(예: OpenAI API)는 사용자 직접 비용을 지불해야 할 수 있습니다.
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