RSS 到 LinkedIn 自动发布器
高级
这是一个Social Media, Multimodal AI领域的自动化工作流,包含 19 个节点。主要使用 If, Code, LinkedIn, Aggregate, HttpRequest 等节点。 使用 RSS + Gemini AI + Templated.io 自动策划并发布到 LinkedIn 公司页面
前置要求
- •LinkedIn API 凭证
- •可能需要目标 API 的认证凭证
- •Google Gemini API Key
使用的节点 (19)
工作流预览
可视化展示节点连接关系,支持缩放和平移
无法加载工作流预览
导出工作流
复制以下 JSON 配置到 n8n 导入,即可使用此工作流
{
"meta": {
"templateCredsSetupCompleted": false
},
"name": "RSS 到 LinkedIn 自动发布器",
"nodes": [
{
"name": "便签",
"type": "n8n-nodes-base.stickyNote",
"position": [
-496,
-360
],
"parameters": {
"width": 384,
"height": 704,
"content": "## 🧠 工作流概览"
},
"typeVersion": 1
},
{
"name": "便签 1",
"type": "n8n-nodes-base.stickyNote",
"position": [
208,
176
],
"parameters": {
"color": 7,
"width": 464,
"height": 80,
"content": "## 内容筛选器"
},
"typeVersion": 1
},
{
"name": "便签 2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1264,
16
],
"parameters": {
"color": 7,
"width": 464,
"height": 80,
"content": "## 创建器与优化器"
},
"typeVersion": 1
},
{
"name": "便签 3",
"type": "n8n-nodes-base.stickyNote",
"position": [
2176,
160
],
"parameters": {
"color": 7,
"width": 464,
"height": 80,
"content": "## 设计师与发布器"
},
"typeVersion": 1
},
{
"name": "计划触发器",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
0,
300
],
"parameters": {
"rule": {
"interval": [
{
"field": "cronExpression",
"expression": "0 11 * * TUE"
},
{
"field": "cronExpression",
"expression": "0 11 * * THU"
}
]
}
},
"typeVersion": 1.2
},
{
"name": "RSS 读取",
"type": "n8n-nodes-base.rssFeedRead",
"position": [
224,
300
],
"parameters": {
"url": "https://blog.hubspot.com/marketing/rss.xml",
"options": {}
},
"retryOnFail": true,
"typeVersion": 1.2
},
{
"name": "聚合",
"type": "n8n-nodes-base.aggregate",
"position": [
448,
300
],
"parameters": {
"options": {},
"fieldsToAggregate": {
"fieldToAggregate": [
{
"fieldToAggregate": "title"
},
{
"fieldToAggregate": "content"
},
{
"fieldToAggregate": "link"
}
]
}
},
"typeVersion": 1
},
{
"name": "将新闻分组为 1 个项目",
"type": "n8n-nodes-base.code",
"position": [
672,
300
],
"parameters": {
"jsCode": "// Inputs expected from Aggregate/RSS: arrays: title[], content[], link[]\nconst all = items[0].json; // aggregated item\nconst titles = all.title || [];\nconst contents = all.content || [];\nconst links = all.link || [];\n\nconst articles = [];\nconst lines = [];\n\nconst maxLen = Math.max(titles.length, contents.length, links.length);\nfor (let i = 0; i < maxLen; i++) {\n const obj = {\n id: i + 1, // stable ID (1..N). Use guid if you have one.\n title: titles[i] ?? \"\",\n content: contents[i] ?? \"\",\n link: links[i] ?? \"\"\n };\n articles.push(obj);\n // Short preview for the AI to choose from:\n const preview = (obj.content || \"\").replace(/\\s+/g, \" \").slice(0, 220);\n lines.push(`${obj.id}. ${obj.title}\\n${preview}${preview.length === 220 ? \"…\" : \"\"}`);\n}\n\nreturn [\n {\n json: {\n articles, // keep the structured mapping\n forAI: lines.join(\"\\n\\n\") // human-readable list for the model\n }\n }\n];"
},
"typeVersion": 2
},
{
"name": "最佳文章查找器",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
896,
300
],
"parameters": {
"text": "=You are (company name) content curator. Select the BEST article for our audience.\n\nCOMPANY AUDIENCE:\n\n\nSELECTION CRITERIA:\nCHECK:\n- Can someone practically apply this TODAY or is it just knowledge?\n- Will they want to save this?\n\nSKIP ARTICLES ABOUT:\n- Pure theory without practical steps\n\nPick only 1 and give only {{ $json.articles[0].link }} as output\n\n{{ $json.forAI }}\n\n",
"options": {},
"promptType": "define"
},
"typeVersion": 2.2
},
{
"name": "Google Gemini聊天模型",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
968,
524
],
"parameters": {
"options": {},
"modelName": "models/gemini-1.5-flash"
},
"typeVersion": 1
},
{
"name": "Google Gemini 聊天模型1",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1320,
400
],
"parameters": {
"options": {}
},
"typeVersion": 1
},
{
"name": "内容创建器",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1248,
176
],
"parameters": {
"text": "=Turn blog into quick byte below 200 words. \n\nCOMPANY AUDIENCE:\n\n\nWRITING RULES:\n- Write for the audience keeping in mind that they need opinion/insights, they don't have time to spare so be very on point and crisp and profound\n- Include specific numbers/time when possible\n- Keep it to the point like in news/bulletin \n- Always use bullets/classified structure, no extra output needed\n\nHere is the blog to use: {{ $json.output }}",
"options": {},
"promptType": "define"
},
"retryOnFail": true,
"typeVersion": 2.2
},
{
"name": "帖子优化器",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
1600,
176
],
"parameters": {
"text": "=Analyze this post deeply\n\nPost = {{ $json.output }}\n\nCHECK & OPTIMIZE FOR:\n- Can someone practically apply this TODAY or is it just knowledge?\n- Will THEY want to save this?\n- Does this have fluff/filler words that inflate sentences? Keep sentences small and easy to read.\n- Does it look AI Generated? Prefer human sentence construction\n- No emoji, use → or other symbols for bullets, don't use * or em dash in post, space after every bullet\n- Analyze First line: should not be in text:text format, only mention crux like \"loop marketing strategy\", or use title like \"here's why you need loop marketing\"\n\nAlso create a headline for image for this post, keep it crisp and catchy\n\nOUTPUT:\n{\n \"final_post\": \"[LinkedIn-ready post]\",\n\"image_text\": \"[Headline for image= what the post is about]\"\n \"confidence_score\": [1-10],\n \"post_now\": [true if score >= 7]\n} ",
"options": {},
"promptType": "define",
"hasOutputParser": true
},
"retryOnFail": true,
"typeVersion": 2.2
},
{
"name": "Google Gemini 聊天模型2",
"type": "@n8n/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1608,
400
],
"parameters": {
"options": {},
"modelName": "models/gemini-1.5-pro"
},
"typeVersion": 1
},
{
"name": "结构化输出解析器",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
1736,
400
],
"parameters": {
"jsonSchemaExample": "{\n \"final_post\": \"[LinkedIn-ready post]\",\n \"image_text\": \"[Image Title Catcy]\",\n \"confidence_score\": [10],\n \"post_now\": [true]\n} "
},
"typeVersion": 1.3
},
{
"name": "条件判断",
"type": "n8n-nodes-base.if",
"position": [
1952,
300
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "boolean",
"operation": "true",
"singleValue": true
},
"leftValue": "={{ $json.output.post_now[0] }}",
"rightValue": "true"
}
]
}
},
"typeVersion": 2.2
},
{
"name": "Templated",
"type": "n8n-nodes-templated.templated",
"position": [
2176,
300
],
"parameters": {
"layers": {
"layer": [
{
"text": "={{ $json.output.image_text }}",
"layerName": "paragraph-text"
}
]
},
"template": "",
"requestOptions": {}
},
"retryOnFail": true,
"typeVersion": 1
},
{
"name": "创建帖子",
"type": "n8n-nodes-base.linkedIn",
"position": [
2624,
300
],
"parameters": {
"text": "={{ $('Post optimizer').item.json.output.final_post }}",
"postAs": "organization",
"organization": "",
"additionalFields": {},
"shareMediaCategory": "IMAGE"
},
"typeVersion": 1
},
{
"name": "HTTP 请求",
"type": "n8n-nodes-base.httpRequest",
"position": [
2400,
300
],
"parameters": {
"url": "={{ $json.render_url }}",
"options": {
"response": {
"response": {
"responseFormat": "file"
}
}
}
},
"typeVersion": 4.2
}
],
"pinData": {},
"connections": {
"If": {
"main": [
[
{
"node": "Templated",
"type": "main",
"index": 0
}
],
[
{
"node": "Best Article finder",
"type": "main",
"index": 0
}
]
]
},
"RSS Read": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
},
"Aggregate": {
"main": [
[
{
"node": "group the news into 1 item",
"type": "main",
"index": 0
}
]
]
},
"Templated": {
"main": [
[
{
"node": "HTTP Request",
"type": "main",
"index": 0
}
]
]
},
"HTTP Request": {
"main": [
[
{
"node": "Create a post",
"type": "main",
"index": 0
}
]
]
},
"Post optimizer": {
"main": [
[
{
"node": "If",
"type": "main",
"index": 0
}
]
]
},
"Content Creator": {
"main": [
[
{
"node": "Post optimizer",
"type": "main",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "RSS Read",
"type": "main",
"index": 0
}
]
]
},
"Best Article finder": {
"main": [
[
{
"node": "Content Creator",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "Best Article finder",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Structured Output Parser": {
"ai_outputParser": [
[
{
"node": "Post optimizer",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"Google Gemini Chat Model1": {
"ai_languageModel": [
[
{
"node": "Content Creator",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Google Gemini Chat Model2": {
"ai_languageModel": [
[
{
"node": "Post optimizer",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"group the news into 1 item": {
"main": [
[
{
"node": "Best Article finder",
"type": "main",
"index": 0
}
]
]
}
}
}常见问题
如何使用这个工作流?
复制上方的 JSON 配置代码,在您的 n8n 实例中创建新工作流并选择「从 JSON 导入」,粘贴配置后根据需要修改凭证设置即可。
这个工作流适合什么场景?
高级 - 社交媒体, 多模态 AI
需要付费吗?
本工作流完全免费,您可以直接导入使用。但请注意,工作流中使用的第三方服务(如 OpenAI API)可能需要您自行付费。
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