每日 AI 新闻摘要自动生成 LinkedIn 帖子
RSS 订阅 → n8n 定时触发 → 代码过滤 → OpenAI 摘要与文案 → Gmail 审阅发送
- 给谁
- 希望自动获取 AI 新闻并生成 LinkedIn 内容的运营者或创始人
- 你会得到
- 每天早上收到一封包含待审阅 LinkedIn 帖子的邮件
硬约束
在 n8n 中导入模板,配置 OpenAI API 密钥和 Gmail OAuth2 授权,设置收件邮箱,按需调整 RSS 源与模型。工作流每日触发,读取多个 RSS 源,用 JavaScript 过滤近 48 小时内的 AI 相关文章并去重,合并后交由 OpenAI 生成摘要,再生成 LinkedIn 风格帖子,最后通过 Gmail 发送给自己审阅。若当天无文章则发送无新闻通知。
他们做了什么
模板作者 itechnotion 在 n8n 中创建了一个工作流:每日定时从 VentureBeat、TechCrunch AI 和 OpenAI Blog 的 RSS 源抓取文章,用 JavaScript 过滤近 48 小时的 AI 相关内容并去重,随后通过两个 OpenAI 节点先后生成行业摘要和 LinkedIn 风格帖子,最终用 Gmail 将结果发送到用户邮箱审阅。
效果如何
作者报告该模板可用于每日自动化内容生产,减少手动浏览和撰写时间(author_report)。模板在 n8n.io 上发布,视图数显示有一定关注度。
值得知道
模板默认过滤 48 小时而非 24 小时的文章,与描述中的 'last 24 hrs' 存在差异,建议用户根据需求调整代码中的时间窗口。两个 OpenAI 节点均使用 gpt-4.1-mini,用户可切换为 gpt-4.1 或 gpt-4 以提升质量。RSS 源为硬编码默认值,需自行检查可访问性。Gmail 节点需要 OAuth2 授权,非普通密码登录。本站未实际导入运行,复现前请用样例数据测试完整链路。
n8n 工作流模板
结构已检查 · 未实际运行下载后在 n8n 选择“Import from File”,或复制 JSON 后粘贴到编辑器。先配置自己的账号,再用测试数据运行;模板默认未启用。
配置与测试清单
需要绑定的凭证
- AI News Summarizer1 节点:绑定OpenAI API 凭证。
- Generate LinkedIn Post1 节点:绑定OpenAI API 凭证。
- Send for Review1 节点:绑定Gmail OAuth2 凭证。
- No Articles Notification1 节点:绑定Gmail OAuth2 凭证。
需要替换的配置
- 源模板来自 n8n 公开库 #5068(约 15 个节点)。导入后先保持未启用,核对触发器、表达式与外部 API 端点。
- Sticky Note 中的说明仅供参考;按自己的账号、表结构或频道 ID 替换占位配置。
测试输入与预期结果
- 在测试环境手动执行一次主路径,确认每个需凭证的节点已连接且无鉴权错误。
- 用一条合成/脱敏样例数据跑通,核对输出字段与下游写入目标,再考虑生产启用。
模板处理说明
- 已移除原作者凭证绑定、webhookId 与执行数据,工作流设为未启用;节点、连线与原文提示词保持原样。未在 n8n 中实际运行。
- 未改业务逻辑;运行前请自行核对密钥、配额与隐私合规。
模板获取日期: 2026-10-24
步骤
配置定时触发
在 n8n 工作流中添加 Schedule Trigger 节点(或从模板导入),设置每 24 小时执行一次。该节点将作为整个自动化的时间入口。
添加 RSS 订阅源
配置三个 RSS Feed Read 节点,分别读取 VentureBeat AI、TechCrunch AI 和 OpenAI Blog 的 RSS 地址。模板已提供默认 URL,可替换为其他 AI 相关源。
合并并过滤文章
使用 Merge 节点将三个 RSS 源输出合并,再通过 Code 节点运行 JavaScript:筛选近 48 小时内发布、标题或摘要包含 AI 关键词的文章,去重后按时间排序,最多保留 10 篇。
运行提示词 · 来源原文。Filter Recent AI Articles1 节点的 JS Code 字段
// Filter articles from last 48 hours and relevant to AI const now = new Date(); const twoDaysAgo = new Date(now.getTime() - (48 * 60 * 60 * 1000)); // Create a Set to track unique articles (by title or link) const uniqueArticles = new Map(); items.forEach(item => { const articleDate = new Date(item.json.pubDate || item.json.date); const isRecent = articleDate >= twoDaysAgo; const title = (item.json.title || '').toLowerCase(); const description = (item.json.description || '').toLowerCase(); const aiKeywords = ['ai', 'artificial intelligence', 'machine learning', 'ml', 'neural', 'gpt', 'llm', 'chatbot', 'automation', 'deep learning', 'agentic ai']; const isAIRelated = aiKeywords.some(keyword => title.includes(keyword) || description.includes(keyword) ); // Only add if recent, AI-related, and not already added if (isRecent && isAIRelated) { const uniqueKey = item.json.link || item.json.title; if (!uniqueArticles.has(uniqueKey)) { uniqueArticles.set(uniqueKey, { title: item.json.title, description: item.json.description, link: item.json.link, pubDate: item.json.pubDate || item.json.date, source: item.json.source || 'RSS Feed', dateObj: articleDate // Keep for sorting }); } } }); // Convert Map to array, sort by date (newest first) and limit to top 10 const sortedItems = Array.from(uniqueArticles.values()) .sort((a, b) => b.dateObj - a.dateObj) .slice(0, 10); // Return formatted items without dateObj return sortedItems.map(item => ({ json: { title: item.title, description: item.description, link: item.link, pubDate: item.pubDate, source: item.source } }));准备文章并检查存在性
通过 Code 节点将过滤后的文章格式化为单一字符串,包含标题、摘要、来源、日期和链接。随后用 If 节点检查 articleCount 是否大于 0,决定后续走向。
运行提示词 · 来源原文。Prepare Articles for Summary1 节点的 JS Code 字段
// Combine all articles into a single string for summarization const articles = items.map(item => { return `Title: ${item.json.title}\nDescription: ${item.json.description}\nSource: ${item.json.source}\nDate: ${item.json.pubDate}\nLink: ${item.json.link}\n---`; }).join('\n\n'); return [{ json: { articles: articles, articleCount: items.length, processedAt: new Date().toISOString() } }];AI 摘要生成
将准备好的文章文本传入 OpenAI 节点(默认 gpt-4.1-mini),使用系统提示词让模型分析多篇 AI 新闻,提取最重要的 2-3 条发展,写成 80-120 词的摘要,适合 LinkedIn 专业人士阅读。
运行提示词 · 来源原文。AI News Summarizer1 节点的 messages.values[0].content 字段
=You are an expert AI industry analyst with deep knowledge of artificial intelligence trends, breakthroughs, and market developments. Your task is to analyze multiple AI news articles and create a compelling, insightful summary for LinkedIn professionals. **Your Analysis Should:** - Identify the most significant and impactful AI developments from the provided articles - Focus on stories that will matter to business leaders, developers, and AI enthusiasts - Highlight breakthrough technologies, major company announcements, funding news, or industry shifts - Connect developments to broader AI trends and implications - Prioritize recency and relevance over minor updates **Content Requirements:** - Write 3-4 concise, punchy sentences (80-120 words total) - Lead with the most newsworthy development - Include specific company names, product names, or key figures when relevant - Mention concrete details (funding amounts, performance metrics, release dates) if significant - End with a forward-looking statement about industry impact - Use professional but engaging language suitable for LinkedIn **Style Guidelines:** - Write in active voice with strong, decisive language - Avoid technical jargon that would confuse general business audience - Use numbers and specific details to add credibility - Create a sense of momentum and importance - Don't oversell - be factual but compelling **If Multiple Major Stories Exist:** - Mention 2-3 key developments maximum - Connect them thematically if possible (e.g., "funding surge," "enterprise adoption," "new capabilities") - Prioritize stories with broader business implications Now analyze these AI news articles and create a summary covering the most important developments: {{ $json.articles }} Focus particularly on major funding rounds, significant product launches, and industry-changing developments from the list above.生成 LinkedIn 帖子
将上一步的摘要传入第二个 OpenAI 节点(默认 gpt-4.1-mini),使用系统提示词生成包含钩子、正文、行动号召和话题标签的 LinkedIn 帖子,长度控制在 250-300 词,适合移动端阅读。
运行提示词 · 来源原文。Generate LinkedIn Post1 节点的 messages.values[0].content 字段
=You are a professional LinkedIn content creator specializing in AI and technology. Your expertise lies in transforming complex AI news into engaging, shareable posts that drive meaningful professional discussions. **Your Mission:** Create a compelling LinkedIn post that will stop professionals from scrolling and encourage them to engage through likes, comments, and shares. **Content Foundation:** {{ $json.message.content }} **Post Requirements:** **Structure:** - Hook: Start with an attention-grabbing opening line or question - Body: 2-3 short paragraphs (2-3 sentences each) - Call-to-Action: End with an engaging question that invites discussion **Tone & Style:** - Professional yet conversational and approachable - Confident but not overly promotional - Use "I" or "We" occasionally to add personal touch - Mix of industry insights with accessible language **Content Elements:** - Lead with the most impactful development from the summary - Include specific numbers, company names, and concrete details - Connect AI developments to broader business implications - Add 2-3 relevant emojis (🚀 🤖 💡 🧠 ⚡ 🔥 🎯) - use sparingly and strategically - Keep total length 250-300 words maximum **Engagement Optimization:** - Use short paragraphs for mobile readability - Include 5-7 relevant hashtags at the end: #AI #ArtificialIntelligence #TechNews #Innovation #MachineLearning #StartupFunding #TechTrends - End with a thought-provoking question that encourages comments - Use line breaks for visual appeal **Question Examples for Ending:** - "What's your take on this development?" - "How do you see this impacting your industry?" - "Which of these developments excites you most?" - "Are we moving too fast or not fast enough?" - "What challenges do you foresee with this technology?" **Visual Format:** Use line breaks between paragraphs and before hashtags for better readability. **Sample Structure:** [Hook/Opening statement] 🚀 [Key development with specifics] [Industry impact/implications] [Engaging question] #AI #TechNews #Innovation #MachineLearning #StartupFunding **Important:** - Make it shareable - professionals should want to repost this - Focus on business relevance, not just technical details - Create urgency around staying informed in AI - Avoid buzzwords and hype - be authentic and informative邮件发送审阅
使用 Gmail 节点将生成的帖子以纯文本邮件发送给自己,主题为 'LinkedIn AI Post Ready for Review'。若当天无匹配文章,则走另一分支发送 'No AI News Found Today' 通知。需在节点中配置收件人邮箱地址。
可复制提示词
搭建指导 · 本站建议版本。交给搭建助手,先确认输入和权限
这一段是提示词,页面不会在这里插入广告。
请根据以下材料在 n8n 中搭建工作流:先确认已拥有 OpenAI API 密钥和 Gmail OAuth2 凭证,然后导入模板或按节点清单手动创建。重点检查 RSS 源地址、过滤代码中的时间窗口与关键词、两个 OpenAI 节点的模型选择,以及 Gmail 节点的收件人地址。先用样例数据手动执行一次,确认文章过滤、摘要和帖子生成符合预期后再启用定时触发。
搭建前需准备 OpenAI API key 和 Gmail OAuth2 授权;建议首次运行使用手动触发测试。
来源
Daily AI news digest to LinkedIn posts with OpenAI GPT and RSS feeds · itechnotion · n8n.io · 2025-06-20
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