将微信文章分类和总结到 Google Sheets 和 Notion
高级
这是一个Market Research, AI Summarization领域的自动化工作流，包含 26 个节点。主要使用 If, Set, Code, Merge, Notion 等节点。 使用 GPT-4 Nano 将微信文章分类和总结到 Google Sheets 和 Notion
前置要求
- •Notion API Key
- •Google Sheets API 凭证
- •OpenAI API Key
使用的节点 (26)
工作流预览
可视化展示节点连接关系，支持缩放和平移
导出工作流
复制以下 JSON 配置到 n8n 导入，即可使用此工作流
{
"id": "KJI3ivu0QdOeWQnp",
"meta": {
"instanceId": "bddc3f9d7220ab462121a22afd09fa37a953a530ce58fc501da29a1454364846",
"templateCredsSetupCompleted": true
},
"name": "将微信文章分类和总结到 Google Sheets 和 Notion",
"tags": [],
"nodes": [
{
"id": "379aa7e3-f0f9-431a-b86d-4e1ed71fd307",
"name": "读取初始链接",
"type": "n8n-nodes-base.googleSheets",
"position": [
-140,
160
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": 198451233,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/12HW0_goHSaO2QpqLTYxNpEWePBK4o0nsniyAx-hkkXE/edit#gid=198451233",
"cachedResultName": "Save Initial Links"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "12HW0_goHSaO2QpqLTYxNpEWePBK4o0nsniyAx-hkkXE",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/12HW0_goHSaO2QpqLTYxNpEWePBK4o0nsniyAx-hkkXE/edit?usp=drivesdk",
"cachedResultName": "5am project"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "12vQQF43dZTfyiVE",
"name": "Google Sheets account"
}
},
"typeVersion": 4.6
},
{
"id": "def0ea7d-7da8-4506-9c90-4312bd6e5b64",
"name": "读取 RSS 链接",
"type": "n8n-nodes-base.googleSheets",
"position": [
-140,
360
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "list",
"value": "gid=0",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/12HW0_goHSaO2QpqLTYxNpEWePBK4o0nsniyAx-hkkXE/edit#gid=0",
"cachedResultName": "Read RSS Links"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "12HW0_goHSaO2QpqLTYxNpEWePBK4o0nsniyAx-hkkXE",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/12HW0_goHSaO2QpqLTYxNpEWePBK4o0nsniyAx-hkkXE/edit?usp=drivesdk",
"cachedResultName": "5am project"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "12vQQF43dZTfyiVE",
"name": "Google Sheets account"
}
},
"typeVersion": 4.6
},
{
"id": "c21ea372-874b-4b85-ae7d-d546deb92d06",
"name": "IF (按日期筛选)",
"type": "n8n-nodes-base.if",
"position": [
500,
360
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "c059092a-cddd-4790-bb65-a26afefa40af",
"operator": {
"type": "number",
"operation": "gt"
},
"leftValue": "={{ new Date($json.pubDate).getTime() }}",
"rightValue": "={{ new Date(Date.now() - 10* 24 * 60 * 60 * 1000).getTime() }}"
}
]
},
"looseTypeValidation": true
},
"typeVersion": 2.2
},
{
"id": "2213c327-38d5-4a7c-a06c-d9bad22e7d2a",
"name": "保存初始数据",
"type": "n8n-nodes-base.googleSheets",
"position": [
980,
340
],
"parameters": {
"columns": {
"value": {
"link": "={{ $json.link }}",
"title": "={{ $json.title }}",
"pubDate": "={{ $json.pubDate }}"
},
"schema": [
{
"id": "pubDate",
"type": "string",
"display": true,
"required": false,
"displayName": "pubDate",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "creator",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "creator",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "title",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "title",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "link",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "link",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "author",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "author",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "content:encoded",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "content:encoded",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "content:encodedSnippet",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "content:encodedSnippet",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "contentSnippet",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "contentSnippet",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "content",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "content",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "itunes",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "itunes",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"link"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "appendOrUpdate",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 198451233,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/12HW0_goHSaO2QpqLTYxNpEWePBK4o0nsniyAx-hkkXE/edit#gid=198451233",
"cachedResultName": "Save Initial Links"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "12HW0_goHSaO2QpqLTYxNpEWePBK4o0nsniyAx-hkkXE",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/12HW0_goHSaO2QpqLTYxNpEWePBK4o0nsniyAx-hkkXE/edit?usp=drivesdk",
"cachedResultName": "5am project"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "12vQQF43dZTfyiVE",
"name": "Google Sheets account"
}
},
"typeVersion": 4.6
},
{
"id": "2f5de224-3143-44c3-9730-766110cc4a03",
"name": "RSS 读取",
"type": "n8n-nodes-base.rssFeedRead",
"onError": "continueRegularOutput",
"position": [
80,
360
],
"parameters": {
"url": "={{ $json.rss_feed_url }}",
"options": {
"ignoreSSL": false
}
},
"executeOnce": false,
"typeVersion": 1.1
},
{
"id": "8c5bd286-a773-4e2e-9418-a1399ad80ab3",
"name": "当点击\"执行工作流\"时",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-320,
160
],
"parameters": {},
"typeVersion": 1
},
{
"id": "202633fe-ec3d-43c8-bdca-a19e40db1961",
"name": "合并",
"type": "n8n-nodes-base.merge",
"position": [
1100,
180
],
"parameters": {},
"typeVersion": 3.2
},
{
"id": "ceec6d61-4ec8-4073-9693-ca768af3d6eb",
"name": "筛选唯一链接",
"type": "n8n-nodes-base.code",
"position": [
1520,
180
],
"parameters": {
"jsCode": "const allItems = $input.all();\nconst linkCount = {};\n\n// 统计每个 link 的出现次数\nallItems.forEach(item => {\n const link = item.json.link;\n linkCount[link] = (linkCount[link] || 0) + 1;\n});\n\n// 过滤只出现 1 次的记录\nconst uniqueItems = allItems.filter(item => {\n const link = item.json.link;\n return linkCount[link] === 1;\n}).map(item => item.json);\n\nreturn uniqueItems;"
},
"typeVersion": 2
},
{
"id": "bda380c5-c9a3-4d16-b999-15ecbc296706",
"name": "筛选后的数据",
"type": "n8n-nodes-base.set",
"position": [
740,
340
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "298296a8-44f6-439d-8c4f-b86041721db4",
"name": "pubDate",
"type": "string",
"value": "={{ $json.pubDate }}"
},
{
"id": "6458616a-df3e-45ca-ba15-e7ef84283965",
"name": "creator",
"type": "string",
"value": "={{ $json.creator }}"
},
{
"id": "bb14c554-47d5-47c9-8be4-bcc4a9eaf1c3",
"name": "title",
"type": "string",
"value": "={{ $json.title }}"
},
{
"id": "e0cff4cc-2a8d-4d1b-9fe2-351c1dd2950b",
"name": "link",
"type": "string",
"value": "={{ $json.link }}"
},
{
"id": "c1d5909b-8a8f-4493-a67b-09b10fa2009a",
"name": "author",
"type": "string",
"value": "={{ $json.author }}"
},
{
"id": "8ea445ef-50ac-468d-b13d-90330447de13",
"name": "content:encoded",
"type": "string",
"value": "={{ $json['content:encoded'] }}"
},
{
"id": "a8a22f59-4a2c-413c-9c53-a37431d6debc",
"name": "content:encodedSnippet",
"type": "string",
"value": "={{ $json['content:encodedSnippet'] }}"
},
{
"id": "425df1ea-dacf-4cbe-b685-36f7722b36a7",
"name": "contentSnippet",
"type": "string",
"value": "={{ $json.contentSnippet }}"
},
{
"id": "81f67650-86bd-4aec-87e0-ab1ba85293f5",
"name": "content",
"type": "string",
"value": "={{ $json.content }}"
},
{
"id": "bb60c7f5-817a-4331-8e03-ad29ff07bf7a",
"name": "itunes",
"type": "string",
"value": "={{ $json.itunes }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "77fdc062-a331-43c3-b702-66152ed0be5e",
"name": "仅 pubDate 和 link",
"type": "n8n-nodes-base.set",
"position": [
1320,
180
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "07cf0b6d-9310-49d0-a515-bbd7377a8033",
"name": "pubDate",
"type": "string",
"value": "={{ $json.pubDate }}"
},
{
"id": "c04d9abf-d522-4951-b2b7-249d1c00b47f",
"name": "link",
"type": "string",
"value": "={{ $json.link }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "04040e72-be20-40c4-9f99-b3036de54d12",
"name": "pubDate 处理",
"type": "n8n-nodes-base.set",
"position": [
300,
360
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "274a88d7-5b91-4934-b7cd-7ae56e8587b2",
"name": "pubDate",
"type": "string",
"value": "={{ new Date($json.pubDate).toISOString() }}"
},
{
"id": "f2f5b242-c94d-4a4a-a97b-5dac938021c4",
"name": "creator",
"type": "string",
"value": ""
},
{
"id": "633465a4-8473-456b-aa1b-2d35a3544e28",
"name": "title",
"type": "string",
"value": "={{ $json.title }}"
},
{
"id": "edd82c33-3325-47ef-a4a1-58cd88181ed8",
"name": "link",
"type": "string",
"value": "={{ $json.link }}"
},
{
"id": "877279c6-052b-475a-a1d8-75e748bd8691",
"name": "author",
"type": "string",
"value": "={{ $json.author }}"
},
{
"id": "ea83ca2f-306a-4c2f-8fdd-0e54b473716d",
"name": "content:encoded",
"type": "string",
"value": "={{ $json['content:encoded'] }}"
},
{
"id": "b4f54fd1-1bb5-4def-926d-83246786214e",
"name": "content:encodedSnippet",
"type": "string",
"value": "={{ $json['content:encodedSnippet'] }}"
},
{
"id": "063d3f43-c626-4c96-aca0-5249efab4693",
"name": "contentSnippet",
"type": "string",
"value": "={{ $json.contentSnippet }}"
},
{
"id": "2e90a2e2-94d7-4d91-a85d-06facd879e44",
"name": "content",
"type": "string",
"value": "={{ $json.content }}"
},
{
"id": "b589c9c7-0330-4b6c-b974-9ba924ff51a6",
"name": "itunes",
"type": "object",
"value": "={{ $json.itunes }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "79ad6600-91ba-43f8-9a93-baf75671b4da",
"name": "合并1",
"type": "n8n-nodes-base.merge",
"position": [
1220,
360
],
"parameters": {},
"typeVersion": 3.2
},
{
"id": "ee826fb2-5542-42cc-ae2f-9636c1db930a",
"name": "使用代码恢复完整数据",
"type": "n8n-nodes-base.code",
"position": [
-140,
620
],
"parameters": {
"jsCode": "const items = $input.all();\n\n// 创建一个对象来跟踪链接出现次数和对应项\nconst linkTracker = {};\n\n// 第一次遍历：统计每个链接出现的次数和记录对应项\nitems.forEach(item => {\n const link = item.json.link ? item.json.link.trim().toLowerCase() : \"\";\n if (link) {\n if (!linkTracker[link]) {\n linkTracker[link] = {\n count: 0,\n items: []\n };\n }\n linkTracker[link].count++;\n linkTracker[link].items.push(item);\n }\n});\n\nconsole.log(\"Link Tracker:\", JSON.stringify(linkTracker, null, 2));\n\n// 第二次遍历：筛选出重复链接且带有 content 的项\nconst result = [];\nconst processedLinks = new Set(); // 用于避免重复处理同一个链接\n\nfor (const [link, data] of Object.entries(linkTracker)) {\n if (data.count > 1 && !processedLinks.has(link)) {\n processedLinks.add(link);\n const itemsWithContent = data.items.filter(item => item.json.content !== undefined && item.json.content !== \"\");\n if (itemsWithContent.length > 0) {\n result.push(...itemsWithContent);\n }\n }\n}\n\nconsole.log(\"Result:\", JSON.stringify(result, null, 2));\nreturn result;"
},
"executeOnce": false,
"typeVersion": 2,
"alwaysOutputData": false
},
{
"id": "980da728-dcc1-4eec-a590-9899c29a8982",
"name": "主题监控的相关性分类",
"type": "@n8n/n8n-nodes-langchain.textClassifier",
"position": [
300,
620
],
"parameters": {
"options": {
"fallback": "discard"
},
"inputText": "={{ $json.title }}{{ $json.cleanedContent }}",
"categories": {
"categories": [
{
"category": "relevant",
"description": "Articles related to 欧阳良宜, 读书笔记，AI in these fields."
},
{
"category": "not_relevant",
"description": "Articles not directly related to 欧阳良宜, 招生, 超级个体 in these fields."
}
]
}
},
"typeVersion": 1
},
{
"id": "50642d77-04a1-40b0-87a7-41d073dff5e6",
"name": "OpenAI 聊天模型1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
320,
840
],
"parameters": {
"model": "gpt-4.1-nano",
"options": {}
},
"credentials": {
"openAiApi": {
"id": "qyulXDWn9kVtVZp1",
"name": "OpenAi account"
}
},
"typeVersion": 1.1
},
{
"id": "7c91fad5-56b5-466f-b320-6c0fc8f55254",
"name": "基础LLM链",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
720,
600
],
"parameters": {
"text": "={{ $json.cleanedContent }}",
"messages": {
"messageValues": [
{
"message": "=You are an expert AI assistant responsible for analyzing and summarizing articles from WeChat public accounts **in Chinese**, formatting the output into Slack-compatible messages. Your task is to provide a deep, insightful summary that captures the main ideas, key points, and purpose of the article, while adding your own thoughtful analysis and interpretation to enhance understanding. Follow the guidelines below and use Slack-specific Markdown format.\n\n---\n\n### Instructions:\n1. **Input Analysis**: The input text may include incomplete HTML fragments, JavaScript code, or metadata. Focus only on meaningful textual content (e.g., article body or description) and ignore non-content elements (e.g., scripts, tags, or emojis).\n2. **Summary Requirements**:\n - Provide a comprehensive overview of the article's content, highlighting the central theme and key points without unnecessary details.\n - Add your own analysis and interpretation to offer deeper insights, connecting the content to broader contexts or implications.\n - Use clear, natural, and professional Chinese suitable for a general audience.\n3. **Output Structure**:\n - **Title with Link**: Format the article title as a clickable link using Slack Markdown: `<URL|*文章标题*>`. Ensure the title is engaging and reflective of the content.\n - **Summary Sections**: Use **bold text** (`*`) for section headings (e.g., *文章概要*, *关键要点*, *背景与相关性*) to guide readers.\n - **Key Points**: Present key insights as bullet points using `•` for concise and scannable information.\n - **Context and Relevance**: Explain the article’s importance, its relevance to readers’ interests, and its connection to trends or industry developments.\n4. **Slack Markdown Formatting**:\n - **Bold text**: `*bold text*`.\n - **Italic text**: `_italic text_` (optional for emphasis).\n - **Bullet points**: Use `•` for lists.\n - **Links**: Use `<URL|*text*>` for clickable links.\n - **Line breaks**: Use a blank line to separate paragraphs for readability.\n\n---\n\n### Input Text:\n{{ $json.cleanedContent }}\n\n### Output:\n[Provide the summary in the structured format below, tailored to the input text.]\n\n1. **Title with Link** – `<URL|*文章标题*>` \n2. **文章概要** – [Comprehensive overview with deep analysis.] \n3. **关键要点** – \n • [Key point 1] \n • [Key point 2] \n • [Key point 3] \n4. **背景与相关性** – [Explanation of importance and relevance with your interpretation.]"
}
]
},
"promptType": "define"
},
"typeVersion": 1.5
},
{
"id": "770887c4-4278-448a-961a-71eacbd57f3d",
"name": "OpenAI 聊天模型",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
740,
840
],
"parameters": {
"model": "gpt-4.1-nano",
"options": {}
},
"credentials": {
"openAiApi": {
"id": "VuKsr5L939eSa1c9",
"name": "KG API"
}
},
"typeVersion": 1.1
},
{
"id": "7efc776d-d8f0-4014-9551-ce6817450c91",
"name": "设置字段 - 相关文章",
"type": "n8n-nodes-base.set",
"position": [
1140,
600
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "3fbf5256-f06b-450a-adf7-65591a19c7dd",
"name": "article_url",
"type": "string",
"value": "={{ $('Relevance Classification for Topic Monitoring').item.json.link }}"
},
{
"id": "02f506cf-28fe-46ef-b97e-7ec938805151",
"name": "summarized",
"type": "string",
"value": "YES"
},
{
"id": "e23059bd-8bb2-439a-85bd-f9e191930d1e",
"name": "summary",
"type": "string",
"value": "={{ $json.text }}"
},
{
"id": "096acb35-4e9e-48fd-8e61-8ceb525591fa",
"name": "fetched_at",
"type": "string",
"value": "={{$now}}"
},
{
"id": "427243d1-01c4-458a-9626-75366e4264cd",
"name": "publish_date",
"type": "string",
"value": "={{ $('Relevance Classification for Topic Monitoring').item.json.pubDate.toDateTime().format('yyyy-MM-dd') }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "6250fcff-7557-4fcb-8de1-e23e3673d545",
"name": "Google Sheets - 添加相关文章",
"type": "n8n-nodes-base.googleSheets",
"position": [
1400,
600
],
"parameters": {
"columns": {
"value": {
"title": "{{ $('Relevance Classification for Topic Monitoring').item.json.title }}",
"summary": "={{ $json.summary }}",
"fetched_at": "={{ $json.fetched_at }}",
"summarized": "={{ $json.summarized }}",
"article_url": "={{ $json.article_url }}",
"publish_date": "={{ $json.publish_date }}"
},
"schema": [
{
"id": "article_url",
"type": "string",
"display": true,
"required": false,
"displayName": "article_url",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "summarized",
"type": "string",
"display": true,
"required": false,
"displayName": "summarized",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "title",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "title",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "summary",
"type": "string",
"display": true,
"required": false,
"displayName": "summary",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "website",
"type": "string",
"display": true,
"removed": true,
"required": false,
"displayName": "website",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "fetched_at",
"type": "string",
"display": true,
"required": false,
"displayName": "fetched_at",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "publish_date",
"type": "string",
"display": true,
"required": false,
"displayName": "publish_date",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
},
"options": {},
"operation": "append",
"sheetName": {
"__rl": true,
"mode": "list",
"value": 1936091950,
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/12HW0_goHSaO2QpqLTYxNpEWePBK4o0nsniyAx-hkkXE/edit#gid=1936091950",
"cachedResultName": "Save Processed Data"
},
"documentId": {
"__rl": true,
"mode": "list",
"value": "12HW0_goHSaO2QpqLTYxNpEWePBK4o0nsniyAx-hkkXE",
"cachedResultUrl": "https://docs.google.com/spreadsheets/d/12HW0_goHSaO2QpqLTYxNpEWePBK4o0nsniyAx-hkkXE/edit?usp=drivesdk",
"cachedResultName": "5am project"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "12vQQF43dZTfyiVE",
"name": "Google Sheets account"
}
},
"typeVersion": 4.5
},
{
"id": "3f3c8159-d130-46c9-be36-a44274639dc2",
"name": "清理 HTML 内容",
"type": "n8n-nodes-base.code",
"position": [
80,
620
],
"parameters": {
"jsCode": "const items = $input.all().map(item => item.json);\n\nconst cleanedData = items.map(item => {\n let text = \"\";\n\n // 尝试从 meta description 提取\n const metaDescriptionMatch = item.content.match(/<meta\\s+name=[\"']description[\"']\\s+content=[\"'](.*?)[\"']/i);\n if (metaDescriptionMatch && metaDescriptionMatch[1]) {\n text = metaDescriptionMatch[1].trim();\n } else {\n // 移除脚本和样式，提取可能正文\n text = item.content\n .replace(/<script[^>]*>[\\s\\S]*?<\\/script>/gi, \"\") // 移除脚本\n .replace(/<style[^>]*>[\\s\\S]*?<\\/style>/gi, \"\") // 移除样式\n .replace(/<!--[\\s\\S]*?-->/g, \"\") // 移除注释\n .replace(/<[^>]+>/g, \" \") // 移除标签\n .replace(/window\\..*?(?=\\s|$)/g, \"\") // 移除 window 对象\n .replace(/[\\s\\n\\r]+/g, \" \") // 合并多余空格\n .trim();\n }\n\n // 如果仍为空，标记为无内容\n if (!text) {\n text = \"No content extracted\";\n }\n\n return {\n ...item,\n cleanedContent: text\n };\n});\n\nconsole.log(\"Cleaned Data:\", JSON.stringify(cleanedData, null, 2));\nreturn cleanedData;"
},
"typeVersion": 2
},
{
"id": "de9ca195-a03d-4e81-9764-be1b15c30698",
"name": "创建数据库页面",
"type": "n8n-nodes-base.notion",
"position": [
1400,
800
],
"parameters": {
"options": {},
"resource": "databasePage",
"databaseId": {
"__rl": true,
"mode": "list",
"value": "22e79d55-2675-8055-a143-d55302c3c1b1",
"cachedResultUrl": "https://www.notion.so/22e79d5526758055a143d55302c3c1b1",
"cachedResultName": "wechat"
},
"propertiesUi": {
"propertyValues": [
{
"key": "article_url|title",
"title": "={{ $json.article_url }}"
},
{
"key": "summary|rich_text",
"textContent": "={{ $json.summary }}"
},
{
"key": "fetched_at|rich_text",
"textContent": "={{ $json.fetched_at }}"
}
]
}
},
"credentials": {
"notionApi": {
"id": "PVVFSqHzNo1O6H5j",
"name": "Notion account"
}
},
"typeVersion": 2.2
},
{
"id": "7417f405-bb62-4fb7-842f-81b6c6e8a21c",
"name": "便签",
"type": "n8n-nodes-base.stickyNote",
"position": [
-800,
-40
],
"parameters": {
"width": 360,
"height": 380,
"content": "## 工作流概述"
},
"typeVersion": 1
},
{
"id": "45d493a4-c20a-4da1-a01c-6db4be67e127",
"name": "便签1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-180,
-40
],
"parameters": {
"color": 5,
"width": 1020,
"height": 560,
"content": "## 步骤 1 - 数据输入 📥"
},
"typeVersion": 1
},
{
"id": "f7be9779-8638-40f7-92e7-9db22cf16d62",
"name": "便签2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1140,
-40
],
"parameters": {
"color": 5,
"width": 560,
"height": 560,
"content": "## 步骤 2 - 去重步骤 🔄"
},
"typeVersion": 1
},
{
"id": "598b9f22-f977-4269-92f2-1b512b3d61f3",
"name": "便签3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-180,
880
],
"parameters": {
"color": 5,
"width": 1200,
"height": 280,
"content": "## 步骤 3 - 处理 ⚙️"
},
"typeVersion": 1
},
{
"id": "4e6ff59a-5788-415c-a463-ceb0bd448b1e",
"name": "便签4",
"type": "n8n-nodes-base.stickyNote",
"position": [
1140,
1000
],
"parameters": {
"color": 5,
"content": "## 步骤 4 - 输出 📤"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "5e456447-8c95-43af-a068-075b86c084fb",
"connections": {
"Merge": {
"main": [
[
{
"node": "pubDate&link Only",
"type": "main",
"index": 0
}
]
]
},
"Merge1": {
"main": [
[
{
"node": "Restore Full Data with Code",
"type": "main",
"index": 0
}
]
]
},
"RSS Read": {
"main": [
[
{
"node": "pubDate Processing",
"type": "main",
"index": 0
}
]
]
},
"Filtered Data": {
"main": [
[
{
"node": "Save Initial Data",
"type": "main",
"index": 0
},
{
"node": "Merge1",
"type": "main",
"index": 0
}
]
]
},
"Read RSS Links": {
"main": [
[
{
"node": "RSS Read",
"type": "main",
"index": 0
}
]
]
},
"Basic LLM Chain": {
"main": [
[
{
"node": "Set Fields - Relevant Articles",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "Basic LLM Chain",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Save Initial Data": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 1
}
]
]
},
"pubDate&link Only": {
"main": [
[
{
"node": "Filter Unique Links",
"type": "main",
"index": 0
}
]
]
},
"Clean HTML Content": {
"main": [
[
{
"node": "Relevance Classification for Topic Monitoring",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model1": {
"ai_languageModel": [
[
{
"node": "Relevance Classification for Topic Monitoring",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Read Initial Links": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 0
}
]
]
},
"pubDate Processing": {
"main": [
[
{
"node": "IF (Filter by Date)",
"type": "main",
"index": 0
}
]
]
},
"Filter Unique Links": {
"main": [
[
{
"node": "Merge1",
"type": "main",
"index": 1
}
]
]
},
"IF (Filter by Date)": {
"main": [
[
{
"node": "Filtered Data",
"type": "main",
"index": 0
}
]
]
},
"Restore Full Data with Code": {
"main": [
[
{
"node": "Clean HTML Content",
"type": "main",
"index": 0
}
]
]
},
"Set Fields - Relevant Articles": {
"main": [
[
{
"node": "Google Sheets - Add relevant article",
"type": "main",
"index": 0
},
{
"node": "Create a database page",
"type": "main",
"index": 0
}
]
]
},
"When clicking ‘Execute workflow’": {
"main": [
[
{
"node": "Read Initial Links",
"type": "main",
"index": 0
},
{
"node": "Read RSS Links",
"type": "main",
"index": 0
}
]
]
},
"Relevance Classification for Topic Monitoring": {
"main": [
[
{
"node": "Basic LLM Chain",
"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 - 市场调研, AI 摘要总结
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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