Seven Liu This workflow corresponds to n8n.io template #5933 — we link there as the canonical source.
This workflow follows the Chainllm → Google Sheets recipe pattern — see all workflows that pair these two integrations.
The workflow JSON
Copy or download the full n8n JSON below. Paste it into a new n8n workflow, add your credentials, activate. Full import guide →
{
"id": "KJI3ivu0QdOeWQnp",
"meta": {
"templateCredsSetupCompleted": true
},
"name": "Classify and Summarize WeChat Articles to Google Sheets and Notion",
"tags": [],
"nodes": [
{
"id": "379aa7e3-f0f9-431a-b86d-4e1ed71fd307",
"name": "Read Initial Links",
"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": {
"name": "<your credential>"
}
},
"typeVersion": 4.6
},
{
"id": "def0ea7d-7da8-4506-9c90-4312bd6e5b64",
"name": "Read RSS Links",
"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": {
"name": "<your credential>"
}
},
"typeVersion": 4.6
},
{
"id": "c21ea372-874b-4b85-ae7d-d546deb92d06",
"name": "IF (Filter by Date)",
"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": "Save Initial Data",
"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": {
"name": "<your credential>"
}
},
"typeVersion": 4.6
},
{
"id": "2f5de224-3143-44c3-9730-766110cc4a03",
"name": "RSS Read",
"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": "When clicking \u2018Execute workflow\u2019",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-320,
160
],
"parameters": {},
"typeVersion": 1
},
{
"id": "202633fe-ec3d-43c8-bdca-a19e40db1961",
"name": "Merge",
"type": "n8n-nodes-base.merge",
"position": [
1100,
180
],
"parameters": {},
"typeVersion": 3.2
},
{
"id": "ceec6d61-4ec8-4073-9693-ca768af3d6eb",
"name": "Filter Unique Links",
"type": "n8n-nodes-base.code",
"position": [
1520,
180
],
"parameters": {
"jsCode": "const allItems = $input.all();\nconst linkCount = {};\n\n// \u7edf\u8ba1\u6bcf\u4e2a link \u7684\u51fa\u73b0\u6b21\u6570\nallItems.forEach(item => {\n const link = item.json.link;\n linkCount[link] = (linkCount[link] || 0) + 1;\n});\n\n// \u8fc7\u6ee4\u53ea\u51fa\u73b0 1 \u6b21\u7684\u8bb0\u5f55\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": "Filtered Data",
"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": "pubDate&link Only",
"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": "={{ $json.link }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "04040e72-be20-40c4-9f99-b3036de54d12",
"name": "pubDate Processing",
"type": "n8n-nodes-base.set",
"position": [
300,
360
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "274a88d7-5b91-4934-b7cd-7ae56e8587b2",
"name": "pubDate",
"type": "string",
"value": "={{ new Date($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": "Merge1",
"type": "n8n-nodes-base.merge",
"position": [
1220,
360
],
"parameters": {},
"typeVersion": 3.2
},
{
"id": "ee826fb2-5542-42cc-ae2f-9636c1db930a",
"name": "Restore Full Data with Code",
"type": "n8n-nodes-base.code",
"position": [
-140,
620
],
"parameters": {
"jsCode": "const items = $input.all();\n\n// \u521b\u5efa\u4e00\u4e2a\u5bf9\u8c61\u6765\u8ddf\u8e2a\u94fe\u63a5\u51fa\u73b0\u6b21\u6570\u548c\u5bf9\u5e94\u9879\nconst linkTracker = {};\n\n// \u7b2c\u4e00\u6b21\u904d\u5386\uff1a\u7edf\u8ba1\u6bcf\u4e2a\u94fe\u63a5\u51fa\u73b0\u7684\u6b21\u6570\u548c\u8bb0\u5f55\u5bf9\u5e94\u9879\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// \u7b2c\u4e8c\u6b21\u904d\u5386\uff1a\u7b5b\u9009\u51fa\u91cd\u590d\u94fe\u63a5\u4e14\u5e26\u6709 content \u7684\u9879\nconst result = [];\nconst processedLinks = new Set(); // \u7528\u4e8e\u907f\u514d\u91cd\u590d\u5904\u7406\u540c\u4e00\u4e2a\u94fe\u63a5\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": "Relevance Classification for Topic Monitoring",
"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 \u6b27\u9633\u826f\u5b9c, \u8bfb\u4e66\u7b14\u8bb0\uff0cAI in these fields."
},
{
"category": "not_relevant",
"description": "Articles not directly related to \u6b27\u9633\u826f\u5b9c, \u62db\u751f, \u8d85\u7ea7\u4e2a\u4f53 in these fields."
}
]
}
},
"typeVersion": 1
},
{
"id": "50642d77-04a1-40b0-87a7-41d073dff5e6",
"name": "OpenAI Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
320,
840
],
"parameters": {
"model": "gpt-4.1-nano",
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.1
},
{
"id": "7c91fad5-56b5-466f-b320-6c0fc8f55254",
"name": "Basic LLM Chain",
"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|*\u6587\u7ae0\u6807\u9898*>`. Ensure the title is engaging and reflective of the content.\n - **Summary Sections**: Use **bold text** (`*`) for section headings (e.g., *\u6587\u7ae0\u6982\u8981*, *\u5173\u952e\u8981\u70b9*, *\u80cc\u666f\u4e0e\u76f8\u5173\u6027*) to guide readers.\n - **Key Points**: Present key insights as bullet points using `\u2022` for concise and scannable information.\n - **Context and Relevance**: Explain the article\u2019s importance, its relevance to readers\u2019 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 `\u2022` 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** \u2013 `<URL|*\u6587\u7ae0\u6807\u9898*>` \n2. **\u6587\u7ae0\u6982\u8981** \u2013 [Comprehensive overview with deep analysis.] \n3. **\u5173\u952e\u8981\u70b9** \u2013 \n \u2022 [Key point 1] \n \u2022 [Key point 2] \n \u2022 [Key point 3] \n4. **\u80cc\u666f\u4e0e\u76f8\u5173\u6027** \u2013 [Explanation of importance and relevance with your interpretation.]"
}
]
},
"promptType": "define"
},
"typeVersion": 1.5
},
{
"id": "770887c4-4278-448a-961a-71eacbd57f3d",
"name": "OpenAI Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
740,
840
],
"parameters": {
"model": "gpt-4.1-nano",
"options": {}
},
"credentials": {
"openAiApi": {
"name": "<your credential>"
}
},
"typeVersion": 1.1
},
{
"id": "7efc776d-d8f0-4014-9551-ce6817450c91",
"name": "Set Fields - Relevant Articles",
"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 - Add relevant article",
"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": {
"name": "<your credential>"
}
},
"typeVersion": 4.5
},
{
"id": "3f3c8159-d130-46c9-be36-a44274639dc2",
"name": "Clean HTML Content",
"type": "n8n-nodes-base.code",
"position": [
80,
620
],
"parameters": {
"jsCode": "const items = $input.all().map(item => item.json);\n\nconst cleanedData = items.map(item => {\n let text = \"\";\n\n // \u5c1d\u8bd5\u4ece meta description \u63d0\u53d6\n const metaDescriptionMatch = item.content.match(/<meta\\s+name=[\"']description[\"']\\s+content=[\"'](.*?)[\"']/i);\n if (metaDescriptionMatch && metaDescriptionMatch[1]) {\n text = metaDescriptionMatch[1].trim();\n } else {\n // \u79fb\u9664\u811a\u672c\u548c\u6837\u5f0f\uff0c\u63d0\u53d6\u53ef\u80fd\u6b63\u6587\n text = item.content\n .replace(/<script[^>]*>[\\s\\S]*?<\\/script>/gi, \"\") // \u79fb\u9664\u811a\u672c\n .replace(/<style[^>]*>[\\s\\S]*?<\\/style>/gi, \"\") // \u79fb\u9664\u6837\u5f0f\n .replace(/<!--[\\s\\S]*?-->/g, \"\") // \u79fb\u9664\u6ce8\u91ca\n .replace(/<[^>]+>/g, \" \") // \u79fb\u9664\u6807\u7b7e\n .replace(/window\\..*?(?=\\s|$)/g, \"\") // \u79fb\u9664 window \u5bf9\u8c61\n .replace(/[\\s\\n\\r]+/g, \" \") // \u5408\u5e76\u591a\u4f59\u7a7a\u683c\n .trim();\n }\n\n // \u5982\u679c\u4ecd\u4e3a\u7a7a\uff0c\u6807\u8bb0\u4e3a\u65e0\u5185\u5bb9\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": "Create a database page",
"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": {
"name": "<your credential>"
}
},
"typeVersion": 2.2
},
{
"id": "7417f405-bb62-4fb7-842f-81b6c6e8a21c",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-800,
-40
],
"parameters": {
"width": 360,
"height": 380,
"content": "## Workflow Overview\n\nThis workflow automates classifying and summarizing WeChat articles! \ud83d\udcd1 It reads RSS links from Google Sheets, filters by date \u23f3, cleans content \ud83e\uddf9, classifies relevance (e.g., AI, specific person) \ud83c\udfaf, and creates Slack-formatted summaries with GPT-4.1-nano. \ud83e\udd16 Results save to Google Sheets and Notion. \ud83d\udcca\n\n- **Setup Guide**: Replace documentId and rss_feed_url with your own. \ud83d\udd27 Configure OpenAI and Google Sheets credentials\u2014don\u2019t hardcode! \ud83d\udd10\n- **Customization**: Tweak AI prompts or add outputs (e.g., Slack). \ud83c\udfa8\n- **Note**: Use n8n credentials for security. \ud83d\udee1\ufe0f\n(Optional: Add a Loom video or YouTube link here! \ud83c\udfa5)"
},
"typeVersion": 1
},
{
"id": "45d493a4-c20a-4da1-a01c-6db4be67e127",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-180,
-40
],
"parameters": {
"color": 5,
"width": 1020,
"height": 560,
"content": "## Step 1 - Data Input\ud83d\udce5\n\nRead initial links and RSS feeds from Google Sheets. \ud83d\udccb"
},
"typeVersion": 1
},
{
"id": "f7be9779-8638-40f7-92e7-9db22cf16d62",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1140,
-40
],
"parameters": {
"color": 5,
"width": 560,
"height": 560,
"content": "## Step 2 - Deduplication Step \ud83d\udd04\n\nCheck for already processed URLs using \"Filter Unique Links\" node. \u2705 \nIf a URL is duplicate, skip it; process only new content. \u23e9 \nThis ensures efficiency and avoids redundant work! \ud83d\ude80"
},
"typeVersion": 1
},
{
"id": "598b9f22-f977-4269-92f2-1b512b3d61f3",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-180,
880
],
"parameters": {
"color": 5,
"width": 1200,
"height": 280,
"content": "## Step 3 - Processing\u2699\ufe0f\n\n- Classification \ud83d\udcca: Use \"Relevance Classification\" node to categorize articles (e.g., relevant to AI/specific person or not). \ud83c\udfaf AI determines relevance based on content.\n- AI Summarization \ud83e\udde0: Leverage \"Basic LLM Chain\" with GPT-4.1-nano to generate insightful, Slack-formatted summaries in Chinese. \ud83e\udd16 Focuses on key points and analysis."
},
"typeVersion": 1
},
{
"id": "4e6ff59a-5788-415c-a463-ceb0bd448b1e",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
1140,
1000
],
"parameters": {
"color": 5,
"content": "## Step 4 - Output\ud83d\udce4\n\nSave to Google Sheets and Notion.\n"
},
"typeVersion": 1
}
],
"active": false,
"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 \u2018Execute workflow\u2019": {
"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
}
]
]
}
}
}
Credentials you'll need
Each integration node will prompt for credentials when you import. We strip credential IDs before publishing — you'll add your own.
googleSheetsOAuth2ApinotionApiopenAiApi
Pro
For the full experience including quality scoring and batch install features for each workflow upgrade to Pro
About this workflow
This template is perfect for content creators, marketers, and researchers managing WeChat public account articles! 🚀 It’s ideal for n8n newcomers or anyone wanting to save time on manual content analysis, especially if you use Google Sheets for tracking. 📊 Whether you’re into…
Source: https://n8n.io/workflows/5933/ — original creator credit. Request a take-down →
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