Hugging Face到Notion
中级
这是一个AI领域的自动化工作流，包含 11 个节点。主要使用 If, Html, Notion, SplitOut, HttpRequest 等节点，结合人工智能技术实现智能自动化。 使用AI分析Hugging Face论文并存储到Notion
前置要求
- •Notion API Key
- •可能需要目标 API 的认证凭证
- •OpenAI API Key
分类
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": "FU3MrLkaTHmfdG4n",
"meta": {
"instanceId": "3294023dd650d95df294922b9d55d174ef26f4a2e6cce97c8a4ab5f98f5b8c7b",
"templateCredsSetupCompleted": true
},
"name": "Hugging Face 到 Notion",
"tags": [],
"nodes": [
{
"id": "32d5bfee-97f1-4e92-b62e-d09bdd9c3821",
"name": "计划触发器",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-2640,
-300
],
"parameters": {
"rule": {
"interval": [
{
"field": "weeks",
"triggerAtDay": [
1,
2,
3,
4,
5
],
"triggerAtHour": 8
}
]
}
},
"typeVersion": 1.2
},
{
"id": "b1f4078e-ac77-47ec-995c-f52fd98fafef",
"name": "条件判断",
"type": "n8n-nodes-base.if",
"position": [
-1360,
-280
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "7094d6db-1fa7-4b59-91cf-6bbd5b5f067e",
"operator": {
"type": "object",
"operation": "empty",
"singleValue": true
},
"leftValue": "={{ $json }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2.2
},
{
"id": "afac08e1-b629-4467-86ef-907e4a5e8841",
"name": "遍历项目",
"type": "n8n-nodes-base.splitInBatches",
"position": [
-1760,
-300
],
"parameters": {
"options": {
"reset": false
}
},
"typeVersion": 3
},
{
"id": "807ba450-9c89-4f88-aa84-91f43e3adfc6",
"name": "分离输出",
"type": "n8n-nodes-base.splitOut",
"position": [
-1960,
-300
],
"parameters": {
"options": {},
"fieldToSplitOut": "url, url"
},
"typeVersion": 1
},
{
"id": "08dd3f15-2030-48f2-ab0f-f85f797268e1",
"name": "请求 Hugging Face 论文",
"type": "n8n-nodes-base.httpRequest",
"position": [
-2440,
-300
],
"parameters": {
"url": "https://huggingface.co/papers",
"options": {},
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "date",
"value": "={{ $now.minus(1,'days').format('yyyy-MM-dd') }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "f37ba769-d881-4aad-927d-ca1f4a68b9a1",
"name": "提取 Hugging Face 论文",
"type": "n8n-nodes-base.html",
"position": [
-2200,
-300
],
"parameters": {
"options": {},
"operation": "extractHtmlContent",
"extractionValues": {
"values": [
{
"key": "url",
"attribute": "href",
"cssSelector": ".line-clamp-3",
"returnArray": true,
"returnValue": "attribute"
}
]
}
},
"typeVersion": 1.2
},
{
"id": "94ba99bf-a33b-4311-a4e6-86490e1bb9ad",
"name": "检查论文 URL 是否存在",
"type": "n8n-nodes-base.notion",
"position": [
-1540,
-280
],
"parameters": {
"filters": {
"conditions": [
{
"key": "URL|url",
"urlValue": "={{ 'https://huggingface.co'+$json.url }}",
"condition": "equals"
}
]
},
"options": {},
"resource": "databasePage",
"operation": "getAll",
"databaseId": {
"__rl": true,
"mode": "list",
"value": "17b67aba-1fcc-80ae-baa1-d88ffda7ae83",
"cachedResultUrl": "https://www.notion.so/17b67aba1fcc80aebaa1d88ffda7ae83",
"cachedResultName": "huggingface-abstract"
},
"filterType": "manual"
},
"credentials": {
"notionApi": {
"id": "I5KdUzwhWnphQ862",
"name": "notion"
}
},
"typeVersion": 2.2,
"alwaysOutputData": true
},
{
"id": "ece8dee2-e444-4557-aad9-5bdcb5ecd756",
"name": "请求 Hugging Face 论文详情",
"type": "n8n-nodes-base.httpRequest",
"position": [
-1080,
-300
],
"parameters": {
"url": "={{ 'https://huggingface.co'+$('Split Out').item.json.url }}",
"options": {}
},
"typeVersion": 4.2
},
{
"id": "53b266fe-e7c4-4820-92eb-78a6ba7a6430",
"name": "OpenAI 分析摘要",
"type": "@n8n/n8n-nodes-langchain.openAi",
"position": [
-640,
-300
],
"parameters": {
"modelId": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-2024-11-20",
"cachedResultName": "GPT-4O-2024-11-20"
},
"options": {},
"messages": {
"values": [
{
"role": "system",
"content": "Extract the following key details from the paper abstract:\n\nCore Introduction: Summarize the main contributions and objectives of the paper, highlighting its innovations and significance.\nKeyword Extraction: List 2-5 keywords that best represent the research direction and techniques of the paper.\nKey Data and Results: Extract important performance metrics, comparison results, and the paper's advantages over other studies.\nTechnical Details: Provide a brief overview of the methods, optimization techniques, and datasets mentioned in the paper.\nClassification: Assign an appropriate academic classification based on the content of the paper.\n\n\nOutput as json：\n{\n \"Core_Introduction\": \"PaSa is an advanced Paper Search agent powered by large language models that can autonomously perform a series of decisions (including invoking search tools, reading papers, and selecting relevant references) to provide comprehensive and accurate results for complex academic queries.\",\n \"Keywords\": [\n \"Paper Search Agent\",\n \"Large Language Models\",\n \"Reinforcement Learning\",\n \"Academic Queries\",\n \"Performance Benchmarking\"\n ],\n \"Data_and_Results\": \"PaSa outperforms existing baselines (such as Google, GPT-4, chatGPT) in tests using AutoScholarQuery (35k academic queries) and RealScholarQuery (real-world academic queries). For example, PaSa-7B exceeds Google with GPT-4o by 37.78% in recall@20 and 39.90% in recall@50.\",\n \"Technical_Details\": \"PaSa is optimized using reinforcement learning with the AutoScholarQuery synthetic dataset, demonstrating superior performance in multiple benchmarks.\",\n \"Classification\": [\n \"Artificial Intelligence (AI)\",\n \"Academic Search and Information Retrieval\",\n \"Natural Language Processing (NLP)\",\n \"Reinforcement Learning\"\n ]\n}\n```"
},
{
"content": "={{ $json.abstract }}"
}
]
},
"jsonOutput": true
},
"credentials": {
"openAiApi": {
"id": "LmLcxHwbzZNWxqY6",
"name": "Unnamed credential"
}
},
"typeVersion": 1.8
},
{
"id": "f491cd7f-598e-46fd-b80c-04cfa9766dfd",
"name": "存储摘要到 Notion",
"type": "n8n-nodes-base.notion",
"position": [
-300,
-300
],
"parameters": {
"options": {},
"resource": "databasePage",
"databaseId": {
"__rl": true,
"mode": "list",
"value": "17b67aba-1fcc-80ae-baa1-d88ffda7ae83",
"cachedResultUrl": "https://www.notion.so/17b67aba1fcc80aebaa1d88ffda7ae83",
"cachedResultName": "huggingface-abstract"
},
"propertiesUi": {
"propertyValues": [
{
"key": "URL|url",
"urlValue": "={{ 'https://huggingface.co'+$('Split Out').item.json.url }}"
},
{
"key": "title|title",
"title": "={{ $('Extract Hugging Face Paper Abstract').item.json.title }}"
},
{
"key": "abstract|rich_text",
"textContent": "={{ $('Extract Hugging Face Paper Abstract').item.json.abstract.substring(0,2000) }}"
},
{
"key": "scrap-date|date",
"date": "={{ $today.format('yyyy-MM-dd') }}",
"includeTime": false
},
{
"key": "Classification|rich_text",
"textContent": "={{ $json.message.content.Classification.join(',') }}"
},
{
"key": "Technical_Details|rich_text",
"textContent": "={{ $json.message.content.Technical_Details }}"
},
{
"key": "Data_and_Results|rich_text",
"textContent": "={{ $json.message.content.Data_and_Results }}"
},
{
"key": "keywords|rich_text",
"textContent": "={{ $json.message.content.Keywords.join(',') }}"
},
{
"key": "Core Introduction|rich_text",
"textContent": "={{ $json.message.content.Core_Introduction }}"
}
]
}
},
"credentials": {
"notionApi": {
"id": "I5KdUzwhWnphQ862",
"name": "notion"
}
},
"typeVersion": 2.2
},
{
"id": "d5816a1c-d1fa-4be2-8088-57fbf68e6b43",
"name": "提取 Hugging Face 论文摘要",
"type": "n8n-nodes-base.html",
"position": [
-840,
-300
],
"parameters": {
"options": {},
"operation": "extractHtmlContent",
"extractionValues": {
"values": [
{
"key": "abstract",
"cssSelector": ".text-gray-700"
},
{
"key": "title",
"cssSelector": ".text-2xl"
}
]
}
},
"typeVersion": 1.2
}
],
"active": true,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "4b0ec2a3-253d-46d5-a4d4-1d9ff21ba4a3",
"connections": {
"If": {
"main": [
[
{
"node": "Request Hugging Face Paper Detail",
"type": "main",
"index": 0
}
],
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Split Out": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Loop Over Items": {
"main": [
[],
[
{
"node": "Check Paper URL Existed",
"type": "main",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "Request Hugging Face Paper",
"type": "main",
"index": 0
}
]
]
},
"Store Abstract Notion": {
"main": [
[
{
"node": "Loop Over Items",
"type": "main",
"index": 0
}
]
]
},
"Check Paper URL Existed": {
"main": [
[
{
"node": "If",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Analysis Abstract": {
"main": [
[
{
"node": "Store Abstract Notion",
"type": "main",
"index": 0
}
]
]
},
"Extract Hugging Face Paper": {
"main": [
[
{
"node": "Split Out",
"type": "main",
"index": 0
}
]
]
},
"Request Hugging Face Paper": {
"main": [
[
{
"node": "Extract Hugging Face Paper",
"type": "main",
"index": 0
}
]
]
},
"Request Hugging Face Paper Detail": {
"main": [
[
{
"node": "Extract Hugging Face Paper Abstract",
"type": "main",
"index": 0
}
]
]
},
"Extract Hugging Face Paper Abstract": {
"main": [
[
{
"node": "OpenAI Analysis Abstract",
"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？
中级 - 人工智能
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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