使用 Tavily 的职位发布
高级
这是一个Miscellaneous, AI Summarization领域的自动化工作流，包含 17 个节点。主要使用 Set, Code, Gmail, Aggregate, Agent 等节点。 基于 Tavily 的自动化职位搜索
前置要求
- •Google 账号和 Gmail API 凭证
- •OpenAI API Key
使用的节点 (17)
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": "sre2RfUnMtFx3bXB",
"meta": {
"instanceId": "2ca4984385c3b4ae87442f36287f909e6c3da21289fc19cfc9b0d35c9fbde67e",
"templateCredsSetupCompleted": true
},
"name": "使用 Tavily 的职位发布",
"tags": [],
"nodes": [
{
"id": "374469c4-e958-4be3-977d-b0227a86caa5",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
280,
0
],
"parameters": {
"text": "You are an autonomous research agent tasked with monitoring job postings with Tavily API tool.\nYou will interact with the workflow in three stages:\n",
"options": {
"systemMessage": "You are an information extraction and formatting specialist.\n\nYou have received job postings retrieved via the Tavily API tool. Your job is to:\n\nCount how many individual job postings are included in the input. Each posting is a separate object with its own title, URL, company, location, description, and other metadata.\n\nThen, for each job posting, extract and format:\n\nJob Title\n\nURL\n\nPosting date (use ISO format: YYYY-MM-DD, if available)\n\nA 2–3 sentence summary of the job description\n\n1–2 key requirements or highlights\n\nCompany name\n\nCompany description (if provided)\n\nCompany website (if available)\n\nLocation (if provided)\n\nDo not include any hallucinated or assumed data. Only format what's explicitly in the input.\n\nFormat each job posting like this:\n\nJob Posting <number>\nJob Title: <Job Title>\nURL: <URL>\nPosting date: <YYYY-MM-DD>\nJob Description: <Brief description in 2–3 sentences>\nKey Requirements:\n<Point 1>\n<Point 2>\nCompany: <Company Name>\nCompany Description: <Short description>\nCompany Website: <URL>\nLocation: <Location>\n--- END JOB POSTING ---\n\nOutput only structured job postings in this format.\n\nYou must process all available job postings in the input. Do not stop early, do not skip entries, and do not truncate the output.\n\nUse only the input below. Do not perform any web searches or add external information.\n"
},
"promptType": "define"
},
"typeVersion": 2
},
{
"id": "6b53c752-134e-4835-a23a-5426f84cd3fa",
"name": "OpenAI 聊天模型",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
220,
220
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4.1-mini"
},
"options": {
"responseFormat": "text"
}
},
"credentials": {
"openAiApi": {
"id": "qlYYPSkolNpxulIN",
"name": "OpenAi account 5"
}
},
"typeVersion": 1.2
},
{
"id": "5adcd1ef-64f4-4734-9023-60bbd0d8aede",
"name": "在 Tavily 中搜索",
"type": "@tavily/n8n-nodes-tavily.tavilyTool",
"position": [
520,
220
],
"parameters": {
"query": "Roles posted this week for Software Engineering",
"options": {
"time_range": "week",
"max_results": 15,
"search_depth": "advanced",
"include_domains": [
"indeed.com",
"glassdoor.com",
"linkedin.com"
],
"include_raw_content": true
}
},
"credentials": {
"tavilyApi": {
"id": "o9UztDdPrsUey15i",
"name": "Tavily account 4"
}
},
"typeVersion": 1
},
{
"id": "b34a8697-2b7f-4263-b2a9-7234e65c6eb4",
"name": "发送消息",
"type": "n8n-nodes-base.gmail",
"position": [
1720,
0
],
"webhookId": "d3d1135b-2633-4826-b54c-7311445b94e6",
"parameters": {
"sendTo": "may@tavily.com",
"message": "={{ \n $json.data.map(post => {\n return `Job Posting ${post.posting_number} - ${post.job_title}\n\n🔗 URL: ${post.url}\n\n🗓️ Posting Date: ${post.posting_date}\n\n📝 Job Description:\n${post.job_description}\n\n📌 Requirements:\n${post.requirements && post.requirements.length > 0 \n ? post.requirements.map((point, i) => `${i + 1}. ${point}`).join('\\n') \n : 'No requirements available.'}\n\n🏢 Company Name: ${post.company_name}\n\n📝 Company Description: ${post.company_description}\n\n🔗 Company Website: ${post.company_website}\n\n📍 Location: ${post.location}\n---`;\n }).join('\\n\\n')\n}}\n",
"options": {},
"subject": "New Jobs for this week!",
"emailType": "text"
},
"credentials": {
"gmailOAuth2": {
"id": "tJbWRxNBB3mNW43v",
"name": "Gmail account 3"
}
},
"typeVersion": 2.1
},
{
"id": "e9b4dfe7-1a60-44e9-a445-f991352b5f9f",
"name": "编辑字段",
"type": "n8n-nodes-base.set",
"position": [
680,
0
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "97eac08d-b72e-442b-a537-b092434789e7",
"name": "Response",
"type": "string",
"value": "={{ $json.output }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "f2543a75-2680-4cad-a475-fcfdd5d7cb73",
"name": "计划触发器",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
0,
0
],
"parameters": {
"rule": {
"interval": [
{
"field": "weeks",
"triggerAtHour": 8
}
]
}
},
"typeVersion": 1.2
},
{
"id": "cfbddace-b185-47b0-b7d4-85f3961e1d36",
"name": "简单记忆",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
380,
220
],
"parameters": {
"sessionKey": "1234",
"sessionIdType": "customKey"
},
"typeVersion": 1.3
},
{
"id": "2173e130-cb1b-409b-a8d6-05a16b7864f0",
"name": "向模型发送消息",
"type": "@n8n/n8n-nodes-langchain.openAi",
"position": [
920,
0
],
"parameters": {
"modelId": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini",
"cachedResultName": "GPT-4O-MINI"
},
"options": {},
"messages": {
"values": [
{
"content": "=You will receive a block of content containing multiple job postings from the last week. Each post includes a job title, URL, posting date, job description, requirements, company name, company description, compamy website, and location.\n\nYour only task is to structure each job posting into its own block using the exact content provided — do not rewrite, paraphrase, or shorten anything except for the following exception:\n\nIf company, posting date, company description, or company Website are missing or not specified, you may not use your own knowledge to fill in these four fields only.\n\nUse the following exact format for each mention:\n\nJob Posting <number>\n1. Job Title: <Exact title>\n2. URL: <Exact URL>\n3. Posting Date: <Exact posting date or \"Not specified\">\n4. Job Description: <Exact description as written>\n5. Requirements:\n<Point 1>\n<Point 2>\n(and so on…)\n6. Company Name: <company name>\n7. Company Description: <Company Description>\n8. Company Website: <Company website exactly as written or use your knowledge if not specified>\n9. Location: <location>\n\n10. End each job posting with the line:\n--- END JOB POSTING ---\n\nOnly structure the content — do not rewrite or shorten any summaries or key points. If a field is not present and not listed as allowed for lookup, write \"Not specified\".\n\nHere is the content to format:\n{{ $json.Response }}"
}
]
}
},
"credentials": {
"openAiApi": {
"id": "qlYYPSkolNpxulIN",
"name": "OpenAi account 5"
}
},
"typeVersion": 1.8
},
{
"id": "aa6fd23f-7a66-490d-94b0-5c80e96367c1",
"name": "代码",
"type": "n8n-nodes-base.code",
"position": [
1280,
0
],
"parameters": {
"jsCode": "// Collect all inputs\nconst allInputs = $input.all();\n\n// Flatten all job contents into a single string\nconst raw = allInputs\n .map(item => item.json.message?.content || \"\")\n .join(\"\\n\\n\");\n\n// If nothing found, stop\nif (!raw.trim()) {\n return [];\n}\n\n// Split the raw content by job postings\nconst postings = raw\n .split('--- END JOB POSTING ---')\n .filter(p => p.trim() !== '');\n\nconst structuredPostings = postings.map((post, index) => {\n const jobTitle = post.match(/Job Title:\\s*(.+)/)?.[1]?.trim() || \"Not specified\";\n const url = post.match(/URL:\\s*(.+)/)?.[1]?.trim() || \"Not specified\";\n const postingDate = post.match(/Posted|Posting Date:\\s*(.+)/)?.[1]?.trim() || \"Not specified\";\n\n const descriptionMatch = post.match(/Job Description:\\s*([\\s\\S]*?)(?:\\nRequirements:|\\n6\\.)/) ||\n post.match(/Job Description:\\s*([\\s\\S]*)/);\n const jobDescription = descriptionMatch?.[1]?.trim() || \"Not specified\";\n\n const requirementsMatch = post.match(/Requirements:\\s*([\\s\\S]*?)(?:\\n6\\.|$)/);\n const requirements = requirementsMatch\n ? requirementsMatch[1]\n .split('\\n')\n .map(r => r.replace(/^-?\\s*/, '').trim())\n .filter(Boolean)\n : [];\n\n const companyName = post.match(/Company Name:\\s*(.+)/)?.[1]?.trim() || \"Not specified\";\n const companyDescription = post.match(/Company Description:\\s*(.+)/)?.[1]?.trim() || \"Not specified\";\n const companyWebsite = post.match(/Company Website:\\s*(.+)/)?.[1]?.trim() || \"Not specified\";\n const location = post.match(/Location:\\s*(.+)/)?.[1]?.trim() || \"Not specified\";\n\n return {\n json: {\n posting_number: index + 1,\n job_title: jobTitle,\n url,\n posting_date: postingDate,\n job_description: jobDescription,\n requirements,\n company_name: companyName,\n company_description: companyDescription,\n company_website: companyWebsite,\n location\n }\n };\n});\n\nreturn structuredPostings;\n"
},
"typeVersion": 2
},
{
"id": "d19fcd6c-2d59-4023-883a-c9502790eb8f",
"name": "聚合",
"type": "n8n-nodes-base.aggregate",
"position": [
1500,
0
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1
},
{
"id": "d639bcdf-af55-40c5-a536-e37ea241e597",
"name": "便签",
"type": "n8n-nodes-base.stickyNote",
"position": [
-40,
-120
],
"parameters": {
"color": 3,
"width": 200,
"height": 100,
"content": "按您选择的时间间隔（每日或每周）自动运行此工作流"
},
"typeVersion": 1
},
{
"id": "d045adcb-fb7d-4605-9701-ffa1e0360c05",
"name": "便签1",
"type": "n8n-nodes-base.stickyNote",
"position": [
280,
-220
],
"parameters": {
"color": 5,
"height": 200,
"content": "根据您的查询执行职位发布的网络搜索。您可以通过更改查询来自定义特定职位或关键词的搜索，并将结果限制在特定时间范围内。通过可信域和可选的搜索深度过滤结果"
},
"typeVersion": 1
},
{
"id": "b921a830-831e-4902-83a7-bf7114871286",
"name": "便签2",
"type": "n8n-nodes-base.stickyNote",
"position": [
660,
-140
],
"parameters": {
"width": 150,
"height": 120,
"content": "将所有搜索结果收集到一个结构化数据包中进行处理"
},
"typeVersion": 1
},
{
"id": "79361797-a2fa-4f76-aae7-1b43256ba2d2",
"name": "便签3",
"type": "n8n-nodes-base.stickyNote",
"position": [
920,
-140
],
"parameters": {
"color": 3,
"width": 260,
"height": 120,
"content": "将原始职位发布重新构建为清晰易读的格式。提取职位标题、描述、要求、公司信息和地点"
},
"typeVersion": 1
},
{
"id": "04b65e37-b208-4579-b83d-8e17ad6a02dc",
"name": "便签4",
"type": "n8n-nodes-base.stickyNote",
"position": [
1240,
-140
],
"parameters": {
"color": 5,
"width": 180,
"height": 120,
"content": "将多个职位发布拆分为独立对象并提取每个字段以便于聚合"
},
"typeVersion": 1
},
{
"id": "8ce0186f-cc76-4a90-be4a-11c8e8c1f729",
"name": "便签5",
"type": "n8n-nodes-base.stickyNote",
"position": [
1480,
-140
],
"parameters": {
"width": 150,
"height": 120,
"content": "将所有处理过的发布合并到一个数组中，以便在单封邮件中发送"
},
"typeVersion": 1
},
{
"id": "376937ef-599e-4700-a409-0e82df315b5e",
"name": "便签6",
"type": "n8n-nodes-base.stickyNote",
"position": [
1700,
-140
],
"parameters": {
"color": 3,
"width": 160,
"height": 120,
"content": "发送一封整合邮件，包含所有格式化的职位发布，便于阅读"
},
"typeVersion": 1
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "dc38f1d1-760c-47dc-a7f1-ae3fa061618f",
"connections": {
"Code": {
"main": [
[
{
"node": "Aggregate",
"type": "main",
"index": 0
}
]
]
},
"AI Agent": {
"main": [
[
{
"node": "Edit Fields",
"type": "main",
"index": 0
}
]
]
},
"Aggregate": {
"main": [
[
{
"node": "Send a message",
"type": "main",
"index": 0
}
]
]
},
"Edit Fields": {
"main": [
[
{
"node": "Message a model",
"type": "main",
"index": 0
}
]
]
},
"Simple Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Message a model": {
"main": [
[
{
"node": "Code",
"type": "main",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Search in Tavily": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"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 - 杂项, 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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工作流信息
难度等级
高级
节点数量17
分类2
节点类型11
作者
May Ramati Kroitero
@may-kroiteroI am an AI Engineer at Tavily, where I focus on building AI solutions that integrate real-time web data to power intelligent applications.
外部链接
在 n8n.io 查看 →
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