About this recipe
A recipe for Hacker News Throwback Machine See What Was Hot On This Day, Every Year!
Recipe Template
{
"nodes": [
{
"id": "6ea4e702-1af8-407b-b653-964a519db1c2",
"name": "Basic LLM Chain",
"type": "@n8n\/n8n-nodes-langchain.chainLlm",
"position": [
1560,
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],
"parameters": {
"text": "=You are a highly skilled news categorizer, specializing in indentifying interesting stuff from Hacker News front-page headlines.\n\nYou are provided with JSON data containing a list of dates and their corresponding top headlines from the Hacker News front page. Each headline will also include a URL linking to the original article or discussion. Importantly, the dates provided will be the SAME DAY across MULTIPLE YEARS (e.g., January 1st, 2023, January 1st, 2022, January 1st, 2021, etc.). You need to indentify key headlines and also analyze how the tech landscape has evolved over the years, as reflected in the headlines for this specific day.\n\nYour task is to indentify top 10-15 headlines from across the years from the given json data and return in Markdown formatted bullet points categorizing into themes and adding markdown hyperlinks to the source URL with Prefixing Year before the headline. Follow the Output Foramt Mentioned.\n\n**Input Format:**\n\n```json\n[\n {\n \"headlines\": [\n \"Headline 1 Title [URL1]\",\n \"Headline 2 Title [URL2]\",\n \"Headline 3 Title [URL3]\",\n ...\n ]\n \"date\": \"YYYY-MM-DD\",\n },\n {\n \"headlines\": [\n \"Headline 1 Title [URL1]\",\n \"Headline 2 Title [URL2]\",\n ...\n ]\n \"date\": \"YYYY-MM-DD\",\n },\n ...\n]\n```\n\n**Output Format In Markdown**\n\n```\n# HN Lookback <FullMonthName-DD> | <start YYYY> to <end YYYY> \n\n## [Theme 1]\n- YYYY [Headline 1](URL1)\n- YYYY [Headline 2](URL2)\n...\n\n## [Theme 2]\n- YYYY [Headline 1](URL1)\n- YYYY [Headline 2](URL2)\n...\n\n... \n\n## <this is optional>\n<if any interesing ternds emerge mention them in oneline>\n```\n\n**Here is the Json data for Hackernews Headlines across the years**\n\n```\n{{ JSON.stringify($json.data) }}\n```",
"promptType": "define"
},
"typeVersion": 1.5
},
{
"id": "b5a97c2a-0c3b-4ebe-aec5-7bca6b55ad4c",
"name": "Google Gemini Chat Model",
"type": "@n8n\/n8n-nodes-langchain.lmChatGoogleGemini",
"position": [
1740,
-200
],
"parameters": {
"options": [],
"modelName": "models\/gemini-1.5-pro"
},
"credentials": {
"googlePalmApi": {
"id": "Hx1fn2jrUvojSKye",
"name": "Google Gemini(PaLM) Api account"
}
},
"typeVersion": 1
},
{
"id": "18cba750-aef5-451d-880f-2c12d8540d78",
"name": "Schedule Trigger",
"type": "n8n-nodes-base.scheduleTrigger",
"position": [
-380,
-360
],
"parameters": {
"rule": {
"interval": [
{
"triggerAtHour": 21
}
]
}
},
"typeVersion": 1.2
},
{
"id": "341da616-8670-4cd9-b47a-ee25e2ae9862",
"name": "CreateYearsList",
"type": "n8n-nodes-base.code",
"position": [
-200,
-360
],
"parameters": {
"jsCode": "for (const item of $input.all()) {\n const currentDateStr = item.json.timestamp.split('T')[0];\n const currentDate = new Date(currentDateStr);\n const currentYear = currentDate.getFullYear();\n const currentMonth = currentDate.getMonth(); \/\/ 0 for January, 1 for February, etc.\n const currentDay = currentDate.getDate();\n\n const datesToFetch = [];\n for (let year = currentYear; year >= 2007; year--) {\n let targetDate;\n if (year === 2007) {\n \/\/ Special handling for 2007 to start from Feb 19\n if (currentMonth > 1 || (currentMonth === 1 && currentDay >= 19))\n {\n targetDate = new Date(2007, 1, 19); \/\/ Feb 19, 2007\n } else {\n continue; \/\/ Skip 2007 if currentDate is before Feb 19\n }\n } else {\n targetDate = new Date(year, currentMonth, currentDay);\n }\n \n \/\/ Format the date as YYYY-MM-DD\n const formattedDate = targetDate.toISOString().split('T')[0];\n datesToFetch.push(formattedDate);\n }\n item.json.datesToFetch = datesToFetch;\n}\n\nreturn $input.all();"
},
"typeVersion": 2
},
{
"id": "42e24547-be24-4f29-8ce8-c0df7d47a6ff",
"name": "CleanUpYearList",
"type": "n8n-nodes-base.set",
"position": [
0,
-360
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "b269dc0d-21e1-4124-8f3a-2c7bfa4add5c",
"name": "datesToFetch",
"type": "array",
"value": "={{ $json.datesToFetch }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "6e51ad05-0f3d-4bfb-8c8d-5b71e7355344",
"name": "SplitOutYearList",
"type": "n8n-nodes-base.splitOut",
"position": [
200,
-360
],
"parameters": {
"options": [],
"fieldToSplitOut": "datesToFetch"
},
"typeVersion": 1
},
{
"id": "6f827071-718f-4e27-9f7a-cc50296f7bc4",
"name": "GetFrontPage",
"type": "n8n-nodes-base.httpRequest",
"position": [
420,
-360
],
"parameters": {
"url": "=https:\/\/news.ycombinator.com\/front",
"options": {
"batching": {
"batch": {
"batchSize": 1,
"batchInterval": 3000
}
}
},
"sendQuery": true,
"queryParameters": {
"parameters": [
{
"name": "day",
"value": "={{ $json.datesToFetch }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "7287e6b1-337f-4634-ac23-5ceaa87b0db3",
"name": "ExtractDetails",
"type": "n8n-nodes-base.html",
"position": [
640,
-360
],
"parameters": {
"options": [],
"operation": "extractHtmlContent",
"extractionValues": {
"values": [
{
"key": "=headlines",
"cssSelector": ".titleline",
"returnArray": true,
"skipSelectors": "span"
},
{
"key": "date",
"cssSelector": ".pagetop > font"
}
]
}
},
"typeVersion": 1.2
},
{
"id": "fceff31e-4dcd-4199-89c5-8eb75cd479bf",
"name": "GetHeadlines",
"type": "n8n-nodes-base.set",
"position": [
920,
-460
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "e1ce33e9-e4f8-4215-bbdb-156a955a0a97",
"name": "headlines",
"type": "array",
"value": "={{ $json.headlines }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "f7683614-7225-4f05-ba12-86b326fdb4a1",
"name": "GetDate",
"type": "n8n-nodes-base.set",
"position": [
920,
-280
],
"parameters": {
"options": [],
"assignments": {
"assignments": [
{
"id": "fc1d15f6-a999-4d6b-a7bc-3ffa9427679e",
"name": "date",
"type": "string",
"value": "={{ $json.date }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "7e09ce85-ece1-46a0-aa59-8e3da66413b2",
"name": "MergeHeadlinesDate",
"type": "n8n-nodes-base.merge",
"position": [
1180,
-360
],
"parameters": {
"mode": "combine",
"options": [],
"combineBy": "combineByPosition"
},
"typeVersion": 3
},
{
"id": "db3bf408-8179-4ca4-a5b4-8a390b68f994",
"name": "SingleJson",
"type": "n8n-nodes-base.aggregate",
"position": [
1380,
-360
],
"parameters": {
"options": [],
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1
},
{
"id": "2abbc0e9-ed1e-4ba0-9d2f-7c3cd314a0fe",
"name": "Telegram",
"type": "n8n-nodes-base.telegram",
"position": [
2020,
-360
],
"parameters": {
"text": "={{ $json.text }}",
"chatId": "@OnThisDayHN",
"additionalFields": {
"parse_mode": "Markdown",
"appendAttribution": false
}
},
"credentials": {
"telegramApi": {
"id": "6nIwfhIWcwJFTPTg",
"name": "OnThisDayHNBot"
}
},
"typeVersion": 1.2
}
],
"pinData": [],
"connections": {
"GetDate": {
"main": [
[
{
"node": "MergeHeadlinesDate",
"type": "main",
"index": 1
}
]
]
},
"SingleJson": {
"main": [
[
{
"node": "Basic LLM Chain",
"type": "main",
"index": 0
}
]
]
},
"GetFrontPage": {
"main": [
[
{
"node": "ExtractDetails",
"type": "main",
"index": 0
}
]
]
},
"GetHeadlines": {
"main": [
[
{
"node": "MergeHeadlinesDate",
"type": "main",
"index": 0
}
]
]
},
"ExtractDetails": {
"main": [
[
{
"node": "GetHeadlines",
"type": "main",
"index": 0
},
{
"node": "GetDate",
"type": "main",
"index": 0
}
]
]
},
"Basic LLM Chain": {
"main": [
[
{
"node": "Telegram",
"type": "main",
"index": 0
}
]
]
},
"CleanUpYearList": {
"main": [
[
{
"node": "SplitOutYearList",
"type": "main",
"index": 0
}
]
]
},
"CreateYearsList": {
"main": [
[
{
"node": "CleanUpYearList",
"type": "main",
"index": 0
}
]
]
},
"Schedule Trigger": {
"main": [
[
{
"node": "CreateYearsList",
"type": "main",
"index": 0
}
]
]
},
"SplitOutYearList": {
"main": [
[
{
"node": "GetFrontPage",
"type": "main",
"index": 0
}
]
]
},
"MergeHeadlinesDate": {
"main": [
[
{
"node": "SingleJson",
"type": "main",
"index": 0
}
]
]
},
"Google Gemini Chat Model": {
"ai_languageModel": [
[
{
"node": "Basic LLM Chain",
"type": "ai_languageModel",
"index": 0
}
]
]
}
}
}How to Use an n8n Template
1
Create a New Workflow
Click "New Workflow" in your n8n dashboard to get started.
2
Copy & Paste Template
First, copy this template:
Click here to copy the JSON
.
Then, in n8n, click the three dots (···) → "Import from file" and paste the JSON code.
3
Customize the Nodes
Go through each node in the workflow to update inputs like spreadsheet IDs, email addresses, or message content. Adjust field mappings to match your data.
4
Grant Access
For nodes that connect to external apps (like Google Sheets or Slack), you'll need to grant access. Connect your accounts using OAuth or an API key and save the credentials in the node.
5
Test It
Run the workflow by clicking "Execute Node" for each step or "Run Once" for the whole thing. Check the right sidebar to inspect data and debug any errors (they'll show up in red).
6
Activate Workflow
Once everything works as expected, click the "Activate" toggle to turn your workflow on. You're all set!