Hacker News Zeitmaschine - Beliebte Inhalte von heute vor einem Jahr ansehen

Fortgeschritten

Dies ist ein Other, AI-Bereich Automatisierungsworkflow mit 13 Nodes. Hauptsächlich werden Set, Code, Html, Merge, SplitOut und andere Nodes verwendet, kombiniert mit KI-Technologie für intelligente Automatisierung. Hacker News Zeitmaschine - Beliebte Inhalte von heute in früheren Jahren anzeigen

Voraussetzungen
  • Telegram Bot Token
  • Möglicherweise sind Ziel-API-Anmeldedaten erforderlich
  • Google Gemini API Key
Workflow-Vorschau
Visualisierung der Node-Verbindungen, mit Zoom und Pan
Workflow exportieren
Kopieren Sie die folgende JSON-Konfiguration und importieren Sie sie in n8n
{
  "nodes": [
    {
      "id": "6ea4e702-1af8-407b-b653-964a519db1c2",
      "name": "Basic LLM Kette",
      "type": "@n8n/n8n-nodes-langchain.chainLlm",
      "position": [
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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-Modell",
      "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": "Zeitplan-Trigger",
      "type": "n8n-nodes-base.scheduleTrigger",
      "position": [
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      ],
      "parameters": {
        "rule": {
          "interval": [
            {
              "triggerAtHour": 21
            }
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        }
      },
      "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": "ZusammenführenHeadlinesDate",
      "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": {
    "f7683614-7225-4f05-ba12-86b326fdb4a1": {
      "main": [
        [
          {
            "node": "MergeHeadlinesDate",
            "type": "main",
            "index": 1
          }
        ]
      ]
    },
    "db3bf408-8179-4ca4-a5b4-8a390b68f994": {
      "main": [
        [
          {
            "node": "Basic LLM Chain",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "6f827071-718f-4e27-9f7a-cc50296f7bc4": {
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    "fceff31e-4dcd-4199-89c5-8eb75cd479bf": {
      "main": [
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            "node": "MergeHeadlinesDate",
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    },
    "7287e6b1-337f-4634-ac23-5ceaa87b0db3": {
      "main": [
        [
          {
            "node": "fceff31e-4dcd-4199-89c5-8eb75cd479bf",
            "type": "main",
            "index": 0
          },
          {
            "node": "f7683614-7225-4f05-ba12-86b326fdb4a1",
            "type": "main",
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        ]
      ]
    },
    "Basic LLM Chain": {
      "main": [
        [
          {
            "node": "2abbc0e9-ed1e-4ba0-9d2f-7c3cd314a0fe",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "42e24547-be24-4f29-8ce8-c0df7d47a6ff": {
      "main": [
        [
          {
            "node": "6e51ad05-0f3d-4bfb-8c8d-5b71e7355344",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "341da616-8670-4cd9-b47a-ee25e2ae9862": {
      "main": [
        [
          {
            "node": "42e24547-be24-4f29-8ce8-c0df7d47a6ff",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Schedule Trigger": {
      "main": [
        [
          {
            "node": "341da616-8670-4cd9-b47a-ee25e2ae9862",
            "type": "main",
            "index": 0
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    },
    "6e51ad05-0f3d-4bfb-8c8d-5b71e7355344": {
      "main": [
        [
          {
            "node": "6f827071-718f-4e27-9f7a-cc50296f7bc4",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "MergeHeadlinesDate": {
      "main": [
        [
          {
            "node": "db3bf408-8179-4ca4-a5b4-8a390b68f994",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Google Gemini Chat Model": {
      "ai_languageModel": [
        [
          {
            "node": "Basic LLM Chain",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    }
  }
}
Häufig gestellte Fragen

Wie verwende ich diesen Workflow?

Kopieren Sie den obigen JSON-Code, erstellen Sie einen neuen Workflow in Ihrer n8n-Instanz und wählen Sie "Aus JSON importieren". Fügen Sie die Konfiguration ein und passen Sie die Anmeldedaten nach Bedarf an.

Für welche Szenarien ist dieser Workflow geeignet?

Fortgeschritten - Sonstiges, Künstliche Intelligenz

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Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.

Workflow-Informationen
Schwierigkeitsgrad
Fortgeschritten
Anzahl der Nodes13
Kategorie2
Node-Typen11
Schwierigkeitsbeschreibung

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