AutomationFlowsAI & RAG › Epic

Epic

Epic. Uses rssFeedRead, httpRequest, dataTable, lmChatOpenAi. Scheduled trigger; 10 nodes.

Cron / scheduled trigger★★★★☆ complexityAI-powered10 nodesRSS Feed ReadHTTP RequestData TableOpenAI ChatInformation Extractor
AI & RAG Trigger: Cron / scheduled Nodes: 10 Complexity: ★★★★☆ AI nodes: yes Added:

This workflow follows the Datatable → HTTP Request 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 →

Download .json
{
  "nodes": [
    {
      "parameters": {
        "rule": {
          "interval": [
            {
              "field": "hours",
              "triggerAtMinute": 3
            }
          ]
        }
      },
      "id": "ee53ecaf-abe3-460f-98bd-07d9c946314c",
      "name": "Cron Trigger",
      "type": "n8n-nodes-base.scheduleTrigger",
      "position": [
        -1136,
        608
      ],
      "typeVersion": 1.2
    },
    {
      "parameters": {
        "jsCode": "// return $input.all()\n\n// \u83b7\u53d6\u6240\u6709\u7f13\u5b58\u5217\u8868\nlet cacheList = $input.all();\n\nlet unReadRssList = $('RsshubGet').all()\n// \u6253\u5370\u9700\u8981\u5728\u6d4f\u89c8\u5668console\u67e5\u770b\nconsole.log('cacheList:', cacheList) \nconsole.log('unReadRssList:', unReadRssList)\n// return \u5fc5\u987b\u662f\u4e00\u4e2a\u5e26\u5bf9\u8c61\u7684json,\u4e0d\u80fd\u662fstring[]\nlet resultList = unReadRssList\n  .filter(item => {\n    console.log(\"item: \", item.json.title)\n    return !cacheList.some(cacheItem => cacheItem.json.title === item.json.title)\n  })\n// resultList.push({json: {\"title\": 'test2'}})\nreturn resultList\n"
      },
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        -448,
        608
      ],
      "id": "aead5a51-52b4-4c9d-975d-9563f41d94e3",
      "name": "FilterNew",
      "alwaysOutputData": true
    },
    {
      "parameters": {
        "url": "=https://rsshub.xxx.com/epicgames/freegames/en-US/US",
        "options": {
          "ignoreSSL": false
        }
      },
      "type": "n8n-nodes-base.rssFeedRead",
      "typeVersion": 1.1,
      "position": [
        -880,
        608
      ],
      "id": "ea73f8de-b877-4810-b9d6-c956d76b5528",
      "name": "RsshubGet",
      "onError": "continueRegularOutput"
    },
    {
      "parameters": {
        "jsCode": "console.log('AI output\uff1a', $input.all())\n// \u79fb\u9664\u5916\u5c42output\nlet result = $input.all().map(item => {\n  return item.json.output\n})\n\nreturn result"
      },
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        400,
        592
      ],
      "id": "563b3430-32fc-4d6a-9b63-399dcaf330d6",
      "name": "FormatAIOutput",
      "alwaysOutputData": true
    },
    {
      "parameters": {
        "jsCode": "// return $input.all().splice(0, 3).filter(item => Boolean(item.json.link))\nreturn $input.all().filter(item => Boolean(item.json.title))"
      },
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [
        -160,
        608
      ],
      "id": "66e53850-0eb1-4a83-9aad-ce0304c979aa",
      "name": "FilterNullObject",
      "alwaysOutputData": false
    },
    {
      "parameters": {
        "method": "POST",
        "url": "https://pusher.xxx.com/webhook/xxx",
        "sendBody": true,
        "bodyParameters": {
          "parameters": [
            {
              "name": "content",
              "value": "=\ud83c\udfc6  Epic \u559c\u52a0\u4e00\n\ud83d\udd79\ufe0f  {{ $json.title_en }}\n\ud83d\udcdd  {{ $json.description }}  \n\ud83c\udf10  {{ $json.link }}"
            }
          ]
        },
        "options": {}
      },
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4.3,
      "position": [
        688,
        672
      ],
      "id": "32a8770f-2f61-4323-8615-082504d23cf7",
      "name": "\u63a8\u9001\u5230TG"
    },
    {
      "parameters": {
        "operation": "get",
        "dataTableId": {
          "__rl": true,
          "value": "vmMVnyry917iahnF",
          "mode": "list",
          "cachedResultName": "epic",
          "cachedResultUrl": "/projects/67mC9JYeQ8KrO6ni/datatables/vmMVnyry917iahnF"
        },
        "filters": {
          "conditions": [
            {
              "keyName": "title",
              "keyValue": "={{ $json.title }}"
            }
          ]
        }
      },
      "type": "n8n-nodes-base.dataTable",
      "typeVersion": 1,
      "position": [
        -656,
        608
      ],
      "id": "24d8beff-b1d8-4df5-864f-758452e7e3a0",
      "name": "Get row(s)",
      "alwaysOutputData": true
    },
    {
      "parameters": {
        "dataTableId": {
          "__rl": true,
          "value": "vmMVnyry917iahnF",
          "mode": "list",
          "cachedResultName": "epic",
          "cachedResultUrl": "/projects/67mC9JYeQ8KrO6ni/datatables/vmMVnyry917iahnF"
        },
        "columns": {
          "mappingMode": "defineBelow",
          "value": {
            "title": "={{ $json.title_en }}"
          },
          "matchingColumns": [
            "repo_title"
          ],
          "schema": [
            {
              "id": "type",
              "displayName": "type",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "readOnly": false,
              "removed": true
            },
            {
              "id": "title",
              "displayName": "title",
              "required": false,
              "defaultMatch": false,
              "display": true,
              "type": "string",
              "readOnly": false,
              "removed": false
            }
          ],
          "attemptToConvertTypes": false,
          "convertFieldsToString": false
        },
        "options": {}
      },
      "type": "n8n-nodes-base.dataTable",
      "typeVersion": 1,
      "position": [
        672,
        464
      ],
      "id": "12e65a26-3cde-404d-8164-38ad8810a253",
      "name": "Insert row"
    },
    {
      "parameters": {
        "model": {
          "__rl": true,
          "value": "git-gpt-4o-mini",
          "mode": "list",
          "cachedResultName": "git-gpt-4o-mini"
        },
        "options": {
          "temperature": 0.5
        }
      },
      "type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
      "typeVersion": 1.2,
      "position": [
        112,
        704
      ],
      "id": "67b295c8-dd6b-4459-8de2-573c9f8dc040",
      "name": "AI Model",
      "notesInFlow": false,
      "credentials": {
        "openAiApi": {
          "name": "<your credential>"
        }
      }
    },
    {
      "parameters": {
        "text": "=title: {{ $json.title }} \ntitle_en: {{ $json.title }} \nauthor: {{ $json.author }}\nlink: {{ $json.link }}\ndesc: {{ $json.contentSnippet }}",
        "attributes": {
          "attributes": [
            {
              "name": "description",
              "description": "Chinese description",
              "required": true
            },
            {
              "name": "=link",
              "description": "=link",
              "required": true
            },
            {
              "name": "title",
              "description": "=title",
              "required": true
            },
            {
              "name": "title_en",
              "description": "title_en",
              "required": true
            },
            {
              "name": "deadline",
              "description": "deadline",
              "required": true
            }
          ]
        },
        "options": {
          "systemPromptTemplate": "\u60a8\u662f\u4e00\u4f4d\u6587\u672c\u4fe1\u606f\u63d0\u53d6\u4e13\u5bb6\u3002\u8bf7\u6839\u636e\u4ee5\u4e0b\u8981\u6c42\uff0c\u4ece\u6587\u672c\u4e2d\u63d0\u53d6\u548c\u603b\u7ed3\u6709\u7528\u7684\u4fe1\u606f\uff1a\n\n1. \u63d0\u53d6\u6587\u672c\u4e2d\u51fa\u73b0\u7684\u91cd\u8981\u5c5e\u6027\uff08\u5982\u9879\u76ee\u540d\u79f0\u3001\u4e3b\u8981\u5185\u5bb9\u3001\u6d89\u53ca\u7684\u6280\u672f\u6216\u6a21\u578b\u3001\u4f7f\u7528\u7684\u7f16\u7a0b\u8bed\u8a00\uff09\u3002\n2. \u5982\u679c\u6587\u672c\u4e3a\u975e\u4e2d\u6587\uff0c\u8bf7\u5148\u7ffb\u8bd1\u6210\u4e2d\u6587\u518d\u8fdb\u884c\u603b\u7ed3\u3002\n3. \u7528\u7b80\u660e\u7684\u4e2d\u6587\u81ea\u7136\u8bed\u8a00\uff0c\u5c06\u8fd9\u4e9b\u5173\u952e\u4fe1\u606f\u52a0\u4e0e\u81ea\u7136\u63cf\u8ff0\u3002\u5982\u679c\u67d0\u4e9b\u5c5e\u6027\u65e0\u6cd5\u5224\u65ad\u6216\u4e0d\u660e\u786e\uff0c\u53ef\u4ee5\u4fdd\u6301\u539f\u6587\u63cf\u8ff0\u6216\u76f4\u63a5\u8bf4\u660e\u3002\u5bf9\u4e8e\u67d0\u4e9btitle\uff0c\u4e0d\u9700\u8981\u7ffb\u8bd1\uff0c\u4f8b\u5982\u6e38\u620f\u540d\u79f0\u3002\n4. \u4e0d\u8981\u7528\u8fd9\u662f\uff0c\u8fd9\u4e2a\u7b49\u5f00\u5934\uff0c\u5c3d\u91cf\u81ea\u7136\u8bed\u8a00\u63cf\u8ff0\u3002\n"
        }
      },
      "type": "@n8n/n8n-nodes-langchain.informationExtractor",
      "typeVersion": 1,
      "position": [
        48,
        480
      ],
      "id": "ca1e13c1-f15d-48ec-8dda-5c97c89f9df3",
      "name": "AI-Analysis",
      "retryOnFail": true,
      "waitBetweenTries": 5000,
      "notesInFlow": false,
      "alwaysOutputData": true,
      "executeOnce": false,
      "maxTries": 5,
      "onError": "continueRegularOutput"
    }
  ],
  "connections": {
    "Cron Trigger": {
      "main": [
        [
          {
            "node": "RsshubGet",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "FilterNew": {
      "main": [
        [
          {
            "node": "FilterNullObject",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "RsshubGet": {
      "main": [
        [
          {
            "node": "Get row(s)",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "FormatAIOutput": {
      "main": [
        [
          {
            "node": "Insert row",
            "type": "main",
            "index": 0
          },
          {
            "node": "\u63a8\u9001\u5230TG",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "FilterNullObject": {
      "main": [
        [
          {
            "node": "AI-Analysis",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "Get row(s)": {
      "main": [
        [
          {
            "node": "FilterNew",
            "type": "main",
            "index": 0
          }
        ]
      ]
    },
    "AI Model": {
      "ai_languageModel": [
        [
          {
            "node": "AI-Analysis",
            "type": "ai_languageModel",
            "index": 0
          }
        ]
      ]
    },
    "AI-Analysis": {
      "main": [
        [
          {
            "node": "FormatAIOutput",
            "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.

Pro

For the full experience including quality scoring and batch install features for each workflow upgrade to Pro

About this workflow

Epic. Uses rssFeedRead, httpRequest, dataTable, lmChatOpenAi. Scheduled trigger; 10 nodes.

Source: https://gist.github.com/chaos-zhu/12bc9aa2acd582fb2fe51a97d04ec10a — original creator credit. Request a take-down →

More AI & RAG workflows → · Browse all categories →

Related workflows

Workflows that share integrations, category, or trigger type with this one. All free to copy and import.

AI & RAG

Deduplicate Scraping Ai Grants For Eligibility Using Ai. Uses splitOut, httpRequest, lmChatOpenAi, informationExtractor. Scheduled trigger; 24 nodes.

HTTP Request, OpenAI Chat, Information Extractor +2
AI & RAG

This n8n template scrapes a list of AI grants from grants.gov and qualifies them using AI; determining interest and eligibility for the business. It then sends an email alert of interesting items to t

HTTP Request, OpenAI Chat, Information Extractor +2
AI & RAG

2619. Uses httpRequest, lmChatOpenAi, informationExtractor, airtable. Scheduled trigger; 24 nodes.

HTTP Request, OpenAI Chat, Information Extractor +2
AI & RAG

This n8n workflow automates domain level keyword ranking analysis and enriches raw SEO metrics with AI-generated summaries. It combines structured keyword data from SE Ranking with natural-language in

OpenAI Chat, Information Extractor, HTTP Request +2
AI & RAG

Sign up for Decodo — get better pricing here

@Decodo/N8N Nodes Decodo, Information Extractor, OpenAI Chat +4