Artikel basierend auf Fakten aus Wissensquellen mit Super RAG und GPT-5 erstellen
Experte
Dies ist ein AI RAG, Multimodal AI-Bereich Automatisierungsworkflow mit 19 Nodes. Hauptsächlich werden Set, SplitOut, Aggregate, FormTrigger, HttpRequest und andere Nodes verwendet. Erstellen Sie faktenbasierte Artikel aus Wissensquellen mit Super RAG und GPT-5
Voraussetzungen
- •Möglicherweise sind Ziel-API-Anmeldedaten erforderlich
- •OpenAI API Key
Verwendete Nodes (19)
Kategorie
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": "9a0f0715-0f7f-4779-8f3a-c35bcf2ca175",
"name": "Neuer Inhalt - Forschungsfragen generieren",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
-1008,
528
],
"parameters": {
"text": "=Content title: {{ $json.Title }}\n\nArticle guidelines: {{ $json.Guidelines }}\n\n",
"messages": {
"messageValues": [
{
"message": "=You will receive a content title and an angle. Return 5–8 non-overlapping questions in JSON array format that cover everything needed to write excellent content as it breaks down the topic into sub-questions.\n\nGuidelines: \n- Start with simple, short broad questions for example to define the terms (e.g., What is X?, Why is X important?, How to do X?). \n- Then move into more specific, advanced, or analytical questions. \n- Ensure questions together form a complete coverage of the topic. \n\n## Output format:\n\nYou'll return the questions in such a JSON ARRAY:\n\n[\n {\n \"question\": \"Lorem ipsum dolor sit amet, consectetur adipiscing elit?\"\n },\n {\n \"question\": \"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua?\"\n },\n {\n \"question\": \"Lorem ipsum dolor sit amet?\"\n },\n {\n \"question\": \"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua, ut enim ad minim veniam?\"\n },\n {\n \"question\": \"Lorem ipsum dolor sit amet, consectetur?\"\n }\n]"
}
]
},
"promptType": "define",
"hasOutputParser": true
},
"typeVersion": 1.5
},
{
"id": "97aa9da3-f03f-4ef5-8645-6ca9a941dfd4",
"name": "Fragen und Antworten formatieren",
"type": "n8n-nodes-base.set",
"position": [
320,
768
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "1e33a1f4-a1a2-4962-ac72-cc518d7ff043",
"name": "Question",
"type": "string",
"value": "={{ $('Loop Over Questions').item.json.question }}"
},
{
"id": "903bcf38-13dd-48fb-8eb3-83f7a232aa53",
"name": "Answer",
"type": "string",
"value": "={{ $json.answer.replace(/\\{\\[(\\d+)\\]\\((.*?)\\)\\}/g, '([source]($2))') }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "8ce76a1b-d79b-43e7-8b47-c61b6167b1af",
"name": "Neuer Inhalt - KI-Ausgabe generieren",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
144,
-48
],
"parameters": {
"text": "=Article title:\n\n{{ $('Prepare form values').first().json.Title }}\n\nArticle guidelines:\n\n{{ $('Prepare form values').first().json.Guidelines }}\n\n\nContent to leverage:\n\nThis Q&A research provides high-quality knowledge, insights, and sources for your content. Be sure to include source links in your output whenever a source was used.\n\n{{ JSON.stringify($json['questions and answers'], null, 2) }}\n",
"messages": {
"messageValues": [
{
"message": "=# Role\n\nYour role is to write an article based on the request in the user message.\n\n# What the user message contains\n\nThe user message includes the article title, any guidelines to follow, and comprehensive research material. This research is the sole basis for your article — do not invent information beyond it. When the research includes source links, integrate them smoothly as hyperlinks in the article.\n\n# How to write good articles\n\nYou excel at writing articles by making sure that they deliver value, are concise, seem like they are human-written, not using typical AI useless sentence formulations.\n\n# Your output format\n\nOutput only the full article.\n\n* Begin with a `# H1` title.\n* Use subheadings throughout the article."
}
]
},
"promptType": "define"
},
"typeVersion": 1.5
},
{
"id": "97939f7a-faf8-4b86-a566-ac55a1f3272a",
"name": "Neue Artikelform",
"type": "n8n-nodes-base.formTrigger",
"position": [
-1568,
528
],
"webhookId": "61cdfeab-f3ce-4b9a-925b-63f813c267f9",
"parameters": {
"options": {},
"formTitle": "New article",
"formFields": {
"values": [
{
"fieldLabel": "Article title",
"placeholder": "10 ways to do Influencer Marketing in 2025",
"requiredField": true
},
{
"fieldLabel": "Article guidelines",
"placeholder": "Promote xyz and write in British English...",
"requiredField": true
}
]
},
"formDescription": "Fill in this form to trigger the generation of a new article."
},
"typeVersion": 2.3
},
{
"id": "dda874a4-b51e-46f1-b99b-a181beaae73c",
"name": "Formularwerte vorbereiten",
"type": "n8n-nodes-base.set",
"position": [
-1312,
528
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "ec4734ed-654f-478a-ab90-91bfcee1e208",
"name": "Title",
"type": "string",
"value": "={{ $json['Article title'] }}"
},
{
"id": "c034402e-a7b9-4c91-aaed-f24a838c3d91",
"name": "Guidelines",
"type": "string",
"value": "={{ $json['Article guidelines'] }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "86265d5e-ad97-429c-af6b-3876b8d14a83",
"name": "Structured Output Parser",
"type": "@n8n/n8n-nodes-langchain.outputParserStructured",
"position": [
-880,
752
],
"parameters": {
"jsonSchemaExample": "[\n {\n \"question\": \"Lorem ipsum dolor sit amet, consectetur adipiscing elit?\"\n },\n {\n \"question\": \"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua?\"\n },\n {\n \"question\": \"Lorem ipsum dolor sit amet?\"\n },\n {\n \"question\": \"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua, ut enim ad minim veniam?\"\n },\n {\n \"question\": \"Lorem ipsum dolor sit amet, consectetur?\"\n }\n]"
},
"typeVersion": 1.2
},
{
"id": "41053ca5-776c-4f11-84ee-9799a44546f6",
"name": "GPT 5 mini",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
-1008,
752
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-5-mini",
"cachedResultName": "gpt-5-mini"
},
"options": {}
},
"typeVersion": 1.2
},
{
"id": "a41214eb-8650-43ab-9a29-26709c89e838",
"name": "Fragen aufteilen",
"type": "n8n-nodes-base.splitOut",
"position": [
-608,
528
],
"parameters": {
"options": {},
"fieldToSplitOut": "output"
},
"typeVersion": 1
},
{
"id": "fe8a86db-6972-4416-8223-ae7b9bc3c90f",
"name": "Fragen durchlaufen",
"type": "n8n-nodes-base.splitInBatches",
"position": [
-352,
512
],
"parameters": {
"options": {}
},
"typeVersion": 3
},
{
"id": "d6d46dbf-c20f-4c0d-a9f8-c3d3059d0678",
"name": "Super Assistant abfragen",
"type": "n8n-nodes-base.httpRequest",
"position": [
-32,
544
],
"parameters": {
"url": "https://api.super.work/v1/super",
"method": "POST",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "question",
"value": "={{ $json.question }}"
},
{
"name": "assistantId",
"value": "YOUR-ASSISTANT-ID"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "1e6c7b70-60e0-44f9-a418-82b806b8d9ae",
"name": "GPT 5 chat",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
224,
176
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-5-chat-latest",
"cachedResultName": "gpt-5-chat-latest"
},
"options": {}
},
"typeVersion": 1.2
},
{
"id": "8b34795b-bc61-4c27-88dd-8a942c50a44a",
"name": "Artikelergebnis",
"type": "n8n-nodes-base.set",
"position": [
560,
-48
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "d3b8c4bc-27d9-4d57-b8d6-3a40b84d7b7d",
"name": "Article",
"type": "string",
"value": "={{ $json.text }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "5afd58d4-99f9-48c2-9d34-3d353cbbfc6f",
"name": "Haftnotiz",
"type": "n8n-nodes-base.stickyNote",
"position": [
-96,
512
],
"parameters": {
"color": 7,
"width": 224,
"height": 320,
"content": "\n\n\n\n\n\n\n\n\n\n\n\r\n\n\n\n\n\n### Connect your super.com credentials & replace your assistant ID"
},
"typeVersion": 1
},
{
"id": "5429c604-cf0e-4635-b47e-7f436a5399c7",
"name": "Forschungsinhalte zusammenfassen",
"type": "n8n-nodes-base.aggregate",
"position": [
-112,
160
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData",
"destinationFieldName": "Content to leverage"
},
"typeVersion": 1
},
{
"id": "b86d6f11-dd1a-4b65-8342-6420b8ee4b61",
"name": "Haftnotiz1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1152,
-256
],
"parameters": {
"width": 832,
"height": 560,
"content": "# AI Article Writer Based on Your Knowledge Base\n\nThis isn't just a writer; it's an automated research and content team. It generates high-quality, reliable articles by grounding the entire process in *your own* knowledge base.\n\n## How it works\n1. **Decompose:** An AI planner breaks your article topic into a series of sub-questions.\n2. **Research:** It queries your **Super assistant** to answer each question using *your* connected documents (Notion, Drive, etc.).\n3. **Write:** A final, powerful AI writes the article based *only* on this verified research, including source links.\n\n## How to use\n1. **Set up in Super:** First, build your assistant in **Super** with your knowledge sources and get your **API Token** & **Assistant ID**.\n2. **Configure this workflow:**\n * Connect your **AI provider** to the LLM nodes.\n * In the **Query Super Assistant** node, add your **Assistant ID** and **API Token**.\n3. **Run:** Use the form to enter a title and guidelines, and let the workflow generate your article.\n\n\n*A template built by Guillaume Duvernay*"
},
"typeVersion": 1
},
{
"id": "615bc59d-5d05-4986-9bee-5a8ac089a390",
"name": "Haftnotiz2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-448,
384
],
"parameters": {
"color": 6,
"width": 976,
"height": 608,
"content": "## Answering each sub-question one by one with Super"
},
"typeVersion": 1
},
{
"id": "a256f168-dbac-4a99-9617-32641916fae2",
"name": "Haftnotiz3",
"type": "n8n-nodes-base.stickyNote",
"position": [
80,
-208
],
"parameters": {
"color": 5,
"width": 368,
"height": 512,
"content": "## AI step writing the final article based on the research and initial request"
},
"typeVersion": 1
},
{
"id": "b909335e-7b65-41e8-b716-65605a278d29",
"name": "Haftnotiz4",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1152,
384
],
"parameters": {
"color": 6,
"width": 480,
"height": 608,
"content": "## Breaking down the topic into sub-questions"
},
"typeVersion": 1
},
{
"id": "b0e02f1f-73b2-4834-8a0e-2251ac1f53e1",
"name": "Haftnotiz5",
"type": "n8n-nodes-base.stickyNote",
"position": [
-1648,
400
],
"parameters": {
"color": 4,
"width": 272,
"height": 304,
"content": "## Fill in this form to request a new article"
},
"typeVersion": 1
}
],
"connections": {
"1e6c7b70-60e0-44f9-a418-82b806b8d9ae": {
"ai_languageModel": [
[
{
"node": "8ce76a1b-d79b-43e7-8b47-c61b6167b1af",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"41053ca5-776c-4f11-84ee-9799a44546f6": {
"ai_languageModel": [
[
{
"node": "9a0f0715-0f7f-4779-8f3a-c35bcf2ca175",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"97939f7a-faf8-4b86-a566-ac55a1f3272a": {
"main": [
[
{
"node": "dda874a4-b51e-46f1-b99b-a181beaae73c",
"type": "main",
"index": 0
}
]
]
},
"fe8a86db-6972-4416-8223-ae7b9bc3c90f": {
"main": [
[
{
"node": "5429c604-cf0e-4635-b47e-7f436a5399c7",
"type": "main",
"index": 0
}
],
[
{
"node": "d6d46dbf-c20f-4c0d-a9f8-c3d3059d0678",
"type": "main",
"index": 0
}
]
]
},
"dda874a4-b51e-46f1-b99b-a181beaae73c": {
"main": [
[
{
"node": "9a0f0715-0f7f-4779-8f3a-c35bcf2ca175",
"type": "main",
"index": 0
}
]
]
},
"a41214eb-8650-43ab-9a29-26709c89e838": {
"main": [
[
{
"node": "fe8a86db-6972-4416-8223-ae7b9bc3c90f",
"type": "main",
"index": 0
}
]
]
},
"d6d46dbf-c20f-4c0d-a9f8-c3d3059d0678": {
"main": [
[
{
"node": "97aa9da3-f03f-4ef5-8645-6ca9a941dfd4",
"type": "main",
"index": 0
}
]
]
},
"86265d5e-ad97-429c-af6b-3876b8d14a83": {
"ai_outputParser": [
[
{
"node": "9a0f0715-0f7f-4779-8f3a-c35bcf2ca175",
"type": "ai_outputParser",
"index": 0
}
]
]
},
"5429c604-cf0e-4635-b47e-7f436a5399c7": {
"main": [
[
{
"node": "8ce76a1b-d79b-43e7-8b47-c61b6167b1af",
"type": "main",
"index": 0
}
]
]
},
"97aa9da3-f03f-4ef5-8645-6ca9a941dfd4": {
"main": [
[
{
"node": "fe8a86db-6972-4416-8223-ae7b9bc3c90f",
"type": "main",
"index": 0
}
]
]
},
"8ce76a1b-d79b-43e7-8b47-c61b6167b1af": {
"main": [
[
{
"node": "8b34795b-bc61-4c27-88dd-8a942c50a44a",
"type": "main",
"index": 0
}
]
]
},
"9a0f0715-0f7f-4779-8f3a-c35bcf2ca175": {
"main": [
[
{
"node": "a41214eb-8650-43ab-9a29-26709c89e838",
"type": "main",
"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?
Experte - KI RAG, Multimodales KI
Ist es kostenpflichtig?
Dieser Workflow ist völlig kostenlos. Beachten Sie jedoch, dass Drittanbieterdienste (wie OpenAI API), die im Workflow verwendet werden, möglicherweise kostenpflichtig sind.
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