Public Form Auto Triage
Workflow automatisé avec 12 nodes incluant : stickyNote, webhook, @n8n/langchain.textSplitterCharacterTextSplitter, @n8...
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📋 Auto-tag Blog Posts
Workflow automatisé avec 12 nodes incluant : stickyNote, webhook, @n8n/langchain.textSplitterCharacterTextSplitter, @n8n/langchain.embeddingsOpenAi, @n8n/langchain.vectorStoreSupabase
🔧 Composition du workflow
Nombre total de nodes : 12
🚀 Déclencheurs
- Webhook Trigger
⚡ Actions
- Sticky Note
- Text Splitter
- Embeddings
- Supabase Insert
- Supabase Query
- Vector Tool
- Window Memory
- Chat Model
- RAG Agent
- Append Sheet
- Slack Alert
🔗 Services intégrés
- Webhook
- Google Sheets
- Slack
🔄 Flux de données
Le workflow contient 11 connexion(s) entre les nodes, définissant le flux de données et l'ordre d'exécution.
💡 Utilisation
- Importez ce workflow dans votre instance n8n
- Configurez les credentials nécessaires pour chaque service
- Adaptez les paramètres selon vos besoins
- Testez le workflow avant de l'activer
📝 Note : Cette documentation a été générée automatiquement. Pour une analyse plus détaillée, configurez l'API OpenAI dans les paramètres système.
Structure JSON
Voir le code JSON complet
{
"name": "Auto-tag Blog Posts",
"nodes": [
{
"parameters": {
"content": "Placeholder for Auto-tag Blog Posts",
"height": 530,
"width": 1100,
"color": 5
},
"id": "84e22aae-0a0b-4bc9-94d9-aec2d9a07826",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
-480,
-240
]
},
{
"parameters": {
"httpMethod": "POST",
"path": "auto-tag-blog-posts"
},
"id": "e83f725c-c083-4c9d-9623-d9c092bbad2a",
"name": "Webhook Trigger",
"type": "n8n-nodes-base.webhook",
"typeVersion": 1,
"position": [
-300,
0
]
},
{
"parameters": {
"chunkSize": 400,
"chunkOverlap": 40
},
"id": "95ca42a5-e984-4245-b770-ef64b6495ec9",
"name": "Text Splitter",
"type": "@n8n\/n8n-nodes-langchain.textSplitterCharacterTextSplitter",
"typeVersion": 1,
"position": [
-130,
0
]
},
{
"parameters": {
"model": "text-embedding-3-small",
"options": []
},
"id": "e515e8bb-c532-4428-a593-29f5d71ba000",
"name": "Embeddings",
"type": "@n8n\/n8n-nodes-langchain.embeddingsOpenAi",
"typeVersion": 1,
"position": [
70,
0
],
"credentials": {
"openAiApi": {
"id": "OPENAI_API",
"name": "OpenAI"
}
}
},
{
"parameters": {
"mode": "insert",
"options": [],
"indexName": "auto-tag_blog_posts"
},
"id": "1aa98ca1-c389-4a1a-8f0c-58fcc64e08b4",
"name": "Supabase Insert",
"type": "@n8n\/n8n-nodes-langchain.vectorStoreSupabase",
"typeVersion": 1,
"position": [
270,
0
],
"credentials": {
"supabaseApi": {
"id": "SUPABASE_API",
"name": "Supabase account"
}
}
},
{
"parameters": {
"indexName": "auto-tag_blog_posts"
},
"id": "53510366-3cdd-40ec-a22b-d344bbbe434f",
"name": "Supabase Query",
"type": "@n8n\/n8n-nodes-langchain.vectorStoreSupabase",
"typeVersion": 1,
"position": [
270,
-180
],
"credentials": {
"supabaseApi": {
"id": "SUPABASE_API",
"name": "Supabase account"
}
}
},
{
"parameters": {
"name": "Supabase",
"description": "Vector context"
},
"id": "1693f5ae-6022-4fea-8e94-ebd59d4cbd31",
"name": "Vector Tool",
"type": "@n8n\/n8n-nodes-langchain.toolVectorStore",
"typeVersion": 1,
"position": [
450,
-180
]
},
{
"parameters": [],
"id": "fff55186-78c9-4196-829c-0416c8c7d547",
"name": "Window Memory",
"type": "@n8n\/n8n-nodes-langchain.memoryBufferWindow",
"typeVersion": 1.3,
"position": [
450,
-40
]
},
{
"parameters": {
"options": []
},
"id": "ddbd622f-6ec7-499d-a48d-613db67e5f2b",
"name": "Chat Model",
"type": "@n8n\/n8n-nodes-langchain.lmChatAnthropic",
"typeVersion": 1,
"position": [
450,
-340
],
"credentials": {
"anthropicApi": {
"id": "ANTHROPIC_API",
"name": "Anthropic"
}
}
},
{
"parameters": {
"promptType": "define",
"text": "Handle data",
"options": {
"systemMessage": "You are an assistant for Auto-tag Blog Posts"
}
},
"id": "b12856e2-bed9-41ff-bdbd-4b4a2fd98aa2",
"name": "RAG Agent",
"type": "@n8n\/n8n-nodes-langchain.agent",
"typeVersion": 1,
"position": [
720,
-40
]
},
{
"parameters": {
"operation": "append",
"documentId": {
"__rl": true,
"value": "SHEET_ID",
"mode": "list",
"cachedResultName": "Auto-tag Blog Posts"
},
"sheetName": {
"__rl": true,
"value": "Log",
"mode": "list",
"cachedResultName": "Log"
},
"columns": {
"mappingMode": "defineBelow",
"value": "Status",
"schema": []
}
},
"id": "a8f14a3c-3865-4097-b1ee-0265ac6ffa47",
"name": "Append Sheet",
"type": "n8n-nodes-base.googleSheets",
"typeVersion": 4,
"position": [
930,
-40
],
"credentials": {
"googleSheetsOAuth2Api": {
"id": "SHEETS_API",
"name": "Google Sheets account"
}
}
},
{
"parameters": {
"channel": "#alerts",
"text": "Auto-tag Blog Posts error: {$json.error.message}"
},
"id": "54b60e92-3672-4042-94c7-df1b6d28c221",
"name": "Slack Alert",
"type": "n8n-nodes-base.slack",
"typeVersion": 1,
"position": [
930,
120
],
"credentials": {
"slackApi": {
"id": "SLACK_API",
"name": "Slack"
}
}
}
],
"connections": {
"Webhook Trigger": {
"main": [
[
{
"node": "Text Splitter",
"type": "main",
"index": 0
},
{
"node": "Window Memory",
"type": "main",
"index": 0
}
]
]
},
"Text Splitter": {
"main": [
[
{
"node": "Embeddings",
"type": "main",
"index": 0
}
]
],
"ai_textSplitter": [
[
{
"node": "Supabase Insert",
"type": "ai_textSplitter",
"index": 0
}
]
]
},
"Embeddings": {
"ai_embedding": [
[
{
"node": "Supabase Insert",
"type": "ai_embedding",
"index": 0
},
{
"node": "Supabase Query",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Supabase Insert": {
"ai_document": [
[]
]
},
"Supabase Query": {
"ai_vectorStore": [
[
{
"node": "Vector Tool",
"type": "ai_vectorStore",
"index": 0
}
]
]
},
"Vector Tool": {
"ai_tool": [
[
{
"node": "RAG Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Window Memory": {
"ai_memory": [
[
{
"node": "RAG Agent",
"type": "ai_memory",
"index": 0
}
]
]
},
"Chat Model": {
"ai_languageModel": [
[
{
"node": "RAG Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"RAG Agent": {
"main": [
[
{
"node": "Append Sheet",
"type": "main",
"index": 0
}
]
],
"onError": [
[
{
"node": "Slack Alert",
"type": "main",
"index": 0
}
]
]
}
},
"settings": {
"executionOrder": "v1"
},
"triggerCount": 1
}
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