Comprehensive n8n Creator Stats Automation Workflow
Automate the reporting of top n8n creators and workflows with this powerful workflow. By aggregating data from GitHub, g...
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📋 Optimisez votre base de connaissances avec l'IA et Milvus
💡 Description
Ce workflow n8n vous permet de scrapper automatiquement les derniers essais de Paul Graham, d'extraire le contenu textuel et de le charger dans une base de données vectorielle Milvus. Grâce à l'intégration d'OpenAI, les textes sont enrichis par des embeddings puissants qui facilitent leur recherche et analyse. Utilisez cet outil pour booster la gestion de votre base de connaissances avec des capacités avancées d'intelligence artificielle, tout en économisant un temps précieux grâce à l'automatisation.
📈 Impact & ROI: Réduisez le temps passé sur la collecte et l'organisation des informations tout en augmentant la précision et l'accessibilité des données grâce à l'intelligence artificielle.
🚀 Fonctionnalités Clés
- ✅ Automatisation complète du scraping d'essais - gagnez du temps
- ✅ Intégration avec Milvus pour un stockage optimisé des données
- ✅ Enrichissement des données avec OpenAI - améliorez la précision
- ✅ Utilisation d'agents IA pour interagir efficacement avec les données
📊 Architecture Technique
21
Nodes
Nodes
14
Connexions
Connexions
3
Services
Services
🔌 Services Intégrés
n8n-nodes-base.httpRequest@n8n/n8n-nodes-langchain.vectorStoreMilvus@n8n/n8n-nodes-langchain.embeddingsOpenAi
🔧 Composition du Workflow
| Node | Type | Description |
|---|---|---|
| When clicking "Execute Workflow" | manualTrigger | Traitement des données |
| Fetch Essay List | httpRequest | Requête HTTP vers une API externe |
| Extract essay names | html | Traitement des données |
| Split out into items | splitOut | Division des données en plusieurs branches |
| Fetch essay texts | httpRequest | Requête HTTP vers une API externe |
| Limit to first 3 | limit | Traitement des données |
| Extract Text Only | html | Traitement des données |
| Sticky Note3 | stickyNote | Traitement des données |
| Sticky Note5 | stickyNote | Traitement des données |
| Recursive Character Text Splitter1 | @n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter | Division des données en plusieurs branches |
| Milvus Vector Store | @n8n/n8n-nodes-langchain.vectorStoreMilvus | Traitement des données |
| AI Agent | @n8n/n8n-nodes-langchain.agent | Traitement des données |
| When chat message received | @n8n/n8n-nodes-langchain.chatTrigger | Traitement des données |
| Sticky Note | stickyNote | Traitement des données |
| Default Data Loader | @n8n/n8n-nodes-langchain.documentDefaultDataLoader | Traitement des données |
| Milvus Vector Store as tool | @n8n/n8n-nodes-langchain.vectorStoreMilvus | Traitement des données |
| Sticky Note1 | stickyNote | Traitement des données |
| Embeddings OpenAI | @n8n/n8n-nodes-langchain.embeddingsOpenAi | Traitement des données |
| OpenAI Chat Model | @n8n/n8n-nodes-langchain.lmChatOpenAi | Traitement des données |
| Embeddings OpenAI1 | @n8n/n8n-nodes-langchain.embeddingsOpenAi | Traitement des données |
| Sticky Note2 | stickyNote | Traitement des données |
📖 Guide d'Implémentation
- Import du workflow: Téléchargez le fichier JSON et importez-le dans votre instance n8n
- Configuration des credentials: Configurez les accès pour chaque service utilisé
- Personnalisation: Adaptez les paramètres selon vos besoins spécifiques
- Test: Exécutez le workflow en mode test pour vérifier le bon fonctionnement
- Activation: Activez le workflow pour une exécution automatique
🏷️ Tags
Structure JSON
Voir le code JSON complet
{
"id": "A5R7XYSzrCJKlw9k",
"meta": {
"instanceId": "2c4c1e23e7b067270c08aab616bada21d0c384d16f212b23cf1143c6baa09219",
"templateCredsSetupCompleted": true
},
"name": "Agent Milvus tool",
"tags": [
{
"id": "msnDWKHQmwMDxWQH",
"name": "Milvus",
"createdAt": "2025-04-16T12:48:14.539Z",
"updatedAt": "2025-04-16T12:48:14.539Z"
},
{
"id": "tnCpo8hq8uKrdASK",
"name": "AI",
"createdAt": "2025-04-16T12:47:57.976Z",
"updatedAt": "2025-04-16T12:47:57.976Z"
}
],
"nodes": [
{
"id": "cfe6264a-2be1-4d1e-974b-ee05ca8ae9ab",
"name": "When clicking \"Execute Workflow\"",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-280,
-40
],
"parameters": [],
"typeVersion": 1
},
{
"id": "c0665cc9-2bce-48db-a3bc-15baac68e569",
"name": "Fetch Essay List",
"type": "n8n-nodes-base.httpRequest",
"position": [
-20,
-40
],
"parameters": {
"url": "http:\/\/www.paulgraham.com\/articles.html",
"options": []
},
"typeVersion": 4.2
},
{
"id": "00bcdc0b-eb6d-41eb-ac0d-a6710d6232e4",
"name": "Extract essay names",
"type": "n8n-nodes-base.html",
"position": [
180,
-40
],
"parameters": {
"options": [],
"operation": "extractHtmlContent",
"extractionValues": {
"values": [
{
"key": "essay",
"attribute": "href",
"cssSelector": "table table a",
"returnArray": true,
"returnValue": "attribute"
}
]
}
},
"typeVersion": 1.2
},
{
"id": "523c319e-d1c7-4214-a725-dc557f6471a2",
"name": "Split out into items",
"type": "n8n-nodes-base.splitOut",
"position": [
380,
-40
],
"parameters": {
"options": [],
"fieldToSplitOut": "essay"
},
"typeVersion": 1
},
{
"id": "be155368-99f5-43b3-ba6c-50cccf2b72d2",
"name": "Fetch essay texts",
"type": "n8n-nodes-base.httpRequest",
"position": [
780,
-40
],
"parameters": {
"url": "=http:\/\/www.paulgraham.com\/{{ $json.essay }}",
"options": []
},
"typeVersion": 4.2
},
{
"id": "92af113c-dd71-4ddd-b50a-f5932392ed82",
"name": "Limit to first 3",
"type": "n8n-nodes-base.limit",
"position": [
580,
-40
],
"parameters": {
"maxItems": 3
},
"typeVersion": 1
},
{
"id": "1a1893c4-e8b2-454a-b49f-a0b0f3c01aca",
"name": "Extract Text Only",
"type": "n8n-nodes-base.html",
"position": [
1100,
-40
],
"parameters": {
"options": [],
"operation": "extractHtmlContent",
"extractionValues": {
"values": [
{
"key": "data",
"cssSelector": "body",
"skipSelectors": "img,nav"
}
]
}
},
"typeVersion": 1.2
},
{
"id": "d14ae606-f002-4fde-a896-bf1c7fa675b2",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-100,
-160
],
"parameters": {
"width": 1071.752021563343,
"height": 285.66037735849045,
"content": "## Scrape latest Paul Graham essays"
},
"typeVersion": 1
},
{
"id": "dfb0cb32-9d7c-4588-b75e-0b79231eb72a",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
1020,
-160
],
"parameters": {
"width": 625,
"height": 607,
"content": "## Load into Milvus vector database"
},
"typeVersion": 1
},
{
"id": "862a1a02-50e2-42af-9fa9-eb3a4f2ca463",
"name": "Recursive Character Text Splitter1",
"type": "@n8n\/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
1440,
300
],
"parameters": {
"options": [],
"chunkSize": 6000
},
"typeVersion": 1
},
{
"id": "91ac110a-57db-44b1-b22f-d2a63f22f173",
"name": "Milvus Vector Store",
"type": "@n8n\/n8n-nodes-langchain.vectorStoreMilvus",
"position": [
1320,
-40
],
"parameters": {
"mode": "insert",
"options": {
"clearCollection": true
},
"milvusCollection": {
"__rl": true,
"mode": "list",
"value": "n8n_test",
"cachedResultName": "n8n_test"
}
},
"credentials": {
"milvusApi": {
"id": "8tMHHoLiWXIAXa7S",
"name": "Milvus account"
}
},
"typeVersion": 1.1
},
{
"id": "456e917f-d466-4ec8-8df9-3774ba58151d",
"name": "AI Agent",
"type": "@n8n\/n8n-nodes-langchain.agent",
"position": [
60,
360
],
"parameters": {
"options": []
},
"typeVersion": 1.9
},
{
"id": "a5c5f308-097d-4fe0-92be-d717fd1e0b74",
"name": "When chat message received",
"type": "@n8n\/n8n-nodes-langchain.chatTrigger",
"position": [
-280,
360
],
"webhookId": "cd2703a7-f912-46fe-8787-3fb83ea116ab",
"parameters": {
"options": []
},
"typeVersion": 1.1
},
{
"id": "dc352f07-335f-47cb-8270-32a4a0b87df7",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
-460,
-200
],
"parameters": {
"width": 280,
"height": 180,
"content": "## Step 1\n1. Set up a Milvus server based on [this guide](https:\/\/milvus.io\/docs\/install_standalone-docker-compose.md). And then create a collection named `n8n_test`.\n2. Click this workflow to load scrape and load Paul Graham essays to Milvus collection.\n"
},
"typeVersion": 1
},
{
"id": "5c9e9871-c9c1-458e-b35c-eab87ac5ca26",
"name": "Default Data Loader",
"type": "@n8n\/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
1360,
180
],
"parameters": {
"options": [],
"jsonData": "={{ $('Extract Text Only').item.json.data }}",
"jsonMode": "expressionData"
},
"typeVersion": 1
},
{
"id": "5b202001-525c-4481-a263-56b69c9b1bd8",
"name": "Milvus Vector Store as tool",
"type": "@n8n\/n8n-nodes-langchain.vectorStoreMilvus",
"position": [
180,
560
],
"parameters": {
"mode": "retrieve-as-tool",
"toolName": "milvus_knowledge_base",
"toolDescription": "useful when you need to retrieve information",
"milvusCollection": {
"__rl": true,
"mode": "list",
"value": "n8n_test",
"cachedResultName": "n8n_test"
}
},
"credentials": {
"milvusApi": {
"id": "8tMHHoLiWXIAXa7S",
"name": "Milvus account"
}
},
"typeVersion": 1.1
},
{
"id": "6b5b95c7-dde2-4c3f-952b-97a8f5c267c9",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-460,
260
],
"parameters": {
"width": 280,
"height": 120,
"content": "## Step 2\nStart to chat with the AI Agent with Milvus tool"
},
"typeVersion": 1
},
{
"id": "5ccfe636-2bb3-4026-98f0-57ba8d5780f0",
"name": "Embeddings OpenAI",
"type": "@n8n\/n8n-nodes-langchain.embeddingsOpenAi",
"position": [
1220,
200
],
"parameters": {
"options": []
},
"credentials": {
"openAiApi": {
"id": "hH2PTDH4fbS7fdPv",
"name": "OpenAi account"
}
},
"typeVersion": 1.2
},
{
"id": "982622e9-af05-4ee2-ae7d-166c47f75ce9",
"name": "OpenAI Chat Model",
"type": "@n8n\/n8n-nodes-langchain.lmChatOpenAi",
"position": [
20,
560
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": []
},
"credentials": {
"openAiApi": {
"id": "hH2PTDH4fbS7fdPv",
"name": "OpenAi account"
}
},
"typeVersion": 1.2
},
{
"id": "abd97878-cce6-44a0-8bae-91536ea48b6b",
"name": "Embeddings OpenAI1",
"type": "@n8n\/n8n-nodes-langchain.embeddingsOpenAi",
"position": [
200,
740
],
"parameters": {
"options": []
},
"credentials": {
"openAiApi": {
"id": "hH2PTDH4fbS7fdPv",
"name": "OpenAi account"
}
},
"typeVersion": 1.2
},
{
"id": "00d49aab-3200-44fc-a0fc-8f7f22998617",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-80,
300
],
"parameters": {
"color": 7,
"width": 574,
"height": 629,
"content": ""
},
"typeVersion": 1
}
],
"active": false,
"pinData": [],
"settings": {
"executionOrder": "v1"
},
"versionId": "8e6f0bb5-1fb5-48fc-8a1f-488362be4ef7",
"connections": {
"Fetch Essay List": {
"main": [
[
{
"node": "Extract essay names",
"type": "main",
"index": 0
}
]
]
},
"Limit to first 3": {
"main": [
[
{
"node": "Fetch essay texts",
"type": "main",
"index": 0
}
]
]
},
"Embeddings OpenAI": {
"ai_embedding": [
[
{
"node": "Milvus Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Extract Text Only": {
"main": [
[
{
"node": "Milvus Vector Store",
"type": "main",
"index": 0
}
]
]
},
"Fetch essay texts": {
"main": [
[
{
"node": "Extract Text Only",
"type": "main",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Embeddings OpenAI1": {
"ai_embedding": [
[
{
"node": "Milvus Vector Store as tool",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Milvus Vector Store",
"type": "ai_document",
"index": 0
}
]
]
},
"Extract essay names": {
"main": [
[
{
"node": "Split out into items",
"type": "main",
"index": 0
}
]
]
},
"Split out into items": {
"main": [
[
{
"node": "Limit to first 3",
"type": "main",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Milvus Vector Store as tool": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"When clicking \"Execute Workflow\"": {
"main": [
[
{
"node": "Fetch Essay List",
"type": "main",
"index": 0
}
]
]
},
"Recursive Character Text Splitter1": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
}
}
}
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