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Workflow automatisé avec 12 nodes incluant : stickyNote, webhook, @n8n/langchain.textSplitterCharacterTextSplitter, @n8...
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📋 Optimisez vos données clients avec Google Sheets et AI
💡 Description
Ce workflow n8n révolutionne la gestion des données clients en intégrant Google Sheets avec des capacités avancées d'intelligence artificielle. En utilisant un agent AI puissant, vous pouvez interroger efficacement votre feuille de calcul Google pour extraire des informations clés sur vos clients, comme leur volume d'achat ou la valeur de leurs transactions. Ce processus automatisé élimine le besoin d'une extraction manuelle fastidieuse, permettant ainsi une prise de décision plus rapide et éclairée. Idéal pour les équipes de vente et de marketing cherchant à maximiser l'efficacité et à obtenir un avantage concurrentiel.
📈 Impact & ROI: Amélioration significative de la productivité et réduction des erreurs humaines dans la gestion des données clients, menant à une meilleure compréhension du marché et à une augmentation potentielle des ventes.
🚀 Fonctionnalités Clés
- ✅ Intégration transparente avec Google Sheets pour une gestion simplifiée des données
- ✅ Utilisation de l'AI pour des requêtes complexes sans surcharge manuelle
- ✅ Automatisation des tâches répétitives pour un gain de temps considérable
- ✅ Capacité à traiter de grandes quantités de données client efficacement
📊 Architecture Technique
19
Nodes
Nodes
12
Connexions
Connexions
2
Services
Services
🔌 Services Intégrés
Google SheetsOpenAI
🔧 Composition du Workflow
| Node | Type | Description |
|---|---|---|
| Execute Workflow Trigger | executeWorkflowTrigger | Traitement des données |
| Sticky Note1 | stickyNote | Traitement des données |
| Sticky Note2 | stickyNote | Traitement des données |
| Sticky Note3 | stickyNote | Traitement des données |
| Get Google sheet contents | googleSheets | Traitement des données |
| Set Google Sheet URL | set | Traitement des données |
| Get column names | set | Traitement des données |
| Prepare output | code | Traitement des données |
| List columns tool | @n8n/n8n-nodes-langchain.toolWorkflow | Traitement des données |
| Get customer tool | @n8n/n8n-nodes-langchain.toolWorkflow | Traitement des données |
| Get column values tool | @n8n/n8n-nodes-langchain.toolWorkflow | Traitement des données |
| Sticky Note | stickyNote | Traitement des données |
| Sticky Note4 | stickyNote | Traitement des données |
| Prepare column data | set | Traitement des données |
| Filter | filter | Traitement des données |
| Check operation | switch | Traitement des données |
| OpenAI Chat Model | @n8n/n8n-nodes-langchain.lmChatOpenAi | Traitement des données |
| Chat Trigger | @n8n/n8n-nodes-langchain.chatTrigger | Traitement des données |
| AI Agent | @n8n/n8n-nodes-langchain.agent | 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": "ZVUQL1bUQ8gBCZTl",
"meta": {
"instanceId": "23e6ce638471979c8a2c72a9fb50e44f4f2bfd5a9fc2f5b7f5c842b9abeb9393"
},
"name": "Chat with Google Sheet",
"tags": [],
"nodes": [
{
"id": "89af21df-1125-4df6-9d43-a643e02bb53f",
"name": "Execute Workflow Trigger",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
540,
1240
],
"parameters": [],
"typeVersion": 1
},
{
"id": "f571d0cc-eb43-46c9-bdd5-45abc51dfbe7",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
461.9740563285368,
970.616715060075
],
"parameters": {
"color": 7,
"width": 1449.2963504228514,
"height": 612.0936015224503,
"content": "### Sub-workflow: Custom tool\nThis can be called by the agent above. It returns three different types of data from the Google Sheet, which can be used together for more complex queries without returning the whole sheet (which might be too big for GPT to handle)"
},
"typeVersion": 1
},
{
"id": "8761e314-c1f2-4edd-88ea-bfeb02dc8f1a",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
460,
460
],
"parameters": {
"color": 7,
"width": 927.5,
"height": 486.5625,
"content": "### Main workflow: AI agent using custom tool"
},
"typeVersion": 1
},
{
"id": "e793b816-68d9-42ef-b9b0-6fe22aa375e8",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
300,
540
],
"parameters": {
"width": 185.9375,
"height": 183.85014518022527,
"content": "## Try me out\n\nClick the 'Chat' button at the bottom and enter:\n\n_Which is our biggest customer?_"
},
"typeVersion": 1
},
{
"id": "f895d926-0f70-415b-9492-c3ecf186e761",
"name": "Get Google sheet contents",
"type": "n8n-nodes-base.googleSheets",
"position": [
980,
1240
],
"parameters": {
"options": [],
"sheetName": {
"__rl": true,
"mode": "url",
"value": "={{ $json.sheetUrl }}"
},
"documentId": {
"__rl": true,
"mode": "url",
"value": "={{ $json.sheetUrl }}"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "cTLaIZBSFJlHuZNs",
"name": "Google Sheets account"
}
},
"typeVersion": 4.2
},
{
"id": "daca1624-6c35-473a-bf3a-5fa0686a0a62",
"name": "Set Google Sheet URL",
"type": "n8n-nodes-base.set",
"position": [
760,
1240
],
"parameters": {
"fields": {
"values": [
{
"name": "sheetUrl",
"stringValue": "https:\/\/docs.google.com\/spreadsheets\/d\/1GjFBV8HpraNWG_JyuaQAgTb3zUGguh0S_25nO0CMd8A\/edit#gid=736425281"
}
]
},
"options": []
},
"typeVersion": 3.2
},
{
"id": "68edca41-0196-47d8-9378-31fed0a70918",
"name": "Get column names",
"type": "n8n-nodes-base.set",
"position": [
1460,
1060
],
"parameters": {
"fields": {
"values": [
{
"name": "response",
"stringValue": "={{ Object.keys($json) }}"
}
]
},
"include": "none",
"options": []
},
"executeOnce": true,
"typeVersion": 3.2
},
{
"id": "7a9dea08-f9e9-4139-842a-9066a9cf04ea",
"name": "Prepare output",
"type": "n8n-nodes-base.code",
"position": [
1720,
1240
],
"parameters": {
"jsCode": "return {\n 'response': JSON.stringify($input.all().map(x => x.json))\n}"
},
"typeVersion": 2
},
{
"id": "616eebc5-5c5c-4fa1-b13f-61a477742c72",
"name": "List columns tool",
"type": "@n8n\/n8n-nodes-langchain.toolWorkflow",
"position": [
940,
780
],
"parameters": {
"name": "list_columns",
"fields": {
"values": [
{
"name": "operation",
"stringValue": "column_names"
}
]
},
"workflowId": "={{ $workflow.id }}",
"description": "=List all column names in customer data\n\nCall this tool to find out what data is available for each customer. It should be called first at the beginning to understand which columns are available for querying."
},
"typeVersion": 1
},
{
"id": "891ad3a8-72f0-45ad-8777-1647a7342c00",
"name": "Get customer tool",
"type": "@n8n\/n8n-nodes-langchain.toolWorkflow",
"position": [
1220,
780
],
"parameters": {
"name": "get_customer",
"fields": {
"values": [
{
"name": "operation",
"stringValue": "row"
}
]
},
"workflowId": "={{ $workflow.id }}",
"description": "=Get all columns for a given customer\n\nThe input should be a stringified row number of the customer to fetch; only single string inputs are allowed. Returns a JSON object with all the column names and their values."
},
"typeVersion": 1
},
{
"id": "0f3ca6ff-fc01-4f33-b1a7-cb82a0ec5c88",
"name": "Get column values tool",
"type": "@n8n\/n8n-nodes-langchain.toolWorkflow",
"position": [
1080,
780
],
"parameters": {
"name": "column_values",
"fields": {
"values": [
{
"name": "operation",
"stringValue": "column_values"
}
]
},
"workflowId": "={{ $workflow.id }}",
"description": "=Get the specified column value for all customers\n\nUse this tool to find out which customers have a certain value for a given column. Returns an array of JSON objects, one per customer. Each JSON object includes the column being requested plus the row_number column. Input should be a single string representing the name of the column to fetch.\n"
},
"typeVersion": 1
},
{
"id": "deef6eb4-2a11-4490-ad56-bc1ea9077843",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
900,
740.8693557231958
],
"parameters": {
"color": 7,
"width": 432.3271051132649,
"height": 179.21380662202682,
"content": "These tools all call the sub-workflow below"
},
"typeVersion": 1
},
{
"id": "94e4dbe5-dc41-4879-bffc-ec8f5341f3b5",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
723,
1172
],
"parameters": {
"width": 179.99762227826224,
"height": 226.64416053838073,
"content": "Change the URL of the Google Sheet here"
},
"typeVersion": 1
},
{
"id": "dbb887f0-93a7-466e-9c9f-8aa4e7da935d",
"name": "Prepare column data",
"type": "n8n-nodes-base.set",
"position": [
1460,
1240
],
"parameters": {
"fields": {
"values": [
{
"name": "={{ $('Execute Workflow Trigger').item.json.query }}",
"stringValue": "={{ $json[$('Execute Workflow Trigger').item.json.query] }}"
},
{
"name": "row_number",
"stringValue": "={{ $json.row_number }}"
}
]
},
"include": "none",
"options": []
},
"typeVersion": 3.2
},
{
"id": "041d32ca-e59a-4b67-a3e6-4e2f19e3de72",
"name": "Filter",
"type": "n8n-nodes-base.filter",
"position": [
1460,
1400
],
"parameters": {
"options": {
"looseTypeValidation": true
},
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "loose"
},
"combinator": "and",
"conditions": [
{
"id": "bf712098-97e4-42cb-8e08-2ee32d19d3e7",
"operator": {
"type": "number",
"operation": "equals"
},
"leftValue": "={{ $json.row_number }}",
"rightValue": "={{ $('Execute Workflow Trigger').item.json.query }}"
}
]
}
},
"typeVersion": 2,
"alwaysOutputData": true
},
{
"id": "69b9e70a-9104-4731-9f16-8324a3f7e423",
"name": "Check operation",
"type": "n8n-nodes-base.switch",
"position": [
1200,
1240
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "col names",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Execute Workflow Trigger').item.json.operation }}",
"rightValue": "column_names"
}
]
},
"renameOutput": true
},
{
"outputKey": "col values",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "b7968ce7-0d20-43d0-bcca-7b66e0aec715",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Execute Workflow Trigger').item.json.operation }}",
"rightValue": "column_values"
}
]
},
"renameOutput": true
},
{
"outputKey": "rows",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "de3bb9b5-edc6-4448-839e-eda07b72144a",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('Execute Workflow Trigger').item.json.operation }}",
"rightValue": "row"
}
]
},
"renameOutput": true
}
]
},
"options": []
},
"typeVersion": 3
},
{
"id": "d955e499-5a3e-45a3-9fc8-266e2f687ecc",
"name": "OpenAI Chat Model",
"type": "@n8n\/n8n-nodes-langchain.lmChatOpenAi",
"position": [
800,
780
],
"parameters": {
"model": "gpt-3.5-turbo-0125",
"options": {
"temperature": 0
}
},
"credentials": {
"openAiApi": {
"id": "58qWzMjeNE8GjMmI",
"name": "OpenAi account"
}
},
"typeVersion": 1
},
{
"id": "28fbda0b-1e01-4f59-af5b-fe02eba899b1",
"name": "Chat Trigger",
"type": "@n8n\/n8n-nodes-langchain.chatTrigger",
"position": [
620,
560
],
"webhookId": "2b9d9c42-adf4-425d-b0a5-e4f60c750e63",
"parameters": [],
"typeVersion": 1
},
{
"id": "c89614f4-d8b1-4f7b-9e7c-856e3f89eadb",
"name": "AI Agent",
"type": "@n8n\/n8n-nodes-langchain.agent",
"position": [
900,
560
],
"parameters": {
"agent": "reActAgent",
"options": {
"suffix": "Begin! Use `list_columns` tool first to determine which columns are available.\n\n\tQuestion: {input}\n\tThought:{agent_scratchpad}",
"returnIntermediateSteps": false
}
},
"typeVersion": 1.3
}
],
"active": false,
"pinData": {
"Execute Workflow Trigger": [
{
"json": {
"query": "222",
"operation": "row"
}
}
]
},
"settings": {
"executionOrder": "v1"
},
"versionId": "94885609-92bb-498c-9628-35d9044593e7",
"connections": {
"Filter": {
"main": [
[
{
"node": "Prepare output",
"type": "main",
"index": 0
}
]
]
},
"Chat Trigger": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"Check operation": {
"main": [
[
{
"node": "Get column names",
"type": "main",
"index": 0
}
],
[
{
"node": "Prepare column data",
"type": "main",
"index": 0
}
],
[
{
"node": "Filter",
"type": "main",
"index": 0
}
]
]
},
"Get column names": {
"main": [
[
{
"node": "Prepare output",
"type": "main",
"index": 0
}
]
]
},
"Get customer tool": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"List columns tool": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"OpenAI Chat Model": {
"ai_languageModel": [
[
{
"node": "AI Agent",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Prepare column data": {
"main": [
[
{
"node": "Prepare output",
"type": "main",
"index": 0
}
]
]
},
"Set Google Sheet URL": {
"main": [
[
{
"node": "Get Google sheet contents",
"type": "main",
"index": 0
}
]
]
},
"Get column values tool": {
"ai_tool": [
[
{
"node": "AI Agent",
"type": "ai_tool",
"index": 0
}
]
]
},
"Execute Workflow Trigger": {
"main": [
[
{
"node": "Set Google Sheet URL",
"type": "main",
"index": 0
}
]
]
},
"Get Google sheet contents": {
"main": [
[
{
"node": "Check operation",
"type": "main",
"index": 0
}
]
]
}
}
}
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