Workflow n8n
Automatisation Google Sheets avec n8n : gestion des données en temps réel
- Ce workflow n8n a pour objectif d'automatiser la gestion des données dans Google Sheets en intégrant des messages de chat et des modèles d'IA. Dans un contexte où la collaboration et la gestion efficace des informations sont cruciales, ce workflow permet aux équipes de synchroniser les données en temps réel, d'extraire des informations pertinentes et de les organiser de manière structurée. Par exemple, une équipe de vente peut utiliser ce workflow pour récupérer des données clients directement depuis Google Sheets en réponse à des requêtes dans un chat, améliorant ainsi leur réactivité et leur efficacité.
- Le workflow débute avec le déclencheur 'When chat message received', qui active le processus dès qu'un message est reçu dans le chat. Ensuite, il utilise des nœuds comme 'OpenAI Chat Model1' pour traiter les demandes et 'Get Google sheet contents' pour extraire les données nécessaires. Les nœuds 'Filter' et 'Check operation' permettent d'appliquer des conditions spécifiques pour affiner les résultats. Par ailleurs, des nœuds comme 'Set Google Sheet URL' et 'Prepare output' sont utilisés pour structurer et renvoyer les données au format souhaité.
- Les bénéfices de ce workflow sont multiples : il réduit le temps de recherche d'informations, minimise les erreurs humaines et optimise la collaboration entre les équipes. Grâce à cette automatisation n8n, les utilisateurs peuvent se concentrer sur des tâches à plus forte valeur ajoutée tout en ayant accès à des données précises et à jour.
Tags clés :automatisationGoogle SheetsworkflowIAcollaboration
Catégorie: Webhook · Tags: automatisation, Google Sheets, workflow, IA, collaboration❤ 0
Workflow n8n Google Sheets, collaboration : vue d'ensemble
Schéma des nœuds et connexions de ce workflow n8n, généré à partir du JSON n8n.
Workflow n8n Google Sheets, collaboration : détail des nœuds
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"meta": {
"instanceId": "408f9fb9940c3cb18ffdef0e0150fe342d6e655c3a9fac21f0f644e8bedabcd9",
"templateCredsSetupCompleted": true
},
"nodes": [
{
"id": "f3f7546a-8bb3-484c-b0a1-750a8d7d3a74",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
0,
520
],
"parameters": {
"color": 7,
"width": 1549,
"height": 612,
"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": "a5afaa40-0b68-4d7c-8f78-5cb176fde81d",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
0,
-40
],
"parameters": {
"color": 7,
"width": 1068,
"height": 547,
"content": "### Main workflow: AI agent using custom tool"
},
"typeVersion": 1
},
{
"id": "2dc0ce2f-a09c-4804-9962-f542ec78eb87",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
-160,
40
],
"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": "8fc97d52-1c18-47ed-ba6f-4c7c9ce8b7d4",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
480,
240
],
"parameters": {
"color": 7,
"width": 572,
"height": 219,
"content": "These tools all call the sub-workflow below"
},
"typeVersion": 1
},
{
"id": "60cafb69-818f-49fe-b75e-e770304a6aa9",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
260,
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],
"parameters": {
"width": 179.99762227826224,
"height": 226.64416053838073,
"content": "Change the URL of the Google Sheet here"
},
"typeVersion": 1
},
{
"id": "cd8d92fa-f7ef-47d8-a1a7-5b5aa6faaa96",
"name": "When chat message received",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
120,
40
],
"webhookId": "7668b567-b983-479f-a3e0-ad945707ae6b",
"parameters": {
"options": {}
},
"typeVersion": 1.1
},
{
"id": "72ac3bdb-56dc-4634-a0ab-0b1c82e2b23d",
"name": "OpenAI Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatOpenAi",
"position": [
160,
320
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "gpt-4o-mini"
},
"options": {}
},
"credentials": {
"openAiApi": {
"id": "8gccIjcuf3gvaoEr",
"name": "OpenAi account"
}
},
"typeVersion": 1.2
},
{
"id": "37e5bca6-4274-4714-a9e7-a8e4b7d732e5",
"name": "Simple Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
340,
320
],
"parameters": {},
"typeVersion": 1.3
},
{
"id": "81bf7de8-c4c6-49ce-a2cf-4afca5dce7e2",
"name": "When Executed by Another Workflow",
"type": "n8n-nodes-base.executeWorkflowTrigger",
"position": [
80,
800
],
"parameters": {
"workflowInputs": {
"values": [
{
"name": "operation"
},
{
"name": "query"
}
]
}
},
"typeVersion": 1.1
},
{
"id": "24e5a49d-8f1f-4569-8072-c35f059ebd46",
"name": "AI Agent",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
480,
40
],
"parameters": {
"options": {}
},
"typeVersion": 1.8
},
{
"id": "8cc35cb9-3371-4034-86b6-3d125d70d81b",
"name": "List columns tool",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
540,
320
],
"parameters": {
"name": "list_columns",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $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.",
"workflowInputs": {
"value": {
"query": "none",
"operation": "column_names"
},
"schema": [
{
"id": "query",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "query",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "operation",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "operation",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [],
"attemptToConvertTypes": false,
"convertFieldsToString": false
}
},
"typeVersion": 2
},
{
"id": "acf19978-dd84-4cfb-8034-eb9f14dd9c86",
"name": "Get column values tool",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
720,
320
],
"parameters": {
"name": "column_values",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $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",
"workflowInputs": {
"value": {
"query": "none",
"operation": "column_values"
},
"schema": [
{
"id": "operation",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "operation",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "query",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "query",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"operation"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
}
},
"typeVersion": 2
},
{
"id": "acd8dad6-2ce5-4a53-9909-da7bc03cf0e2",
"name": "Get customer tool",
"type": "@n8n/n8n-nodes-langchain.toolWorkflow",
"position": [
900,
320
],
"parameters": {
"name": "get_customer",
"workflowId": {
"__rl": true,
"mode": "id",
"value": "={{ $workflow.id }}",
"cachedResultName": "={{ $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.",
"workflowInputs": {
"value": {
"query": "={{ /*n8n-auto-generated-fromAI-override*/ $fromAI('query', ``, 'string') }}",
"operation": "row"
},
"schema": [
{
"id": "operation",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "operation",
"defaultMatch": false,
"canBeUsedToMatch": true
},
{
"id": "query",
"type": "string",
"display": true,
"removed": false,
"required": false,
"displayName": "query",
"defaultMatch": false,
"canBeUsedToMatch": true
}
],
"mappingMode": "defineBelow",
"matchingColumns": [
"operation"
],
"attemptToConvertTypes": false,
"convertFieldsToString": false
}
},
"typeVersion": 2
},
{
"id": "43988dff-2270-4d09-a091-8b719c281faf",
"name": "Set Google Sheet URL",
"type": "n8n-nodes-base.set",
"position": [
300,
800
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "a96650f2-3a0c-45cb-afdd-ef7ca90b21cc",
"name": "sheetUrl",
"type": "string",
"value": "https://docs.google.com/spreadsheets/d/1GjFBV8HpraNWG_JyuaQAgTb3zUGguh0S_25nO0CMd8A/edit#gid=736425281"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "536225e9-e33c-4819-a2dc-994d8f7c3f30",
"name": "Get Google sheet contents",
"type": "n8n-nodes-base.googleSheets",
"position": [
520,
800
],
"parameters": {
"options": {},
"sheetName": {
"__rl": true,
"mode": "name",
"value": "customer_data"
},
"documentId": {
"__rl": true,
"mode": "url",
"value": "={{ $json.sheetUrl }}"
}
},
"credentials": {
"googleSheetsOAuth2Api": {
"id": "XHvC7jIRR8A2TlUl",
"name": "Google Sheets account"
}
},
"typeVersion": 4.5
},
{
"id": "a5668364-8824-44cc-8a0f-516906d8f821",
"name": "Check operation",
"type": "n8n-nodes-base.switch",
"position": [
740,
800
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "Column Names",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "db07e0a3-0a1d-44bd-84a7-59a9442e63a6",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('When Executed by Another Workflow').item.json.operation }}",
"rightValue": "column_names"
}
]
},
"renameOutput": true
},
{
"outputKey": "Column Values",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "96c82351-de4a-4299-903d-8b9b3a3bb931",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('When Executed by Another Workflow').item.json.operation }}",
"rightValue": "column_values"
}
]
},
"renameOutput": true
},
{
"outputKey": "Rows",
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "fbc2afd0-361f-4181-94e3-4addc65a9086",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $('When Executed by Another Workflow').item.json.operation }}",
"rightValue": "row"
}
]
},
"renameOutput": true
}
]
},
"options": {}
},
"typeVersion": 3.2
},
{
"id": "46c3a8c4-ffaf-4373-b421-4d7ee65567b2",
"name": "Get column names",
"type": "n8n-nodes-base.set",
"position": [
1040,
620
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "36a7be13-e792-4c0a-9997-f61fe2a7b225",
"name": "response",
"type": "array",
"value": "={{ Object.keys($json) }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "190c48e8-4d4b-4e95-a694-49ab76b730da",
"name": "Prepare column data",
"type": "n8n-nodes-base.set",
"position": [
1040,
800
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "bcb75b32-3253-4a31-9771-4faaf12cc2ed",
"name": "row_number",
"type": "number",
"value": "={{ $json.row_number }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "9c65e5e6-a3ac-4ed7-8546-b7f2b09b4f96",
"name": "Filter",
"type": "n8n-nodes-base.filter",
"position": [
1040,
980
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "dbe89d36-e411-4765-8d4e-91a6425350ac",
"operator": {
"name": "filter.operator.equals",
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.row_number.toString() }}",
"rightValue": "={{ $('When Executed by Another Workflow').item.json.query }}"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "39265f3e-a2ea-4174-952a-3665747ff856",
"name": "Prepare output",
"type": "n8n-nodes-base.code",
"position": [
1340,
800
],
"parameters": {
"jsCode": "return {\n 'response': JSON.stringify($input.all().map(x => x.json))\n}"
},
"executeOnce": true,
"typeVersion": 2
}
],
"pinData": {},
"connections": {
"Filter": {
"main": [
[
{
"node": "Prepare output",
"type": "main",
"index": 0
}
]
]
},
"Simple Memory": {
"ai_memory": [
[
{
"node": "AI Agent",
"type": "ai_memory",
"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 Model1": {
"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
}
]
]
},
"Get Google sheet contents": {
"main": [
[
{
"node": "Check operation",
"type": "main",
"index": 0
}
]
]
},
"When chat message received": {
"main": [
[
{
"node": "AI Agent",
"type": "main",
"index": 0
}
]
]
},
"When Executed by Another Workflow": {
"main": [
[
{
"node": "Set Google Sheet URL",
"type": "main",
"index": 0
}
]
]
}
}
}Workflow n8n Google Sheets, collaboration : pour qui est ce workflow ?
Ce workflow s'adresse aux équipes commerciales, aux responsables de la gestion des données et aux professionnels cherchant à améliorer leur efficacité opérationnelle. Il est particulièrement adapté aux entreprises de taille moyenne à grande qui utilisent Google Sheets pour la gestion de leurs données et qui souhaitent intégrer des solutions d'IA dans leur processus de travail.
Workflow n8n Google Sheets, collaboration : problème résolu
Ce workflow résout le problème de la lenteur et de l'inefficacité dans la gestion des données. En automatisant la récupération et le traitement des informations à partir de Google Sheets en réponse à des messages de chat, il élimine les frustrations liées à la recherche manuelle d'informations. Les utilisateurs bénéficient d'une réponse rapide et précise, ce qui améliore leur productivité et réduit les risques d'erreurs.
Workflow n8n Google Sheets, collaboration : étapes du workflow
Étape 1 : Le workflow est déclenché par un message reçu dans le chat.
- Étape 1 : Les données sont traitées par le nœud 'OpenAI Chat Model1' pour comprendre la demande.
- Étape 2 : Le nœud 'Get Google sheet contents' extrait les informations pertinentes depuis Google Sheets.
- Étape 3 : Des conditions sont appliquées via le nœud 'Filter' pour s'assurer que seules les données pertinentes sont renvoyées.
- Étape 4 : Enfin, les données sont structurées et renvoyées au format souhaité grâce aux nœuds 'Set Google Sheet URL' et 'Prepare output'.
Workflow n8n Google Sheets, collaboration : guide de personnalisation
Pour personnaliser ce workflow, commencez par ajuster le déclencheur 'When chat message received' pour qu'il réponde à des canaux ou types de messages spécifiques. Modifiez les paramètres du nœud 'OpenAI Chat Model1' pour adapter le modèle d'IA à vos besoins. Vous pouvez également changer le nom de la feuille et l'ID du document dans le nœud 'Get Google sheet contents' pour cibler d'autres feuilles de calcul. Pour une meilleure sécurité, envisagez d'ajouter des vérifications supplémentaires dans le nœud 'Check operation'. Enfin, vous pouvez intégrer d'autres outils ou services en ajoutant des nœuds supplémentaires selon vos besoins.