Workflow n8n
Automatisation de fichiers avec n8n : gestion intelligente des données
Ce workflow n8n a pour objectif d'automatiser la gestion des fichiers en intégrant des fonctionnalités avancées de traitement de données. Dans un contexte où les entreprises doivent gérer un volume croissant d'informations, ce workflow permet d'optimiser le traitement des fichiers et d'améliorer l'efficacité opérationnelle. Les cas d'usage incluent la lecture de fichiers locaux, la gestion de données via des notes autocollantes, et l'intégration avec des modèles de langage pour des réponses intelligentes.
- Étape 1 : Le déclencheur 'Local File Trigger' active le workflow lorsque des fichiers sont ajoutés.
- Étape 2 : Les variables sont définies grâce au noeud 'Set Variables', permettant de préparer les données pour le traitement.
- Étape 3 : Le noeud 'Read File' lit le contenu du fichier, tandis que le 'Default Data Loader' et le 'Embeddings Mistral Cloud' traitent les données pour en extraire des informations pertinentes.
- Étape 4 : Le 'Chat Trigger' permet d'interagir avec les utilisateurs, et le 'Question and Answer Chain' fournit des réponses basées sur les données traitées. En intégrant des vérifications pour les points existants, ce workflow assure une gestion efficace des données, réduisant ainsi les risques d'erreurs et améliorant la prise de décision. Les bénéfices business incluent une réduction des délais de traitement, une meilleure organisation des informations, et une augmentation de la productivité des équipes.
Tags clés :automatisationn8ngestion des donnéesintelligence artificielleworkflow
Catégorie: Local File Trigger · Tags: automatisation, n8n, gestion des données, intelligence artificielle, workflow❤ 0
Workflow n8n gestion des données, intelligence artificielle : vue d'ensemble
Schéma des nœuds et connexions de ce workflow n8n, généré à partir du JSON n8n.
Workflow n8n gestion des données, intelligence artificielle : détail des nœuds
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"meta": {
"instanceId": "26ba763460b97c249b82942b23b6384876dfeb9327513332e743c5f6219c2b8e"
},
"nodes": [
{
"id": "c5525f47-4d91-4b98-87bb-566b90da64a1",
"name": "Local File Trigger",
"type": "n8n-nodes-base.localFileTrigger",
"position": [
660,
700
],
"parameters": {
"path": "/home/node/host_mount/local_file_search",
"events": [
"add",
"change",
"unlink"
],
"options": {
"awaitWriteFinish": true
},
"triggerOn": "folder"
},
"typeVersion": 1
},
{
"id": "804334d6-e34d-40d1-9555-b331ffe66f6f",
"name": "When clicking \"Test workflow\"",
"type": "n8n-nodes-base.manualTrigger",
"position": [
664.5766613599001,
881.8474780113352
],
"parameters": {},
"typeVersion": 1
},
{
"id": "7ab0e284-b667-4d1f-8ceb-fb05e4081a06",
"name": "Set Variables",
"type": "n8n-nodes-base.set",
"position": [
840,
700
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "35ea70c4-8669-4975-a68d-bbaa094713c0",
"name": "directory",
"type": "string",
"value": "/home/node/BankStatements"
},
{
"id": "1d081d19-ff4e-462a-9cbe-7af2244bf87f",
"name": "file_added",
"type": "string",
"value": "={{ $json.event === 'add' && $json.path || ''}}"
},
{
"id": "18f8dc03-51ca-48c7-947f-87ce8e1979bf",
"name": "file_changed",
"type": "string",
"value": "={{ $json.event === 'change' && $json.path || '' }}"
},
{
"id": "65074ff7-037b-4b3b-b2c3-8a61755ab43b",
"name": "file_deleted",
"type": "string",
"value": "={{ $json.event === 'unlink' && $json.path || '' }}"
},
{
"id": "9a1902e7-f94d-4d1f-9006-91c67354d3e8",
"name": "qdrant_collection",
"type": "string",
"value": "local_file_search"
}
]
}
},
"typeVersion": 3.3
},
{
"id": "76173972-ceca-43a4-b85f-00b41f774304",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
580,
460
],
"parameters": {
"color": 7,
"width": 665.0909497859384,
"height": 596.8351502261468,
"content": "## Step 1. Select the target folder\n[Read more about local file trigger](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.localfiletrigger)\n\nIn this workflow, we'll monitor a specific folder on disk that n8n has access to. Since we're using docker, we can either use the n8n volume or mount a folder from the host machine.\n\nThe local file trigger is useful to execute the workflow whenever changes are made to our target folder."
},
"typeVersion": 1
},
{
"id": "eda839f7-dde4-4d1f-9fe6-692df4ac7282",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
184.57666135990007,
461.84747801133517
],
"parameters": {
"width": 372.51107341403605,
"height": 356.540665091993,
"content": "## Try It Out!\n### This workflow does the following:\n* Monitors a target folder for changes using the local file trigger\n* Synchronises files in the target folder with their vectors in Qdrant\n* Mistral AI is used to create a Q&A AI agent on all files in the target folder\n\n### Need Help?\nJoin the [Discord](https://discord.com/invite/XPKeKXeB7d) or ask in the [Forum](https://community.n8n.io/)!\n\nHappy Hacking!"
},
"typeVersion": 1
},
{
"id": "f82f6de0-af8f-4fdf-a733-f59ba4fed02f",
"name": "Read File",
"type": "n8n-nodes-base.readWriteFile",
"position": [
1340,
1120
],
"parameters": {
"options": {},
"fileSelector": "={{ $json.file_added }}"
},
"typeVersion": 1
},
{
"id": "7354a080-051b-479f-97b1-49cc0c14c9d8",
"name": "Embeddings Mistral Cloud",
"type": "@n8n/n8n-nodes-langchain.embeddingsMistralCloud",
"position": [
1720,
1280
],
"parameters": {
"options": {}
},
"credentials": {
"mistralCloudApi": {
"id": "EIl2QxhXAS9Hkg37",
"name": "Mistral Cloud account"
}
},
"typeVersion": 1
},
{
"id": "a1ad45ff-a882-4aed-82e2-cad2483cf4e8",
"name": "Default Data Loader",
"type": "@n8n/n8n-nodes-langchain.documentDefaultDataLoader",
"position": [
1820,
1280
],
"parameters": {
"options": {
"metadata": {
"metadataValues": [
{
"name": "filter_by_filename",
"value": "={{ $json.file_location }}"
},
{
"name": "filter_by_created_month",
"value": "={{ $now.year + '-' + $now.monthShort }}"
},
{
"name": "filter_by_created_week",
"value": "={{ $now.year + '-' + $now.monthShort + '-W' + $now.weekNumber }}"
}
]
}
},
"jsonData": "={{ $json.data }}",
"jsonMode": "expressionData"
},
"typeVersion": 1
},
{
"id": "0b0e29b9-8873-4074-94dc-9f0364c28835",
"name": "Recursive Character Text Splitter",
"type": "@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter",
"position": [
1840,
1400
],
"parameters": {
"options": {}
},
"typeVersion": 1
},
{
"id": "c0555ba6-a1bd-4aa9-a340-a9c617f8e6db",
"name": "Prepare Embedding Document",
"type": "n8n-nodes-base.set",
"position": [
1520,
1120
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "41a1d4ca-e5a5-4fb9-b249-8796ae759b33",
"name": "data",
"type": "string",
"value": "=## file location\n{{ [$json.directory, $json.fileName].join('/') }}\n## file created\n{{ $now.toISO() }}\n## file contents\n{{ $input.item.binary.data.data.base64Decode() }}"
},
{
"id": "c091704d-b81c-448b-8c90-156ef568b871",
"name": "file_location",
"type": "string",
"value": "={{ [$json.directory, $json.fileName].join('/') }}"
}
]
}
},
"typeVersion": 3.3
},
{
"id": "ffe8c363-0809-4d21-aa8f-34b0fc2dc57f",
"name": "Chat Trigger",
"type": "@n8n/n8n-nodes-langchain.chatTrigger",
"position": [
2280,
680
],
"webhookId": "37587fe0-b8db-4012-90a7-1f65b9bfd0df",
"parameters": {},
"typeVersion": 1
},
{
"id": "8d958669-60be-4bb2-80fc-2a6c7c7bfae6",
"name": "Question and Answer Chain",
"type": "@n8n/n8n-nodes-langchain.chainRetrievalQa",
"position": [
2500,
680
],
"parameters": {},
"typeVersion": 1.3
},
{
"id": "f143e438-8176-4923-a866-3f9a2a16793d",
"name": "Mistral Cloud Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatMistralCloud",
"position": [
2500,
840
],
"parameters": {
"model": "mistral-small-2402",
"options": {}
},
"credentials": {
"mistralCloudApi": {
"id": "EIl2QxhXAS9Hkg37",
"name": "Mistral Cloud account"
}
},
"typeVersion": 1
},
{
"id": "06dd8f4c-3b66-43e0-85c8-ec222e275f87",
"name": "Vector Store Retriever",
"type": "@n8n/n8n-nodes-langchain.retrieverVectorStore",
"position": [
2620,
840
],
"parameters": {},
"typeVersion": 1
},
{
"id": "2fdabcb5-a7a7-4e02-8c1b-9190e2e52385",
"name": "Embeddings Mistral Cloud1",
"type": "@n8n/n8n-nodes-langchain.embeddingsMistralCloud",
"position": [
2620,
1080
],
"parameters": {
"options": {}
},
"credentials": {
"mistralCloudApi": {
"id": "EIl2QxhXAS9Hkg37",
"name": "Mistral Cloud account"
}
},
"typeVersion": 1
},
{
"id": "e5664534-de07-481f-87dd-68d7d0715baa",
"name": "Remap for File_Added Flow",
"type": "n8n-nodes-base.set",
"position": [
1920,
700
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "840219e1-ed47-4b00-83fd-6b3c0bd71650",
"name": "file_added",
"type": "string",
"value": "={{ $('Set Variables').item.json.file_changed }}"
}
]
}
},
"typeVersion": 3.3
},
{
"id": "1fd14832-aafe-4d72-b4f2-7afc72df97dc",
"name": "Search For Existing Point",
"type": "n8n-nodes-base.httpRequest",
"position": [
1340,
280
],
"parameters": {
"url": "=http://qdrant:6333/collections/{{ $('Set Variables').item.json.qdrant_collection }}/points/scroll",
"method": "POST",
"options": {},
"jsonBody": "={\n \"filter\": {\n \"must\": [\n {\n \"key\": \"metadata.filter_by_filename\",\n \"match\": {\n \"value\": \"{{ $json.file_changed }}\"\n }\n }\n ]\n },\n \"limit\": 1,\n \"with_payload\": false,\n \"with_vector\": false\n}",
"sendBody": true,
"specifyBody": "json",
"authentication": "predefinedCredentialType",
"nodeCredentialType": "qdrantApi"
},
"credentials": {
"qdrantApi": {
"id": "NyinAS3Pgfik66w5",
"name": "QdrantApi account"
}
},
"typeVersion": 4.2
},
{
"id": "b5fa817f-82d6-41dd-9817-4c1dd9137b76",
"name": "Has Existing Point?",
"type": "n8n-nodes-base.if",
"position": [
1520,
280
],
"parameters": {
"options": {},
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "0392bac0-8fb5-406b-b59f-575edf5ab30d",
"operator": {
"type": "array",
"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json.result.points }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2
},
{
"id": "b0fa4fa4-5d1b-4a12-b8ba-a10d71f31f94",
"name": "Delete Existing Point",
"type": "n8n-nodes-base.httpRequest",
"position": [
1720,
700
],
"parameters": {
"url": "=http://qdrant:6333/collections/{{ $('Set Variables').item.json.qdrant_collection }}/points/delete",
"method": "POST",
"options": {},
"sendBody": true,
"authentication": "predefinedCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "points",
"value": "={{ $json.result.points.map(point => point.id) }}"
}
]
},
"nodeCredentialType": "qdrantApi"
},
"credentials": {
"qdrantApi": {
"id": "NyinAS3Pgfik66w5",
"name": "QdrantApi account"
}
},
"typeVersion": 4.2
},
{
"id": "5408adfe-4d6b-407c-aac7-e87c9b1a1592",
"name": "Search For Existing Point1",
"type": "n8n-nodes-base.httpRequest",
"position": [
1340,
700
],
"parameters": {
"url": "=http://qdrant:6333/collections/{{ $('Set Variables').item.json.qdrant_collection }}/points/scroll",
"method": "POST",
"options": {},
"jsonBody": "={\n \"filter\": {\n \"must\": [\n {\n \"key\": \"metadata.filter_by_filename\",\n \"match\": {\n \"value\": \"{{ $json.file_changed }}\"\n }\n }\n ]\n },\n \"limit\": 1,\n \"with_payload\": false,\n \"with_vector\": false\n}",
"sendBody": true,
"specifyBody": "json",
"authentication": "predefinedCredentialType",
"nodeCredentialType": "qdrantApi"
},
"credentials": {
"qdrantApi": {
"id": "NyinAS3Pgfik66w5",
"name": "QdrantApi account"
}
},
"typeVersion": 4.2
},
{
"id": "fac43587-0d24-4d6e-a0d5-8cc8f9615967",
"name": "Has Existing Point?1",
"type": "n8n-nodes-base.if",
"position": [
1520,
700
],
"parameters": {
"options": {},
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "0392bac0-8fb5-406b-b59f-575edf5ab30d",
"operator": {
"type": "array",
"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json.result.points }}",
"rightValue": ""
}
]
}
},
"typeVersion": 2
},
{
"id": "010baacd-fac1-4cc1-86bf-9d6ef11916fe",
"name": "Delete Existing Point1",
"type": "n8n-nodes-base.httpRequest",
"position": [
1700,
280
],
"parameters": {
"url": "=http://qdrant:6333/collections/{{ $('Set Variables').item.json.qdrant_collection }}/points/delete",
"method": "POST",
"options": {},
"sendBody": true,
"authentication": "predefinedCredentialType",
"bodyParameters": {
"parameters": [
{
"name": "points",
"value": "={{ $json.result.points.map(point => point.id) }}"
}
]
},
"nodeCredentialType": "qdrantApi"
},
"credentials": {
"qdrantApi": {
"id": "NyinAS3Pgfik66w5",
"name": "QdrantApi account"
}
},
"typeVersion": 4.2
},
{
"id": "2d6fb29c-2fac-41de-9ad0-cc781b246378",
"name": "Handle File Event",
"type": "n8n-nodes-base.switch",
"position": [
1000,
700
],
"parameters": {
"rules": {
"values": [
{
"outputKey": "file_deleted",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "a1f6d86a-9805-4d0e-ac70-90c9cf0ad339",
"operator": {
"type": "string",
"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json.file_deleted }}",
"rightValue": ""
}
]
},
"renameOutput": true
},
{
"outputKey": "file_changed",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "d15cde67-b5b0-4676-b4fb-ead749147392",
"operator": {
"type": "string",
"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json.file_changed }}",
"rightValue": ""
}
]
},
"renameOutput": true
},
{
"outputKey": "file_added",
"conditions": {
"options": {
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"operator": {
"type": "string",
"operation": "notEmpty",
"singleValue": true
},
"leftValue": "={{ $json.file_added }}",
"rightValue": ""
}
]
},
"renameOutput": true
}
]
},
"options": {}
},
"typeVersion": 3
},
{
"id": "da91b2aa-613c-4e3e-af83-fbd3bb7e922e",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
1280,
123.92779403575491
],
"parameters": {
"color": 7,
"width": 847.032584995578,
"height": 335.8400964393443,
"content": "## Step 2. When files are removed, the vector point is cleared.\n[Learn how to delete points using the Qdrant API](https://qdrant.tech/documentation/concepts/points/#delete-points)\n\nTo keep our vectorstore relevant, we'll implement a simple synchronisation system whereby documents deleted from the local file folder are also purged from Qdrant. This can be simply achieved using Qdrant APIs."
},
"typeVersion": 1
},
{
"id": "2f9f5b2b-6504-4b27-a0c4-f3373df352df",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
1280,
480
],
"parameters": {
"color": 7,
"width": 855.9952607674757,
"height": 433.01782147687817,
"content": "## Step 3. When files are updated, the vector point is updated.\n[Learn how to delete points using the Qdrant API](https://qdrant.tech/documentation/concepts/points/#delete-points)\n\nSimilarly to the files deleted branch, when we encounter a change in a file we'll update the matching vector point in Qdrant to ensure our vector store stays relevant. Here, we can achieve this my deleting the existing vector point and creating it anew with the updated bank statement."
},
"typeVersion": 1
},
{
"id": "38128b7f-d0f2-405c-a7de-662df812c344",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
1280,
940
],
"parameters": {
"color": 7,
"width": 846.8204626627492,
"height": 629.9714759033081,
"content": "## Step 4. When new files are added, add them to Qdrant Vectorstore.\n[Read more about the Qdrant node](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.vectorstoreqdrant)\n\nUsing Qdrant, we'll able to create a simple yet powerful RAG based application for our bank statements. One of Qdrant's most powerful features is its filtering system, we'll use it to manage the synchronisation of our local file system and Qdrant."
},
"typeVersion": 1
},
{
"id": "e85e2a30-e775-42fe-a12a-ac5de4eb4673",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
2180,
491.43199269284935
],
"parameters": {
"color": 7,
"width": 744.4578330639196,
"height": 759.7908149448928,
"content": "## Step 5. Create AI Agent expert on historic bank statements \n[Read more about the Question & Answer Chain](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.chainretrievalqa)\n\nFinally, let's use a Question & Answer AI node to combine the Mistral AI model and Qdrant as the vector store retriever to create a local expert for all our bank statements questions. "
},
"typeVersion": 1
},
{
"id": "7b29b0b9-ffee-4456-b036-9b39400d2b31",
"name": "Qdrant Vector Store",
"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
"position": [
1700,
1120
],
"parameters": {
"mode": "insert",
"options": {},
"qdrantCollection": {
"__rl": true,
"mode": "id",
"value": "={{ $('Set Variables').item.json.qdrant_collection }}"
}
},
"credentials": {
"qdrantApi": {
"id": "NyinAS3Pgfik66w5",
"name": "QdrantApi account"
}
},
"typeVersion": 1
},
{
"id": "1857bebb-b492-415e-96c8-235329bfd28a",
"name": "Qdrant Vector Store1",
"type": "@n8n/n8n-nodes-langchain.vectorStoreQdrant",
"position": [
2620,
960
],
"parameters": {
"qdrantCollection": {
"__rl": true,
"mode": "id",
"value": "BankStatements"
}
},
"credentials": {
"qdrantApi": {
"id": "NyinAS3Pgfik66w5",
"name": "QdrantApi account"
}
},
"typeVersion": 1
}
],
"pinData": {},
"connections": {
"Read File": {
"main": [
[
{
"node": "Prepare Embedding Document",
"type": "main",
"index": 0
}
]
]
},
"Chat Trigger": {
"main": [
[
{
"node": "Question and Answer Chain",
"type": "main",
"index": 0
}
]
]
},
"Set Variables": {
"main": [
[
{
"node": "Handle File Event",
"type": "main",
"index": 0
}
]
]
},
"Handle File Event": {
"main": [
[
{
"node": "Search For Existing Point",
"type": "main",
"index": 0
}
],
[
{
"node": "Search For Existing Point1",
"type": "main",
"index": 0
}
],
[
{
"node": "Read File",
"type": "main",
"index": 0
}
]
]
},
"Local File Trigger": {
"main": [
[
{
"node": "Set Variables",
"type": "main",
"index": 0
}
]
]
},
"Default Data Loader": {
"ai_document": [
[
{
"node": "Qdrant Vector Store",
"type": "ai_document",
"index": 0
}
]
]
},
"Has Existing Point?": {
"main": [
[
{
"node": "Delete Existing Point1",
"type": "main",
"index": 0
}
]
]
},
"Has Existing Point?1": {
"main": [
[
{
"node": "Delete Existing Point",
"type": "main",
"index": 0
}
]
]
},
"Qdrant Vector Store1": {
"ai_vectorStore": [
[
{
"node": "Vector Store Retriever",
"type": "ai_vectorStore",
"index": 0
}
]
]
},
"Delete Existing Point": {
"main": [
[
{
"node": "Remap for File_Added Flow",
"type": "main",
"index": 0
}
]
]
},
"Vector Store Retriever": {
"ai_retriever": [
[
{
"node": "Question and Answer Chain",
"type": "ai_retriever",
"index": 0
}
]
]
},
"Embeddings Mistral Cloud": {
"ai_embedding": [
[
{
"node": "Qdrant Vector Store",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Mistral Cloud Chat Model": {
"ai_languageModel": [
[
{
"node": "Question and Answer Chain",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Embeddings Mistral Cloud1": {
"ai_embedding": [
[
{
"node": "Qdrant Vector Store1",
"type": "ai_embedding",
"index": 0
}
]
]
},
"Remap for File_Added Flow": {
"main": [
[
{
"node": "Read File",
"type": "main",
"index": 0
}
]
]
},
"Search For Existing Point": {
"main": [
[
{
"node": "Has Existing Point?",
"type": "main",
"index": 0
}
]
]
},
"Prepare Embedding Document": {
"main": [
[
{
"node": "Qdrant Vector Store",
"type": "main",
"index": 0
}
]
]
},
"Search For Existing Point1": {
"main": [
[
{
"node": "Has Existing Point?1",
"type": "main",
"index": 0
}
]
]
},
"When clicking \"Test workflow\"": {
"main": [
[
{
"node": "Set Variables",
"type": "main",
"index": 0
}
]
]
},
"Recursive Character Text Splitter": {
"ai_textSplitter": [
[
{
"node": "Default Data Loader",
"type": "ai_textSplitter",
"index": 0
}
]
]
}
}
}Workflow n8n gestion des données, intelligence artificielle : pour qui est ce workflow ?
Ce workflow s'adresse aux entreprises de taille moyenne à grande qui cherchent à automatiser la gestion de leurs fichiers et à intégrer des solutions d'intelligence artificielle. Les équipes techniques et opérationnelles, ainsi que les responsables de la gestion des données, trouveront un grand intérêt à cette automatisation n8n.
Workflow n8n gestion des données, intelligence artificielle : problème résolu
Ce workflow résout le problème de la gestion manuelle des fichiers, qui peut être chronophage et sujet à des erreurs. En automatisant le traitement des données, il élimine les frustrations liées à la recherche d'informations et à la duplication des efforts. Les utilisateurs bénéficient d'une solution rapide et efficace pour gérer leurs fichiers, ce qui leur permet de se concentrer sur des tâches à plus forte valeur ajoutée.
Workflow n8n gestion des données, intelligence artificielle : étapes du workflow
Étape 1 : Le workflow est déclenché par l'ajout d'un fichier via le noeud 'Local File Trigger'.
- Étape 1 : Les variables nécessaires sont définies avec le noeud 'Set Variables'.
- Étape 2 : Le contenu du fichier est lu grâce au noeud 'Read File'.
- Étape 3 : Les données sont chargées et traitées avec 'Default Data Loader' et 'Embeddings Mistral Cloud'.
- Étape 4 : Le noeud 'Chat Trigger' permet d'interagir avec les utilisateurs, tandis que le 'Question and Answer Chain' fournit des réponses basées sur les données traitées.
- Étape 5 : Des vérifications sont effectuées pour s'assurer qu'aucun point existant n'est dupliqué, grâce aux noeuds 'Has Existing Point?' et 'Delete Existing Point'.
Workflow n8n gestion des données, intelligence artificielle : guide de personnalisation
Pour personnaliser ce workflow, vous pouvez modifier le chemin du fichier dans le noeud 'Local File Trigger' pour pointer vers votre répertoire spécifique. Les paramètres des noeuds 'Set Variables' et 'Prepare Embedding Document' peuvent être ajustés pour répondre à vos besoins spécifiques en matière de données. Si vous souhaitez intégrer d'autres outils, vous pouvez ajouter des noeuds HTTP pour des appels API externes. Assurez-vous également de sécuriser le workflow en configurant les authentifications nécessaires dans les noeuds HTTP.