Workflow n8n
Automatisation n8n : Chaînage de modèles LLM en temps réel
Ce workflow n8n est conçu pour automatiser le chaînage de modèles de langage (LLM) en utilisant des requêtes HTTP et des modèles de chat d'Anthropic. Il s'adresse principalement aux entreprises qui souhaitent intégrer des capacités avancées de traitement du langage naturel dans leurs applications. Par exemple, ce workflow peut être utilisé pour générer des réponses automatiques dans un service client ou pour enrichir des contenus marketing avec des suggestions intelligentes. Le processus commence par un déclencheur manuel, où l'utilisateur clique sur 'Test workflow'. Ensuite, une requête HTTP est effectuée pour récupérer des données nécessaires. Les étapes suivantes impliquent l'utilisation de plusieurs modèles de chat d'Anthropic, permettant de traiter et de générer des réponses basées sur les entrées fournies. Les résultats sont ensuite fusionnés et restructurés pour une utilisation optimale. Ce workflow illustre parfaitement comment l'automatisation n8n peut simplifier des tâches complexes tout en offrant une flexibilité et une personnalisation élevées. En intégrant ce type de solution, les entreprises peuvent gagner en efficacité, réduire les erreurs humaines et améliorer l'expérience utilisateur grâce à des interactions plus fluides et intelligentes. Tags clés : automatisation, n8n, LLM.
Catégorie: Manual · Tags: automatisation, n8n, LLM, traitement du langage, intelligence artificielle❤ 0
Vue d'ensemble du workflow n8n
Schéma des nœuds et connexions de ce workflow n8n, généré à partir du JSON n8n.
Détail des nœuds du workflow n8n
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"id": "43gMd18arOcxqDcC",
"meta": {
"instanceId": "fb924c73af8f703905bc09c9ee8076f48c17b596ed05b18c0ff86915ef8a7c4a",
"templateCredsSetupCompleted": true
},
"name": "LLM Chaining examples",
"tags": [],
"nodes": [
{
"id": "35e53ce7-06b4-47ca-b7f3-b147bd059fcf",
"name": "When clicking ‘Test workflow’",
"type": "n8n-nodes-base.manualTrigger",
"position": [
200,
520
],
"parameters": {},
"typeVersion": 1
},
{
"id": "aeef734e-1c3b-4a91-93ae-2ae9c50951b8",
"name": "HTTP Request",
"type": "n8n-nodes-base.httpRequest",
"position": [
400,
520
],
"parameters": {
"url": "https://blog.n8n.io/",
"options": {}
},
"typeVersion": 4.2
},
{
"id": "7f6b95eb-df8c-4f0f-ba69-6b298d624ccd",
"name": "Markdown",
"type": "n8n-nodes-base.markdown",
"position": [
600,
520
],
"parameters": {
"html": "={{ $json.data }}",
"options": {},
"destinationKey": "markdown"
},
"typeVersion": 1
},
{
"id": "994dbe06-4c25-4fb3-a8f3-566eb5b66c6d",
"name": "Sticky Note",
"type": "n8n-nodes-base.stickyNote",
"position": [
160,
340
],
"parameters": {
"color": 4,
"width": 700,
"height": 360,
"content": "# Connect to one of the blue sections -->\n## This can be anything:\n- Chat input\n- Trigger from external system\n- CRON-scheduled event"
},
"typeVersion": 1
},
{
"id": "8ba3039d-dabf-43b7-ab35-117332f65ced",
"name": "Anthropic Chat Model",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
1460,
-20
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-3-7-sonnet-20250219",
"cachedResultName": "Claude 3.7 Sonnet"
},
"options": {
"temperature": 0.5
}
},
"credentials": {
"anthropicApi": {
"id": "cJno7gKlYez56WtP",
"name": "Anthropic account"
}
},
"typeVersion": 1.3
},
{
"id": "7e1da020-e01d-410c-aa7f-a19d6e1c368d",
"name": "Anthropic Chat Model1",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
1820,
-20
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-3-7-sonnet-20250219",
"cachedResultName": "Claude 3.7 Sonnet"
},
"options": {
"temperature": 0.5
}
},
"credentials": {
"anthropicApi": {
"id": "cJno7gKlYez56WtP",
"name": "Anthropic account"
}
},
"typeVersion": 1.3
},
{
"id": "620503cb-2d51-4102-8975-75255cf15b1b",
"name": "Anthropic Chat Model2",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
2180,
-20
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-3-7-sonnet-20250219",
"cachedResultName": "Claude 3.7 Sonnet"
},
"options": {
"temperature": 0.5
}
},
"credentials": {
"anthropicApi": {
"id": "cJno7gKlYez56WtP",
"name": "Anthropic account"
}
},
"typeVersion": 1.3
},
{
"id": "5f0d11ce-c1ea-4c36-8b2d-d3f70b19f0ba",
"name": "Anthropic Chat Model3",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
2540,
-20
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-3-7-sonnet-20250219",
"cachedResultName": "Claude 3.7 Sonnet"
},
"options": {
"temperature": 0.5
}
},
"credentials": {
"anthropicApi": {
"id": "cJno7gKlYez56WtP",
"name": "Anthropic account"
}
},
"typeVersion": 1.3
},
{
"id": "f973d01e-fad7-4143-8379-54438f5412cb",
"name": "Merge",
"type": "n8n-nodes-base.merge",
"position": [
2440,
360
],
"parameters": {
"mode": "combine",
"options": {
"includeUnpaired": true
},
"combineBy": "combineByPosition"
},
"typeVersion": 3.1
},
{
"id": "c7e58b90-bc96-421c-88f2-4e9f95f87248",
"name": "Simple Memory",
"type": "@n8n/n8n-nodes-langchain.memoryBufferWindow",
"position": [
2680,
780
],
"parameters": {
"sessionKey": "fixed_session",
"sessionIdType": "customKey",
"contextWindowLength": 10
},
"typeVersion": 1.3
},
{
"id": "0e606f7c-2cdb-4e34-8c0b-2303996077fb",
"name": "Clean memory",
"type": "@n8n/n8n-nodes-langchain.memoryManager",
"position": [
1500,
480
],
"parameters": {
"mode": "delete",
"deleteMode": "all"
},
"typeVersion": 1.1
},
{
"id": "af0fb574-9964-4f7d-8348-a2cf614b8562",
"name": "Initial prompts",
"type": "n8n-nodes-base.set",
"position": [
1880,
480
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "84a50c9c-2265-4dd6-a774-efc852615862",
"name": "system_prompt",
"type": "string",
"value": "You are a helpful assistant"
},
{
"id": "559f19f7-042c-465e-b85f-ab52cfbab04a",
"name": "step1",
"type": "string",
"value": "What is on this page?"
},
{
"id": "6791cd09-c5f7-48c8-b753-8d383db6863f",
"name": "step2",
"type": "string",
"value": "List all authors on this page"
},
{
"id": "1f92ac04-e5dd-4161-afde-14562aea454c",
"name": "step3",
"type": "string",
"value": "List all posts on this page"
},
{
"id": "ad8ee0b0-fa7d-4f4a-85a8-82d0d0dc0a40",
"name": "step4",
"type": "string",
"value": "Make a bold funny joke based on the content on this page"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "6743e44a-cc76-4e73-b4f3-ba7c65d179d3",
"name": "Split Out",
"type": "n8n-nodes-base.splitOut",
"position": [
2240,
480
],
"parameters": {
"include": "selectedOtherFields",
"options": {},
"fieldToSplitOut": "data",
"fieldsToInclude": "system_prompt"
},
"typeVersion": 1
},
{
"id": "caddd26c-ee84-455f-8ee6-aecf21536930",
"name": "Reshape",
"type": "n8n-nodes-base.set",
"position": [
2060,
480
],
"parameters": {
"mode": "raw",
"include": "selected",
"options": {},
"jsonOutput": "={ \"data\" : {{ Object.entries($json).filter(([key]) => key !== \"system_prompt\").map(([key, value]) => ({ step: key, instruction: value })) }}\n}",
"includeFields": "system_prompt",
"includeOtherFields": true
},
"typeVersion": 3.4
},
{
"id": "bd244988-d074-42f3-af42-960e5aa1d35d",
"name": "Sticky Note1",
"type": "n8n-nodes-base.stickyNote",
"position": [
1840,
400
],
"parameters": {
"width": 540,
"height": 240,
"content": "# An array of prompts here"
},
"typeVersion": 1
},
{
"id": "7e9e5287-8d4e-43a9-b8cf-ae26a177bfbb",
"name": "Anthropic Chat Model4",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
2600,
600
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-3-7-sonnet-20250219",
"cachedResultName": "Claude 3.7 Sonnet"
},
"options": {
"thinking": false,
"temperature": 0.5
}
},
"credentials": {
"anthropicApi": {
"id": "cJno7gKlYez56WtP",
"name": "Anthropic account"
}
},
"typeVersion": 1.3
},
{
"id": "47816a45-b906-47ef-9510-c63867bfc8b7",
"name": "Merge2",
"type": "n8n-nodes-base.merge",
"position": [
1860,
1120
],
"parameters": {
"mode": "combine",
"options": {},
"combineBy": "combineAll"
},
"typeVersion": 3
},
{
"id": "e63b89a1-c2ca-4ed2-ae50-e3a7b429609c",
"name": "Sticky Note2",
"type": "n8n-nodes-base.stickyNote",
"position": [
2040,
1020
],
"parameters": {
"width": 320,
"height": 520,
"content": "## Make sure URL matches\n### ⚠️ Cloud users!\nReplace `{{ $env.WEBHOOK_URL }}` \nwith your n8n instance URL"
},
"typeVersion": 1
},
{
"id": "7b99df1a-bf6c-4cf1-b58a-346873136715",
"name": "Basic LLM Chain4",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
2440,
1300
],
"parameters": {
"text": "={{ $json.body.userprompt }}\n\nHere's page data:\n~~~~\n{{ $json.body.markdown }}\n~~~~",
"promptType": "define"
},
"typeVersion": 1.5
},
{
"id": "6f6e0667-5164-4b65-a796-1d2112c7c072",
"name": "Split Out1",
"type": "n8n-nodes-base.splitOut",
"position": [
1680,
1340
],
"parameters": {
"options": {},
"fieldToSplitOut": "userprompt"
},
"typeVersion": 1
},
{
"id": "9dfd2145-2427-4131-92d2-99aca620217f",
"name": "Anthropic Chat Model5",
"type": "@n8n/n8n-nodes-langchain.lmChatAnthropic",
"position": [
2420,
1460
],
"parameters": {
"model": {
"__rl": true,
"mode": "list",
"value": "claude-3-7-sonnet-20250219",
"cachedResultName": "Claude 3.7 Sonnet"
},
"options": {
"thinking": false,
"temperature": 0.5
}
},
"credentials": {
"anthropicApi": {
"id": "cJno7gKlYez56WtP",
"name": "Anthropic account"
}
},
"typeVersion": 1.3
},
{
"id": "616fc635-107d-4929-b9d6-4ccd34e42909",
"name": "Webhook",
"type": "n8n-nodes-base.webhook",
"position": [
2140,
1400
],
"webhookId": "58d2b899-e09c-45bf-b59b-961a5d7a2470",
"parameters": {
"path": "58d2b899-e09c-45bf-b59b-961a5d7a2470",
"options": {},
"httpMethod": "POST",
"responseMode": "lastNode"
},
"typeVersion": 2
},
{
"id": "c863252b-f8b6-4704-be4e-a69d3005a85a",
"name": "CONNECT ME",
"type": "n8n-nodes-base.noOp",
"position": [
1240,
-220
],
"parameters": {},
"typeVersion": 1
},
{
"id": "90ab4402-cbea-4441-9097-558ec72e5d38",
"name": "CONNECT ME1",
"type": "n8n-nodes-base.noOp",
"position": [
1280,
340
],
"parameters": {},
"typeVersion": 1
},
{
"id": "1c04650f-8043-496f-aeab-866e85548f9d",
"name": "CONNECT ME2",
"type": "n8n-nodes-base.noOp",
"position": [
1280,
1100
],
"parameters": {},
"typeVersion": 1
},
{
"id": "4097f12d-eba7-477a-9152-da5eb8c9aa03",
"name": "Sticky Note3",
"type": "n8n-nodes-base.stickyNote",
"position": [
960,
-300
],
"parameters": {
"color": 5,
"width": 1980,
"height": 440,
"content": "# 1 - Naive Chaining\n### PROs:\n- Easy to setup\n- Beginner-friendly\n\n### CONs\n- Not scalable\n- Hard to maintain long chains\n- SLOOOW!"
},
"typeVersion": 1
},
{
"id": "ce806bc6-a57e-47da-bbba-4698c3956022",
"name": "Sticky Note4",
"type": "n8n-nodes-base.stickyNote",
"position": [
960,
240
],
"parameters": {
"color": 5,
"width": 2160,
"height": 660,
"content": "# 2 - Iterative Agent Processing\n\n### PROs:\n- Scalable\n- All inputs & outputs in a single node\n- Supports Agent memory\n\n### CONs\n- Still Slow!"
},
"typeVersion": 1
},
{
"id": "49c4507f-de1e-422b-8058-db82668614d3",
"name": "Sticky Note5",
"type": "n8n-nodes-base.stickyNote",
"position": [
960,
1000
],
"parameters": {
"color": 5,
"width": 1880,
"height": 600,
"content": "# 3 - Parallel Processing\n\n### PROs:\n- Scalable\n- All inputs & outputs in a single place\n- FAST!\n\n### CONs\n- Independent requests\n (no Agent memory)"
},
"typeVersion": 1
},
{
"id": "c30b8132-9291-4855-89ec-6a98bcee8247",
"name": "Sticky Note6",
"type": "n8n-nodes-base.stickyNote",
"position": [
1420,
1260
],
"parameters": {
"width": 400,
"height": 240,
"content": "# Array of prompts here"
},
"typeVersion": 1
},
{
"id": "4c1b5816-7393-47f6-8a88-008d8deea119",
"name": "Initial prompts1",
"type": "n8n-nodes-base.set",
"position": [
1460,
1340
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "ed7f1cc6-99d3-481c-b5fb-d9900d6ee0f6",
"name": "userprompt",
"type": "array",
"value": "=[\n\"What is on this page?\",\n\"List all authors on this page\",\n\"List all posts on this page\",\n\"Make a bold funny joke based on the content on this page\"\n]"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "8248a20f-1f90-42b0-8167-7ddcc90242a2",
"name": "LLM Chain - Step 1",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
1500,
-220
],
"parameters": {
"text": "={{ $('Markdown').first().json.markdown }}",
"messages": {
"messageValues": [
{
"message": "What is on this page?"
}
]
},
"promptType": "define"
},
"typeVersion": 1.6
},
{
"id": "3788b23b-ccdc-4326-8ce0-1e57934d23bd",
"name": "LLM Chain - Step 2",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
1860,
-220
],
"parameters": {
"text": "={{ $('Markdown').first().json.markdown }}",
"messages": {
"messageValues": [
{
"message": "List all authors on this page"
}
]
},
"promptType": "define"
},
"typeVersion": 1.6
},
{
"id": "89e69a39-bf13-4599-8ddc-a01c4590fb9c",
"name": "LLM Chain - Step 3",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
2220,
-220
],
"parameters": {
"text": "={{ $('Markdown').first().json.markdown }}",
"messages": {
"messageValues": [
{
"message": "List all posts on this page"
}
]
},
"promptType": "define"
},
"typeVersion": 1.6
},
{
"id": "7e395991-9404-490e-8946-0da8f81e7243",
"name": "LLM Chain - Step 4",
"type": "@n8n/n8n-nodes-langchain.chainLlm",
"position": [
2580,
-220
],
"parameters": {
"text": "={{ $('Markdown').first().json.markdown }}",
"messages": {
"messageValues": [
{
"message": "Make a bold funny joke based on the content on this page"
}
]
},
"promptType": "define"
},
"typeVersion": 1.6
},
{
"id": "efb8d836-8a4a-4a70-baed-4a9b77461aca",
"name": "All LLM steps here - sequentially",
"type": "@n8n/n8n-nodes-langchain.agent",
"position": [
2640,
440
],
"parameters": {
"text": "={{ $json.markdown || \"\" }}\n{{ `Your task: ${$json.data.step}. ${$json.data.instruction}` }}",
"options": {
"systemMessage": "={{ $json.system_prompt }}"
},
"promptType": "define"
},
"typeVersion": 1.8
},
{
"id": "926b1705-a24c-4659-bf61-8ed97ade7290",
"name": "LLM steps - parallel",
"type": "n8n-nodes-base.httpRequest",
"position": [
2140,
1240
],
"parameters": {
"url": "={{ $env.WEBHOOK_URL }}webhook/58d2b899-e09c-45bf-b59b-961a5d7a2470",
"method": "POST",
"options": {},
"jsonBody": "={{ $json }}",
"sendBody": true,
"specifyBody": "json"
},
"typeVersion": 4.2
},
{
"id": "7748574b-1abd-4697-9644-db8bb79fb08d",
"name": "Merge output with initial prompts",
"type": "n8n-nodes-base.merge",
"position": [
2440,
1140
],
"parameters": {
"mode": "combine",
"options": {},
"combineBy": "combineByPosition"
},
"typeVersion": 3.1
},
{
"id": "b207d83b-ecda-4a9f-af78-cfbb2253c119",
"name": "Merge output with initial prompts1",
"type": "n8n-nodes-base.merge",
"position": [
3000,
380
],
"parameters": {
"mode": "combine",
"options": {},
"combineBy": "combineByPosition"
},
"typeVersion": 3.1
}
],
"active": true,
"pinData": {},
"settings": {
"callerPolicy": "workflowsFromSameOwner",
"executionOrder": "v1",
"saveDataSuccessExecution": "all"
},
"versionId": "7b1849db-1c4c-4943-89b1-184926649776",
"connections": {
"Merge": {
"main": [
[
{
"node": "All LLM steps here - sequentially",
"type": "main",
"index": 0
},
{
"node": "Merge output with initial prompts1",
"type": "main",
"index": 0
}
]
]
},
"Merge2": {
"main": [
[
{
"node": "LLM steps - parallel",
"type": "main",
"index": 0
},
{
"node": "Merge output with initial prompts",
"type": "main",
"index": 0
}
]
]
},
"Reshape": {
"main": [
[
{
"node": "Split Out",
"type": "main",
"index": 0
}
]
]
},
"Webhook": {
"main": [
[
{
"node": "Basic LLM Chain4",
"type": "main",
"index": 0
}
]
]
},
"Markdown": {
"main": [
[]
]
},
"Split Out": {
"main": [
[
{
"node": "Merge",
"type": "main",
"index": 1
}
]
]
},
"CONNECT ME": {
"main": [
[
{
"node": "LLM Chain - Step 1",
"type": "main",
"index": 0
}
]
]
},
"Split Out1": {
"main": [
[
{
"node": "Merge2",
"type": "main",
"index": 1
}
]
]
},
"CONNECT ME1": {
"main": [
[
{
"node": "Clean memory",
"type": "main",
"index": 0
},
{
"node": "Merge",
"type": "main",
"index": 0
}
]
]
},
"CONNECT ME2": {
"main": [
[
{
"node": "Initial prompts1",
"type": "main",
"index": 0
},
{
"node": "Merge2",
"type": "main",
"index": 0
}
]
]
},
"Clean memory": {
"main": [
[
{
"node": "Initial prompts",
"type": "main",
"index": 0
}
]
]
},
"HTTP Request": {
"main": [
[
{
"node": "Markdown",
"type": "main",
"index": 0
}
]
]
},
"Simple Memory": {
"ai_memory": [
[
{
"node": "All LLM steps here - sequentially",
"type": "ai_memory",
"index": 0
},
{
"node": "Clean memory",
"type": "ai_memory",
"index": 0
}
]
]
},
"Initial prompts": {
"main": [
[
{
"node": "Reshape",
"type": "main",
"index": 0
}
]
]
},
"Initial prompts1": {
"main": [
[
{
"node": "Split Out1",
"type": "main",
"index": 0
}
]
]
},
"LLM Chain - Step 1": {
"main": [
[
{
"node": "LLM Chain - Step 2",
"type": "main",
"index": 0
}
]
]
},
"LLM Chain - Step 2": {
"main": [
[
{
"node": "LLM Chain - Step 3",
"type": "main",
"index": 0
}
]
]
},
"LLM Chain - Step 3": {
"main": [
[
{
"node": "LLM Chain - Step 4",
"type": "main",
"index": 0
}
]
]
},
"Anthropic Chat Model": {
"ai_languageModel": [
[
{
"node": "LLM Chain - Step 1",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"LLM steps - parallel": {
"main": [
[
{
"node": "Merge output with initial prompts",
"type": "main",
"index": 1
}
]
]
},
"Anthropic Chat Model1": {
"ai_languageModel": [
[
{
"node": "LLM Chain - Step 2",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Anthropic Chat Model2": {
"ai_languageModel": [
[
{
"node": "LLM Chain - Step 3",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Anthropic Chat Model3": {
"ai_languageModel": [
[
{
"node": "LLM Chain - Step 4",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Anthropic Chat Model4": {
"ai_languageModel": [
[
{
"node": "All LLM steps here - sequentially",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"Anthropic Chat Model5": {
"ai_languageModel": [
[
{
"node": "Basic LLM Chain4",
"type": "ai_languageModel",
"index": 0
}
]
]
},
"All LLM steps here - sequentially": {
"main": [
[
{
"node": "Merge output with initial prompts1",
"type": "main",
"index": 1
}
]
]
},
"When clicking ‘Test workflow’": {
"main": [
[
{
"node": "HTTP Request",
"type": "main",
"index": 0
}
]
]
}
}
}Pour qui est ce workflow ?
Ce workflow s'adresse aux développeurs, aux équipes de marketing et aux entreprises technologiques qui cherchent à intégrer des solutions d'intelligence artificielle dans leurs processus. Un niveau technique intermédiaire à avancé est recommandé pour la mise en œuvre.
Problème résolu
Ce workflow résout le problème de l'intégration des modèles de langage dans des applications pratiques, permettant ainsi aux entreprises de générer automatiquement des réponses et de traiter des données textuelles de manière efficace. Il élimine les tâches manuelles répétitives et réduit le temps nécessaire pour obtenir des résultats pertinents. Grâce à cette automatisation, les utilisateurs peuvent se concentrer sur des tâches à plus forte valeur ajoutée.
Étapes du workflow
Étape 1 : Le workflow est déclenché manuellement par l'utilisateur. Étape 2 : Une requête HTTP est effectuée pour récupérer les données nécessaires. Étape 3 : Les données sont traitées à travers plusieurs modèles de chat d'Anthropic, chacun générant des réponses basées sur les entrées fournies. Étape 4 : Les résultats sont fusionnés et restructurés pour une utilisation optimale. Étape 5 : Les notes autocollantes sont utilisées pour afficher des informations pertinentes tout au long du processus.
Guide de personnalisation du workflow n8n
Pour personnaliser ce workflow, vous pouvez modifier l'URL de la requête HTTP pour pointer vers votre source de données. Les modèles de chat d'Anthropic peuvent être ajustés en fonction des besoins spécifiques de votre projet. Il est également possible d'ajouter ou de supprimer des étapes selon les exigences de votre flux de travail. Assurez-vous de sécuriser les données en configurant correctement les paramètres de mémoire et de nettoyage pour éviter toute fuite d'informations sensibles.