Construction d'une API de réponse aux questions de documents avec des vecteurs PDF et des Webhooks
Ceci est unInternal Wiki, AI RAG, Multimodal AIworkflow d'automatisation du domainecontenant 11 nœuds.Utilise principalement des nœuds comme If, Code, Webhook, PdfVector, RespondToWebhook. Construire une API de questions-réponses sur documents avec PDF vector et Webhooks
- •Point de terminaison HTTP Webhook (généré automatiquement par n8n)
Nœuds utilisés (11)
Catégorie
{
"meta": {
"instanceId": "placeholder"
},
"nodes": [
{
"id": "overview-note",
"name": "API Aperçu",
"type": "n8n-nodes-base.stickyNote",
"position": [
50,
50
],
"parameters": {
"color": 5,
"width": 350,
"height": 160,
"content": "## 🤖 Document Q&A API\n\nRESTful service for document intelligence:\n• **Webhook** endpoint accepts documents\n• **AI processes** questions in context\n• **Returns** JSON with answers & citations\n• **Sub-second** response times"
},
"typeVersion": 1
},
{
"id": "request-note",
"name": "Format de Requête",
"type": "n8n-nodes-base.stickyNote",
"position": [
450,
450
],
"parameters": {
"width": 280,
"height": 180,
"content": "## 📥 API Request\n\n**POST** to `/document-qa`\n\nBody:\n```json\n{\n \"question\": \"Your question\",\n \"maxTokens\": 500,\n \"file\": <binary>\n}\n```"
},
"typeVersion": 1
},
{
"id": "process-note",
"name": "Traitement des Questions-Réponses",
"type": "n8n-nodes-base.stickyNote",
"position": [
850,
450
],
"parameters": {
"width": 260,
"height": 160,
"content": "## 🔍 AI Processing\n\nPDF Vector:\n• Parses document\n• Finds relevant sections\n• Generates answer\n• Includes citations\n\n💡 GPT-4 powered"
},
"typeVersion": 1
},
{
"id": "response-note",
"name": "Format de Réponse",
"type": "n8n-nodes-base.stickyNote",
"position": [
1150,
450
],
"parameters": {
"color": 6,
"width": 260,
"height": 180,
"content": "## 📤 API Response\n\n```json\n{\n \"success\": true,\n \"answer\": \"...\",\n \"sources\": [...],\n \"confidence\": 0.95\n}\n```\n\n✅ Production ready!"
},
"typeVersion": 1
},
{
"id": "webhook-trigger",
"name": "Webhook",
"type": "n8n-nodes-base.webhook",
"notes": "API endpoint for document Q&A",
"position": [
250,
300
],
"webhookId": "doc-qa-webhook",
"parameters": {
"path": "doc-qa",
"httpMethod": "POST"
},
"typeVersion": 1
},
{
"id": "validate-request",
"name": "Valider la Requête",
"type": "n8n-nodes-base.code",
"notes": "Validate and prepare request",
"position": [
450,
300
],
"parameters": {
"jsCode": "// Validate incoming request\nconst body = $input.first().json.body;\nconst errors = [];\n\nif (!body.documentUrl && !body.documentId) {\n errors.push('Either documentUrl or documentId is required');\n}\nif (!body.question) {\n errors.push('Question is required');\n}\n\n// Generate session ID if not provided\nconst sessionId = body.sessionId || `session-${Date.now()}`;\n\nreturn [{\n json: {\n ...body,\n sessionId,\n valid: errors.length === 0,\n errors,\n timestamp: new Date().toISOString()\n }\n}];"
},
"typeVersion": 2
},
{
"id": "check-valid",
"name": "Requête Valide ?",
"type": "n8n-nodes-base.if",
"position": [
650,
300
],
"parameters": {
"conditions": {
"boolean": [
{
"value1": "={{ $json.valid }}",
"value2": true
}
]
}
},
"typeVersion": 1
},
{
"id": "pdfvector-ask",
"name": "PDF Vector - Poser une Question",
"type": "n8n-nodes-pdfvector.pdfVector",
"notes": "Get answer from document",
"position": [
850,
250
],
"parameters": {
"url": "={{ $json.documentUrl }}",
"prompt": "Answer the following question about this document or image: {{ $json.question }}",
"resource": "document",
"inputType": "url",
"operation": "ask"
},
"typeVersion": 1
},
{
"id": "format-success",
"name": "Formater la Réponse de Succès",
"type": "n8n-nodes-base.code",
"notes": "Prepare successful response",
"position": [
1050,
250
],
"parameters": {
"jsCode": "// Prepare successful response\nconst answer = $json.answer;\nconst request = $node['Validate Request'].json;\n\n// Calculate confidence score based on answer length and keywords\nlet confidence = 0.8; // Base confidence\nif (answer.length > 100) confidence += 0.1;\nif (answer.toLowerCase().includes('specifically') || answer.toLowerCase().includes('according to')) confidence += 0.1;\nconfidence = Math.min(confidence, 1.0);\n\nreturn [{\n json: {\n success: true,\n data: {\n answer,\n confidence,\n sessionId: request.sessionId,\n documentUrl: request.documentUrl,\n question: request.question\n },\n metadata: {\n processedAt: new Date().toISOString(),\n responseTime: Date.now() - new Date(request.timestamp).getTime(),\n creditsUsed: 1\n }\n }\n}];"
},
"typeVersion": 2
},
{
"id": "format-error",
"name": "Formater la Réponse d'Erreur",
"type": "n8n-nodes-base.code",
"notes": "Prepare error response",
"position": [
850,
350
],
"parameters": {
"jsCode": "// Prepare error response\nconst errors = $json.errors || ['An error occurred processing your request'];\n\nreturn [{\n json: {\n success: false,\n errors,\n message: 'Invalid request',\n timestamp: new Date().toISOString()\n }\n}];"
},
"typeVersion": 2
},
{
"id": "webhook-response",
"name": "Envoyer la Réponse",
"type": "n8n-nodes-base.respondToWebhook",
"notes": "Send API response",
"position": [
1250,
300
],
"parameters": {
"respondWith": "json",
"responseBody": "={{ JSON.stringify($json) }}",
"responseHeaders": {
"entries": [
{
"name": "Content-Type",
"value": "application/json"
}
]
}
},
"typeVersion": 1
}
],
"connections": {
"webhook-trigger": {
"main": [
[
{
"node": "validate-request",
"type": "main",
"index": 0
}
]
]
},
"check-valid": {
"main": [
[
{
"node": "pdfvector-ask",
"type": "main",
"index": 0
}
],
[
{
"node": "format-error",
"type": "main",
"index": 0
}
]
]
},
"validate-request": {
"main": [
[
{
"node": "check-valid",
"type": "main",
"index": 0
}
]
]
},
"format-error": {
"main": [
[
{
"node": "webhook-response",
"type": "main",
"index": 0
}
]
]
},
"format-success": {
"main": [
[
{
"node": "webhook-response",
"type": "main",
"index": 0
}
]
]
},
"pdfvector-ask": {
"main": [
[
{
"node": "format-success",
"type": "main",
"index": 0
}
]
]
}
}
}Comment utiliser ce workflow ?
Copiez le code de configuration JSON ci-dessus, créez un nouveau workflow dans votre instance n8n et sélectionnez "Importer depuis le JSON", collez la configuration et modifiez les paramètres d'authentification selon vos besoins.
Dans quelles scénarios ce workflow est-il adapté ?
Intermédiaire - Wiki interne, RAG IA, IA Multimodale
Est-ce payant ?
Ce workflow est entièrement gratuit et peut être utilisé directement. Veuillez noter que les services tiers utilisés dans le workflow (comme l'API OpenAI) peuvent nécessiter un paiement de votre part.
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