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Homelab/services/n8n/workflows/homelab-integration-advisor.json

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{
"name": "Homelab Integration Advisor",
"nodes": [
{
"parameters": {
"rule": {
"interval": [
{
"field": "days",
"daysInterval": 1,
"triggerAtHour": 9
}
]
}
},
"id": "daily-trigger",
"name": "Daily at 9 AM",
"type": "n8n-nodes-base.scheduleTrigger",
"typeVersion": 1.2,
"position": [
250,
400
]
},
{
"parameters": {
"httpMethod": "POST",
"path": "integration-advisor",
"responseMode": "responseNode",
"options": {}
},
"id": "webhook-trigger",
"name": "Manual Trigger",
"type": "n8n-nodes-base.webhook",
"typeVersion": 2,
"position": [
250,
600
],
"webhookId": "integration-advisor"
},
{
"parameters": {
"command": "docker service ls --format '{{.Name}}|{{.Mode}}|{{.Replicas}}|{{.Image}}|{{.Ports}}'"
},
"id": "get-services",
"name": "Get All Services",
"type": "n8n-nodes-base.executeCommand",
"typeVersion": 1,
"position": [
500,
400
]
},
{
"parameters": {
"url": "=http://prometheus:9090/api/v1/query?query=up",
"options": {
"timeout": 5000
}
},
"id": "get-prometheus-metrics",
"name": "Get Prometheus Metrics",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
500,
550
],
"continueOnFail": true
},
{
"parameters": {
"url": "=http://lm-studio:1234/v1/models",
"options": {}
},
"id": "get-ai-models",
"name": "Get Available AI Models",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
500,
700
],
"continueOnFail": true
},
{
"parameters": {
"jsCode": "const items = $input.all();\n\nconst inventory = {\n timestamp: new Date().toISOString(),\n services: [],\n capabilities: {\n ai: [],\n monitoring: [],\n automation: [],\n storage: [],\n productivity: [],\n media: [],\n development: []\n },\n integration_potential: []\n};\n\n// Parse service list\nconst serviceData = items.find(i => i.json.stdout);\nif (serviceData && serviceData.json.stdout) {\n const lines = serviceData.json.stdout.split('\\n').filter(l => l.trim());\n lines.forEach(line => {\n const [name, mode, replicas, image, ports] = line.split('|');\n const service = { name, mode, replicas, image, ports };\n inventory.services.push(service);\n \n // Categorize by capability\n if (name.includes('openwebui') || name.includes('lm-studio') || name.includes('ollama')) {\n inventory.capabilities.ai.push(name);\n } else if (name.includes('prometheus') || name.includes('grafana') || name.includes('alert')) {\n inventory.capabilities.monitoring.push(name);\n } else if (name.includes('n8n') || name.includes('komodo')) {\n inventory.capabilities.automation.push(name);\n } else if (name.includes('paperless') || name.includes('stirling') || name.includes('nextcloud')) {\n inventory.capabilities.productivity.push(name);\n } else if (name.includes('plex') || name.includes('jellyfin') || name.includes('immich')) {\n inventory.capabilities.media.push(name);\n } else if (name.includes('gitea') || name.includes('code-server')) {\n inventory.capabilities.development.push(name);\n } else if (name.includes('omv') || name.includes('samba')) {\n inventory.capabilities.storage.push(name);\n }\n });\n}\n\n// Get AI models\nconst aiModels = items.find(i => i.json.data);\nif (aiModels && aiModels.json.data) {\n inventory.ai_models = aiModels.json.data.map(m => m.id);\n}\n\n// Define integration opportunities\nconst integrations = [\n { from: 'n8n', to: 'paperless', type: 'Document automation', potential: 'high' },\n { from: 'n8n', to: 'prometheus', type: 'Metric-based triggers', potential: 'high' },\n { from: 'n8n', to: 'openwebui', type: 'AI-powered workflows', potential: 'high' },\n { from: 'openwebui', to: 'searxng', type: 'Enhanced search', potential: 'medium' },\n { from: 'prometheus', to: 'grafana', type: 'Visualization', potential: 'existing' },\n { from: 'gitea', to: 'komodo', type: 'CI/CD automation', potential: 'high' },\n { from: 'paperless', to: 'nextcloud', type: 'Document storage', potential: 'medium' },\n { from: 'immich', to: 'openwebui', type: 'Photo analysis', potential: 'medium' },\n { from: 'home-assistant', to: 'all', type: 'Smart home integration', potential: 'high' }\n];\n\ninventory.integration_potential = integrations.filter(i => {\n const fromExists = inventory.services.some(s => s.name.includes(i.from.split('-')[0]));\n const toExists = i.to === 'all' || inventory.services.some(s => s.name.includes(i.to.split('-')[0]));\n return fromExists && toExists;\n});\n\nreturn [{ json: inventory }];"
},
"id": "build-inventory",
"name": "Build Service Inventory",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
750,
500
]
},
{
"parameters": {
"method": "POST",
"url": "=http://lm-studio:1234/v1/chat/completions",
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "model",
"value": "=deepseek-r1-distill-llama-8b"
},
{
"name": "messages",
"value": "={{ [{\"role\":\"system\",\"content\":\"You are a homelab integration expert specializing in service orchestration with n8n, Docker, and modern DevOps tools. Analyze the provided service inventory and recommend specific integration workflows. For each recommendation provide: 1) Services involved 2) Integration type 3) Specific n8n workflow pattern 4) Expected benefits 5) Complexity (low/medium/high). Respond in JSON format with an array of recommendations.\"}, {\"role\":\"user\",\"content\":\"Analyze this homelab and recommend integration workflows:\\n\\nServices: \" + JSON.stringify($json.capabilities, null, 2) + \"\\n\\nAvailable AI Models: \" + JSON.stringify($json.ai_models || [], null, 2) + \"\\n\\nPotential Integrations Identified: \" + JSON.stringify($json.integration_potential, null, 2)}] }}"
},
{
"name": "temperature",
"value": "=0.4"
},
{
"name": "max_tokens",
"value": "=2000"
}
]
},
"options": {
"timeout": 40000
}
},
"id": "ai-integration-advisor",
"name": "AI Integration Advisor",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
1000,
500
]
},
{
"parameters": {
"jsCode": "const inventory = $('Build Service Inventory').item.json;\nconst aiResponse = $json.choices[0].message.content;\n\nlet recommendations;\ntry {\n const jsonMatch = aiResponse.match(/\\{[\\s\\S]*\\}|\\[[\\s\\S]*\\]/);\n recommendations = jsonMatch ? JSON.parse(jsonMatch[0]) : { raw: aiResponse };\n} catch (e) {\n recommendations = { raw: aiResponse, error: e.message };\n}\n\nconst report = {\n generated_at: new Date().toISOString(),\n homelab_summary: {\n total_services: inventory.services.length,\n capabilities: inventory.capabilities,\n ai_models_available: inventory.ai_models?.length || 0\n },\n integration_opportunities: inventory.integration_potential,\n ai_recommendations: recommendations,\n priority_integrations: [],\n quick_wins: []\n};\n\n// Extract priority integrations from AI response\nif (Array.isArray(recommendations)) {\n report.priority_integrations = recommendations\n .filter(r => r.complexity === 'low' || r.complexity === 'medium')\n .slice(0, 5);\n report.quick_wins = recommendations\n .filter(r => r.complexity === 'low')\n .slice(0, 3);\n} else if (recommendations.recommendations) {\n report.priority_integrations = recommendations.recommendations.slice(0, 5);\n}\n\nreturn [{ json: report }];"
},
"id": "build-integration-report",
"name": "Build Integration Report",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
1250,
500
]
},
{
"parameters": {
"respondWith": "json",
"responseBody": "={{ $json }}"
},
"id": "webhook-response",
"name": "Webhook Response",
"type": "n8n-nodes-base.respondToWebhook",
"typeVersion": 1,
"position": [
1500,
500
]
}
],
"pinData": {},
"connections": {
"Daily at 9 AM": {
"main": [
[
{
"node": "Get All Services",
"type": "main",
"index": 0
},
{
"node": "Get Prometheus Metrics",
"type": "main",
"index": 0
},
{
"node": "Get Available AI Models",
"type": "main",
"index": 0
}
]
]
},
"Manual Trigger": {
"main": [
[
{
"node": "Get All Services",
"type": "main",
"index": 0
},
{
"node": "Get Prometheus Metrics",
"type": "main",
"index": 0
},
{
"node": "Get Available AI Models",
"type": "main",
"index": 0
}
]
]
},
"Get All Services": {
"main": [
[
{
"node": "Build Service Inventory",
"type": "main",
"index": 0
}
]
]
},
"Get Prometheus Metrics": {
"main": [
[
{
"node": "Build Service Inventory",
"type": "main",
"index": 0
}
]
]
},
"Get Available AI Models": {
"main": [
[
{
"node": "Build Service Inventory",
"type": "main",
"index": 0
}
]
]
},
"Build Service Inventory": {
"main": [
[
{
"node": "AI Integration Advisor",
"type": "main",
"index": 0
}
]
]
},
"AI Integration Advisor": {
"main": [
[
{
"node": "Build Integration Report",
"type": "main",
"index": 0
}
]
]
},
"Build Integration Report": {
"main": [
[
{
"node": "Webhook Response",
"type": "main",
"index": 0
}
]
]
}
},
"active": false,
"settings": {
"executionOrder": "v1"
},
"versionId": "1",
"meta": {
"templateCredsSetupCompleted": true,
"instanceId": "homelab"
},
"id": "homelab-integration-advisor",
"tags": []
}
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