be2068b7e4
- Add optional chaining (?.) for safe navigation of response properties - Add fallback values if response fields are missing - Extract vertrauen field directly in Parse node for easier reference - Update Check Confidence node to reference $json.vertrauen instead of nested path - Handles cases where LLM response format is unexpected
282 lines
8.5 KiB
JSON
282 lines
8.5 KiB
JSON
{
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"name": "Workflow A - Mail Processing (HTTP)",
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"description": "Fetch unprocessed conversations from Freescout, analyze with AI, save suggestions",
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"nodes": [
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{
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"id": "uuid-trigger-1",
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"name": "Trigger",
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"type": "n8n-nodes-base.cron",
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"typeVersion": 1,
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"position": [250, 200],
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"parameters": {
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"cronExpression": "*/5 * * * *"
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}
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},
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{
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"id": "uuid-get-conversations",
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"name": "Get Unprocessed Conversations",
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"type": "n8n-nodes-base.httpRequest",
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"typeVersion": 4,
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"position": [450, 200],
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"parameters": {
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"url": "http://host.docker.internal:4000/query/freescout",
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"method": "POST",
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"headers": {
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"Content-Type": "application/json"
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},
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"sendBody": true,
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"specifyBody": "json",
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"jsonBody": "{\"query\":\"SELECT c.id, c.number, c.subject, c.customer_email, c.status, GROUP_CONCAT(t.body SEPARATOR ',') as threads_text FROM conversations c LEFT JOIN threads t ON c.id = t.conversation_id LEFT JOIN conversation_custom_field ccf ON c.id = ccf.conversation_id AND ccf.custom_field_id = 8 WHERE c.status = 1 AND ccf.id IS NULL GROUP BY c.id LIMIT 20\"}"
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}
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},
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{
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"id": "uuid-split-results",
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"name": "Split Results",
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"type": "n8n-nodes-base.splitInBatches",
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"typeVersion": 3,
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"position": [650, 200],
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"parameters": {
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"batchSize": 1,
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"options": {
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"basePath": "data"
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}
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}
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},
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{
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"id": "uuid-extract-data",
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"name": "Extract Conversation Data",
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"type": "n8n-nodes-base.set",
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"typeVersion": 3,
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"position": [850, 200],
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"parameters": {
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"options": {},
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"assignments": {
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"assignments": [
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{
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"name": "ticket_id",
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"value": "={{ $json.id }}",
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"type": "number"
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},
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{
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"name": "ticket_number",
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"value": "={{ $json.number }}",
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"type": "number"
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},
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{
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"name": "subject",
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"value": "={{ $json.subject }}",
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"type": "string"
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},
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{
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"name": "problem_text",
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"value": "={{ ($json.threads_text || 'No description provided').substring(0, 2000) }}",
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"type": "string"
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},
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{
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"name": "customer_email",
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"value": "={{ $json.customer_email }}",
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"type": "string"
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}
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]
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}
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}
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},
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{
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"id": "uuid-llm-analyze",
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"name": "LiteLLM AI Analysis",
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"type": "n8n-nodes-base.httpRequest",
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"typeVersion": 4,
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"position": [850, 200],
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"parameters": {
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"url": "http://llm.eks-ai.apps.asgard.eks-lnx.fft-it.de/v1/chat/completions",
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"method": "POST",
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"headers": {
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"Content-Type": "application/json"
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},
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"sendBody": true,
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"specifyBody": "json",
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"jsonBody": "{\"model\":\"gpt-oss_120b_128k-gpu\",\"messages\":[{\"role\":\"system\",\"content\":\"Du bist ein IT-Support-Assistent. Analysiere das folgende IT-Support-Ticket und gib eine strukturierte JSON-Antwort mit folgenden Feldern: kategorie (z.B. Hardware, Software, Netzwerk, Zugriff), lösung_typ (BARAMUNDI_JOB, AUTOMATISCHE_ANTWORT, oder ESKALATION), vertrauen (Dezimal zwischen 0.0 und 1.0 - wie sicher bist du bei dieser Lösung), baramundi_job (Name des Jobs falls BARAMUNDI_JOB), antwort_text (Die Antwort an den Nutzer), begründung (Kurze Erklärung deiner Analyse)\"},{\"role\":\"user\",\"content\":\"Ticket-Nummer: {{$json.ticket_number}}\\nBetreff: {{$json.subject}}\\nProblembeschreibung:\\n{{$json.problem_text}}\\n\\nBitte antworte NUR mit gültiger JSON in dieser Struktur: {\\\"kategorie\\\": \\\"...\\\", \\\"lösung_typ\\\": \\\"...\\\", \\\"vertrauen\\\": 0.75, \\\"baramundi_job\\\": \\\"...\\\", \\\"antwort_text\\\": \\\"...\\\", \\\"begründung\\\": \\\"...\\\"}\"}],\"temperature\":0.7,\"max_tokens\":1000}"
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}
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},
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{
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"id": "uuid-parse-response",
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"name": "Parse AI Response",
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"type": "n8n-nodes-base.set",
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"typeVersion": 3,
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"position": [1050, 200],
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"parameters": {
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"options": {},
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"assignments": {
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"assignments": [
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{
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"name": "response_text",
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"value": "={{ $json.choices?.[0]?.message?.content || '{}' }}",
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"type": "string"
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},
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{
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"name": "ai_response",
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"value": "={{ typeof $json.response_text === 'string' ? JSON.parse($json.response_text) : $json.response_text }}",
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"type": "object"
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},
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{
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"name": "vertrauen",
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"value": "={{ $json.ai_response?.vertrauen || 0.5 }}",
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"type": "number"
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}
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]
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}
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}
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},
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{
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"id": "uuid-check-confidence",
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"name": "Check Confidence >= 0.6",
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"type": "n8n-nodes-base.if",
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"typeVersion": 2,
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"position": [1250, 200],
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"parameters": {
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"conditions": {
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"options": {
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"caseSensitive": true,
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"extractValue": false
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},
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"combinator": "and",
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"conditions": [
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{
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"id": "condition_1",
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"leftValue": "={{ $json.vertrauen }}",
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"rightValue": 0.6,
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"operator": {
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"name": "filter.operator.gte",
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"value": ">="
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}
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}
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]
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}
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}
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},
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{
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"id": "uuid-save-to-db",
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"name": "Save Suggestion to Freescout DB",
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"type": "n8n-nodes-base.httpRequest",
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"typeVersion": 4,
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"position": [1450, 100],
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"parameters": {
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"url": "http://host.docker.internal:4000/query/freescout",
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"method": "POST",
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"headers": {
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"Content-Type": "application/json"
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},
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"sendBody": true,
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"specifyBody": "json",
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"jsonBody": "{\"query\":\"INSERT INTO conversation_custom_field (conversation_id, custom_field_id, value) VALUES ({{$json.ticket_id}}, 6, '{{$json.ai_response | json.stringify}}') ON DUPLICATE KEY UPDATE value = VALUES(value); INSERT INTO conversation_custom_field (conversation_id, custom_field_id, value) VALUES ({{$json.ticket_id}}, 7, 'PENDING') ON DUPLICATE KEY UPDATE value = VALUES(value); INSERT INTO conversation_custom_field (conversation_id, custom_field_id, value) VALUES ({{$json.ticket_id}}, 8, '1') ON DUPLICATE KEY UPDATE value = VALUES(value);\"}"
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}
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},
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{
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"id": "uuid-no-action",
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"name": "Skip - Low Confidence",
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"type": "n8n-nodes-base.set",
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"typeVersion": 3,
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"position": [1450, 350],
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"parameters": {
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"options": {},
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"assignments": {
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"assignments": [
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{
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"name": "skipped",
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"value": true,
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"type": "boolean"
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},
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{
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"name": "reason",
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"value": "Confidence {{$json.vertrauen}} < 0.6",
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"type": "string"
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}
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]
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}
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}
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}
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],
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"connections": {
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"Trigger": {
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"main": [
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[
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{
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"node": "Get Unprocessed Conversations",
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"index": 0
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}
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]
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]
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},
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"Get Unprocessed Conversations": {
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"main": [
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[
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{
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"node": "Split Results",
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"index": 0
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}
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]
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]
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},
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"Split Results": {
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"main": [
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[
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{
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"node": "Extract Conversation Data",
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"index": 0
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}
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]
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]
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},
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"Extract Conversation Data": {
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"main": [
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[
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{
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"node": "LiteLLM AI Analysis",
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"index": 0
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}
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]
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]
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},
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"LiteLLM AI Analysis": {
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"main": [
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[
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{
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"node": "Parse AI Response",
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"index": 0
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}
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]
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]
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},
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"Parse AI Response": {
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"main": [
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[
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{
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"node": "Check Confidence >= 0.6",
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"index": 0
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}
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]
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]
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},
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"Check Confidence >= 0.6": {
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"main": [
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[
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{
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"node": "Save Suggestion to Freescout DB",
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"index": 0
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}
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],
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[
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{
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"node": "Skip - Low Confidence",
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"index": 0
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}
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]
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]
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}
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},
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"active": false,
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"settings": {
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"errorHandler": "continueOnError"
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}
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}
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