{
  "name": "Workflow A - Mail Processing (HTTP)",
  "description": "Fetch unprocessed conversations from Freescout, analyze with AI, save suggestions",
  "nodes": [
    {
      "id": "uuid-trigger-1",
      "name": "Trigger",
      "type": "n8n-nodes-base.cron",
      "typeVersion": 1,
      "position": [250, 200],
      "parameters": {
        "cronExpression": "*/5 * * * *"
      }
    },
    {
      "id": "uuid-get-conversations",
      "name": "Get Unprocessed Conversations",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [450, 200],
      "parameters": {
        "url": "http://host.docker.internal:4000/query/freescout",
        "method": "POST",
        "headers": {
          "Content-Type": "application/json"
        },
        "sendBody": true,
        "specifyBody": "json",
        "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\"}"
      }
    },
    {
      "id": "uuid-split-results",
      "name": "Split Results",
      "type": "n8n-nodes-base.splitInBatches",
      "typeVersion": 3,
      "position": [650, 200],
      "parameters": {
        "batchSize": 1,
        "options": {
          "basePath": "data"
        }
      }
    },
    {
      "id": "uuid-extract-data",
      "name": "Extract Conversation Data",
      "type": "n8n-nodes-base.set",
      "typeVersion": 3,
      "position": [850, 200],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "name": "ticket_id",
              "value": "={{ $json.id }}",
              "type": "number"
            },
            {
              "name": "ticket_number",
              "value": "={{ $json.number }}",
              "type": "number"
            },
            {
              "name": "subject",
              "value": "={{ $json.subject }}",
              "type": "string"
            },
            {
              "name": "problem_text",
              "value": "={{ ($json.threads_text || 'No description provided').substring(0, 2000) }}",
              "type": "string"
            },
            {
              "name": "customer_email",
              "value": "={{ $json.customer_email }}",
              "type": "string"
            }
          ]
        }
      }
    },
    {
      "id": "uuid-llm-analyze",
      "name": "LiteLLM AI Analysis",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [850, 200],
      "parameters": {
        "url": "http://llm.eks-ai.apps.asgard.eks-lnx.fft-it.de/v1/chat/completions",
        "method": "POST",
        "headers": {
          "Content-Type": "application/json"
        },
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "{\"model\":\"gpt-oss_120b_128k-gpu\",\"messages\":[{\"role\":\"system\",\"content\":\"Du bist ein IT-Support-Assistent. Analysiere das folgende IT-Support-Ticket und gib eine strukturierte JSON-Antwort mit folgenden Feldern: kategorie (z.B. Hardware, Software, Netzwerk, Zugriff), lösung_typ (BARAMUNDI_JOB, AUTOMATISCHE_ANTWORT, oder ESKALATION), vertrauen (Dezimal zwischen 0.0 und 1.0 - wie sicher bist du bei dieser Lösung), baramundi_job (Name des Jobs falls BARAMUNDI_JOB), antwort_text (Die Antwort an den Nutzer), begründung (Kurze Erklärung deiner Analyse)\"},{\"role\":\"user\",\"content\":\"Ticket-Nummer: {{$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}"
      }
    },
    {
      "id": "uuid-parse-response",
      "name": "Parse AI Response",
      "type": "n8n-nodes-base.set",
      "typeVersion": 3,
      "position": [1050, 200],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "name": "response_text",
              "value": "={{ $json.choices?.[0]?.message?.content || '{}' }}",
              "type": "string"
            },
            {
              "name": "ai_response",
              "value": "={{ typeof $json.response_text === 'string' ? JSON.parse($json.response_text) : $json.response_text }}",
              "type": "object"
            },
            {
              "name": "vertrauen",
              "value": "={{ $json.ai_response?.vertrauen || 0.5 }}",
              "type": "number"
            }
          ]
        }
      }
    },
    {
      "id": "uuid-check-confidence",
      "name": "Check Confidence >= 0.6",
      "type": "n8n-nodes-base.if",
      "typeVersion": 2,
      "position": [1250, 200],
      "parameters": {
        "conditions": {
          "options": {
            "caseSensitive": true,
            "extractValue": false
          },
          "combinator": "and",
          "conditions": [
            {
              "id": "condition_1",
              "leftValue": "={{ $json.vertrauen }}",
              "rightValue": 0.6,
              "operator": {
                "name": "filter.operator.gte",
                "value": ">="
              }
            }
          ]
        }
      }
    },
    {
      "id": "uuid-save-to-db",
      "name": "Save Suggestion to Freescout DB",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [1450, 100],
      "parameters": {
        "url": "http://host.docker.internal:4000/query/freescout",
        "method": "POST",
        "headers": {
          "Content-Type": "application/json"
        },
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "{\"query\":\"INSERT INTO conversation_custom_field (conversation_id, custom_field_id, value) VALUES ({{$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 ({{$json.ticket_id}}, 8, '1') ON DUPLICATE KEY UPDATE value = VALUES(value);\"}"
      }
    },
    {
      "id": "uuid-no-action",
      "name": "Skip - Low Confidence",
      "type": "n8n-nodes-base.set",
      "typeVersion": 3,
      "position": [1450, 350],
      "parameters": {
        "options": {},
        "assignments": {
          "assignments": [
            {
              "name": "skipped",
              "value": true,
              "type": "boolean"
            },
            {
              "name": "reason",
              "value": "Confidence {{$json.vertrauen}} < 0.6",
              "type": "string"
            }
          ]
        }
      }
    }
  ],
  "connections": {
    "Trigger": {
      "main": [
        [
          {
            "node": "Get Unprocessed Conversations",
            "index": 0
          }
        ]
      ]
    },
    "Get Unprocessed Conversations": {
      "main": [
        [
          {
            "node": "Split Results",
            "index": 0
          }
        ]
      ]
    },
    "Split Results": {
      "main": [
        [
          {
            "node": "Extract Conversation Data",
            "index": 0
          }
        ]
      ]
    },
    "Extract Conversation Data": {
      "main": [
        [
          {
            "node": "LiteLLM AI Analysis",
            "index": 0
          }
        ]
      ]
    },
    "LiteLLM AI Analysis": {
      "main": [
        [
          {
            "node": "Parse AI Response",
            "index": 0
          }
        ]
      ]
    },
    "Parse AI Response": {
      "main": [
        [
          {
            "node": "Check Confidence >= 0.6",
            "index": 0
          }
        ]
      ]
    },
    "Check Confidence >= 0.6": {
      "main": [
        [
          {
            "node": "Save Suggestion to Freescout DB",
            "index": 0
          }
        ],
        [
          {
            "node": "Skip - Low Confidence",
            "index": 0
          }
        ]
      ]
    }
  },
  "active": false,
  "settings": {
    "errorHandler": "continueOnError"
  }
}