n8n-compose/n8n-workflows/workflow-a-http.json

{
  "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-out",
      "name": "Split Array into Items",
      "type": "n8n-nodes-base.splitOut",
      "typeVersion": 1,
      "position": [650, 200],
      "parameters": {
        "fieldToSplitOut": "data",
        "options": {}
      }
    },
    {
      "id": "uuid-extract-data",
      "name": "Extract Conversation Data",
      "type": "n8n-nodes-base.code",
      "typeVersion": 2,
      "position": [850, 200],
      "parameters": {
        "mode": "runOnceForEachItem",
        "jsCode": "const item = $input.item.json;\n// HTML-Tags entfernen damit die AI lesbaren Text bekommt\nconst rawText = item.threads_text || 'Keine Beschreibung vorhanden';\nconst plainText = rawText\n  .replace(/<[^>]+>/g, ' ')\n  .replace(/&nbsp;/g, ' ')\n  .replace(/&amp;/g, '&')\n  .replace(/&lt;/g, '<')\n  .replace(/&gt;/g, '>')\n  .replace(/&quot;/g, '\"')\n  .replace(/\\s+/g, ' ')\n  .trim()\n  .substring(0, 2000);\nreturn { json: {\n  ticket_id: item.id,\n  ticket_number: item.number,\n  subject: item.subject,\n  customer_email: item.customer_email,\n  problem_text: plainText\n}};"
      }
    },
    {
      "id": "uuid-llm-analyze",
      "name": "LiteLLM AI Analysis",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [1050, 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": "={{ JSON.stringify({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.code",
      "typeVersion": 2,
      "position": [1250, 200],
      "parameters": {
        "mode": "runOnceForEachItem",
        "jsCode": "const content = $input.item.json.choices[0].message.content;\nconst extractData = $('Extract Conversation Data').item.json;\nconst ticketId = extractData.ticket_id !== undefined ? extractData.ticket_id : extractData.id;\nlet vertrauen = 0.1;\nlet loesung_typ = 'UNBEKANNT';\nlet kategorie = '';\nlet antwort_text = '';\nlet baramundi_job = '';\ntry {\n  const parsed = JSON.parse(content);\n  vertrauen = typeof parsed.vertrauen === 'number' ? parsed.vertrauen : 0.1;\n  loesung_typ = parsed['lösung_typ'] || parsed.loesung_typ || 'UNBEKANNT';\n  kategorie = parsed.kategorie || '';\n  antwort_text = parsed.antwort_text || '';\n  baramundi_job = parsed.baramundi_job || '';\n} catch(e) { vertrauen = 0.1; }\n// Human-readable for Freescout textarea\nconst lines = [loesung_typ + ' | Vertrauen: ' + vertrauen + ' | Kategorie: ' + kategorie];\nif (baramundi_job) lines.push('Baramundi-Job: ' + baramundi_job);\nlines.push('---');\nlines.push(antwort_text);\nconst display_text = lines.join(' | ');\n// SQL-safe: Quotes escapen, Zeilenumbrüche als ¶ (Pilcrow) erhalten damit\n// Workflow B die Struktur der KI-Antwort wiederherstellen kann.\nconst ai_content_sql = display_text.replace(/'/g, \"''\").replace(/\\r/g, '').replace(/\\n/g, '¶');\nconst ai_json_sql = content.replace(/'/g, \"''\").replace(/[\\n\\r]/g, ' ');\nreturn { json: { vertrauen, ticket_id: ticketId, ai_content: content, ai_content_sql, ai_json_sql } };"
      }
    },
    {
      "id": "uuid-check-confidence",
      "name": "Check Confidence >= 0.6",
      "type": "n8n-nodes-base.if",
      "typeVersion": 2,
      "position": [1450, 200],
      "parameters": {
        "conditions": {
          "options": {
            "caseSensitive": true,
            "leftValue": "",
            "typeValidation": "loose"
          },
          "conditions": [
            {
              "id": "cond-confidence",
              "leftValue": "={{ $json.vertrauen }}",
              "rightValue": 0.6,
              "operator": {
                "type": "number",
                "operation": "gte"
              }
            }
          ],
          "combinator": "and"
        }
      }
    },
    {
      "id": "uuid-save-ai-suggestion",
      "name": "Save AI Suggestion (field 6)",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [1650, 100],
      "parameters": {
        "url": "http://host.docker.internal:4000/query/freescout",
        "method": "POST",
        "headers": {
          "Content-Type": "application/json"
        },
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "={{ JSON.stringify({query: \"INSERT INTO conversation_custom_field (conversation_id, custom_field_id, value) VALUES (\" + $json.ticket_id + \", 6, '\" + $json.ai_content_sql + \"') ON DUPLICATE KEY UPDATE value = VALUES(value)\"}) }}"
      }
    },
    {
      "id": "uuid-save-status-pending",
      "name": "Save Status PENDING (field 7)",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [1650, 200],
      "parameters": {
        "url": "http://host.docker.internal:4000/query/freescout",
        "method": "POST",
        "headers": {
          "Content-Type": "application/json"
        },
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "={{ JSON.stringify({query: \"INSERT INTO conversation_custom_field (conversation_id, custom_field_id, value) VALUES (\" + $('Parse AI Response').item.json.ticket_id + \", 7, '0') ON DUPLICATE KEY UPDATE value = VALUES(value)\"}) }}"
      }
    },
    {
      "id": "uuid-save-processed-flag",
      "name": "Save Processed Flag (field 8)",
      "type": "n8n-nodes-base.httpRequest",
      "typeVersion": 4,
      "position": [1650, 300],
      "parameters": {
        "url": "http://host.docker.internal:4000/query/freescout",
        "method": "POST",
        "headers": {
          "Content-Type": "application/json"
        },
        "sendBody": true,
        "specifyBody": "json",
        "jsonBody": "={{ JSON.stringify({query: \"INSERT INTO conversation_custom_field (conversation_id, custom_field_id, value) VALUES (\" + $('Parse AI Response').item.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": [1650, 350],
      "parameters": {
        "mode": "manual",
        "options": {},
        "assignments": {
          "assignments": [
            {
              "id": "assign-skipped",
              "name": "skipped",
              "value": true,
              "type": "boolean"
            },
            {
              "id": "assign-reason",
              "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 Array into Items", "index": 0}]
      ]
    },
    "Split Array into Items": {
      "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 AI Suggestion (field 6)", "index": 0}],
        [{"node": "Skip - Low Confidence", "index": 0}]
      ]
    },
    "Save AI Suggestion (field 6)": {
      "main": [
        [{"node": "Save Status PENDING (field 7)", "index": 0}]
      ]
    },
    "Save Status PENDING (field 7)": {
      "main": [
        [{"node": "Save Processed Flag (field 8)", "index": 0}]
      ]
    }
  },
  "active": false,
  "settings": {
    "errorHandler": "continueOnError"
  }
}