Automatische Zuweisung von Support-Tickets mit JIRA, Supabase und KI

• •OpenAI API Key
• •Supabase URL und API Key

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      "parameters": {
        "comment": "=Auto-assigned to {{ $('Count Assigned Open Issues per User').item.json.assignee_name }} due to no assignee within past 5 days.",
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        "resource": "issueComment"
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        "content": "## 1. Get Resolved Issues\n[Learn more about the JIRA node](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.jira/)\n\nTo build our database of successfully resolved issues, we can pull them directly from JIRA with a JQL query. The remove duplicates node ensures we only add an issues into the database once."
      },
      "typeVersion": 1
    },
    {
      "id": "c4868156-e663-46b1-8979-b561dcb0620b",
      "name": "Last 50 Resolved",
      "type": "n8n-nodes-base.jira",
      "position": [
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        -220
      ],
      "parameters": {
        "options": {
          "jql": "=project = \"My Kanban Project\"\nAND status = \"Done\"\nAND assignee IS NOT EMPTY\nAND created >= -1d"
        },
        "operation": "getAll"
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        "content": "## 2. Create Search Index In Vector Database\n[Learn more about the Supabase Vector Store](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.vectorstoresupabase)\n\nSupabase is a third party database provider which serves traditional PostgreSQL but also supports Vector databases via the Pg-Vector extension. You will require some initial setup but easily done through Supabase's [Langchain quickstart method ](https://supabase.com/docs/guides/ai/langchain?database-method=sql)"
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      "position": [
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      ],
      "parameters": {
        "color": 7,
        "width": 500,
        "height": 460,
        "content": "## 3. Watch for Stale Unassigned Issues\n[Read more about the Scheduled Trigger](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.scheduletrigger/)\n\nHere, we're using a scheduled trigger to watch for stale issues where stale means unassigned issues for more than 5 days. As to not let these fall through the cracks, let's see if we can auto-assign to a team member based on relevance."
      },
      "typeVersion": 1
    },
    {
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      "parameters": {
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        "content": "## 4. Find Similar Issues which have been Resolved\n[Learn more about AI Agents](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/)\n\nOur first step is to find similar but resolved issues. The logic is that if we find these issues, the team member who resolved them will likely be the best person in terms of context and experience to address the current stale issue. Here, we tap back into our resolved issues vector store database for this purpose."
      },
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      "position": [
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      "parameters": {
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        "content": "## 5. Work out which Knowledgeable Team Member has most Capacity\n[Learn more about the Summarize node](https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-base.summarize/)\n\nIf we've found similar resolved issues, we can then identify the last assignee of the issue as a possible candidate to assign the stale issue to. But before we do, we can do a quick check to see how many open issues the team member is currently assigned. We'll pick the team member with the least amount or in another way, the most capacity."
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      "position": [
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      "parameters": {
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        "content": "## 6. Auto-assign Stale Issue to Team Member\n[Learn more about the JIRA node](https://docs.n8n.io/integrations/builtin/app-nodes/n8n-nodes-base.jira/)\n\nFinally, we'll auto-assign the team member to the stale issue and leave a comment. This continues until all stale issues that can be assigned, are assigned."
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        "content": "### What is no similar issues are found?\nThis is beyond the scope of this template so we'll skip the issue but in this situation, you may want to escalate to the project manager instead."
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        "content": "## Try it out\n### This n8n template builds a simple automation to ensure no JIRA issues go unassigned for more than a week to prevent them falling through the cracks. It uses AI to perform searching tasks against a Supabase Vector Store.\nThis can be one way to help reduce the amount of manual work in managing the issue backlog for busy teams with little effort.\n\n### How it works\n* This template contains 2 separate flows which run continuously via schedule triggers.\n* The first populates our Supabase vector store with resolved issues within the last day. This helps keep our vector store up-to-date and relevant for the purpose of finding similar issues.\n* It does this by pulling the latest resolved issues from JIRA and populating the Supabase vectorstore with carefully chosen metadata. This will come in handy later.\n* The second flow watches for stale, unassigned issues for the purpose of aut-assigning to a relevant team member.\n* It does this by comparing the stale issue against our vector store of resolved issues with the goal of identifying which team member would have best context regarding the issue.\n* In a busy team, this may net a few team members as possible candidates to assign. Therefore, we can introduce additional logic to count each team member's assigned, in-progress issues. This is intended to not overload our busiest members.\n* The team member with the least assigned issues is pressumed to have the most capacity and therefore is assigned. A comennt is left in the issue to notify the team member that they've been auto-assigned due to age of issue.\n\n### How to use\n* Modify the project and interval parameters to match those of your use-case and team members.\n* Add additional criteria before assigning to a team member eg. department, as required.\n\n### Need Help?\nJoin the [Discord](https://discord.com/invite/XPKeKXeB7d) or ask in the [Forum](https://community.n8n.io/)!\n\nHappy Hacking!"
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